Weather and Climate Extremes最新文献

{"title":"Unravelling the complex interplay between daily and sub-daily rainfall extremes in different climates","authors":"Selma B. Guerreiro ,&nbsp;Stephen Blenkinsop ,&nbsp;Elizabeth Lewis ,&nbsp;David Pritchard ,&nbsp;Amy Green ,&nbsp;Hayley J. Fowler","doi":"10.1016/j.wace.2024.100735","DOIUrl":"10.1016/j.wace.2024.100735","url":null,"abstract":"<div><div>Understanding short-duration intense rainfall is crucial for mitigating flash floods, landslides, soil erosion, and pollution incidents. Yet, most observations from rain gauges are only available at the daily resolution. We use the new Global Sub Daily Rainfall dataset to explore extreme rainfall at both daily and sub-daily durations worldwide. Employing Single Gauge Analysis (SGA) and pioneering global-scale Regional Frequency Analysis (RFA), we reveal for the first time how Generalized Extreme Value Distribution (GEV) parameters change across climates and data durations (1h, 3h, 6h, 24h, and daily). This marks the first-ever near-global-scale RFA, made possible by the development of an algorithm that automates RFA on observed rainfall datasets. We compare our results with GEV applied to a gridded rainfall reanalysis (ERA5). Our key findings are that: 1) using ERA5, return levels are significantly underestimated across all climates for 1h rainfall and across all data durations for gauges in the tropical climate region. Even when accounting for differences between point and areal estimates, the median 1h return level estimates are approximately 40% lower compared to RFA. We therefore strongly advise against the use of reanalysis gridded rainfall for studying these extremes. 2) While most gauges show similar return levels with RFA or SGA, some differ significantly, and either method may yield the highest values. Thus, we strongly recommend using both SGA and RFA simultaneously to estimate return levels for a robust risk assessment in flood infrastructure design. 3) The interaction between daily and sub-daily GEV shape parameters varies across climate regions, rendering a universal method for inferring sub-daily rainfall extremes from daily extremes (e.g., using Intensity-Duration-Frequency curves) impractical. Our research provides innovative methodological insights that warrant consideration in future studies on rainfall extremes. Our results not only benefit local stakeholders globally but also serve as a crucial validation tool for the rising number of convection-permitting climate model experiments conducted worldwide.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"46 ","pages":"Article 100735"},"PeriodicalIF":6.1,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How unusual was Australia's 2017–2019 Tinderbox Drought?","authors":"Georgina Falster ,&nbsp;Sloan Coats ,&nbsp;Nerilie Abram","doi":"10.1016/j.wace.2024.100734","DOIUrl":"10.1016/j.wace.2024.100734","url":null,"abstract":"<div><div>Australia's Murray-Darling Basin experienced three consecutive years of meteorological drought across 2017–2019, collectively named the ‘Tinderbox Drought’. Rainfall deficits during the three-year drought were most pronounced in the Australian cool season (April to September). Deficits in both the cool season and annual total rainfall were unprecedented in the instrumental record. However, the instrumental record provides just one of a range of equally plausible climate trajectories that could have occurred during this period. To determine if the Tinderbox Drought was outside this range, we used observational data from prior to the onset of the drought to construct Linear Inverse Models (LIMs) that emulate the stationary statistics of Australian rainfall and its connection to global sea surface temperature (SST) anomalies. Overall, we find that rainfall deficits were most unusual in the northern Murray-Darling Basin, and during the final year of the drought. The global SST anomalies observed during the first two years of the Tinderbox Drought, particularly the cool anomalies in the central tropical Pacific and western Indian Ocean, are not typically associated with low rainfall across the Murray-Darling Basin. In terms of single-year rainfall anomalies, the only aspect of the Tinderbox Drought that was beyond the range of the LIMs was annual-total rainfall over the northern Murray-Darling Basin during 2019. This coincided with an extreme positive Indian Ocean Dipole event that was also beyond the range of the LIMs. When considered in terms of basin-wide rainfall over the full three years, rainfall deficits during the Tinderbox Drought were beyond the LIM range in terms of both cool-season and annual-total rainfall. This suggests an anthropogenic contribution to the severity of the drought—likely exacerbated by the 2019 extreme positive Indian Ocean Dipole event.