Research

18 pages, 2386 KiB

Open AccessArticle

Future Changes in Thermal Bioclimate Conditions over West Bengal, India, Based on a Climate Model

by Sourabh Bal and Ingo Kirchner

Atmosphere 2023, 14(3), 505; https://doi.org/10.3390/atmos14030505 - 05 Mar 2023

Cited by 2 | Viewed by 1589

Changes in extreme human bioclimate conditions are accepted evidence for and serve as a broad measure of anthropogenic climate change. The essential objective of the current study was to investigate past and future thermal bioclimate conditions across West Bengal (WB), India. The daily [...] Read more.

Changes in extreme human bioclimate conditions are accepted evidence for and serve as a broad measure of anthropogenic climate change. The essential objective of the current study was to investigate past and future thermal bioclimate conditions across West Bengal (WB), India. The daily physiologically equivalent temperature (PET) was calculated by considering definite climate variables as inputs. These meteorological variables were captured from the Coordinated Regional Downscaling Experiment (CORDEX)-South Asia. The initial results from this research work present the mean monthly distribution of each PET class over the considered stations of WB during the period (1986–2005) and three future time periods: (i) near future (2016–2035), (ii) mid-future (2046–2065), and (iii) far future (2080–2099). It was observed that the months from April to June comprise heat stress months in terms of human thermal perception, whereas thermally acceptable conditions begin in November and continue until March for most stations. Results from future PET changes over WB in the context of the reference period (1986–2005) reveal a prominent increase in warm and hot PETs for all future time periods in two different greenhouse gas emission scenarios. During the far-future time period, stations within a kilometer of the Bay of Bengal such as Digha, Diamond Harbour, Canning, and Baruipur account for the highest percentage in the warm PET class (35.7–43.8 °C) in high-end emission scenarios. Simultaneously, during the period from 2080 to 2099, Kolkata, Dum Dum, Kharagpur, and Siliguri will experience a PET greater than 43.8 °C for close to 10% of the days in the year and more than 10% in Sriniketan, Malda, Asansol, and Birbhum. During the far-future period, a negative change in the very cool PET class (<3.3 °C) indicating a decrease in cold days was the largest for Darjeeling. Full article

(This article belongs to the Special Issue Advances in Atmospheric Sciences ‖)

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15 pages, 3793 KiB

Open AccessArticle

Manifestation of the Early 20th Century Warming in the East-European Plain: Atmospheric Circulation Anomalies and Its Connection to the North Atlantic SST and Sea Ice Variability

by Valeria Popova, Tatiana Aldonina and Daria Bokuchava

Atmosphere 2023, 14(3), 428; https://doi.org/10.3390/atmos14030428 - 21 Feb 2023

Cited by 2 | Viewed by 997

Abstract

A study of the climatic characteristics and annual runoff of the Volga and Severnaya Dvina rivers demonstrates that, on the East European Plain (EEP), Early Twentieth Century Warming (ETCW) manifested in a multiyear drought between 1934 and 1940; this drought has no analogues [...] Read more.

A study of the climatic characteristics and annual runoff of the Volga and Severnaya Dvina rivers demonstrates that, on the East European Plain (EEP), Early Twentieth Century Warming (ETCW) manifested in a multiyear drought between 1934 and 1940; this drought has no analogues in this region in terms of intensity and duration according to Palmer’s classification, and caused extreme hydrological events. The circulation conditions during this event were characterized by an extensive anticyclone over Eastern Europe, combined with a cyclonic anomaly in the circumpolar region. An analysis of the spatial features of sea surface temperature (SST) anomalies indicate that the surface air temperature (SAT) anomalies in July on the EEP during ETCW were related not only to the North Atlantic (NA) warming and positive AMO phase, but also to a certain spatial pattern of SST anomalies characteristic of the 1920–1950 period. The difference between the SST anomalies of the opposite sign in the different NA zones, used as the indicator of the obtained spatial pattern, shows the quite close relations between the July SAT anomalies on the EEP and the atmospheric circulation patterns responsible for them. The positive phase of the Atlantic Multidecadal Oscillation (AMO) and the expansion of the subtropical high-pressure belt to the north and to the east can be considered as global-scale drivers of this phenomenon. The AMO also impacts the sea ice cover in the Barents–Kara Sea region, which, in turn, could have led to specific atmospheric circulation patterns and contributed to droughts on the EEP in the 1930s. Full article

