Meteorology doi: 10.3390/meteorology3020007
Authors: André S. W. Teruya Víctor C. Mayta Breno Raphaldini Pedro L. Silva Dias Camila R. Sapucci
Instead of using the traditional space-time Fourier analysis of filtered specific atmospheric fields, a normal-mode decomposition method was used to analyze South American intraseasonal variability (ISV). Intraseasonal variability was examined separately in the 30–90-day band, 20–30-day band, and 10–20-day band. The most characteristic structure in the intraseasonal time-scale, in the three bands, was the dipole-like convection between the South Atlantic Convergence Zone (SACZ) and the central-east South America (CESA) region. In the 30–90-day band, the convective and circulation patterns were modulated by the large-scale Madden–Julian oscillation (MJO). In the 20–30-day and 10–20-day bands, the convection structures were primarily controlled by extratropical Rossby wave trains. The normal-mode decomposition of reanalysis data based on 30–90-day, 20–30-day, and 10–20-day ISV showed that the tropospheric circulation and CESA–SACZ convective structure observed over South America were dominated by rotational modes (i.e., Rossby waves, mixed Rossby-gravity waves). A considerable portion of the 30–90-day ISV was also associated with the inertio-gravity (IGW) modes (e.g., Kelvin waves), mainly prevailing during the austral rainy season. The proposed decomposition methodology demonstrated that a realistic circulation can be reproduced, giving a powerful tool for diagnosing and studying the dynamics of waves and the interactions between them in terms of their ability to provide causal accounts of the features seen in observations.
]]>Meteorology doi: 10.3390/meteorology3010006
Authors: Katherine E. Lukens Kevin Garrett Kayo Ide David Santek Brett Hoover David Huber Ross N. Hoffman Hui Liu
Accurate atmospheric 3D wind observations are one of the top priorities for the global scientific community. To address this requirement, and to support researchers’ needs to acquire and analyze wind data from multiple sources, the System for Analysis of Wind Collocations (SAWC) was jointly developed by NOAA/NESDIS/STAR, UMD/ESSIC/CISESS, and UW-Madison/CIMSS. SAWC encompasses the following: a multi-year archive of global 3D winds observed by Aeolus, sondes, aircraft, stratospheric superpressure balloons, and satellite-derived atmospheric motion vectors, archived and uniformly formatted in netCDF for public consumption; identified pairings between select datasets collocated in space and time; and a downloadable software application developed for users to interactively collocate and statistically compare wind observations based on their research needs. The utility of SAWC is demonstrated by conducting a one-year (September 2019–August 2020) evaluation of Aeolus level-2B (L2B) winds (Baseline 11 L2B processor version). Observations from four archived conventional wind datasets are collocated with Aeolus. The recommended quality controls are applied. Wind comparisons are assessed using the SAWC collocation application. Comparison statistics are stratified by season, geographic region, and Aeolus observing mode. The results highlight the value of SAWC’s capabilities, from product validation through intercomparison studies to the evaluation of data usage in applications and advances in the global Earth observing architecture.
]]>Meteorology doi: 10.3390/meteorology3010005
Authors: Jason Naylor Megan E. Berry Emily G. Gosney
Idealized simulations with a cloud-resolving model are conducted to examine the impact of a simplified city on the structure of a supercell thunderstorm. The simplified city is created by enhancing the surface roughness length and/or surface temperature relative to the surroundings. When the simplified city is both warmer and has larger surface roughness relative to its surroundings, the supercell that passes over it has a larger updraft helicity (at both midlevels and the surface) and enhanced precipitation and hail downwind of the city, all relative to the control simulation. The storm environment within the city has larger convective available potential energy which helps stimulate stronger low-level updrafts. Storm relative helicity (SRH) is actually reduced over the city, but enhanced in a narrow band on the northern edge of the city. This band of larger SRH is ingested by the primary updraft just prior to passing over the city, corresponding with enhancement to the near-surface mesocyclone. Additional simulations in which the simplified city is altered by removing either the heat island or surface roughness length gradient reveal that the presence of a heat island is most closely associated with enhancements in updraft helicity and low-level updrafts relative to the control simulation.
]]>Meteorology doi: 10.3390/meteorology3010004
Authors: Erzsébet Kristóf Ferenc Ács Annamária Zsákai
We characterized the thermal load of a person walking and/or standing in the fog by analyzing the thermal resistance of clothing, rcl, and operative temperature, To. The rcl–To model applies to individuals using weather data. The body mass index and basal metabolic flux density values of the person analyzed in this study are 25 kg m−2 and 40 W m−2, respectively. Weather data are taken from the nearest automatic weather station. We observed 146 fog events in the period 2017–2024 in Martonvásár (Hungary’s Great Plain region, Central Europe). The main results are as follows: (1) The rcl and To values were mostly between 2 and 0.5 clo and −4 and 16 °C during fog events, respectively. (2) The largest and smallest rcl and To values were around 2.5 and 0 clo and −7 and 22 °C, respectively. (3) The rcl differences resulting from interpersonal and wind speed variability are comparable, with a maximum value of around 0.5–0.7 clo. (4) Finally, rcl values are significantly different for standing and walking persons. At the very end, we can emphasize that the thermal load of the fog depends noticeably on the person’s activity and anthropometric characteristics.
]]>Meteorology doi: 10.3390/meteorology3010003
Authors: Edoardo Bucchignani
In the present work, a methodology for wind field reconstruction based on the Meteo Particle model (MPM) from numerical weather prediction (NWP) data is presented. The development of specific wind forecast services is a challenging research topic, in particular for what concerns the availability of accurate local weather forecasts in highly populated areas. Currently, even if NWP limited area models (LAMs) are run at a spatial resolution of about 1 km, this level of information is not sufficient for many applications; for example, to support drone operation in urban contexts. The coupling of the MPM with the NWP limited area model COSMO has been implemented in such a way that the MPM reads the NWP output over a selected area and provides wind values for the generic point considered for the investigation. The numerical results obtained reveal the good behavior of the method in reproducing the general trend of the wind speed, as also confirmed by the power spectra analysis. The MPM is able to step over the intrinsic limitations of the NWP model in terms of the spatial and temporal resolution, even if the MPM inherits the bias that inevitably affects the COSMO output.
]]>Meteorology doi: 10.3390/meteorology3010002
Authors: Andrew R. Jakovlev Sergei P. Smyshlyaev
Tropical sea surface temperature (SST) variability, mainly driven by the El Niño–Southern Oscillation (ENSO), influences the atmospheric circulation and hence the transport of heat and chemical species in both the troposphere and stratosphere. This paper uses Met Office, ERA5 and MERRA2 reanalysis data to examine the impact of SST variability on the dynamics of the polar stratosphere and ozone layer over the period from 1980 to 2020. Particular attention is paid to studying the differences in the influence of different types of ENSO (East Pacific (EP) and Central Pacific (CP)) for the El Niño and La Niña phases. It is shown that during the CP El Niño, the zonal wind weakens more strongly and changes direction more often than during the EP El Niño, and the CP El Niño leads to a more rapid decay of the polar vortex (PV), an increase in stratospheric air temperature and an increase in the concentration and total column ozone than during EP El Niño. For the CP La Niña, the PV is more stable, which often leads to a significant decrease in Arctic ozone. During EP La Niña, powerful sudden stratospheric warming events are often observed, which lead to the destruction of PV and an increase in column ozone.
]]>Meteorology doi: 10.3390/meteorology3010001
Authors: Julie Sherman Christian Sampson Emmanuel Fleurantin Zhimin Wu Christopher K. R. T. Jones
Stratospheric dynamics are strongly affected by the absorption/emission of radiation in the Earth’s atmosphere and Rossby waves that propagate upward from the troposphere, perturbing the zonal flow. Reduced order models of stratospheric wave–zonal interactions, which parameterize these effects, have been used to study interannual variability in stratospheric zonal winds and sudden stratospheric warming (SSW) events. These models are most sensitive to two main parameters: Λ, forcing the mean radiative zonal wind gradient, and h, a perturbation parameter representing the effect of Rossby waves. We take one such reduced order model with 20 years of ECMWF atmospheric reanalysis data and estimate Λ and h using both a particle filter and an ensemble smoother to investigate if the highly-simplified model can accurately reproduce the averaged reanalysis data and which parameter properties may be required to do so. We find that by allowing additional complexity via an unparameterized Λ(t), the model output can closely match the reanalysis data while maintaining behavior consistent with the dynamical properties of the reduced-order model. Furthermore, our analysis shows physical signatures in the parameter estimates around known SSW events. This work provides a data-driven examination of these important parameters representing fundamental stratospheric processes through the lens and tractability of a reduced order model, shown to be physically representative of the relevant atmospheric dynamics.
]]>Meteorology doi: 10.3390/meteorology2040030
Authors: C. Arturo Sánchez P. Alan J. P. Calheiros Sâmia R. Garcia Elbert E. N. Macau
The Amazon Basin is the largest rainforest in the world, and studying the rainfall in this region is crucial for understanding the functioning of the entire rainforest ecosystem and its role in regulating the regional and global climate. This work is part of the application of complex networks, which refer to a network modeled by graphs and are characterized by their high versatility, as well as the extraction of key information from the system under study. The main objective of this article is to examine the precipitation system in the Amazon basin during the austral summer. The networks are defined by nodes and connections, where each node represents a precipitation time series, while the connections can be represented by different similarity functions. For this study, three rainfall networks were created, which differ based on the correlation function used (Pearson, Spearman, and Kendall). By comparing these networks, we can identify the most effective method for analyzing the data and gain a better understanding of rainfall’s spatial structure, thereby enhancing our knowledge of its impact on different Amazon basin regions. The results reveal the presence of three important regions in the Amazon basin. Two areas were identified in the northeast and northwest, showing incursions of warm and humid winds from the oceans and favoring the occurrence of large mesoscale systems, such as squall lines. Additionally, the eastern part of the central Andes may indicate an outflow region from the basin with winds directed toward subtropical latitudes. The networks showed a high level of activity and participation in the center of the Amazon basin and east of the Andes. Regarding information transmission, the betweenness centrality identified the main pathways within a basin, and some of these are directly related to certain rivers, such as the Amazon, Purus, and Madeira. Indicating the relationship between rainfall and the presence of water bodies. Finally, it suggests that the Spearman and Kendall correlation produced the most promising results. Although they showed similar spatial patterns, the major difference was found in the identification of communities, this is due to the meridional differences in the network’s response. Overall, these findings highlight the importance of carefully selecting appropriate techniques and methods when analyzing complex networks.
