Weather and Climate Extremes最新文献

{"title":"Storm surges and extreme sea levels: Review, establishment of model intercomparison and coordination of surge climate projection efforts (SurgeMIP).","authors":"Natacha B. Bernier ,&nbsp;Mark Hemer ,&nbsp;Nobuhito Mori ,&nbsp;Christian M. Appendini ,&nbsp;Oyvind Breivik ,&nbsp;Ricardo de Camargo ,&nbsp;Mercè Casas-Prat ,&nbsp;Trang M. Duong ,&nbsp;Ivan D. Haigh ,&nbsp;Tom Howard ,&nbsp;Vanessa Hernaman ,&nbsp;Oleksandr Huizy ,&nbsp;Jennifer L. Irish ,&nbsp;Ebru Kirezci ,&nbsp;Nadao Kohno ,&nbsp;Jun-Whan Lee ,&nbsp;Kathleen L. McInnes ,&nbsp;ElkeM.I. Meyer ,&nbsp;Marta Marcos ,&nbsp;Reza Marsooli ,&nbsp;Y. Joseph Zhang","doi":"10.1016/j.wace.2024.100689","DOIUrl":"10.1016/j.wace.2024.100689","url":null,"abstract":"<div><p>Coastal flood damage is primarily the result of extreme sea levels. Climate change is expected to drive an increase in these extremes. While proper estimation of changes in storm surges is essential to estimate changes in extreme sea levels, there remains low confidence in future trends of surge contribution to extreme sea levels. Alerting local populations of imminent extreme sea levels is also critical to protecting coastal populations. Both predicting and projecting extreme sea levels require reliable numerical prediction systems. The SurgeMIP (surge model intercomparison) community has been established to tackle such challenges. Efforts to intercompare storm surge prediction systems and coordinate the community's prediction and projection efforts are introduced. An overview of past and recent advances in storm surge science such as physical processes to consider and the recent development of global forecasting systems are briefly introduced. Selected historical events and drivers behind fast increasing service and knowledge requirements for emergency response to adaptation considerations are also discussed. The community's initial plans and recent progress are introduced. These include the establishment of an intercomparison project, the identification of research and development gaps, and the introduction of efforts to coordinate projections that span multiple climate scenarios.</p></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"45 ","pages":"Article 100689"},"PeriodicalIF":8.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2212094724000501/pdfft?md5=418499262d8c0977acedfb1863f3838f&pid=1-s2.0-S2212094724000501-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141050209","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":"A novel approach to a multi-model ensemble for climate change models: Perspectives on the representation of natural variability and historical and future climate","authors":"Yong-Tak Kim ,&nbsp;Jae-Ung Yu ,&nbsp;Tae-Woong Kim ,&nbsp;Hyun-Han Kwon","doi":"10.1016/j.wace.2024.100688","DOIUrl":"10.1016/j.wace.2024.100688","url":null,"abstract":"<div><p>This study developed a novel approach that integrated climate model selection and multi-model ensemble (MME) construction to effectively represent model uncertainties and, consequently, improve consistency in the evaluation of changes to extreme rainfall in different scenarios. Our focus was to combine 10 regional climate model (RCM) simulations, forced by two global climate models (GCM), especially for estimation of design rainfall in a changing climate. We hypothesized that the natural variability and statistically higher moment attributes in the extreme rainfall simulations from RCMs were not fully preserved. Therefore, the MME approach could be more effective in climate change studies, largely due to the use of multiple climate models. First, an experimental study was proposed to validate the efficacy of the proposed modeling framework approach adopting L-moments to quantify relative importance among climate models and their use for representing natural variability in the MME construction. The proposed approach was then applied to climate change scenarios collected from multiple RCMs for the Han-River watershed during both historical (1981–2005) and future (2006–2 100) periods. The results showed that the climate model selection informed by natural variability demonstrated better performance, representing nearly identical distribution to the observed annual maximum rainfall (AMR) in the Han River watershed. The range of the selected scenario was relatively narrower than that of all the scenarios, and the change rate was more consistent with the limited zero crossing, reflecting improvement in both model performance and consistency over historical and future periods, respectively. The change rate of the MME under RCP8.5 appeared to be an approximately 20% increase for the near (2011–2040) and far (2071–2 100) future, and the degree of increase in the rate for the mid-future (2041–2070) was slightly lower than that for the other periods, with increase of approximately 10%.