(This article belongs to the Special Issue Advances in Atmospheric Sciences ‖)

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19 pages, 5061 KiB

Open AccessArticle

On the Calculation of Urban Morphological Parameters Using GIS: An Application to Italian Cities

by Antonio Esposito, Myrtille Grulois, Gianluca Pappaccogli, Olga Palusci, Antonio Donateo, Pietro Salizzoni, Jose Luis Santiago, Alberto Martilli, Giuseppe Maffeis and Riccardo Buccolieri

Atmosphere 2023, 14(2), 329; https://doi.org/10.3390/atmos14020329 - 07 Feb 2023

Cited by 5 | Viewed by 2516

Abstract

The identification of parameters that can quantitatively describe the different characteristics of urban morphology is fundamental to studying urban ventilation and microclimate at the local level and developing parameterizations of the dynamic effect of an urban area in mesoscale models. This paper proposes [...] Read more.

The identification of parameters that can quantitatively describe the different characteristics of urban morphology is fundamental to studying urban ventilation and microclimate at the local level and developing parameterizations of the dynamic effect of an urban area in mesoscale models. This paper proposes a methodology to calculate four morphological parameters, namely mean height, aspect ratio, sky view factor, and plan area ratio, of five cities located in southern (Bari and Lecce), central (Naples and Rome), and northern (Milan) Italy. The calculation is performed using the Geographical Information System (GIS), starting from morphological and land use data collected and analyzed in shapefiles. The proposed methodology, which can be replicated in other cities, also presents in detail the procedure followed to properly build input data to calculate the sky view factor using the UMEP GIS tool. The results show a gradual increase in the plan area index, λ_p, and mean building height,

\bar{H}

, moving from the south to the north of Italy. Maximum values of λ_p and

\bar{H}

are obtained in the regions of Milan, Rome, and Naples, where the highest spatially-averaged values are also found, i.e., λ_p = 0.22,

\bar{H}

= 10.9 m in Milan; λ_p = 0.19,

\bar{H}

= 12.7 m in Rome; λ_p = 0.20,

\bar{H}

= 12 m in Naples. Furthermore, for all the cities investigated, areas characterized by the Corine Land Cover class as “continuous urban fabric” are those with medium sky view factor SVF values (around 0.6–0.7) and λ_p values (around 0.3) typical of intermediate/compact cities. The methodology employed here for calculating morphological parameters using GIS proves to be replicable in different urban contexts. This opens to a better classification of cities in local climate zones (LCZ), as shown for the Lecce region, useful for urban heat island (UHI) studies and to the development of parameterizations of the urban effects in global and regional climate models. Full article

(This article belongs to the Special Issue Advances in Atmospheric Sciences ‖)

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12 pages, 5218 KiB

Open AccessArticle

Impact of Various Disturbance Sources on the Atmospheric Electric Field and Thunderstorm Activity of the Northern Tien-Shan

by Valentina Antonova, Vadim Lutsenko, Galina Gordiyenko and Sergey Kryukov

Atmosphere 2023, 14(1), 164; https://doi.org/10.3390/atmos14010164 - 12 Jan 2023

Viewed by 1635

Abstract

Features of the manifestations of various sources of disturbances in the atmospheric electric field at the Tien-Shan high-mountain station have been studied, and the statistical relationship between solar and thunderstorm activity has been established. Air currents arising over the ocean, having overcome the [...] Read more.

Features of the manifestations of various sources of disturbances in the atmospheric electric field at the Tien-Shan high-mountain station have been studied, and the statistical relationship between solar and thunderstorm activity has been established. Air currents arising over the ocean, having overcome the mountain gorges of the Himalayas, carry moisture to the Northern Tien-Shan and determine the weather features and thunderstorm activity at the Tien-Shan high-mountain station. It was established that the maximum and minimum thunderstorm activity at the Tien-Shan high-mountain station corresponds to the distribution curve of daily thunderstorm activity for the Asia–Australia region. The investigation showed that coronal mass ejections (CMEs) affect the atmospheric electric field by increasing or decreasing its level or causing its fluctuations, depending on the features of manifestations in the near-Earth space and in the Earth’s magnetosphere. In at least 70% of cases, thunderstorm activity was observed with a 1–2-day delay after impact on the Earth’s magnetosphere by CMEs and HSSs. A number of cases were studied when thunderstorm activity was observed in a quiet geomagnetic field. In these cases, an increase in the values of fmin (the minimum frequency of reflection from the ionosphere) and foEs (the critical frequency of the sporadic E layer) was observed, which indicated an increase in the level of radio wave absorption in the ionospheric D-region and the level of electron density at altitudes of 100–120 km. Full article