]]>Meteorology doi: 10.3390/meteorology2040029
Authors: Shaun Lovejoy Lenin Del Rio Amador
Beyond their deterministic predictability limits of ≈10 days and 6 months, the atmosphere and ocean become effectively stochastic. This has led to the development of stochastic models specifically for this macroweather regime. A particularly promising approach is based on the Fractional Energy Balance Equation (FEBE), an update of the classical Budyko–Sellers energy balance approach. The FEBE has scaling symmetries that imply long memories, and these are exploited in the Stochastic Seasonal and Interannual Prediction System (StocSIPS). Whereas classical long-range forecast systems are initial value problems based on spatial information, StocSIPS is a past value problem based on (long) series at each pixel. We show how to combine StocSIPS with a classical coupled GCM system (CanSIPS) into a hybrid system (CanStoc), the skill of which is better than either. We show that for one-month lead times, CanStoc’s skill is particularly enhanced over either CanSIPS or StocSIPS, whereas for 2–3-month lead times, CanSIPS provides little extra skill. As expected, the CanStoc skill is higher over ocean than over land with some seasonal dependence. From the classical point of view, CanStoc could be regarded as a post-processing technique. From the stochastic point of view, CanStoc could be regarded as a way of harnessing extra skill at the submonthly scales in which StocSIPS is not expected to apply.
]]>Meteorology doi: 10.3390/meteorology2040028
Authors: Ayman Elyoussoufi Curtis L. Walker Alan W. Black Gregory J. DeGirolamo
Adverse weather conditions impact mobility, safety, and the behavior of drivers on roads. In an average year, approximately 21% of U.S. highway crashes are weather-related. Collectively, these crashes result in over 5300 fatalities each year. As a proof-of-concept, analyzing weather information in the context of traffic mobility data can provide unique insights into driver behavior and actions transportation agencies can pursue to promote safety and efficiency. Using 2019 weather and traffic data along Colorado Highway 119 between Boulder and Longmont, this research analyzed the relationship between adverse weather and traffic conditions. The data were classified into distinct weather types, day of the week, and the direction of travel to capture commuter traffic flows. Novel traffic information crowdsourced from smartphones provided metrics such as volume, speed, trip length, trip duration, and the purpose of travel. The data showed that snow days had a smaller traffic volume than clear and rainy days, with an All Times volume of approximately 18,000 vehicles for each direction of travel, as opposed to 21,000 vehicles for both clear and wet conditions. From a trip purpose perspective, the data showed that the percentage of travel between home and work locations was 21.4% during a snow day compared to 20.6% for rain and 19.6% for clear days. The overall traffic volume reduction during snow days is likely due to drivers deciding to avoid commuting; however, the relative increase in the home–work travel percentage is likely attributable to less discretionary travel in lieu of essential work travel. In comparison, the increase in traffic volume during rainy days may be due to commuters being less likely to walk, bike, or take public transit during inclement weather. This study demonstrates the insight into human behavior by analyzing impact on traffic parameters during adverse weather travel.
]]>Meteorology doi: 10.3390/meteorology2040027
Authors: Vladimir S. Kostsov Dmitry V. Ionov
Liquid water path (LWP) is one of the most important cloud parameters and is crucial for global and regional climate modelling, weather forecasting, and modelling of the hydrological cycle and interactions between different components of the climate system: the atmosphere, the hydrosphere, and the land surface. Space-borne observations by the SEVIRI instrument have already provided evidence of the systematic difference between the cloud LWP values derived over the land surface in Northern Europe and those derived over the Baltic Sea and major lakes during both cold and warm seasons. In the present study, the analysis of this LWP land-sea contrast for the period 2011–2017 reveals specific temporal and spatial variations, which, in some cases, seem to be artefacts rather than of natural origin. The geographical objects of investigation are water bodies and water areas located in Northern Europe that differ in size and other geophysical characteristics: the Gulf of Finland and the Gulf of Riga in the Baltic Sea and large and small lakes in the neighbouring region. The analysis of intra-seasonal features has detected anomalous conditions in the Gulf of Riga and the Gulf of Finland, which show up as very low values of the LWP land-sea contrast in August with respect to the values in June and July every year within the considered time period. This anomaly is likely an artefact caused by the LWP retrieval algorithm since the transition from large LWP contrast to very low contrast occurs sharply, synchronically, and at a certain date every year at different places in the Baltic Sea.
]]>Meteorology doi: 10.3390/meteorology2040026
Authors: Adrian F. Tuck
Four observational results: the intermittency of air temperature; its correlation with ozone photodissociation rate; the diurnal variation of ozone in the upper stratosphere; and the cold bias of meteorological analyses compared to observations, are reviewed. The excitation of photofragments and their persistence of velocity after collision is appealed to as a possible explanation. Consequences are discussed, including the interpretation of the Langevin equation and fluctuation–dissipation in the atmosphere, the role of scale invariance and statistical multifractality, and what the results might mean for the distribution of isotopes among atmospheric molecules. An adjunct of the analysis is an exponent characterizing jet streams. Observational tests are suggested.
]]>Meteorology doi: 10.3390/meteorology2040025
Authors: Léa Berthomier Laurent Perier
Estimating precipitation is of critical importance to climate systems and decision-making processes. This paper presents Espresso, a deep learning model designed for estimating precipitation from satellite observations on a global scale. Conventional methods, like ground-based radars, are limited in terms of spatial coverage. Satellite observations, on the other hand, allow global coverage. Combined with deep learning methods, these observations offer the opportunity to address the challenge of estimating precipitation on a global scale. This research paper presents the development of a deep learning model using geostationary satellite data as input and generating instantaneous rainfall rates, calibrated using data from the Global Precipitation Measurement Core Observatory (GPMCO). The performance impact of various input data configurations on Espresso was investigated. These configurations include a sequence of four images from geostationary satellites and the optimal selection of channels. Additional descriptive features were explored to enhance the model’s robustness for global applications. When evaluated against the GPMCO test set, Espresso demonstrated highly accurate precipitation estimation, especially within equatorial regions. A comparison against six other operational products using multiple metrics indicated its competitive performance. The model’s superior storm localization and intensity estimation were further confirmed through visual comparisons in case studies. Espresso has been incorporated as an operational product at Météo-France, delivering high-quality, real-time global precipitation estimates every 30 min.
]]>Meteorology doi: 10.3390/meteorology2030024
Authors: Mohamed Hachaichi
Cities are progressively heightening their climate aspirations to curtail urban carbon emissions and establish a future where economies and communities can flourish within the Earth’s ecological limits. Consequently, numerous climate initiatives are being launched to control urban carbon emissions, targeting various sectors, including transport, residential, agricultural, and energy. However, recent scientific literature underscores the disproportionate distribution of climate policies. While cities in the Global North have witnessed several initiatives to combat climate change, cities in the Global South remain uncovered and highly vulnerable to climate hazards. To address this disparity, we employed the Balanced Iterative Reducing and Clustering using the Hierarchies (BRICH) algorithm to cluster cities from diverse geographical areas that exhibit comparable socioeconomic profiles. This clustering strives to foster enhanced cooperation and collaboration among cities globally, with the goal of addressing climate change in a comprehensive manner. In summary, we identified similarities, patterns, and clusters among peer cities, enabling mutual and generalizable learning among worldwide peer-cities regarding urban climate policy exchange. This exchange occurs through three approaches: (i) inner-mutual learning, (ii) cross-mutual learning, and (iii) outer-mutual learning. Our findings mark a pivotal stride towards attaining worldwide climate objectives through a shared responsibility approach. Furthermore, they provide preliminary insights into the implementation of “urban climate policy exchange” among peer cities on a global scale.
]]>Meteorology doi: 10.3390/meteorology2030023
Authors: Vasilică Istrate Dorin Podiuc Dragoș Andrei Sîrbu Eduard Popescu Emil Sîrbu Doru Dorian Popescu
Using a database of 378 hail days between 1981 and 2020, the climatic characteristics of 23 convective parameters from sounding data and ERA5 data were statistically analysed. The goal of this work is to evaluate the usefulness and representativeness of convective parameters derived from sounding data and reanalysis data for the operational forecast of the hail phenomenon. As a result, the average values from 12:00 UTC were 433 J/kg for CAPE in the case of data from ERA5 and 505 J/kg from rawinsonde, respectively. The Spearman correlation coefficient matrix between the values of the parameters indicates high correlations among the parameters calculated based on the parcel theory, humidity indices, and the complex indices. The probability for large hail increases with high values of low-level and boundary-layer moisture, high CAPE, and a high lifting condensation level (LCL) height.
]]>Meteorology doi: 10.3390/meteorology2030022
Authors: James A. Schiavone
Better understanding of roll vortices that often occur in the tropical cyclone (TC) boundary layer is required to improve forecasts of TC intensification and the granularity of damaging surface winds. It is especially important to characterize rolls over a wide variety of TCs, their environments, and TC development phases. Boundary layer rolls have been observed in TCs since 1998, but only recently in a TC during its extratropical transition phase. The work reported herein is the first to analyze how boundary layer rolls are distributed among the extratropical features of a transitioning TC. To this end, routine and special operational observations recorded during landfalling Post-tropical Cyclone Sandy (2012) were leveraged, including radar, surface, rawinsonde, and aircraft reconnaissance observations. Large rolls occurred in cold airstreams, both in the cold conveyor belt within the northwestern storm quadrant and in the secluding airstream within the northeastern quadrant, but roll presence was much diminished within the intervening warm sector. The large size of the rolls and their confinement to cold airstreams is attributed to an optimum inflow layer depth, which is deep enough below a strong stable layer to accommodate deep and strong positive radial wind shear to promote roll growth, yet not so deep as to limit radial wind shear magnitude, as occurred in the warm sector.
