Research

22 pages, 5007 KiB

Open AccessArticle

A Statistical Forecasting Model for Extremes of the Fire Behaviour Index in Australia

by Rachel Taylor, Andrew G. Marshall, Steven Crimp, Geoffrey J. Cary and Sarah Harris

Atmosphere 2024, 15(4), 470; https://doi.org/10.3390/atmos15040470 - 10 Apr 2024

Viewed by 545

The increasing frequency and duration of severe fire events in Australia further necessitate accurate and timely forecasting to mitigate their consequences. This study evaluated the performance of two distinct approaches to forecasting extreme fire danger at two- to three-week lead times for the [...] Read more.

The increasing frequency and duration of severe fire events in Australia further necessitate accurate and timely forecasting to mitigate their consequences. This study evaluated the performance of two distinct approaches to forecasting extreme fire danger at two- to three-week lead times for the period 2003 to 2017: the official Australian climate simulation dynamical model and a statistical model based on climate drivers. We employed linear logistic regression to develop the statistical model, assessing the influence of individual climate drivers using single linear regression. The performance of both models was evaluated through case studies of three significant extreme fire events in Australia: the Canberra (2003), Black Saturday (2009), and Pinery (2015) fires. The results revealed that ACCESS-S2 generally underestimated the spatial extent of all three extreme FBI events, but with accuracy scores ranging from 0.66 to 0.86 across the case studies. Conversely, the statistical model tended to overpredict the area affected by extreme FBI, with high false alarm ratios between 0.44 and 0.66. However, the statistical model demonstrated higher probability of detection scores, ranging from 0.57 to 0.87 compared with 0.03 to 0.57 for the dynamic model. These findings highlight the complementary strengths and limitations of both forecasting approaches. Integrating dynamical and statistical models with transparent communication of their uncertainties could potentially improve accuracy and reduce false alarms. This can be achieved through hybrid forecasting, combined with visual inspection and comparison between the statistical and dynamical forecasts. Hybrid forecasting also has the potential to increase forecast lead times to up to several months, ultimately aiding in decision-making and resource allocation for fire management. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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16 pages, 7166 KiB

Open AccessArticle

Annual and Seasonal Characteristics of Rainfall Erosivity in the Eastern Rhodopes (Bulgaria)

by Valentina Nikolova, Nina Nikolova, Miloslava Stefanova and Simeon Matev

Atmosphere 2024, 15(3), 338; https://doi.org/10.3390/atmos15030338 - 09 Mar 2024

Viewed by 646

Abstract

Rainfall, with its intensity, duration, and seasonal distribution, is among the main factors causing soil erosion, which is a widespread environmental problem in Bulgaria. Rainfall erosivity shows the potential of precipitation to generate erosion processes and is an essential indicator of the climate [...] Read more.

Rainfall, with its intensity, duration, and seasonal distribution, is among the main factors causing soil erosion, which is a widespread environmental problem in Bulgaria. Rainfall erosivity shows the potential of precipitation to generate erosion processes and is an essential indicator of the climate vulnerability of a region. This paper aims to evaluate rainfall erosivity in a part of the Eastern Rhodopes Mountains, an area that is characterised by high-intensity erosion processes and high erosion risk. Local peculiarities of rainfall erosivity were revealed by the calculation of some precipitation indices based on the monthly precipitation for the period 2000–2021, such as the precipitation concentration index (PCI), Angot precipitation index, Fournier index (FI), and modified Fournier index (MFI). The analysis of the extremely wet and extremely dry months at the annual and seasonal (October–March and April–September) levels was performed to evaluate the susceptibility to erosion. The results from the study show that rainfall erosivity in the studied area varies from low to moderate in the northern part of the study area and from high to very high in the south. According to the MFI, high and very high erosivities have been observed mainly since 2012. The erosivity increases from north to south, to the area with a complex relief, where the combination of orography and atmospheric circulation make favourable conditions for the occurrence of extreme precipitation. The analyses of the calculated indices show that the precipitations in most of the studied area generally have from a low to a moderate erosivity, but this does not exclude the occurrence of cases with high and very high erosivities, which are characteristic of recent years and are related to the increase in annual precipitations and extreme precipitation months. The results of this study can contribute to the development and implementation of measures and preventive activities for the reduction and possible elimination of the negative impacts of extreme precipitation. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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21 pages, 8578 KiB

Open AccessArticle

Assessing the Effects of Urban Canopy on Extreme Rainfall over the Lake Victoria Basin in East Africa Using the WRF Model

by Joan Birungi, Jinhua Yu, Abdoul Aziz Saidou Chaibou, Nyasulu Matthews and Emmanuel Yeboah

Atmosphere 2024, 15(2), 226; https://doi.org/10.3390/atmos15020226 - 14 Feb 2024

Viewed by 943

Abstract

The model simulation focuses on an extreme rainfall event that triggered a flood hazard in the Lake Victoria basin region of East Africa from June 24th to 26th, 2022. This study investigates the impacts of its urban canopy on the extreme rainfall events [...] Read more.