</p></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"44 ","pages":"Article 100688"},"PeriodicalIF":8.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2212094724000495/pdfft?md5=d3790effe8ae3930e8a96ca6b8068dfc&pid=1-s2.0-S2212094724000495-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141032394","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":"Improved freezing rain forecast using machine learning","authors":"Qiuzi Han Wen ,&nbsp;Dingyu Wan ,&nbsp;Quan Dong ,&nbsp;Yan Yan ,&nbsp;Pingwen Zhang","doi":"10.1016/j.wace.2024.100690","DOIUrl":"10.1016/j.wace.2024.100690","url":null,"abstract":"<div><p>Freezing rain is one of the most damaging weather phenomena in winter or early spring in many parts of the world, affecting traffic, power lines and agriculture. Thus, reliable and computationally efficient prediction of its occurrence is urgently needed in weather forecast operations. However, there are different thermodynamic processes that can lead to freezing rain, resulting in unsatisfactory forecasting performance of the state-of-the-art Numerical Weather Prediction (NWP) models. Here a data-driven forecasting method for freezing rain using machine learning technologies is proposed. Observations of weather phenomenon collected from 2 515 national weather stations of China for winter of 2016–2019 and the corresponding atmospheric predictors derived from ERA5 reanalysis are used. The prediction function is constructed based on the classification and regression tree, and the predicting variables include temporal and vertical profiles of fundamental thermodynamic and kinematic parameters from 500 hPa to 1000 hPa, with a total dimension of 2 304. The LightGBM (Light Gradient Boosting Machine) framework is adopted to train our prediction model and an algorithm-level approach of modifying the loss function is used to address the imbalance of classes to improve forecasting skill. Results show that the data-driven prediction model, namely DDFR (data driven forecast of freezing rain), out-performs the benchmark NWP, i.e., ECMWF IFS product. It's improvements in terms of TS score range from 120% to 258% depending on different forecast leading times, which range from 0 to 12 h. In addition, DDFR is applied in an operational NWP model of China. The problem of domain adaptation is tackled and transfer learning method is employed to adapt the original DDFR to this NWP model. The effectiveness of such adaptation has been demonstrated by its performance on both training and testing datasets.</p></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"44 ","pages":"Article 100690"},"PeriodicalIF":8.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2212094724000513/pdfft?md5=75cd7a66f0aa89012a95b392de6f29d6&pid=1-s2.0-S2212094724000513-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141054064","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":"Wave setup estimation at regional scale: Empirical and modeling-based multi-approach analysis in the Mediterranean Sea","authors":"Tim Toomey ,&nbsp;Marta Marcos ,&nbsp;Thomas Wahl ,&nbsp;Miguel Agulles ,&nbsp;Alejandra R. Enríquez ,&nbsp;Angel Amores ,&nbsp;Alejandro Orfila","doi":"10.1016/j.wace.2024.100685","DOIUrl":"https://doi.org/10.1016/j.wace.2024.100685","url":null,"abstract":"<div><p>Wave setup is a physical process that induces a temporal increase of the mean water level due to wave dissipation by bottom friction and breaking in the surf zone, extending over tens to hundreds of meters in the cross-shore direction. Wave setup contribution to coastal sea level solely induced by wind and atmospheric effects can increase by more than 100% under extreme events and conditions favoring its formation. It is therefore crucial to consider this phenomenon when assessing sea-level-related coastal hazards. Previous studies estimated the wave setup effect by means of numerical modeling and empirical formulations at regional and global scale. Such analyses require either high computational capacity to implement high-resolution numerical models over large domains, and/or accurate information on coastal morphological features from global or regional databases. Although the Mediterranean Sea is a fetch-limited environment, waves generated from extra-tropical cyclones are powerful enough for wave setup to develop, and subsequently for a potential significant wave setup contribution to extreme coastal