]]>Meteorology doi: 10.3390/meteorology2030021
Authors: Nicholas John Cook
The reliability of extreme wind speed predictions at large mean recurrence intervals (MRI) is assessed by bootstrapping samples from representative known distributions. The classical asymptotic generalized extreme value distribution (GEV) and the generalized Pareto (GPD) distribution are compared with a contemporary sub-asymptotic Gumbel distribution that accounts for incomplete convergence to the correct asymptote. The sub-asymptotic model is implemented through a modified Gringorten method for epoch maxima and through the XIMIS method for peak-over-threshold values. The mean bias error is shown to be minimal in all cases, so that the variability expressed by the standard error becomes the principal reliability metric. Peak-over-threshold (POT) methods are shown to always be more reliable than epoch methods due to the additional sub-epoch data. The generalized asymptotic methods are shown to always be less reliable than the sub-asymptotic methods by a factor that increases with MRI. This study reinforces the previously published theory-based arguments that GEV and GPD are unsuitable models for extreme wind speeds by showing that they also provide the least reliable predictions in practice. A new two-step Weibull-XIMIS hybrid method is shown to have superior reliability.
]]>Meteorology doi: 10.3390/meteorology2030020
Authors: Jayesh Phadtare
During the post-monsoon cyclone season, the landfalls of westward-moving cyclonic systems often lead to extreme rainfall over the east coast of the Indian peninsula. A stationary cyclonic system over the coast can produce heavy rainfall for several days and cause catastrophic flooding. This study analyzes the dynamics of a propagating and stationary cyclonic system over the east coast, highlighting the possible cause behind the stagnation. The vorticity budgets of these two systems are presented using a reanalysis dataset. Vortex stretching and horizontal vorticity advection were the dominant terms in the budget. Vertical advection and tilting terms were significant over the orography. The horizontal advection of vorticity was positive (negative) on the western (eastern) side of the systems and, thus, favored westward propagation. Vortex stretching was confined to the upstream of orography in the stationary vortex. In the propagating vortex, the vortex stretching occurred over the orography during its passage. Data from the radiosonde soundings over a coastal station showed orographic blocking of the low-level winds in the stationary case. Conversely, the flow crossed the orographic barrier in the propagating case. Thus, the predominance of the upstream orographic convergence over the vortex circulation can be the reason for system stagnation over the coast.
]]>Meteorology doi: 10.3390/meteorology2030019
Authors: Felipe M. de Andrade Victor A. Godoi José A. Aravéquia
El Niño is generally associated with negative rainfall anomalies (below-average rainfall) in northern Northeast Brazil (NNEB). In 2019, however, the opposite rainfall pattern was observed during an El Niño episode. Here, we explore the mechanisms that overwhelmed typical El Niño-related conditions and resulted in positive rainfall anomalies (above-average rainfall) in NNEB. We focus on the austral autumn when El Niño is most prone to rainfall anomalies in the region. The analysis of several datasets, including weather station data, satellite data, reanalysis data, and modelled data derived from a dry linear baroclinic model, allowed us to identify that the austral autumn 2019 above-average rainfall in NNEB was likely associated with four combined factors; these are (1) the weak intensity of the 2019 El Niño; (2) the negative phase of the Atlantic Meridional Mode; (3) local and remote diabatic heating anomalies, especially over the western South Pacific and tropical South Atlantic, which resulted in anticyclonic and cyclonic circulations in the upper and lower troposphere, respectively, over the tropical South Atlantic; and (4) sub-seasonal atmospheric convection anomalies over the western South Pacific, which reinforced the low-frequency convection signal over that region. This latter factor suggests the influence of the Madden–Julian Oscillation on rainfall in NNEB during the first ten days of March 2019. We discuss these mechanisms in detail and provide evidence that, even during an El Niño event, above-average rainfall in NNEB in the austral autumn may occur, and its modulation is not limited to the influence of a single climate phenomenon. Our results may assist in the planning of several crucial activities, such as water resources management and agriculture.
]]>Meteorology doi: 10.3390/meteorology2030018
Authors: Rae-Seol Park Song-You Hong
In atmospheric models, the representation of cloudiness is a direct linkage between the moisture amount and associated radiative forcing. This paper begins by providing a review of the parameterization of cloudiness that has been used for numerical weather predictions and climate studies. The inherent uncertainties in representing a partial fraction of clouds for radiation feedback and in evaluating it against the corresponding observations are focused. It is also stated that the major hydrometeor categories of water substances such as cloud ice and water that are responsible for cloud cover are readily available in modern weather and climate models. Inconsistencies in cloud cover and hydrometeors, even in the case of the prognostic method, are discussed. The compensating effect of cloudiness for radiative feedback is found to imply that the condensed water amount itself is more influential on the radiative forcing, rather than the accuracy of the cloudiness. Based on the above perspectives, an alternative diagnostic parameterization method is proposed, utilizing a monotonic relation between the cloud water amounts and cloudiness that are obtained from aircraft and satellite observations. The basic premise of this approach lies in the accuracy of the water substance in the models, indicating that future efforts need to be given to improvements in physical processes concerning hydrometeor properties for the accurate representation of cloud radiative feedback.
]]>Meteorology doi: 10.3390/meteorology2020017
Authors: Nicholas John Cook
Most damage to buildings across the contiguous United States, in terms of number and total cost, is caused by gusts in convective events associated with thunderstorms. Their assessment relies on the integrity of meteorological observations. This study examines the impact on risk due to valid gust observations culled erroneously by the real-time quality control algorithm of the US Automated Surface Observation System (ASOS) after 2013. ASOS data before 2014 are used to simulate the effect of this algorithm at 450 well-exposed stations distributed across the contiguous USA. The peak gust is culled in around 10% of these events causing significant underestimates of extreme gusts. The full ASOS record, 2000–2021, is used to estimate and map the 50-year mean recurrence interval (MRI) gust speeds, the conventional metric for structural design. It is concluded that recovery of erroneously culled observations is not possible, so the only practical option to eliminate underestimation is to ensure that the 50-year MRI gust speed at any given station is not less than the mean for nearby surrounding stations. This also affects stations where values are legitimately lower than their neighbors, which represents the price that must be paid to eliminate unacceptable risk.
]]>Meteorology doi: 10.3390/meteorology2020016
Authors: Günther Heinemann Lukas Schefczyk Rolf Zentek Ian M. Brooks Sandro Dahlke Andreas Walbröl
Regional climate models are a valuable tool for the study of the climate processes and climate change in polar regions, but the performance of the models has to be evaluated using experimental data. The regional climate model CCLM was used for simulations for the MOSAiC period with a horizontal resolution of 14 km (whole Arctic). CCLM was used in a forecast mode (nested in ERA5) and used a thermodynamic sea ice model. Sea ice concentration was taken from AMSR2 data (C15 run) and from a high-resolution data set (1 km) derived from MODIS data (C15MOD0 run). The model was evaluated using radiosonde data and data of different profiling systems with a focus on the winter period (November–April). The comparison with radiosonde data showed very good agreement for temperature, humidity, and wind. A cold bias was present in the ABL for November and December, which was smaller for the C15MOD0 run. In contrast, there was a warm bias for lower levels in March and April, which was smaller for the C15 run. The effects of different sea ice parameterizations were limited to heights below 300 m. High-resolution lidar and radar wind profiles as well as temperature and integrated water vapor (IWV) data from microwave radiometers were used for the comparison with CCLM for case studies, which included low-level jets. LIDAR wind profiles have many gaps, but represent a valuable data set for model evaluation. Comparisons with IWV and temperature data of microwave radiometers show very good agreement.
]]>Meteorology doi: 10.3390/meteorology2020015
Authors: Thomas A. Andretta
A heuristic technique for tornado forecasting in the complex terrain of southern Wyoming is proposed for the weather sciences community. This novel approach is based on seasonal tornado climatology and observed mesoscale conditions obtained from in-situ surface and Doppler weather radar sources. The methodology is applied to four severe thunderstorm events which formed tornadoes during the spring and summer months of 2018 and 2019 in Albany County of Wyoming. Tornadic evolution is associated with supercell thunderstorms forming along moisture convergence axes of a dryline and updraft interactions with air mass stretching and shearing over the complex terrain. Applying Bayes’ theorem to each case, there is a low to high (30 to 80%) posterior probability associated with vortex detection.
]]>Meteorology doi: 10.3390/meteorology2020014
Authors: Matej Ogrin Domen Svetlin Sašo Stefanovski Barbara Lampič
Although the urban heat island (UHI) phenomenon is more commonly studied in summer, its influence is also important in winter. In this study, the authors focused on the winter UHI in Ljubljana (Slovenia) and its impact on the urban population, as well as in comparison with a UHI study from 2000. Through a combination of mobile and stationary temperature measurements in different parts of the city, the winter intensity of the UHI in Ljubljana was studied in a dense spatial network of measurements. It was found that the intensity of the winter UHI in Ljubljana decreases as winters become warmer and less snowy. The results showed that the winter UHI in Ljubljana intensifies during the night and reaches the greatest intensity at sunrise. During the winter radiation type of weather, the warmest part of Ljubljana reaches an intensity of 3.5 °C in the evening. In total, 22% of the urban area is in the evening UHI intensity range of 2–4 °C, and 65% of the urban population lives in this range. In the morning, the UHI in Ljubljana has a maximum intensity of 5 °C. The area of >4 °C UHI intensity covers 7% of the urban area, and 28% of the total urban population lives in this area. Higher temperatures in urban centers in winter lead to a longer growing season, fewer snow cover days, lower energy consumption and cold stress, and lower mortality from cold-related diseases compared to the colder periphery.