The model simulation focuses on an extreme rainfall event that triggered a flood hazard in the Lake Victoria basin region of East Africa from June 24th to 26th, 2022. This study investigates the impacts of its urban canopy on the extreme rainfall events over the Lake Victoria basin in East Africa, employing the Weather Research and Forecasting (WRF) model at a convective-permitting resolution. The rapid urbanization of the region has given rise to an urban canopy, which has notable effects on local weather patterns, including the intensity and distribution of rainfall. The model incorporates high-resolution land use and urban canopy parameters to accurately capture the influences of urbanization on local weather patterns. This research comprises three sets of experiments, two with urban areas and one without, using the WRF model; the experiments focus on three days of an extreme rainfall event in the Lake Victoria basin. Satellite-based precipitation products and reanalysis datasets are employed for a synoptic analysis and model evaluation. The results demonstrate the model’s effectiveness in capturing meteorological variables during an extreme event compared to observed data. The synoptic patterns reveal that, during the extreme event, the Mascarene and St. Helena influenced rainfall conditions over the Lake Victoria Basin by directing moist air toward the northwest. This led to increased moisture convergence from the urban–rural interface toward urban areas, enhancing convection and processes that result in extreme rainfall. Moreover, this study indicates that the urban canopy, specifically the building effect parameterization, significantly amplifies the intensity and duration of rainfall in the urban areas of the region. This research also indicates a general increase in air temperature, relative humidity, latent heat flux, and surface sensible heat flux due to the urban canopy. These findings highlight the substantial influence of urbanization on rainfall patterns in the urban environment. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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19 pages, 5045 KiB

Open AccessArticle

Climate Driver Influences on Prediction of the Australian Fire Behaviour Index

by Rachel Taylor, Andrew G. Marshall, Steven Crimp, Geoffrey J. Cary and Sarah Harris

Atmosphere 2024, 15(2), 203; https://doi.org/10.3390/atmos15020203 - 05 Feb 2024

Cited by 1 | Viewed by 735

Abstract

Fire danger poses a pressing threat to ecosystems and societies worldwide. Adequate preparation and forewarning can help reduce these threats, but these rely on accurate prediction of extreme fire danger. With the knowledge that climatic conditions contribute heavily to overall fire danger, this [...] Read more.

Fire danger poses a pressing threat to ecosystems and societies worldwide. Adequate preparation and forewarning can help reduce these threats, but these rely on accurate prediction of extreme fire danger. With the knowledge that climatic conditions contribute heavily to overall fire danger, this study evaluates the skill with which episodes of extreme fire danger in Australia can be predicted from the activity of large-scale climate driver patterns. An extremal dependence index for extreme events is used to depict the historical predictive skill of the Australian Bureau of Meteorology’s subseasonal climate prediction system in replicating known relationships between the probability of top-decile fire danger and climate driver states at a lead time of 2–3 weeks. Results demonstrate that the El Niño Southern Oscillation, Southern Annular Mode, persistent modes of atmospheric blocking, Indian Ocean Dipole and Madden-Julian Oscillation are all key for contributing to predictability of fire danger forecasts in different regions during critical fire danger periods. Northwest Australia is found to be particularly predictable, with the highest mean index differences (>0.50) when certain climate drivers are active, compared with the climatological index mean. This integrated approach offers a valuable resource for decision-making in fire-prone regions, providing greater confidence to users relying on fire danger outlooks for key management decisions, such as those involved in the sectors of national park and forest estate management, agriculture, emergency services, health and energy. Furthermore, the results highlight strengths and weaknesses in both the Australian Fire Danger Rating System and the operational climate model, contributing additional information for improving and refining future iterations of these systems. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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31 pages, 11298 KiB