sea level. Through the use of both numerical and empirical methods, we investigate the uncertainty associated to wave setup representation on the frequency and magnitude of coastal extreme sea levels occurring on sandy beaches in the Mediterranean Sea. Wave setup values are compared at beach scale between process-based modeling and empirical approaches, showing highly variable results. We also quantify the impact of wave setup on return levels of coastal sea level extremes using reconstructed sea levels. We employ various methods to calculate the wave setup component. Results show high spatial dispersion, with clear differences between the numerical and empirical approaches, especially in regions prone to the development of energetic waves. The total inter-method dispersion of 100-year return levels is often higher than 30 cm for average values of 62.4 cm. We emphasize the important limitations related to wave setup modeling (i.e., its underestimation) at large scale, and call for caution when applying empirical formulations (generally developed from local studies) at regional to global scale, which can lead to unrealistic wave setup values.</p></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"44 ","pages":"Article 100685"},"PeriodicalIF":8.0,"publicationDate":"2024-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S221209472400046X/pdfft?md5=278e79c663bc8fe715bff4c1b2193520&pid=1-s2.0-S221209472400046X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140950854","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":"Compound dry and hot events over major river basins of the world from 1921 to 2020","authors":"Tongtiegang Zhao ,&nbsp;Shaotang Xiong ,&nbsp;Yu Tian ,&nbsp;Yongyan Wu ,&nbsp;Bo Li ,&nbsp;Xiaohong Chen","doi":"10.1016/j.wace.2024.100679","DOIUrl":"https://doi.org/10.1016/j.wace.2024.100679","url":null,"abstract":"<div><p>Compound dry and hot events (CDHEs) are among the most destructive compound extremes. Under global warming, changes in precipitation, temperature and their dependence make profound contributions to CDHEs. In this paper, the contributions of these three factors are explicitly quantified based on a novel mathematical method. Specifically, time series of precipitation and temperature are employed to identify CDHEs and then changes of CDHEs are attributed by using the partial derivatives-based sensitivity analysis. Based on the Climatic Research Unit Time-Series (CRU TS), a case study of CDHEs is devised for the major river basins (MRBs) of the world. The results highlight that from the period 1921–1970 to the period 1971–2020, CDHEs did occur more frequently across most MRBs. The temperature tended to make the largest contribution, followed by precipitation and the dependence between precipitation and temperature. In Africa, South America and Western Europe, the rising temperature is generally the dominant factor for increases of heatwaves that contribute to CDHEs. In Asia, increases of droughts along with increases of heatwaves raise the risk of CDHEs. For MRBs with moderate increases in temperature, increasing precipitation is shown to mitigate or even offset the risks of CDHEs. In the meantime, the increasing dependence is observed to reduce the frequency of CDHEs in the Huai He and the Mississippi even though temperature is increasing. Overall, the attributing results of CDHEs from 1921 to 2020 can serve as a reference for the preparation and mitigation of CDHEs for MRBs across the world.</p></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"44 ","pages":"Article 100679"},"PeriodicalIF":8.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2212094724000409/pdfft?md5=ffcfbc362378d88ac23c79e508edef58&pid=1-s2.0-S2212094724000409-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140950853","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":"Amplification of the discrepancy between simplified and physics-based wet-bulb globe temperatures in a warmer climate","authors":"Liying Qiu ,&nbsp;Ziwei Zhu ,&nbsp;Zixuan Zhou ,&nbsp;Eun-Soon Im ,&nbsp;Seung-Ki Min ,&nbsp;Yeon-Hee Kim ,&nbsp;Yujin Kim ,&nbsp;Dong-Hyun Cha ,&nbsp;Joong-Bae Ahn ,&nbsp;Young-Hwa Byun","doi":"10.1016/j.wace.2024.100677","DOIUrl":"https://doi.org/10.1016/j.wace.2024.100677","url":null,"abstract":"<div><p>The Simplified Wet Bulb Globe Temperature (sWBGT) is widely used in heat stress assessments for climate-change studies, but its limitations have not been thoroughly explored. Building on recent critiques of sWBGT's use for current climate on global scale, this study examines sWBGT's biases using dynamically-downscaled sub-daily climate projections under multiple