]]>Meteorology doi: 10.3390/meteorology2020013
Authors: Christopher J. Slocum Richard K. Taft James P. Kossin Wayne H. Schubert
Just before making landfall in Puerto Rico, Hurricane Maria (2017) underwent a concentric eyewall cycle in which the outer convective ring appeared robust while the inner ring first distorted into an ellipse and then disintegrated. The present work offers further support for the simple interpretation of this event in terms of the non-divergent barotropic model, which serves as the basis for a linear stability analysis and for non-linear numerical simulations. For the linear stability analysis the model’s axisymmetric basic state vorticity distribution is piece-wise uniform in five regions: the eye, the inner eyewall, the moat, the outer eyewall, and the far field. The stability of such structures is investigated by solving a simple eigenvalue/eigenvector problem and, in the case of instability, the non-linear evolution into a more stable structure is simulated using the non-linear barotropic model. Three types of instability and vorticity rearrangement are identified: (1) instability across the outer ring of enhanced vorticity; (2) instability across the low vorticity moat; and (3) instability across the inner ring of enhanced vorticity. The first and third types of instability occur when the rings of enhanced vorticity are sufficiently narrow, with non-linear mixing resulting in broader and weaker vorticity rings. The second type of instability, most relevant to Hurricane Maria, occurs when the radial extent of the moat is sufficiently narrow that unstable interactions occur between the outer edge of the primary eyewall and the inner edge of the secondary eyewall. The non-linear dynamics of this type of instability distort the inner eyewall into an ellipse that splits and later recombines, resulting in a vorticity tripole. This type of instability may occur near the end of a concentric eyewall cycle.
]]>Meteorology doi: 10.3390/meteorology2020012
Authors: Johnny C. L. Chan
This paper presents the latest analyses and integrates results of many past studies on the spatial and temporal variations of the annual frequency and intensity of tropical cyclones (TCs) making landfall along different areas of the East Asian (EA) coast. Future projections of such variations based on the past investigations are also presented. No statistically significant trend in the number of landfalling TCs could be identified in most of the EA coastal regions, except for an increasing one in Vietnam and a decreasing one in South China. Multi-decadal as well as interannual variations in the frequency of landfalling TCs are prevalent in almost all the EA coastal regions. Only TCs making landfall in Vietnam and the Korean Peninsula showed an increase in landfall intensity, with no trend in the other regions. Nevertheless, more intense landfalling TCs were evident in most regions during the past two decades. Multidecadal variations were not observed in some regions although interannual variations remained large. Various oscillations in the atmospheric circulation and the ocean conditions can largely explain the observed changes in the frequency and intensity of landfalling TCs in different regions of the EA coast. In the future, most climate models project a decrease in the number of TCs making landfall but an increase in the intensity of these TCs in all the EA coastal regions, especially for the most intense ones.
]]>Meteorology doi: 10.3390/meteorology2020011
Authors: Wayne Schubert Richard Taft Christopher Slocum
This review discusses a simple family of models capable of simulating tropical cyclone life cycles, including intensification, the formation of the axisymmetric version of boundary layer shocks, and the development of an eyewall. Four models are discussed, all of which are axisymmetric, f-plane, three-layer models. All four models have the same parameterizations of convective mass flux and air–sea interaction, but differ in their formulations of the radial and tangential equations of motion, i.e., they have different dry dynamical cores. The most complete model is the primitive equation (PE) model, which uses the unapproximated momentum equations for each of the three layers. The simplest is the gradient balanced (GB) model, which replaces the three radial momentum equations with gradient balance relations and replaces the boundary layer tangential wind equation with a diagnostic equation that is essentially a high Rossby number version of the local Ekman balance. Numerical integrations of the boundary layer equations confirm that the PE model can produce boundary layer shocks, while the GB model cannot. To better understand these differences in GB and PE dynamics, we also consider two hybrid balanced models (HB1 and HB2), which differ from GB only in their treatment of the boundary layer momentum equations. Because their boundary layer dynamics is more accurate than GB, both HB1 and HB2 can produce results more similar to the PE model, if they are solved in an appropriate manner.
]]>Meteorology doi: 10.3390/meteorology2010010
Authors: Edoardo Bucchignani
The importance of meteorological events is felt in everyday life and the critical impact of the weather on human activities has led to the development of the science of weather forecasting [...]
]]>Meteorology doi: 10.3390/meteorology2010009
Authors: Károly Tar Andrea Bíróné Kircsi
In addition to dynamic methods, purely statistical models, i.e., findings from the statistical analysis of the existing measured database, also play an important role in predicting the different characteristics of climate elements. In our article, we try to estimate the monthly amount of global radiation in each day of the month. In our previous articles, we presented the sliding-average model developed for estimating the average or amount of a climatic element, measured over a time interval, from within the interval. A version of this model for estimating the end-of-interval sums, the sliding-sum model, was used to estimate the amount of monthly global radiation. After generating the characteristics required for the estimation and analyzing their properties, we examined the errors of the performed estimation. Our model can also help solar energy users create the schedule.
]]>Meteorology doi: 10.3390/meteorology2010008
Authors: Paul Joe GyuWon Lee Kwonil Kim
The Women’s Slope Style event of 11–12 February 2018 at the PyeongChang 2018 Olympic Winter Games posed considerable challenges to the competitors and decision-makers, requiring sub-kilometer and sub-minute weather predictions in complex terrain. The gusty wind conditions were unfair and unsafe as the competitors could not achieve sufficient speed to initiate or complete their jumps. The term micro-nowcasting is used here to reflect the extreme high-resolution nature of these science and service requirements. The World Meteorological Organization has conducted several research development and forecast demonstration projects to advance, accelerate and promote the art of nowcasting. Data from compact automatic weather stations, located along the field of play, reported every minute and were post-processed using time series, Hovmöller and wavelet transforms to succinctly present the information. The analyses revealed dominant frequencies of about 20 min, presumed to be associated with vortex shedding from the mountain ridges, but were unable to directly capture the gusts that affected the competitors. The systemic challenges from this and previous projects are reviewed. They include the lack of adequate scientific knowledge of microscale processes, gaps in modeling, the need for post-processing, forecast techniques, managing ever-changing service requirements and highlights the role of observations and the critical role of the forecaster. These challenges also apply to future high-resolution operational weather and warning services.
]]>Meteorology doi: 10.3390/meteorology2010007
Authors: Juerg Schmidli Julian Quimbayo-Duarte
Thermally driven local winds are ubiquitous in deep Alpine valleys during fair weather conditions resulting in a unique wind climatology for any given valley. The accurate forecasting of these local wind systems is challenging, as they are the result of complex and multi-scale interactions. Even more so, if the aim is an accurate forecast of the winds from the near-surface to the free atmosphere, which can be considered a prerequisite for the accurate prediction of mountain weather. This study combines the evaluation of the simulated surface winds in several Alpine valleys with a more detailed evaluation of the wind evolution for a particular location in the Swiss Rhone valley, at the town of Sion during the month of September 2016. Four numerical simulations using the COSMO model are evaluated, two using a grid spacing of 1.1 km and two with a grid spacing of 550 m. For each resolution, one simulation is initialised with the soil moisture from the COSMO analysis and one with an increased soil moisture (+30%). In a first part, a comparison with observations from the operational measurement network of MeteoSwiss is used to evaluate the model performance, while, in a second part, data from a wind profiler stationed at Sion airport is used for a more detailed evaluation of the valley atmosphere near the town of Sion. The analysis focuses on 18 valley wind days observed in the Sion region in September 2016. Only the combination of an increased soil moisture and a finer grid spacing resulted in a significant improvement of the simulated flow patterns in the Sion region. This includes a stronger and more homogeneous along-valley wind in the Wallis and a more realistic cross-valley wind and temperature profile near the town of Sion. It is shown that the remaining differences between the observed and simulated near-surface wind are likely due to very local topographic features. Small-scale hills, not resolved on even the finer model grid, result in a constriction of the valley cross section and an acceleration of the observed low-level up-valley wind in the region of Sion.
]]>Meteorology doi: 10.3390/meteorology2010006
Authors: Pedro Silva Miguel Carmo João Rio Ilda Novo
The length of the fire season has not garnered much attention within the broad field of meteorological research on fire regime change. Fire weather research on the Iberian Peninsula is no exception in this case; there is no solid understanding on fire season lengthening in Portugal, although recent decades do suggest ongoing transitions. Based on a complete record of fire occurrence and burned area between 1980 and 2018, we first searched for consistent trends in the monthly distribution of fire activity. To determine day-scale changes, an exceedance date method based on annual cumulative burned area was developed. Results show an early onset of fire activity in a range of 23–50 days and no significant extension into autumn, suggesting that existing projections of the lengthening of the fire season in Portugal over the present century have been already achieved. Fire weather results show a trend in the cumulative Daily Severity Rating (DSR), with the last two decades (2000–2018) displaying an early build-up of meteorological fire danger in late spring and early summer. The detailed spatio-temporal analysis based on the daily Fire Weather Index (FWI) shows that June stands out with the largest increase (year-round) in days per month with an FWI above 38.3, the threshold above which fire conditions make suppression uncertain. This aggravated fire weather is likely sustaining early fire activity, thus contributing to a longer critical fire season.
]]>Meteorology doi: 10.3390/meteorology2010005
Authors: Meteorology Editorial Office Meteorology Editorial Office
High-quality academic publishing is built on rigorous peer review [...]