(This article belongs to the Special Issue Advances in Atmospheric Sciences ‖)

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12 pages, 20658 KiB

Open AccessArticle

Application of Optimal Interpolation to Spatially and Temporally Sparse Observations of Aerosol Optical Depth

by Natallia Miatselskaya, Gennadi Milinevsky, Andrey Bril, Anatoly Chaikovsky, Alexander Miskevich and Yuliia Yukhymchuk

Atmosphere 2023, 14(1), 32; https://doi.org/10.3390/atmos14010032 - 24 Dec 2022

Cited by 1 | Viewed by 1138

Abstract

Aerosol optical depth (AOD) is one of the basic characteristics of atmospheric aerosol. A global ground-based network of sun and sky photometers, the Aerosol Robotic Network (AERONET) provides AOD data with low uncertainty. However, AERONET observations are sparse in space and time. To [...] Read more.

Aerosol optical depth (AOD) is one of the basic characteristics of atmospheric aerosol. A global ground-based network of sun and sky photometers, the Aerosol Robotic Network (AERONET) provides AOD data with low uncertainty. However, AERONET observations are sparse in space and time. To improve data density, we merged AERONET observations with a GEOS-Chem chemical transport model prediction using an optimal interpolation (OI) method. According to OI, we estimated AOD as a linear combination of observational data and a model forecast, with weighting coefficients chosen to minimize a mean-square error in the calculation, assuming a negligible error of AERONET AOD observations. To obtain weight coefficients, we used correlations between model errors in different grid points. In contrast with classical OI, where only spatial correlations are considered, we developed the spatial-temporal optimal interpolation (STOI) technique for atmospheric applications with the use of spatial and temporal correlation functions. Using STOI, we obtained estimates of the daily mean AOD distribution over Europe. To validate the results, we compared daily mean AOD estimated by STOI with independent AERONET observations for two months and three sites. Compared with the GEOS-Chem model results, the averaged reduction of the root-mean-square error of the AOD estimate based on the STOI method is about 25%. The study shows that STOI provides a significant improvement in AOD estimates. Full article

(This article belongs to the Special Issue Advances in Atmospheric Sciences ‖)

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21 pages, 4332 KiB

Open AccessArticle

Climate Patterns and Their Influence in the Cordillera Blanca, Peru, Deduced from Spectral Analysis Techniques

by Adrián Fernández-Sánchez, José Úbeda, Luis Miguel Tanarro, Nuria Naranjo-Fernández, José Antonio Álvarez-Aldegunde and Joshua Iparraguirre

Atmosphere 2022, 13(12), 2107; https://doi.org/10.3390/atmos13122107 - 16 Dec 2022

Viewed by 1675

Abstract

Climate patterns are natural processes that drive climate variability in the short, medium, and long term. Characterizing the patterns behind climate variability is essential to understand the functioning of the regional atmospheric system. Since investigations typically reveal only the link and extent of [...] Read more.

Climate patterns are natural processes that drive climate variability in the short, medium, and long term. Characterizing the patterns behind climate variability is essential to understand the functioning of the regional atmospheric system. Since investigations typically reveal only the link and extent of the influence of climate patterns in specific regions, the magnitude of that influence in meteorological records usually remains unclear. The central Peruvian Andes are affected by most of the common climate patterns of tropical areas, such as Intertropical Convergence Zone (ITCZ), Sea Surface Temperature (SST), solar irradiance, Madden Julian Oscillation (MJO), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO). They are also affected by regional processes that are exclusive from South America, such as the South American Low-Level Jet (SALLJ), South American Monsoon System (SAMS), Bolivian High (BH), and Humboldt Current. The aim of this research is to study the climate variability of precipitation, maximum and minimum temperature records over Cordillera Blanca (Peru), and its relationship with the intensity and periodicity of the common climate patterns that affect this region. To achieve this aim, a spectral analysis based on Lomb’s Periodogram was performed over meteorological records (1986–2019) and over different climate pattern indexes. Results show a coincidence in periodicity between MJO and SALLJ, with monthly cycles for precipitation and temperature (27-day, 56-day, and 90-day cycles). Moreover, the most intense periodicities, such as annual (365 days) and biannual (182 and 122 days) cycles in meteorological variables, possibly would be led by ITCZ and ENSO together, as well as a combination of the Humboldt Current and SALLJ. Additionally, interannual periodicities (3-year, 4.5-year, 5.6–7-year and 11-year cycles) would have coincidence with the ENSO–solar combination, while the longest cycles (16 years) could match PDO variability. Full article