future emission scenarios. The analysis is aimed at understanding caveats in the application of sWBGT and the uncertainties in existing climate change analysis dependent on sWBGT. Results indicate sWBGT's biases are heavily influenced by local near-surface air temperature, with overestimation of heat stress in East Asia regions, particularly hot and humid areas, due to static assumptions of radiation and wind speed. This overestimation is amplified in warmer climates, leading to exaggerated projected heat stress increases in future. In contrast, underestimations are found for heat stress levels attributed to low wind speeds and strong radiations, such as over the Tibetan Plateau and certain extreme events. Additionally, sWBGT underestimates variability in extreme heatwave events compared to WBGT in both current and future climates, irrespective of overestimation in absolute heatwave intensities. This study emphasizes the limitations of sWBGT, especially in future warmer climates. Importance of sub-daily data for capturing daily maximum heat stress level and reflecting diurnal variations in different components is also discussed. In conclusion, we recommend using Liljegren's model (i.e., physics-based calculation) with high-resolution sub-daily climate data for more accurate outdoor heat stress assessments in climate change studies.</p></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"44 ","pages":"Article 100677"},"PeriodicalIF":8.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2212094724000380/pdfft?md5=5787888b8c1137f7db6f41504ea15d7b&pid=1-s2.0-S2212094724000380-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140914267","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":"Investigation of model forecast biases and skilful prediction for Assam heavy rainfall 2022","authors":"Vijay Vishwakarma ,&nbsp;Sandeep Pattnaik ,&nbsp;Pradeep Kumar Rai ,&nbsp;V. Hazra ,&nbsp;R. Jenamani","doi":"10.1016/j.wace.2024.100678","DOIUrl":"https://doi.org/10.1016/j.wace.2024.100678","url":null,"abstract":"<div><p>Extreme rainfall events (ERE) during the summer monsoon season have been occurring over most parts of India resulting in flooding and immense socio-economic loss. These extremes are becoming a frequent norm in the hilly and mountainous regions of the country such as Assam. Assam received one of the most historical EREs from 14–June 17, 2022. The present study analyses the performance of a suite of high-resolution ensemble model forecasts for this extreme event in terms of its intensity, and distribution with a lead time of up to 96 h. Furthermore, the 36 numerical experiments are carried out using two different land use and land cover (LULC) data sets (i.e. ISRO and USGS) and three different sets of parameterization schemes (i.e. planetary boundary layer, cumulus, and microphysics).</p><p>Rainfall distributions in the case of USGS LULC are relatively less coherent and underestimated (60–260 mm/day) against IMD (80–300 mm/day) including the rainfall categories heavy (HR), very heavy (VHR), and extremely heavy (EHR) rainfall throughout the day-1 to day-4. Among all the ensembles (E1-E10), USGS (E6 - E10) has underestimated rainfall (140–260 mm/day) compared to ISRO (150–280 mm/day), specifically in MR and HR categories over the upper Assam (UAD) and lower Assam (LAD) divisions. Further, the Bias Correction Ensemble (BCE) technique is applied to minimize the forecast errors. A rigorous statistical analysis in terms of frequency distribution, Taylor diagram, and benchmark skill scores is carried out to elucidate the model biases. The set of the model ensembles using ISRO (E1- E5) and USGS (E6- E10) reasonably captured the HR, VHR, and EHR. In addition, throughout the forecast hour, BCE E5 (E10) is noted with the distinct realistic (underestimated) representation of model bias (5–20 %) (10–30 %) over all the subdivisions of Assam. Our results suggest that the combined efforts of ensembles of physical parameterization schemes, along with proper LULC, and the BCE approach are required to overcome challenges to improve the skills of rainfall events, particularly over complex terrains such as Assam.</p></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"44 ","pages":"Article 100678"},"PeriodicalIF":8.