]]>Meteorology doi: 10.3390/meteorology2010004
Authors: Man-Lok Chong Hon-Yin Yeung Kai-Kwong Hon
Temperatures over Hong Kong have shown a marked increasing trend since the 1970s due to global warming and urbanization, but outbreaks of intense winter monsoon can bring very low temperatures in Hong Kong at times. This study aims at establishing criteria of extreme cold surges that suit the climatological characteristics of Hong Kong. Surges in this study were selected through percentile ranking of three weather attributes of each cold event: the lowest temperature, the largest temperature drop and the maximum sustained wind speed. Out of 152 cold events in 1991–2020, only four significant cold events in 1991, 1993, 2010 and 2016 met the most extreme 10th percentile of the three attributes concurrently and could be classified operationally as “extreme cold surge”. Very cold temperatures (at or below 7.0 °C), a temperature drop of at least 8.0 °C in two days and gale force wind speed (at or above 17.5 m/s) were recorded in all four surges. The results of classification are illustrated by selected cases. As ensemble products of some numerical weather prediction models tend to have a stable indication of extremity of cold events, the potential applications of cross-referencing the forecast and actual extremity in operational forecasting are also discussed.
]]>Meteorology doi: 10.3390/meteorology2010003
Authors: Kinga Kulesza
The paper aims to analyse the relationship between the amount of global solar radiation (GSR) reaching the Earth’s surface in Poland and the direction of air mass advection, using 72-h backward trajectories (1986–2015). The study determined average daily sums of GSR related to groups of trajectories with certain similarities in shape. It was found that the average daily sums of GSR during air mass inflow from all the directions (clusters) identified were significantly different from the average daily sum in the multi-year period. A significant increase in the amount of GSR over Poland is accompanied by air mass inflow from the north and east. The frequency of these advection directions is 27% of all days. The western directions of advection prompt different GSR sums: from slightly increased during advection from the north-west, to significantly decreased during advection from the west (from the central and western part of the North Atlantic). Special attention was given to days with extremely large (above the 0.95 percentile) and with the largest (above the 0.99 percentile) GSR sums. These are prompted by two main types of synoptic conditions: the Azores High ridge covering Central and Southern Europe; and the high-pressure areas which appear in Northern and Central Europe.
]]>Meteorology doi: 10.3390/meteorology2010002
Authors: Telmo Cosme A. Sumila Simone E. T. Ferraz Angelica Durigon
Unlike global and regional assessments, the spatio-temporal variability of air temperature and precipitation, caused by climate change, must be more useful when the assessment is made at the sub-regional to local scale. Thus, this study aims to assess the possible changes in air temperature and precipitation in patterns for the late 21st century relative to the present climate in Mozambique. The regional model, RegCM4, driven by the global model HadGEM2, was used to perform the downscaling process under two Representative Concentration Pathways (RCPs), moderate RCP4.5 and strong RCP8.5. The three experiments were analyzed in the baseline (1971–2000) and future (2070−2099) range at the subregional scale in Mozambique. In this study domain, the highest amounts of precipitation and the highest air temperatures are observed during the extended summer season. However, the central region is rather warmer and rainier than the northern- and southernmost regions. Hence, the regional model RegCM4 demonstrated agreement relative to the observed weather stations and interpolated dataset from the Climate Research Unit. The strong performance of RegCM4 is revealed by its more realistic local spatio-temporal climate features, tied to the topography and geographical location of the study domain. The future increases in mean annual air temperature are well simulated by the model but, the spatial distribution and magnitude differ between the RCPs and over each of the three regions throughout the country. The sharp hottest response at the end of 21st century occurs in the summer and spring seasons under RCP8.5, spatially over the central and northern region of the study domain, with a hot-spot in the southern region. There is a predominantly drier response in the annual mean precipitation but, during the summer season, a meridional dipolarization pattern is observed, with the wettest response being over the southernmost region and a drier response in the northern and central regions of Mozambique.
]]>Meteorology doi: 10.3390/meteorology2010001
Authors: Renata Barros Vasconcelos Leirias Natalia Fedorova Vladimir Levit
Some meteorological phenomena in South America develop quickly and take on large dimensions. These phenomena cause disasters for aviation, such as incidents and accidents. Mesoscale convective complexes (MCCs) forced a commercial airplane into an emergency landing at Ezeiza International Airport in Buenos Aires (Argentina) in October 2018. The airplane took off from São Paulo (Brazil) to Santiago (Chile) and had to alternate to Ezeiza after encountering unanticipated agglomerations of MCCs along the flight route; its structure was seriously damaged, which affected the safety of the flight. A synoptic and thermodynamic analysis of the atmosphere, prior to the event, was made based on GOES16 infrared satellite data, radiosonde data, maps of several variables such as stream lines, temperature advection, surface synoptic maps and layer thickness from CPTEC/INPE and NCEP reanalysis data. The main observed processes that influenced the formation and development of conglomerates of MCCs were the following: (1) the cyclogenesis of a baroclinic cyclone on the cold front; (2) the coupling of subtropical and polar jet streams; (3) the advection of warm and humid air along a low-level jet stream. Recommendations for meteorologists in weather forecasting and for aviators in flight safety were prepared.
]]>Meteorology doi: 10.3390/meteorology1040032
Authors: Swapan Mallick
Assimilation of cloud properties in the convective scale ensemble data assimilation system is one of the prime topics of research in recent years. Satellites can retrieve cloud properties that are important sources of information of the cloud and atmospheric state. The Advance Baseline Imager (ABI) aboard the GOES-16 geostationary satellite brings an opportunity for retrieving high spatiotemporal resolution cloud properties, including cloud water path over continental United States. This study investigates the potential impacts of assimilating adaptively thinned GOES-16 cloud water path (CWP) observations that are assimilated by the ensemble-based Warn-on-Forecast System and the impact on subsequent weather forecasts. In this study, for CWP assimilation, multiple algorithms have been developed and tested using the adaptive-based thinning method. Three severe weather events are considered that occurred on 19 July 2019, 7 May and 21 June 2020. The superobbing procedure used for CWP data smoothed from 5 to 15 km or more depending on thinning algorithm. The overall performance of adaptively thinned CWP assimilation in the Warn-on-Forecast system is assessed using an object-based verification method. On average, more than 60% of the data was reduced and therefore not used in the assimilation system. Results suggest that assimilating less than 40% of CWP superobbing data into the Warn-on-Forecast system is of similar forecast quality to those obtained from assimilating all available CWP observations. The results of this study can be used on the benefits of cloud assimilation to improve numerical simulation.
]]>Meteorology doi: 10.3390/meteorology1040031
Authors: Moses B. Farr James V. Gasch Evan J. Travis Sarah M. Weaver Veli Yavuz Inna G. Semenova Oleksandr Panasiuk Anthony R. Lupo
In the Mediterranean and occasionally in the Black Sea, low-pressure systems with the character of both mid-latitude and tropical cyclones can form. These hybrid storms are called subtropical storms, subtropical depressions, medistorms/medicanes, or tropical-like cyclones (TLC). A strong low-pressure system given the name Falchion developed in northern part of the Black Sea during 11–20 August 2021. This storm was blamed for damage and more than 30 casualties in the nations bordering the region. At peak intensity, this storm was a as strong as a tropical depression. Falchion developed and moved northeast, reaching peak intensity before becoming nearly stationary. The NCEP reanalyses and satellite data obtained from Eumetsat’s geostationary satellite, Meteosat-8, were used to examine the character of the storm. This study demonstrates that the movement of Falchion was impeded by a blocking event that occurred over central Asia during much of August 2021. The storm did share characteristics with tropical systems, but a comparison of Falchion to tropical depressions and subtropical storms in the North and South Atlantic demonstrated that this storm was more consistent with these types of storms when examining the storm and the proximal environment. This included an examination of integrated water vapor (IVT) plumes, and the plume associated with Falchion did rise to the character of an atmospheric river in spite of the smaller scale.
]]>Meteorology doi: 10.3390/meteorology1040030
Authors: Zdeněk Janků Petr Dobrovolný
This study used homogenised mean, maximum, and minimum daily temperatures from 12 stations located in Brno, Czechia, during the 2011–2020 period to analyse heat waves (HW) and their impact on the canopy urban heat island (UHI). HWs were recognized as at least three consecutive days with Tx ≥ 30 °C and urban–rural and intra-urban differences in their measures were analysed. To express the HWs contribution to UHI, we calculated the UHI intensities (UHII) separately during and outside of HWs to determine the heat magnitude (HM). Our results show that all HW measures are significantly higher in urban areas. UHII is mostly positive, on average 0.65 °C; however, day-time UHII is clearly greater (1.93 °C). Furthermore, day-time UHII is amplified during HWs, since HM is on average almost 0.5 °C and in LCZ 2 it is even 0.9 °C. Land use parameters correlate well with UHII and HM at night, but not during the day, indicating that other factors can affect the air temperature extremity. Considering a long-term context, the air temperature extremity has been significantly increasing recently in the region, together with a higher frequency of circulation types that favour the occurrence of HWs, and the last decade mainly contributed to this increase.
]]>Meteorology doi: 10.3390/meteorology1040029
Authors: Lisa Thalheimer Dorothy Heinrich Karsten Haustein Roop Singh
Populations around the world have already experienced the increasing severity of extreme weather causing disaster displacement. Anthropogenic climate change can intensify these impacts. Extreme event attribution studies center around the question of whether impactful extreme events could have occurred in a pre-industrial climate. Here, we argue that the next step for attribution science is to focus on those most vulnerable populations to future extremes and impacts from climate change. Up until now, the vulnerability dimension has not been systematically addressed in attribution studies, yet it would add urgently needed context, given the vast differences in adaptive capacity. We propose three integrative points to cascade disaster displacement linked to anthropogenic climate change.