Open AccessArticle

Radar, Lightning, and Synoptic Observations for a Thunderstorm on 7 January 2012 during the CHUVA-Vale Campaign

by João Gabriel Martins Ribeiro, Enrique Vieira Mattos, Michelle Simões Reboita, Diego Pereira Enoré, Izabelly Carvalho da Costa, Rachel Ifanger Albrecht, Weber Andrade Gonçalves and Rômulo Augusto Jucá Oliveira

Atmosphere 2024, 15(2), 182; https://doi.org/10.3390/atmos15020182 - 31 Jan 2024

Viewed by 954

Abstract

Thunderstorms can generate intense electrical activity, hail, and result in substantial economic and human losses. The development of very short-term forecasting tools (nowcasting) is essential to provide information to alert systems in order to mobilize most efficiently the population. However, the development of [...] Read more.

Thunderstorms can generate intense electrical activity, hail, and result in substantial economic and human losses. The development of very short-term forecasting tools (nowcasting) is essential to provide information to alert systems in order to mobilize most efficiently the population. However, the development of nowcasting tools depends on a better understanding of the physics and microphysics of clouds and lightning formation and evolution. In this context, the objectives of this study are: (a) to describe the environmental conditions that led to a genesis of a thunderstorm that produce hail on 7 January 2012, in the Metropolitan Area of São Paulo (MASP) during the CHUVA-Vale campaign, and (b) to evaluate the thunderstorm microphysical properties and vertical structure of electrical charge. Data from different sources were used: field campaign data, such as S-band radar, and 2- and 3-dimensional lightning networks, satellite data from the Geostationary Operational Environmental Satellite-13 (GOES-13), the Meteosat Second Generation (MSG), and reanalysis of the European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5). The thunderstorm developed in a region of low-pressure due to the presence of a near-surface inverted trough and moisture convergence, which favored convection. Convective Available Potential Energy (CAPE) of 1053.6 J kg⁻¹ at the start of the thunderstorm indicated that strong convective energy was present. Microphysical variables such as Vertically Integrated Liquid water content (VIL) and Vertically Integrated Ice (VII) showed peaks of 140 and 130 kg m⁻², respectively, before the hail reached the surface, followed by a decrease, indicating content removal from within the clouds to the ground surface. The thunderstorm charge structure evolved from a dipolar structure (with a negative center between 4 and 6 km and a positive center between 8 and 10 km) to a tripolar structure (negative center between 6 and 7.5 km) in the most intense phase. The first lightning peak (100 flashes in 5 min⁻¹) before the hail showed that there had been a lightning jump. The maximum lightning occurred around 18:17 UTC, with approximately 350 flashes 5 min⁻¹ with values higher than 4000 sources 500 m⁻¹ in 5 min⁻¹. Likewise, the vertical cross-sections indicated that the lightning occurred ahead of the thunderstorm’s displacement (maximum reflectivity), which could be useful in predicting these events. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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16 pages, 11766 KiB

Open AccessArticle

Evaluation of Daily Temperature Extremes in the ECMWF Operational Weather Forecasts and ERA5 Reanalysis

by Francisco M. Lopes, Emanuel Dutra and Souhail Boussetta

Atmosphere 2024, 15(1), 93; https://doi.org/10.3390/atmos15010093 - 11 Jan 2024

Viewed by 856

Abstract

In weather forecasting and climate monitoring, daily maximum and minimum air temperatures (TMAX and TMIN) are fundamental for operational and research purposes, from early warning of extreme events to climate change studies. This study provides an integrated evaluation of TMAX and TMIN from [...] Read more.

In weather forecasting and climate monitoring, daily maximum and minimum air temperatures (TMAX and TMIN) are fundamental for operational and research purposes, from early warning of extreme events to climate change studies. This study provides an integrated evaluation of TMAX and TMIN from two European Centre for Medium-range Weather Forecasts (ECMWF) products: ERA5 reanalysis (1980–2019) and operational weather forecasts (2017–2021). Both products are evaluated using in situ observations from the Global Historical Climatology Network (GHCN). While the analyses span globally, emphasis is given to four key regions: Europe, East and West United States, and Australia. Results reveal a general underestimation of TMAX and overestimation of TMIN in both operational forecasts and ERA5, highlighting the limitation of the ECMWF model in estimating the amplitude of the diurnal cycle of air temperature. ERA5′s accuracy has improved over the past decade, due to enhanced constrain of land–atmosphere analysis streaming from more and higher-quality satellite data. Furthermore, ERA5 outperforms one-day-ahead weather forecasts, indicating that non-real-time dependent studies should rely on ERA5 instead of real-time operational forecasts. This study underscores the importance of ongoing research in model and data assimilation, considering the relevance of daily temperature extremes forecasting and reanalysis for operational meteorology and climate monitoring. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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21 pages, 15924 KiB