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2212094724000392/pdfft?md5=7ba5dd9e009215e99c098c59b81fe979&pid=1-s2.0-S2212094724000392-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140905271","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":"Did recent sea surface temperature warming reinforce the extreme East Asian summer monsoon precipitation in 2020?","authors":"Taeho Mun ,&nbsp;Haerin Park ,&nbsp;Dong-Hyun Cha ,&nbsp;Chang-Keun Song ,&nbsp;Seung-Ki Min ,&nbsp;Seok-Woo Son","doi":"10.1016/j.wace.2024.100682","DOIUrl":"https://doi.org/10.1016/j.wace.2024.100682","url":null,"abstract":"<div><p>We analyzed the possible effects of recent sea surface temperature (SST) warming on the extraordinary East Asian summer monsoon (EASM) precipitation in 2020 summer. The dynamic and thermodynamic impacts of SST are examined by conducting regional climate model experiments with observed SST and cold SST where the 22-year SST trend is removed. In the presence of warm SST, precipitation increases in low latitudes but decreases in the EASM region. This dipolar precipitation change pattern opposes the precipitation anomalies in 2020 summer, indicating that the extraordinary 2020 EASM precipitation is not likely driven by recent SST warming. The warm SST suppresses the western North Pacific subtropical high expansion and weakens the southwesterly from the South China Sea toward the EASM region. In terms of large-scale atmospheric circulations, SST-induced wind changes strengthen the local Walker circulation in the South China Sea and the Philippines and the local Hadley circulation across the EASM region. These support the reduced EASM rainfall in the control experiment compared to the cold SST experiment and imply that the precipitation reduction by dynamical effects could exceed the precipitation increase by thermodynamic effects in the EASM region under warm SST.</p></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"44 ","pages":"Article 100682"},"PeriodicalIF":8.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2212094724000434/pdfft?md5=f2da88eb9d2113f336253a93ddd1ca59&pid=1-s2.0-S2212094724000434-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140901403","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":"Corrigendum to “Quantifying uncertainties in tropical cyclone wind hazard assessment due to synthetic track stochastic variability for Southeast Asia” [Weather Clim. Extrem. 41 (2023), 100599]","authors":"Wei Jian ,&nbsp;Edmond Yat-Man Lo ,&nbsp;Pane Stojanovski ,&nbsp;Tso-Chien Pan","doi":"10.1016/j.wace.2024.100686","DOIUrl":"10.1016/j.wace.2024.100686","url":null,"abstract":"","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"44 ","pages":"Article 100686"},"PeriodicalIF":8.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2212094724000471/pdfft?md5=584f4ba15c5a3359c4de02197babf8a7&pid=1-s2.0-S2212094724000471-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141042422","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":"Evaluation of precipitation extremes in ERA5 reanalysis driven regional climate simulations over the CORDEX-Australasia domain","authors":"Fei Ji ,&nbsp;Giovanni Di Virgilio ,&nbsp;Nidhi Nishant ,&nbsp;Eugene Tam ,&nbsp;Jason P. Evans ,&nbsp;Jatin Kala ,&nbsp;Julia Andrys ,&nbsp;Chris Thomas ,&nbsp;Matthew L. Riley","doi":"10.1016/j.wace.2024.100676","DOIUrl":"https://doi.org/10.1016/j.wace.2024.100676","url":null,"abstract":"<div><p>Reanalysis-driven regional climate simulations using the Weather Research and Forecasting (WRF) model in New South Wales (NSW) and Australian Regional Climate Modelling (NARCliM) Version 2.0 are assessed for capturing precipitation extreme indices. Seven configurations of the WRF model driven by ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis v5 (ERA5) for Australia from 1979 to 2020 at 20 km resolution are evaluated. We assess the spatiotemporal patterns of six selected Expert Team on Sector-Specific Climate Indices (ET-SCI) precipitation extremes by comparing regional climate model (RCM) simulations against gridded observations. The RCMs evaluated have varying levels of accuracy in simulating precipitation extremes. While they capture climatology and coefficient of variation of precipitation extremes relatively well, temporal correlation and trend reproduction present challenges. Some RCMs perform more effectively for specific extreme indices, while others encounter challenges in accurately replicating them. No single RCM excels in all aspects, highlighting the need to consider specific strengths when selecting RCMs for global climate model (GCM) driven simulations.</p></div>","PeriodicalId":48630,"journal":{"name":"Weather and Climate Extremes","volume":"44 ","pages":"Article 100676"},"PeriodicalIF":8.0,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2212094724000379/pdfft?md5=4d0de7729d9f1001c311929186b7cd51&pid=1-s2.0-S2212094724000379-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140842689","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}