]]>Meteorology doi: 10.3390/meteorology1040028
Authors: Erzsébet Kristóf
In this study, a pattern detection method is applied on the RCP4.5 and RCP8.5 simulation outputs of seven GCMs—disseminated by the Coupled Model Intercomparison Project Phase 5 (CMIP5)—to determine whether atmospheric teleconnection patterns detected in the ERA-20C reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) will be observable in the future projections of the CMIP5 GCMs. The pattern detection technique—which combines the negative extrema method and receiver operating characteristic (ROC) curve analysis—is used on the geopotential height field at the 500 hPa pressure level in wintertime, in the Northern Hemisphere. It was found that teleconnections obtained from the ERA-20C reanalysis dataset for the period of 1976–2005 remain observable in the majority of the GCM outputs under the RCP4.5 and RCP8.5 scenarios for the periods of 2006–2035, 2021–2050, and 2071–2100. The results imply that atmospheric internal variability is the major factor that controls the teleconnections rather than the impact of radiative forcing.
]]>Meteorology doi: 10.3390/meteorology1040027
Authors: Shaun Lovejoy
Since the first climate models in the 1970s, algorithms and computer speeds have increased by a factor of ≈1017 allowing the simulation of more and more processes at finer and finer resolutions. Yet, the spread of the members of the multi-model ensemble (MME) of the Climate Model Intercomparison Project (CMIP) used in last year’s 6th IPCC Assessment Report was larger than ever: model uncertainty, in the sense of MME uncertainty, has increased. Even if the holy grail is still kilometric scale models, bigger may not be better. Why model structures that live for ≈15 min only to average them over factors of several hundred thousand in order to produce decadal climate projections? In this commentary, I argue that alongside the development of “seamless” (unique) weather-climate models that chase ever smaller—and mostly irrelevant—details, the community should seriously invest in the development of stochastic macroweather models. Such models exploit the statistical laws that are obeyed at scales longer than the lifetimes of planetary scale structures, beyond the deterministic prediction limit (≈10 days). I argue that the conventional General Circulation Models and these new macroweather models are complementary in the same way that statistical mechanics and continuum mechanics are equally valid with the method of choice determined by the application. Candidates for stochastic macroweather models are now emerging, those based on the Fractional Energy Balance Equation (FEBE) are particularly promising. The FEBE is an update and generalization of the classical Budyko–Sellers energy balance models, it respects the symmetries of scaling and energy conservation and it already allows for both state-of-the-art monthly and seasonal, interannual temperature forecasts and multidecadal projections. I demonstrate this with 21st century FEBE climate projections for global mean temperatures. Overall, the projections agree with the CMIP5 and CMIP6 multi-model ensembles and the FEBE parametric uncertainty is about half of the MME structural uncertainty. Without the FEBE, uncertainties are so large that climate policies (mitigation) are largely decoupled from climate consequences (warming) allowing policy makers too much “wiggle room”. The lower FEBE uncertainties will help overcome the current “uncertainty crisis”. Both model types are complementary, a fact demonstrated by showing that CMIP global mean temperatures can be accurately projected using such stochastic macroweather models (validating both approaches). Unsurprisingly, they can therefore be combined to produce an optimum hybrid model in which the two model types are used as copredictors: when combined, the various uncertainties are reduced even further.
]]>Meteorology doi: 10.3390/meteorology1040026
Authors: Jimy Dudhia
At multi-kilometer grid scales, numerical weather prediction models represent surface-based convective eddies as a completely sub-grid one-dimensional vertical mixing and transport process. At tens of meters grid scales, large-eddy simulation models, explicitly resolve all the primary three-dimensional eddies associated with boundary-layer transport from the surface and entrainment at the top. Between these scales, at hundreds of meters grid size, is a so-called grey zone in which the primary transport is neither entirely sub-grid nor resolved, where explicit large-eddy models and sub-grid boundary-layer parameterization models fail in different ways that are outlined in this review article. This article also reviews various approaches that have been taken to span this gap in the proper representation of eddy transports in the sub-kilometer grid range using scale-aware approaches. Introduction of moisture with condensation in the eddies expands this problem to that of handling shallow convection, but similarities between dry and cloud-topped convective boundary layers can lead to some unified views of the processes that need to be represented in convective boundary-layers which will be briefly addressed here.
]]>Meteorology doi: 10.3390/meteorology1040025
Authors: Joshua Chun Kwang Lee Huqiang Zhang Dale Melvyn Barker Song Chen Rajesh Kumar Byoung Woong An Kuldeep Sharma Krishnamoorthy Chandramouli
Singapore is a tiny city-state located in maritime Southeast Asia. Weather systems such as localized thunderstorms, squalls, and monsoon surges bring extreme rainfall to Singapore, influencing the day-to-day conduct of stakeholders in many sectors. Numerical weather prediction models can provide forecast guidance, but existing global models struggle to capture the development and evolution of the small-scale and transient weather systems impacting the region. To address this, Singapore has collaborated with international partners and developed regional numerical weather prediction systems. Steady progress has been made, bringing added value to stakeholders. In recent years, complex earth system and ultra high-resolution urban models have also been developed to meet increasingly diverse stakeholder needs. However, further advancement of weather prediction for Singapore is often hindered by existing challenges, such as the lack of data, limited understanding of underlying processes, and geographical complexities. These may be viewed as opportunities, but are not trivial to address. There are also other opportunities that have remained relatively unexplored over Singapore and the region, such as the integration of earth system models, uncertainty estimation and machine learning methods. These are perhaps key research directions that Singapore should embark on to continue ensuring value for stakeholders.
]]>Meteorology doi: 10.3390/meteorology1040024
Authors: Isidora Jankov Zoltan Toth Jie Feng
Numerical models of the atmosphere are based on the best theory available. Understandably, the theoretical assessment of errors induced by the use of such models is confounding. Without clear theoretical guidance, the experimental separation of the model-induced part of the total forecast error is also challenging. In this study, the forecast error and ensemble perturbation variances were decomposed. Smaller- and larger-scale components, separated as a function of the lead time, were independent. They were associated with features with completely vs. only partially lost skill, respectively. For their phenomenological description, the larger-scale variance was further decomposed orthogonally into positional and structural components. An analysis of the various components revealed that chaotically amplifying initial perturbation and error predominantly led to positional differences in forecasts, while structural differences were interpreted as an indicator of the model-induced error. Model-induced errors were found to be relatively small. These results confirmed earlier assumptions and limited empirical evidence that numerical models of the atmosphere may be near perfect on the scales they well resolve.
]]>Meteorology doi: 10.3390/meteorology1040023
Authors: Peter Lynch
A time integration scheme based on semi-Lagrangian advection and Laplace transform adjustment has been implemented in a baroclinic primitive equation model. The semi-Lagrangian scheme makes it possible to use large time steps. However, errors arising from the semi-implicit scheme increase with the time step size. In contrast, the errors using the Laplace transform adjustment remain relatively small for typical time steps used with semi-Lagrangian advection. Numerical experiments confirm the superior performance of the Laplace transform scheme relative to the semi-implicit reference model. The algorithmic complexity of the scheme is comparable to the reference model, making it computationally competitive, and indicating its potential for integrating weather and climate prediction models.
]]>Meteorology doi: 10.3390/meteorology1040022
Authors: Hein Dieter Behr
This study characterizes the spatiotemporal solar radiation and air temperature patterns and their dependence on the general atmospheric circulation characterized by the North Atlantic Oscillation (NAO) Index in Germany from 1991 to 2015. Germany was selected as the study area because it can be subdivided into three climatologically different regions: the North German lowlands are under the maritime influence of the North and Baltic Seas. Several low mountain ranges dominate Germany’s center. In the south, the highest low mountain ranges and the Alps govern solar radiation and air temperature differently. Solar radiation and air temperature patterns were studied in the context of the NAO index using daily values from satellite and ground measurements. The most significant long-term solar radiation increase was observed in spring, mainly due to seasonal changes in cloud cover. Air temperature shows a noticeable increase in spring and autumn. Solar radiation and air temperature were significantly correlated in spring and autumn, with correlation coefficient values up to 0.93. In addition, a significant dependence of solar radiation and air temperature on the NAO index was revealed, with correlation coefficient values greater than 0.66. The results obtained are important not only for studies on the climate of the study area but also for photovoltaic system operators to design their systems. They need to be massively expanded to support Germany’s climate neutrality ambitions until 2045.
]]>Meteorology doi: 10.3390/meteorology1030021
Authors: Charles R. Sampson James Cummings John A. Knaff Mark DeMaria Efren A. Serra
The upper ocean provides a source of thermal energy for tropical cyclone development and maintenance through a series of complex interactions. In this work, we develop a seventeen-year dataset of upper ocean thermal field metrics for use in tropical cyclone studies and development of tropical cyclone intensity prediction models. These metrics include the surface temperature, two different measures of vertically integrated heat content, and four different measures of vertically averaged temperature. Some metrics have been used to study upper-ocean energy response to tropical cyclone passage, while others have been employed to improve operational tropical cyclone intensity prediction models. The vertically integrated ocean heat content has been used to improve tropical cyclone intensity forecasts at U.S. tropical cyclone forecast centers and is an integral part of several operational intensity forecast models. A static 2005–2021 dataset that includes all twelve metrics described within is available on the Naval Research Laboratory web server, and a subset of six metrics have been produced in real-time at Fleet Numerical Meteorology and Oceanography Center and provided to the public via the GODAE server since 2021.
]]>Meteorology doi: 10.3390/meteorology1030020
Authors: Edoardo Bucchignani
In the last few decades there has been increasing interest in the commercial usage of the stratosphere, especially for Earth observation systems. Stratospheric platforms allow Earth monitoring at a regional scale with persistency toward a limited area. For this reason, accurate meteorological forecasts are needed in order to guarantee stationarity. The main aim of this work is to provide a review of wind prediction techniques in the stratosphere, achieved by the most popular global models, such as ECMWF IFS, NCEP GFS and ICON. Then, the capabilities of the COSMO limited area model to reproduce the wind speed in the stratosphere are evaluated considering a model configuration with very high resolution (about 1 km) over a domain located in Southern Italy, assuming the radio sounding data at Pratica di Mare airport as the reference. Vertical profiles were analyzed for selected days, highlighting good performances, though improvements can be achieved by adopting a fifth-order interpolation of the model data. Finally, monthly wind speed time series for selected heights were post-processed by means of fast Fourier transform, revealing the existence of main frequencies and the presence of a scaling regime and a power law of the form f−β over a broad range of time scales, in the Fourier space. The exponent spectral β is close to the exact 5/3 Kolmogorov value for all the datasets.