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"46 ","pages":"Article 100734"},"PeriodicalIF":6.1,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Projected changes in mean climate and extremes from downscaled high-resolution CMIP6 simulations in Australia","authors":"Sarah Chapman ,&nbsp;Jozef Syktus ,&nbsp;Ralph Trancoso ,&nbsp;Nathan Toombs ,&nbsp;Rohan Eccles","doi":"10.1016/j.wace.2024.100733","DOIUrl":"10.1016/j.wace.2024.100733","url":null,"abstract":"<div><div>High-resolution climate change projections are required to evaluate local and regional climate change impacts. We used CCAM (Conformal Cubic Atmospheric Model) to dynamically downscale CMIP6 GCMs (Global Climate Models) over Australia under three emissions scenarios, producing a set of 60 simulations at a 10 km resolution. Previous work has evaluated the performance of the downscaled models in the historical period. Here, we evaluate the impact of end-of-century climate change in the downscaled CMIP6-CCAM models for mean and extreme climate under three Shared Socioeconomic Pathways (SSP126, 245 and 370). We find the changes in mean climate are in general similar in the host CMIP6 and downscaled models. For extreme temperature, we find that extreme maximum temperatures (TXx) increase by 3.4 °C, while extreme minimum temperatures (TNn) warm by 3.0 °C. Extreme precipitation generally increases in summer and decreases in winter; however, there is a large amount of inter-model variation in the location and magnitude of change. Consecutive dry days also decrease in most areas in Austral summer and increase in Austral winter. Heatwaves become more frequent and hotter by the end of the century. These results suggest a hotter, wetter Austral summer, with longer, more frequent and more intense heatwaves, and a hotter and drier Austral winter in most areas. This dataset provides useful new high-resolution information on how climate change is likely to impact Australia, which will be a valuable resource to underpin local adaptation responses to future impacts.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"46 ","pages":"Article 100733"},"PeriodicalIF":6.1,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting the groundwater levels in the Baltic through standardized index analysis","authors":"Alise Babre ,&nbsp;Konrāds Popovs ,&nbsp;Andis Kalvāns ,&nbsp;Marta Jemeļjanova ,&nbsp;Aija Dēliņa","doi":"10.1016/j.wace.2024.100728","DOIUrl":"10.1016/j.wace.2024.100728","url":null,"abstract":"<div><div>In regions where groundwater forms the primary source of drinking water, comprehending the prospective availability of subsurface water resources due to climate change is of paramount importance.</div><div>This study evaluates the impact of climate change on groundwater levels in the Baltic States until the end of this century. It employs link between surface and subsurface standardized indices. For forecast it uses various Representative Concentration Pathways (RCP) alongside different Regional Climate Models (RCM).</div><div>By linking historical groundwater drought episodes with calculated surface drought indices and accumulation periods observed during defined climate Normals, we project groundwater levels for the short, medium, and long-term future. The study incorporates 13 EURO-CORDEX RCMs under three RCP scenarios.</div><div>Our analysis reveals that, compared to the recent climate Normals, an overall increase in groundwater levels is expected at most study sites. However, lower groundwater levels are estimated in the near future. The projected impacts show no significant seasonal bias or spatial conformity. Although these findings are specific to the Baltic region, the methodologies described can be readily adapted for global application.