Open AccessArticle

Roles of Air–Sea Interactions in the Predictability of Typhoon Mawar and Remote Heavy-Rainfall Events after Five Days

by Akiyoshi Wada

Atmosphere 2023, 14(11), 1638; https://doi.org/10.3390/atmos14111638 - 31 Oct 2023

Viewed by 832

Abstract

This study investigated the relationship between the predicted track of Typhoon Mawar (2023) and the quasi-stationary front along the southern coast of Japan where heavy rainfall occurred. Also, the role of ocean coupling was explored by using global model predictions and numerical simulations [...] Read more.

This study investigated the relationship between the predicted track of Typhoon Mawar (2023) and the quasi-stationary front along the southern coast of Japan where heavy rainfall occurred. Also, the role of ocean coupling was explored by using global model predictions and numerical simulations conducted by a regional atmosphere–wave–ocean coupled model. The track predictions by four major global models showed that the prediction errors became significantly larger after the recurvature. One of the global models could reasonably predict both the track and the location of the front, even after five days. The results of numerical simulations of which the initial and boundary conditions were based on the successful predictions suggest that ocean coupling contributes to the improvement of central pressure simulations compared with fixed oceanic conditions. More northward translation of Mawar after the recurvature simulated by the coupled model could be explained by the separation of the inner-core vortex into two parts in the upper and lower troposphere. However, the predictability of the Subtropical High was more important in determining not only the track but also environmental southerly flow over the moisture road formed between Mawar and the Subtropical High and in accurately predicting the location of the front. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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11 pages, 641 KiB

Open AccessCommunication

For the Record: Second Thoughts on Early Warning, Early Action (EWEA), EW4All, or EWEA4All?

by Michael H. Glantz and Gregory Pierce

Atmosphere 2023, 14(11), 1631; https://doi.org/10.3390/atmos14111631 - 30 Oct 2023

Cited by 1 | Viewed by 895

Abstract

Over the past four decades, people around the globe have experienced unprecedented escalations in the frequency, intensity, magnitude, and location of anomalous hydrometeorological (hydromet) hazards attributed in large measure to the direct and indirect effects of global climate-change-related variability and extremes. The WMO, [...] Read more.

Over the past four decades, people around the globe have experienced unprecedented escalations in the frequency, intensity, magnitude, and location of anomalous hydrometeorological (hydromet) hazards attributed in large measure to the direct and indirect effects of global climate-change-related variability and extremes. The WMO, impelled by an unabated warming of the global climate system and its related extremely anomalous hydromet impacts, chose in March 2022 “Early Warning, Early Action” (EWEA) as the theme for its World Meteorology Day. The theme was praised in a press release by UN Secretary-General Antonio Guterres, who called for the development of a new EWEA initiative to ensure that “every person on Earth is protected by early warning systems within five years”. By mid-2022, several meetings and workshops had already been held by the WMO to forge the new initiative on its road to the UN Climate Conference of Parties (COP27) in November in Sharm El Sheikh, Egypt. COP27 provided a suitably prominent venue for launching the new USD 3.1 billion, 5-year EWEA initiative; there, Secretary-General Guterres formally tasked the WMO, in partnership with the UNDRR, to lead it. But COP27 proved to be interesting as well as illuminating in other, less publicized ways having to do with EWEA. There, what had been the working title of the new initiative was officially changed to EW4A, “Early Warning for All”. Despite the seemingly perfunctory nature of this change, the reality is that it will almost certainly have outsized impacts on the strengths, weaknesses, opportunities, and constraints (SWOC) met specifically in planning and implementing the new initiative’s “early action” strategies and tactics. It is particularly important to bear in mind that, as things now stand, various unanticipated challenges having to do with the lack of organizational experience and capacity with regard to “early action” are likely to arise with the WMO-led implementation of the new initiative. Considering the new EW4A acronym as if it was a commercial brand can, like this, be instructive in thinking about how the seemingly perfunctory name change—from EWEA to EW4A—will impact the initiative’s implementation of “early action”. Doing so can be instructive because, just as the logos of companies like Apple, Nike, or Starbucks eventually became the face of their respective products, so too have branded acronyms like NASA, IOC, WHO, and INTERPOL become the face of their governmental institutions’ or global initiatives’ respective commissions and commitments. It follows then that if “consumer” interest is to be taken seriously and is (hopefully) long-lasting, then the branding of a new product or initiative must be undertaken with great consideration before a final identifier—be it a logo, a catchphrase, or an acronym—is selected. The question in the case of the new WMO-led initiative, then, is the following: Was this issue seriously taken into consideration before EWEA was so abruptly replaced by EW4A at COP27 in Egypt in November 2022? This pointed question is especially meant to highlight how the continued use of the original EWEA acronym by way of developing regional EWEA centers under the “Early Warning for All” umbrella has the possibility of turning regional potential energy into kinetic energy which will be essential if the theoretical gains of future “early warning” (EW) forecasting science are to be effectively translated into “early action” (EA) strategies and tactics that actually, finally, protect people and property across the entirety of the earth from the impending severe impacts of our changing climate future. Thus does this paper raise valid concerns about the balance between support and funding for EW and EA. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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15 pages, 3188 KiB