]]>Meteorology doi: 10.3390/meteorology1030019
Authors: Pao K. Wang
The theoretical studies on the flow fields around falling cloud and precipitation particles are briefly reviewed. The hydrodynamics of these particles, collectively called hydrometeors, are of central importance to cloud development and dissipation, which impact both the short-term weather and long-term climate processes. This review focuses on the solutions of the appropriate Navier–Stokes equations around the falling hydrometeor, particularly those obtained by numerical methods. The hydrometeors reviewed here include cloud drops, raindrops, cloud ice crystals, snow aggregates, conical graupel, and smooth and lobed hailstones. The review is made largely in chronological order so that readers can obtain a sense of how the research in this field has progressed over time. Although this review focuses on theoretical studies, brief summaries of laboratory experiments and field observations on this subject are also provided so as to substantiate the calculation results. An outlook is given at the end to describe future works necessary to improve our knowledge in this area.
]]>Meteorology doi: 10.3390/meteorology1030018
Authors: Dóra Cséke István Ihász
Forecasts of precipitation type are of high priority, as they have a large influence on human safety, the economy and the environment. In recent decades, methods of statistical post-processing of numerical weather prediction (NWP) outputs were only applied beside the experience of the operational forecasters. In the last few years, numerical models developed significantly; thus, precipitation type has become a variable directly calculated in some models. In the European Centre for Medium-Range Weather Forecasts (ECMWF) integrated forecast system (IFS) model, a new method has been used since 2015 to predict the type of precipitation. In this study, we examine the forecast of the ECMWF IFS ensemble model concerning precipitation type through ensemble verification and a case study on a freezing-rain situation for the territory of Hungary. We put emphasis on the investigation of the usability of ensemble forecasts. We introduce the developed forms of visualization supporting the interpretation of ensemble precipitation-type forecasts.
]]>Meteorology doi: 10.3390/meteorology1030017
Authors: Shweta Singh Norbert Kalthoff
This study investigated the relevant processes responsible for differences of convective precipitation caused by land-surface resolution. The simulations were performed with the ICOsahedral Nonhydrostatic model (ICON) with grid spacing of 156 m and Large Eddy Simulation physics. Regions of different orographic complexity, days with weak synoptic forcing and favourable convective conditions were selected. The resolution of land-surface properties (soil type, vegetation) and/or the orography was reduced from 156 to 5000 m. Analyses are based on backward trajectories (Lagrangian Analysis Tool (LAGRANTO)), heat budget and convective organisation potential (COP) calculations. On average, the relative difference of areal mean daily precipitation at 1250 and 5000 m land-surface resolutions compared to 156 m were 6% and 15%, respectively. No consistent dependency of precipitation on orography or land-surface properties was found. Both factors impact convective initiation over areas with embedded mesoscale-sized land-surface heterogeneities. The position of convective precipitation was often influenced by the resolution of orography. Coarsening from 156 to 5000 m considerably changed the location of wind convergence and associated convection initiation. It also affects the onset times of clouds (<20 min) and precipitation (≈1 h). Cloud aggregation and microphysical processes proved to be important for further development towards convective precipitation.
]]>Meteorology doi: 10.3390/meteorology1030016
Authors: Yiwen Xu
The Meteo-France seasonal forecasting system 7 provides a 7-month forecast range with 25 ensembles. The seasonal precipitation re-forecast (from May to November 1993–2015) was evaluated by the Brier score in terms of accuracy and reliability based on tercile probabilities. Multiple analyses were performed to assess the robustness of the score. These results show that the spatial distribution of the Brier score depends significantly on tercile thresholds, reference data, sampling methods, and ensemble types. Large probabilistic errors over the dry regions on land and the Nino regions in the Pacific can be reduced by adjusting the tercile thresholds. The forecast errors were identified when they were insensitive to different analysis methods. All the analyses detected that the errors increase/decrease with the lead time over the tropical Indian/Pacific Ocean. The intra-seasonal analysis reveals that some of these errors are inherited from monthly forecasts, which may be related to large-scale, short-term variability modes. A new confidence interval calculation was formulated for the “uncertain” case in the reference data. The confidence interval at a 95% level for the mean Brier score over the entire tropical region was quantified. The best estimations are ~6% the mean Brier score for both the above and below-normal terciles.
]]>Meteorology doi: 10.3390/meteorology1020015
Authors: Jorge Gonzalo N. Irisarri Pablo A. Cipriotti Marcos Texeira Matias H. Curcio
Due to ongoing global warming, seasonal patterns of aboveground net primary production (ANPP) may be altered by temperature trends. Of particular interest is the seasonal association between ANPP and temperature at the beginning of the growing season (the period encompassing minimum to maximum ANPP), where two contrasting mechanisms are in tension. On the one hand, the restrictions exerted by low temperatures in winter may be relaxed, increasing the slope of seasonal association between ANPP and temperature over the years. On the other hand, increases in temperature may increase water demand, reducing the slope over time. Across 543 wetland meadow areas in Patagonia, we estimated ANPP and obtained temperature records on a monthly basis from 2001 to 2019. The seasonal association between ANPP and temperature, tested through linear regression, was statistically significant in 96% of the cases (9921/10317 (543 wetland areas × 19 growing seasons)). The fitted linear models explained, on average, 84% of ANPP seasonal (June–December) variations. Through regression trees, we found out that the two tested mechanisms, the relaxation of temperature restriction and the increase in water demand, showed clear spatial patterns. The relaxation due to temperature increase took place at higher latitudes, but the water-limiting mechanism increased over mid-latitude areas.
]]>Meteorology doi: 10.3390/meteorology1020014
Authors: Tyler J. Mitchell Paul A. Knapp Jason T. Ortegren
We analyzed summertime (June–August) cold-front activity via frequency and duration in the southeastern USA during 1973–2020 to summarize and identify the temporal trends of the annual and total number of hours associated with cold fronts, cold-front days, and multi-day cold-front events. Using data from 34 ASOS Network stations, we defined summertime cold fronts as events that lowered the dew point temperature below 15.56 °C (< 60 °F). Additionally, we examined 500 hPa geopotential height anomalies associated with years with cold front frequency/duration deviations of +/− 1.0 SD. The extent of the cold-front activity exhibited a north–south latitudinal gradient with a more southerly latitudinal expression on the east side of the Appalachian Mountains and was negligible south of the 30°N latitude. The cold-front activity was most prominent during the first half of June. Our results suggest that all three metrics of summertime cold-front activity were stable at a regional scale during the 48-year study period with a few (three–five) stations experiencing significant decreases. A regional-scale stability was coincident with significant increases in minimum, maximum, and average summertime temperatures in the southeastern USA. Years with either above-average or below-average cold-front activity were concurrent with synoptic conditions that supported either troughing or ridging in the southeastern USA. We conclude that the observed weakening in the southeastern USA warming hole is the result of external and/or internal forcings unrelated to reductions in anomalously cool summer weather.
]]>Meteorology doi: 10.3390/meteorology1020013
Authors: Anthony C. Bernal Ayala Angela K. Rowe Lucia E. Arena Ankur R. Desai
Córdoba Province in Argentina is a global hotspot for deep hail-producing storms. Previous studies of hail formation and detection largely relied on satellite snapshots or modeling studies, but lacked hail validation, relying instead on proxy metrics. To address this limitation, this study used hail collected in the mountainous Córdoba region in collaboration with the citizen science program “Cosecheros de Granizo 2018–2020” including from a record-breaking hail event and from the 2018–2019 RELAMPAGO field campaign. Three cases including a MCS and two supercells, which have verified hail in different environment locations relative to the Sierras de Córdoba, were analyzed for multi-spectral signatures in GOES-16 satellite data. Brightness temperatures decreased over time after convective initiation, reaching values cooler than the tropopause with variations around those values of different magnitudes. Overall, all cases exhibited a slight weakening of the updraft and strong presence of smaller ice crystal sizes just prior to the hail report, especially for the larger hailstones. The results demonstrate promise in using satellite proxies for hail detection in multiple environments for different storm modes. The long-term goal is to better understand hail-producing storms and unique challenges of forecasting hail in this region.
]]>Meteorology doi: 10.3390/meteorology1020012
Authors: William A. Gough Andrew C. W. Leung
Sixty-four airport climate records were examined across Canada. Day-to-day (DTD) temperature variability metrics were used to assess the nature of the local environment. In total, 86% of the airports were assessed as peri-urban, reflective of either their location at the fringe of the urban centers or the creation of a peri-urban microclimate by the airport itself. The remaining nine stations were identified using a previously identified metric as marine, or “mountain”, a new category developed in this study. The analysis included a proposal for a decision flow chart to identify the nature of the local climate based on DTD thermal variability. An analysis of the peri-urban thermal metric and population indicated that a peri-urban climate was consistently identified for airports independent of the magnitude of the local population (or urbanization), lending support to the idea of a localized “airport” climate that matched peri-urban characteristics.