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"46 ","pages":"Article 100728"},"PeriodicalIF":6.1,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fast generation of high-dimensional spatial extremes","authors":"Hans Van de Vyver","doi":"10.1016/j.wace.2024.100732","DOIUrl":"10.1016/j.wace.2024.100732","url":null,"abstract":"<div><div>Widespread extreme climate events cause many fatalities, economic losses and have a huge impact on critical infrastructure. It is therefore of utmost importance to estimate the frequency and associated consequences of spatially concurrent extremes. Impact studies of climate extremes are severely hampered by the lack of extreme observations, and even large ensembles of climate simulations often do not include enough extreme or record-breaking climate events for robust analysis. On the other hand, weather generators specifically fitted to extreme observations can quickly generate many physically or statistically plausible extreme events, even with intensities that have never been observed before. We propose a Fourier-based algorithm for generating high-resolution synthetic datasets of rare events, using essential concepts of classical modelling of (spatial) extremes. Here, the key feature is that the stochastically generated datasets have the same spatial dependence as the observed extreme events. Using high-resolution gridded precipitation and temperature datasets, we show that the new algorithm produces realistic spatial patterns, and is particularly attractive compared to other existing methods for spatial extremes. It is exceptionally fast, easy to implement, scalable to high dimensions and, in principle, applicable for any spatial resolution. We generated datasets with 10,000 gridpoints, a number that can be increased without difficulty. Since current impact models often require high-resolution climate inputs, the new algorithm is particularly useful for improved impact and vulnerability assessment.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"46 ","pages":"Article 100732"},"PeriodicalIF":6.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anthropogenic influence on precipitation in Aotearoa New Zealand with differing circulation types","authors":"Anjali Thomas ,&nbsp;Adrian McDonald ,&nbsp;James Renwick ,&nbsp;Suzanne Rosier ,&nbsp;Jordis S. Tradowsky ,&nbsp;Gregory E. Bodeker","doi":"10.1016/j.wace.2024.100727","DOIUrl":"10.1016/j.wace.2024.100727","url":null,"abstract":"<div><div>This study quantifies the influences of anthropogenic forcing to date on precipitation over Aotearoa New Zealand (ANZ). Large ensembles of simulations from the weather@home regional climate model experiments are analysed under two scenarios, a natural (NAT) or counter-factual scenario which excludes human-induced changes to the climate system and an anthropogenic (ANT) or factual scenario. The impacts of anthropogenic forcing on precipitation are analysed in the context of large-scale circulation types characterized using an existing Self Organizing Map classification. The combined effect of both thermodynamics and dynamics are compared with values expected from the Clausius–Clapeyron (C–C) relation. Changes in the precipitation intensity due to greenhouse gas-forced temperature rise are lower than the expected C–C value. However extreme precipitation changes approach the C–C value for some circulation types. Specifically westerly flows enhance precipitation change across ANZ relative to the C–C rate, particularly over the West Coast. Conversely, northwesterly flows reduce the change over the North Island relative to the C–C value. Moreover, the wet day frequency generally reduces in the ANT scenario relative to NAT, reductions are largest on the West Coast of the South Island for westerly flows. Additionally, the frequency of days with extreme precipitation rises over ANZ for most circulation patterns, except in Northland and for northwesterly flows. This underscores the combined influence of dynamics and thermodynamics in shaping both precipitation intensity and frequency patterns across ANZ.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"46 ","pages":"Article 100727"},"PeriodicalIF":6.1,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142428191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The 2022 record-high heat waves over southwestern Europe and their underlying mechanism","authors":"Jeong-Hun Kim ,&nbsp;So-Hyun Nam ,&nbsp;Maeng-Ki Kim ,&nbsp;Roberto Serrano-Notivoli ,&nbsp;Ernesto Tejedor","doi":"10.1016/j.wace.2024.100729","DOIUrl":"10.1016/j.wace.2024.100729","url":null,"abstract":"<div><div>Recently, the intensity and frequency of heat waves (HWs) have been increased worldwide. Particularly in 2022, Europe was severely affected by unprecedented HWs, which caused approximately 61,672 deaths and 11,324 deaths in Europe and Spain, respectively. In this study, we investigate