Open AccessArticle

Influence of the Madden–Julian Oscillation (MJO) on Tropical Cyclones Affecting Tonga in the Southwest Pacific

by Moleni Tu’uholoaki, Antonio Espejo, Krishneel K. Sharma, Awnesh Singh, Moritz Wandres, Herve Damlamian and Savin Chand

Atmosphere 2023, 14(7), 1189; https://doi.org/10.3390/atmos14071189 - 24 Jul 2023

Viewed by 1270

Abstract

The modulating influence of the Madden–Julian oscillation (MJO) on tropical cyclones (TCs) has been examined globally, regionally, and subregionally, but its impact on the island scale remains unclear. This study investigates how TC activity affecting the Tonga region is being modulated by the [...] Read more.

The modulating influence of the Madden–Julian oscillation (MJO) on tropical cyclones (TCs) has been examined globally, regionally, and subregionally, but its impact on the island scale remains unclear. This study investigates how TC activity affecting the Tonga region is being modulated by the MJO, using the Southwest Pacific Enhanced Archive of Tropical Cyclones (SPEArTC) and the MJO index. In particular, this study investigates how the MJO modulates the frequency and intensity of TCs affecting the Tonga region relative to the entire study period (1970–2019; hereafter referred to as all years), as well as to different phases of the El Niño southern oscillation (ENSO) phenomenon. Results suggest that the MJO strongly modulates TC activity affecting the Tonga region. The frequency and intensity of TCs is enhanced during the active phases (phases six to eight) in all years, including El Niño and ENSO-neutral years. The MJO also strongly influences the climatological pattern of genesis of TCs affecting the Tonga region, where more (fewer) cyclones form in the active (inactive) phases of the MJO and more genesis points are clustered (scattered) near (away from) the Tonga region. There were three regression curves that best described the movement of TCs in the region matching the dominant steering mechanisms in the Southwest Pacific region. The findings of this study can provide climatological information for the Tonga Meteorological Service (TMS) and disaster managers to better understand the TC risk associated with the impact of the MJO on TCs affecting the Tonga region and support its TC early warning system. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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16 pages, 10054 KiB

Open AccessArticle

Similarities of Three Most Extreme Precipitation Events in North China

by Quan Dong, Jun Sun, Boyu Chen, Yun Chen and Yu Shu

Atmosphere 2023, 14(7), 1149; https://doi.org/10.3390/atmos14071149 - 14 Jul 2023

Viewed by 711

Abstract

In this study, three typical and most extreme precipitation events in the history of North China are analyzed and compared in terms of accumulated precipitation and synoptical circulation using surface station observations of China and the ERA5 dataset. The three events happened in [...] Read more.