]]>Meteorology doi: 10.3390/meteorology1020011
Authors: Michael Edgeworth McIntyre
This essay takes a brief personal look at aspects of the climate problem. The emphasis will be on some of the greatest scientific uncertainties, as suggested by what is known about past as well as present climates, including tipping points that likely occurred in the past and might occur in the near future. In the current state of knowledge and understanding, there is massive uncertainty about such tipping points. For one thing, there might or might not be a domino-like succession, or cascade, of tipping points that ultimately sends the climate system into an Eocene-like state, after an uncertain number of centuries. Sea levels would then be about 70 m higher than today, and surface storminess would likely reach extremes well outside human experience. Such worst-case scenarios are highly speculative. However, there is no way to rule them out with complete confidence. Credible assessments are outside the scope of current climate prediction models. So there has never in human history been a stronger case for applying the precautionary principle. Today there is no room for doubt—even from a purely financial perspective—about the need to reduce greenhouse gas emissions urgently and drastically, far more than is possible through so-called “offsetting”.
]]>Meteorology doi: 10.3390/meteorology1020010
Authors: Albenis Pérez-Alarcón José C. Fernández-Alvarez
In this study, we evaluated the ability of the Numerical Tools for Hurricane Forecast (NTHF) system, operational at the Department of Meteorology of the Higher Institute of Technologies and Applied Sciences, University of Havana, Cuba, for forecasting the intensity and trajectory of the North Atlantic (NATL) tropical cyclones (TCs). To assess the ability of the NTHF system in the first five years (2016–2020) of operational runs, we used the best tracks from the National Hurricane Center HURDAT2 database. The errors in the track forecast increased linearly from 41 km at 6 h to 356 km at 120 h. In addition, NTHF underestimates the intensity of TCs, especially those that reach Category 3+ hurricanes on the Saffir–Simpson wind scale. Overall, the mean absolute error in forecasting the maximum wind speed (minimum pressure) ranged from 26.5 km/h (7 hPa) to 33.7 km/h (11.7 hPa). Moreover, the highest BIAS in the intensity forecast was found in the first 48 h, suggesting that model initialization is the main driver of NTHF errors in the forecast maximum wind speed and the minimum central pressure of TCs in the North Atlantic Basin.
]]>Meteorology doi: 10.3390/meteorology1020009
Authors: Arik Tashie
The water-energy balance of many mid-latitude watersheds has been changing in recent decades due to global warming. These changes manifest themselves over both long timescales (e.g., hydrologic drought) and short timescales (e.g., agricultural drought) and may be ameliorated or exacerbated by vegetative response. We apply a Budyko framework to assess short-term response to long-term trends in water and heat stress (HS) across mid-latitude North America. Using high-resolution meteorological data and streamflow records, we calculate the frequency of HS every year since 1980 for every gaged watershed with adequate data (n = 1528). We find that HS has become more frequent in most watersheds in the western US, New England, and southeastern Canada. However, we find that HS has become less frequent in the Midwest and the relatively humid eastern US. By assessing the relationship between trends in HS frequency and proximate forcing variables (annual PPT, annual streamflow, minimum and maximum daily temperatures, actual evapotranspiration, and potential evapotranspiration), we find that these trends in HS frequency are primarily driven by meteorological forcings rather than vegetative response. Finally, we contextualize our findings within the Budyko framework, which assumes a landscape in equilibrium with its climate, with the implication that these trends in HS are only likely to be realized after local vegetation has adapted to new meteorological norms.
]]>Meteorology doi: 10.3390/meteorology1020008
Authors: Weihong Qian Jun Du
To reduce numerical instability and increase forecast accuracy of a numerical weather prediction (NWP) model, one approach is to subtract a reference atmosphere from atmospheric governing equations. In the past, scientists have proposed one-dimensional, two-dimensional, and three-dimensional static (in time) reference atmospheres with respect to temperature and pressure. These three reference atmospheres were first reviewed, and their corresponding perturbation equations were derived. Then, a new four-dimensional (space and time) all-variable (temperature, pressure, wind, moisture, etc.) reference atmosphere was defined using observed climatic states. Unlike the previous three approaches, the perturbations derived from this new method are actual anomalies relative to climate and directly a part of individual weather systems in both structure and strength. By subtracting climatic states, anomaly equations were derived and analyzed. Finally, the benefits and challenges of the anomaly-equation-based NWP model were discussed. Theoretically, an anomaly model should reduce model systematic errors (bias) and should avoid model climate drift to significantly enhance a model’s performance. An example of tropical cyclone track forecasts using the Beta advection model (vorticity) was demonstrated. The separation of model physics into climatic and anomalous physics is a significant challenge if a pure anomaly-equation-based NWP model is desired. Fortunately, a model including both anomaly and climatic equations should work with current full physics. In an anomaly climate mixed model, the anomaly part needs to be predicted and the climate parts are precalculated constants. It is hoped that this study will inspire model developers to explore the approach, which could be a possible new direction in developing next-generation NWP models. A high-resolution reanalysis is also key to the success of this new approach.
]]>Meteorology doi: 10.3390/meteorology1020007
Authors: Boris S. Yurchak
Tropical cyclone (TC) intensity observations considerably improve forecast models. They are particularly used to continuously measure TC intensity for landfalling cyclones to improve their forecast. For example, TC Irving, which operated in the Gulf of Tonkin, South China Sea, on 23–24 July 1989, was observed by a conventional weather radar installed at the Phu Lien Observatory in North Vietnam. The maximum wind speed was calculated by the hyperbolic-logarithmic approximation (HLS-approximation) of spiral cloud-rain bands (SCRBs) of recorded TC radar images. The data spanned about 15 h. Ground-based estimates of the cyclone intensity were obtained from pressure measurements at two coastal weather stations. A comparison of these estimates with the HLS wind resulting from the HLS approximation of SCRBs showed satisfactory synchronization. In particular, radar and meteorological data indicated cyclone intensification near landfall and rapid cyclone intensification after landfall. Both intensifications were accompanied by polygonal eye shapes. This study demonstrates the feasibility of using the HLS-approximation technique for retrieving TC intensity variation from conventional weather radar data.
]]>Meteorology doi: 10.3390/meteorology1010006
Authors: Yi-Leng Chen Chuan-Chi Tu Feng Hsiao Ching-Sen Chen Pay-Liam Lin Po-Hsiung Lin
During the early summer rainy season over Taiwan, three types of low-level jets are observed, including a synoptic low-level jet (SLLJ) situated in the 850–700 hPa layer in the frontal zone, a marine boundary layer jet (MBLJ) embedded within the southwesterly monsoon flow over the northern South China Sea at approximately the 925 hPa level, and an orographically induced jet at approximately the 1 km level off the northwestern Taiwan coast (e.g., barrier jet (BJ)). The characteristics and physical processes of the formation of these three types of low-level jets are reviewed, and their roles in the development of heavy rainfall are discussed.
]]>Meteorology doi: 10.3390/meteorology1010005
Authors: Madeline A. Est Samuel Mount Christopher A. Steward Anthony R. Lupo
Studies have shown that maxima in the time series of Northern Hemisphere (NH) integrated enstrophy (IE) can be associated with large-scale flow regime transitions and, often, the onset and decay of blocking events. During February and March 2019, and then February 2021, strong IE maxima were associated with changes in the NH flow regimes that brought very cold conditions to the central United States. The colder conditions in the central USA during late winter 2019 and 2021 were also associated with very strong Pacific or Atlantic Region blocking events. Using the NCEP re-analyses, three different teleconnection indexes, and surface weather data from nine different cities in the central USA, IE maxima, flow regime transitions, and surface weather regimes are identified. The mean temperature and precipitation characteristics for the cities named here during the different large-scale flow regime characteristics are compared. The results have demonstrated that relatively warm conditions occurred through the first part of February 2019 before a period of anomalously colder (as much as 12 °C below normal) and drier weather, with more snow, persisted into early March. This period was bookended by maxima in the NH IE time series, changes in the character of the main NH teleconnection indexes, and a strong simultaneous NH blocking episode. Following the cold period, the temperature regime returned to values that were closer to seasonal normal values, which were then discussed as a possible indicator of a transition from a winter to a spring regime.
]]>Meteorology doi: 10.3390/meteorology1010004
Authors: Fabio Zimbo Daniele Ingemi Guido Guidi
In this paper, we analyze a Mediterranean TLC (tropical-like cyclone) which occurred between 15 and 20 September 2020 called “Ianos”. First, the paper briefly presents the “medicane” phenomenon; then, it analyzes the synoptic situation that produced Ianos initiation and development, as well as its intensity (minimum pressure, wind speed) and trajectory. A comparison with similar past events is also provided. Furthermore, we analyze its lightning activity, rainfall data from some meteorological stations of the areas most affected by Ianos, such as Calabria and the Ionian islands of Greece, and the hydrogeological and hydraulic instability effects caused by the passage of the TLC on these territories.
]]>Meteorology doi: 10.3390/meteorology1010003
Authors: Adrian F. Tuck
The path from molecular to meteorological scales is traced and reviewed, beginning with the persistence of molecular velocity after collision induces symmetry breaking, from continuous translational to scale invariant, associated with the emergence of hydrodynamic behaviour in a Maxwellian (randomised) population undergoing an anisotropic flux. An empirically based formulation of entropy and Gibbs free energy is proposed and tested with observations of temperature, wind speed and ozone. These theoretical behaviours are then succeeded upscale by key results of statistical multifractal analysis of airborne observations on horizontal scales from 40 m to an Earth radius, and on vertical scales from the surface to 13 km. Radiative, photochemical and dynamical processes are then examined, with the intermittency of temperature implying significant consequences. Implications for vertical scaling of the horizontal wind are examined via the thermal wind and barometric equations. Experimental and observational tests are suggested for free running general circulation models, with the possibility of addressing the cold bias they still exhibit. The causal sequence underlying atmospheric turbulence is proposed.
]]>Meteorology doi: 10.3390/meteorology1010002
Authors: Paul D. Williams
The quest to understand and forecast the weather has occupied human minds since time immemorial [...]
]]>Meteorology doi: 10.3390/meteorology1010001
Authors: Cuixiang Lu Ioana Craciun Shu-Kun Lin
Meteorology is the study of the processes and phenomena of the earth’s atmosphere [...]
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