the mechanisms of the HWs in southwestern Europe (SWEU) to identify the differences between typical HWs and the extreme HWs that occurred in 2022. Our results showed that the SWEU events in 2022 were strongly related to robust heat domes that developed in the lower troposphere due to high-pressure anomalies especially during two periods (9–18 June and 8–19 July). Analyses of the energy budget and thermodynamic equation revealed the processes underlying the amplification of the heat domes over SWEU during both periods. We also discovered that abnormal atmospheric blocking in the upper troposphere was closely associated with the amplification of the Gulf Stream SST, which caused an atmospheric circulation pattern favorable for the 2022 SWEU-HWs. This was further confirmed by modeling experiments. Therefore, our results emphasize that a Gulf Stream SST amplification can trigger an atmospheric circulation pattern favorable for extreme HWs in SWEU, enhancing our understanding of the mechanism behind extreme HWs. Finally, our findings will help improving the forecasting of SWEU-HWs on a sub-seasonal time scale, as well as future projections in global climate models.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"46 ","pages":"Article 100729"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142428372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The flash droughts across the south-central United States in 2022: Drivers, predictability, and impacts","authors":"Jordan I. Christian ,&nbsp;Taylor M. Grace ,&nbsp;Benjamin J. Fellman ,&nbsp;Daniel F. Mesheske ,&nbsp;Stuart G. Edris ,&nbsp;Henry O. Olayiwola ,&nbsp;Jeffrey B. Basara ,&nbsp;Brian A. Fuchs ,&nbsp;Jason C. Furtado","doi":"10.1016/j.wace.2024.100730","DOIUrl":"10.1016/j.wace.2024.100730","url":null,"abstract":"<div><div>A rare subseasonal-to-seasonal phenomenon – two consecutive flash drought events interrupted by a period of recovery – occurred across eastern Oklahoma, Arkansas, and southern Missouri, spanning the summer and early fall of 2022. These flash drought events (the first in June–July, the second in August–September) led to severe (D2) and extreme (D3) drought conditions via the United States Drought Monitor across much of the region following the first period of rapid drought intensification, and extreme (D3) and exceptional (D4) drought conditions by the end of the second event. A notable driver of both flash drought events included a persistent upper-level ridge either centered over or shifted west and upstream of the flash drought region, leading to broad-scale subsidence and reduced mid-level moisture which acted to limit precipitation development and increase evaporative demand. In addition, several heatwave events developed during the warm season in 2022 and either (1) acted to drive flash drought development via increased evaporative demand or (2) were enhanced by land surface desiccation and land-atmosphere feedbacks following rapid drought intensification. Furthermore, S2S composite forecasts predicted drought development for both events. However, only 20% of the ensembles predicted rapid drought development associated with flash drought for the first event and 16% of the ensembles predicted rapid drought development during the second event. This result highlights a key challenge in S2S prediction of rapidly developing drought conditions versus that of more conventional and slower drought development. The ensembles that did predict rapid drought intensification were associated with the forecasting of positive 500 hPa geopotential height anomalies over the south-central United States (first event) or an amplified wave pattern centered over the west-central United States (second event). Lastly, the compounding effects of two flash droughts in a single warm season led to substantial impacts on agricultural, environmental, and hydrologic sectors across the region.