In this study, three typical and most extreme precipitation events in the history of North China are analyzed and compared in terms of accumulated precipitation and synoptical circulation using surface station observations of China and the ERA5 dataset. The three events happened in August 1963 (“63.8” event, hereafter), August 1975 (“75.8” event), and July 2021 (“21.7” event), respectively, mainly in Hebei and Henan Provinces of North China. The results show that the maximum daily and 4-day accumulated precipitation of all three events exceeded 500 mm and 800 mm, with many stations’ daily precipitation ranking Top 1. The “63.8” event persisted for the longest time, affected the largest area, and rained the most in 7 days (over 1000 mm). The “75.8” event was characterized by the most extreme daily precipitation and a concentrated area. All three events characterize a normal northward subtropical high that was located in North China and Northeast China. At 500 hPa, the area from South China to the South China Sea was dominated by a uniform pressure field. In the upper levels, there were troughs and divergence anomalies in all three events. In the low levels, there were anomalous low-level jets and the associated water vapor flux anomalies, which were located at different levels and came from different directions. Stable synoptical circulation and persistent jet and water vapor flux anomalies are the key factors in these extreme events. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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Graphical abstract

13 pages, 2034 KiB

Open AccessArticle

Towards a Volunteered Geographic Information-Facilitated Visual Analytics Pipeline to Improve Impact-Based Weather Warning Systems

by Katerina Vrotsou, Carlo Navarra, Kostiantyn Kucher, Igor Fedorov, Fredrik Schück, Jonas Unger and Tina-Simone Neset

Atmosphere 2023, 14(7), 1141; https://doi.org/10.3390/atmos14071141 - 13 Jul 2023

Viewed by 1438

Abstract

Extreme weather events, such as flooding, are expected to increase in frequency and intensity. Therefore, the prediction of extreme weather events, assessment of their local impacts in urban environments, and implementation of adaptation measures are becoming high-priority challenges for local, regional, and national [...] Read more.

Extreme weather events, such as flooding, are expected to increase in frequency and intensity. Therefore, the prediction of extreme weather events, assessment of their local impacts in urban environments, and implementation of adaptation measures are becoming high-priority challenges for local, regional, and national agencies and authorities. To manage these challenges, access to accurate weather warnings and information about the occurrence, extent, and impacts of extreme weather events are crucial. As a result, in addition to official sources of information for prediction and monitoring, citizen volunteered geographic information (VGI) has emerged as a complementary source of valuable information. In this work, we propose the formulation of an approach to complement the impact-based weather warning system that has been introduced in Sweden in 2021 by making use of such alternative sources of data. We present and discuss design considerations and opportunities towards the creation of a visual analytics (VA) pipeline for the identification and exploration of extreme weather events and their impacts from VGI texts and images retrieved from social media. The envisioned VA pipeline incorporates three main steps: (1) data collection, (2) image/text classification and analysis, and (3) visualization and exploration through an interactive visual interface. We envision that our work has the potential to support three processes that involve multiple stakeholders of the weather warning system: (1) the validation of previously issued warnings, (2) local and regional assessment-support documentation, and (3) the monitoring of ongoing events. The results of this work could thus generate information that is relevant to climate adaptation decision making and provide potential support for the future development of national weather warning systems. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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24 pages, 2993 KiB

Open AccessArticle

Assessing the Performance of the South American Land Data Assimilation System Version 2 (SALDAS-2) Energy Balance across Diverse Biomes

by Álvaro Vasconcellos Araujo de Ávila, Luis Gustavo Gonçalves de Gonçalves, Vanessa de Arruda Souza, Laurizio Emanuel Ribeiro Alves, Giovanna Deponte Galetti, Bianca Muss Maske, Augusto Getirana, Anderson Ruhoff, Marcelo Sacardi Biudes, Nadja Gomes Machado and Débora Regina Roberti

Atmosphere 2023, 14(6), 959; https://doi.org/10.3390/atmos14060959 - 31 May 2023

Cited by 1 | Viewed by 1520

Abstract

Understanding the exchange of energy between the surface and the atmosphere is important in view of the climate scenario. However, it becomes a challenging task due to a sparse network of observations. This study aims to improve the energy balance estimates for the [...] Read more.

Understanding the exchange of energy between the surface and the atmosphere is important in view of the climate scenario. However, it becomes a challenging task due to a sparse network of observations. This study aims to improve the energy balance estimates for the Amazon, Cerrado, and Pampa biomes located in South America using the radiation and precipitation forcing obtained from the Clouds and the Earth’s Radiant Energy System (CERES) and the precipitation CPTEC/MERGE datasets. We employed three surface models—Noah-MP, Community Land Model (CLSM), and Integrated Biosphere Simulator (IBIS)—and conducted modeling experiments, termed South America Land Data Assimilation System (SALDAS-2). The results showed that SALDAS-2 radiation estimates had the smallest errors. Moreover, SALDAS-2 precipitation estimates were better than the Global Land Data Assimilation System (GLDAS) in the Cerrado (MBE = −0.16) and Pampa (MBE = −0.19). Noah-MP presented improvements compared with CLSM and IBIS in 100% of towers located in the Amazon. CLSM tends to overestimate the latent heat flux and underestimate the sensible heat flux in the Amazon. Noah-MP and Ensemble outperformed GLDAS in terms latent and sensible heat fluxes. The potential of SALDAS-2 should be emphasized to provide more accurate estimates of surface energy balance. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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18 pages, 28014 KiB