(This article belongs to the Special Issue Advances in Atmospheric Sciences ‖)

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15 pages, 3511 KiB

Open AccessArticle

Fractional Importance of Various Moisture Sources Influencing Precipitation in Iran Using a Comparative Analysis of Analytical Hierarchy Processes and Machine Learning Techniques

by Mojtaba Heydarizad, Nathsuda Pumijumnong, Rogert Sorí, Pouya Salari and Luis Gimeno

Atmosphere 2022, 13(12), 2019; https://doi.org/10.3390/atmos13122019 - 01 Dec 2022

Viewed by 1356

Abstract

Studying the moisture sources responsible for precipitation in Iran is highly important. In recent years, moisture sources that influence precipitation across Iran have been studied using various methods. In this study, moisture uptake rate from individual sources that influences precipitation across Iran has [...] Read more.

Studying the moisture sources responsible for precipitation in Iran is highly important. In recent years, moisture sources that influence precipitation across Iran have been studied using various methods. In this study, moisture uptake rate from individual sources that influences precipitation across Iran has been determined using the (E − P) values obtained by the FLEXPART model for the 1981–2015 period. Then, moisture uptake rate from individual sources has been used as independent parameters to investigate the fractional importance of moisture sources that influence precipitation in Iran using analytical hierarchy process (AHP) as well as machine learning (ML) methods including artificial neural networks, Decision Tree, Random Forest, Gboost, and XGboost. Furthermore, the average annual precipitation in Iran was simulated using ML methods. The results showed that the Arabian Sea has a dominant fractional influence on precipitation in both wet (November to April) and dry (May to October) periods. Simulation of precipitation amounts using the ML methods presented accurate models during the wet period, whereas the developed models for the dry period were not adequate. Finally, validation of the accuracy of the ML models using RMSE and R² values showed that the models developed using XGboost had the highest accuracy. Full article

(This article belongs to the Special Issue Advances in Atmospheric Sciences ‖)

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10 pages, 1598 KiB

Open AccessArticle

Review of the Observed Energy Flow in the Earth System

by Chunlei Liu, Ni Chen, Jingchao Long, Ning Cao, Xiaoqing Liao, Yazhu Yang, Niansen Ou, Liang Jin, Rong Zheng, Ke Yang and Qianye Su

Atmosphere 2022, 13(10), 1738; https://doi.org/10.3390/atmos13101738 - 21 Oct 2022

Cited by 1 | Viewed by 1465

Abstract

The energy budget imbalance at the top of the atmosphere (TOA) and the energy flow in the Earth’s system plays an essential role in climate change over the global and regional scales. Under the constraint of observations, the radiative fluxes at TOA have [...] Read more.

The energy budget imbalance at the top of the atmosphere (TOA) and the energy flow in the Earth’s system plays an essential role in climate change over the global and regional scales. Under the constraint of observations, the radiative fluxes at TOA have been reconstructed prior to CERES (Clouds and the Earth’s Radiant Energy System) between 1985 and 2000. The total atmospheric energy divergence has been mass corrected based on ERA5 (the fifth generation ECMWF ReAnalysis) atmospheric reanalysis by a newly developed method considering the enthalpy removing of the atmospheric water vapor, which avoids inconsistencies due to the residual lateral total mass flux divergence in the atmosphere, ensuring the balances of the freshwater fluxes at the surface. The net surface energy flux (F_s) has been estimated using the residual method based on energy conservation, which is the difference between the net TOA radiative flux and the atmospheric energy tendency and divergence. The F_s is then verified directly and indirectly with observations, and results show that the estimated F_s in North Atlantic is superior to those from model simulations. This paper gives a brief review of the progress in the estimation of the observed energy flow in the Earth system, discusses some caveats of the existing method, and provides some suggestions for the improvements of the aforementioned data sets. Full article

(This article belongs to the Special Issue Advances in Atmospheric Sciences ‖)

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