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"46 ","pages":"Article 100730"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142428409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Future changes of socioeconomic exposure to potential landslide hazards over mainland China","authors":"Donghuan Li ,&nbsp;Youcun Qi ,&nbsp;Tianjun Zhou ,&nbsp;Wenxia Zhang","doi":"10.1016/j.wace.2024.100731","DOIUrl":"10.1016/j.wace.2024.100731","url":null,"abstract":"<div><div>Landslides are among the most destructive natural disasters, having huge socioeconomic impacts. Here, we investigate future changes in potential rainfall-induced landslide activities and their socioeconomic consequences in mainland China using CMIP6 simulations under five combined scenarios of the Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). The potential landslide activities over mainland China are projected to increase over the 21st century. The regional mean increases over mainland China under the SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, at the end of the 21st century, are approximately 20.6%, 24.8%, 27.2%, 33.1%, and 46.5%, respectively, compared to present day. Population exposure to potential landslide hazards is projected to increase under SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, but decline under SSP1-1.9 and SSP1-2.6 scenarios due to population reduction. Meanwhile, economic exposure is expected to rise substantially across mainland China due to the greatly increased GDP. In general, the most populous and economically developed southern China will experience the largest socioeconomic exposure percentage increase among the subregions due to the joint influence of climate change and socioeconomic change. Compared with SSP1-1.9 scenario, the higher emission levels of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 will result in 20.4%, 32.0%, 60.6%, and 125.8% more increases in potential landslide days and 16.2%, 42.9%, 80.3%, and 4.6% less increases in anti-risk capacity (ability to resist landslide risk) in mainland China, respectively, at the end of the 21st century. The southern Tibetan Plateau is projected to experience greater increases in landslide days and decreases in anti-risk capacity than other subregions, if high emission scenarios are selected over SSP1-1.9.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"46 ","pages":"Article 100731"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Downscaling, bias correction, and spatial adjustment of extreme tropical cyclone rainfall in ERA5 using deep learning","authors":"Guido Ascenso ,&nbsp;Andrea Ficchì ,&nbsp;Matteo Giuliani ,&nbsp;Enrico Scoccimarro ,&nbsp;Andrea Castelletti","doi":"10.1016/j.wace.2024.100724","DOIUrl":"10.1016/j.wace.2024.100724","url":null,"abstract":"<div><div>Hydrological models that are used to analyse flood risk induced by tropical cyclones often input ERA5 reanalysis data. However, ERA5 precipitation has large systematic biases, especially over heavy precipitation events like Tropical Cyclones, compromising its usefulness in such scenarios. Few studies to date have performed bias correction of ERA5 precipitation and none of them for extreme rainfall induced by tropical cyclones. Additionally, most existing works on bias adjustment focus on adjusting pixel-wise metrics of bias, such as the Mean Squared Error (MSE). However, it is equally important to ensure that the rainfall peaks are correctly located within the rainfall maps, especially if these maps are then used as input to hydrological models. In this paper, we describe a novel machine learning model that addresses both gaps, RA-U<span><math><msub><mrow></mrow><mrow><mi>c</mi><mi>m</mi><mi>p</mi><mi>d</mi></mrow></msub></math></span>, based on the popular U-Net model. The key novelty of RA-U<span><math><msub><mrow></mrow><mrow><mi>c</mi><mi>m</mi><mi>p</mi><mi>d</mi></mrow></msub></math></span> is its loss function, the <em>compound loss</em>, which optimizes both a pixel-wise bias metric (the MSE) and a spatial verification metric (a modified version of the Fractions Skill Score). Our results show how RA-U<span><math><msub><mrow></mrow><mrow><mi>c</mi><mi>m</mi><mi>p</mi><mi>d</mi></mrow></msub></math></span> improves ERA5 in almost all metrics by 3-28%—more than the other models we used for comparison which actually worsen the total rainfall bias of ERA5—at the cost of a slightly increased (3%) error on the magnitude of the peak. We analyse the behaviour of RA-U<span><math><msub><mrow></mrow><mrow><mi>c</mi><mi>m</mi><mi>p</mi><mi>d</mi></mrow></msub></math></span> by visualizing accumulated maps of four particularly wet tropical cyclones and by dividing our data according to the Saffir-Simpson scale and to whether they made landfall, and we perform an error analysis to understand under what conditions our model performs best.</div></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"46 ","pages":"Article 100724"},"PeriodicalIF":6.1,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142428370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}