Open AccessArticle

Projected Future Changes in Extreme Climate Indices over Central Asia Using RegCM4.3.5

by Tugba Ozturk

Atmosphere 2023, 14(6), 939; https://doi.org/10.3390/atmos14060939 - 27 May 2023

Cited by 2 | Viewed by 1359

Abstract

This work projected future extreme climate indices’ changes over Central Asia (The Coordinated Regional Climate Downscaling Experiment—CORDEX Region 8). Changes were calculated for 2071–2100 relative to 1971–2000. Climate simulations were obtained by downscaling the RegCM4.3.5 to 50 km resolution under RCP4.5 and 8.5 [...] Read more.

This work projected future extreme climate indices’ changes over Central Asia (The Coordinated Regional Climate Downscaling Experiment—CORDEX Region 8). Changes were calculated for 2071–2100 relative to 1971–2000. Climate simulations were obtained by downscaling the RegCM4.3.5 to 50 km resolution under RCP4.5 and 8.5 with HadGEM2-ES and MPI-ESM-MR. The results indicate that the Central Asian domain will experience warmer and more extreme temperatures with increasing radiative forcing. The annual lowest value of minimum daily temperature was simulated to increase remarkably, up to 8 degrees, especially in high latitudes, with a more than 12 degree increase projected over Siberia. A strong growth in the percentage of warm nights and an increase in the days of warm spells for the whole region, with a decrease in cold spell duration, are anticipated. Model results show an expected reduction of up to 30% in precipitation totals over the domain, except for the increased precipitation over Siberia, the Himalayas, and Tibetan Plateau. Extreme precipitation events are projected to have an increase of 20% over the whole domain, with an 80% increase over high topographical areas. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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15 pages, 5480 KiB

Open AccessArticle

Evaluation of Dynamical Seasonal Prediction Skills for Tropical Cyclone Activity over the South China Sea in FGOALS-f2

by Jinxiao Li, Qun Tian, Zili Shen, Zixiang Yan, Majun Li, Jiaqing Xue, Yaoxian Yang, Lingjun Zeng, Yuxin Zang and Siyuan Li

Atmosphere 2023, 14(1), 85; https://doi.org/10.3390/atmos14010085 - 31 Dec 2022

Viewed by 1407

Abstract

Based on 35-year (1981–2015) ensemble (24 members) hindcasts of the IAP/LASG global seasonal prediction system named FGOALS-f2 V1.0 (FGOALS-f2), the tropical cyclone (TC) seasonal prediction skills over the South China Sea (SCS) during the TC peak season (July–November) are evaluated. Starting the prediction [...] Read more.

Based on 35-year (1981–2015) ensemble (24 members) hindcasts of the IAP/LASG global seasonal prediction system named FGOALS-f2 V1.0 (FGOALS-f2), the tropical cyclone (TC) seasonal prediction skills over the South China Sea (SCS) during the TC peak season (July–November) are evaluated. Starting the prediction from June 20th, FGOALS-f2 can well capture the seasonal mean characteristics for both the genesis location and track of TCs over the SCS. For seasonal anomalous TC numbers, FGOALS-f2 underestimates the maximum and minimum of the TC number compared to the observation. The temporal correlation coefficients (TCCs) between FGOALS-f2 and the observation are 0.39 for the TC number and 0.51 for accumulated cyclone energy (ACE) over the SCS, respectively, which are both above the 95% significant level. Additionally, FGOALS-f2 has acceptable prediction skill for the seasonal mean number of TCs landing on three areas (coastal southeastern China, Indochina Peninsula, and Philippines) surrounding the SCS. The skillful prediction of SCS TCs could be ascribed to the well-predicted tropical anomaly of sea surface temperature (SSTA), TC and El Niño-Southern Oscillation (TC-ENSO) relations, and Genesis potential index (GPI). Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts)

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