{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1360021391873180288.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.1038/s41598-023-36489-3"}},{"identifier":{"@type":"URI","@value":"https://www.nature.com/articles/s41598-023-36489-3.pdf"}},{"identifier":{"@type":"URI","@value":"https://www.nature.com/articles/s41598-023-36489-3"}},{"identifier":{"@type":"DOI","@value":"10.21203/rs.3.rs-2601394/v1"}},{"identifier":{"@type":"URI","@value":"https://www.researchsquare.com/article/rs-2601394/v1"}},{"identifier":{"@type":"URI","@value":"https://www.researchsquare.com/article/rs-2601394/v1.html"}},{"identifier":{"@type":"PMID","@value":"37296205"}}],"resourceType":"学術雑誌論文(journal article)","dc:title":[{"@value":"A downscaling and bias correction method for climate model ensemble simulations of local-scale hourly precipitation"}],"description":[{"type":"abstract","notation":[{"@value":"<jats:title>Abstract</jats:title>\n                  <jats:p>Ensemble simulations of climate models are used to assess the impact of climate change on precipitation, and require downscaling at the local scale. Statistical downscaling methods have been used to estimate daily and monthly precipitation from observed and simulated data. Downscaling of short-term precipitation data is necessary for more accurate prediction of extreme precipitation events and related disasters at the regional level. In this study, we developed and investigated the performance of a downscaling method for climate model simulations of hourly precipitation. Our method was designed to recognize time-varying precipitation systems that can be represented at the same resolution as the numerical model. Downscaling improved the estimation of the spatial distribution of hourly precipitation frequency, monthly average, and 99th percentile values. The climate change in precipitation amount and frequency were shown in almost all areas by using the 50 ensemble averages of estimated precipitation, although the natural variability was too large to compare with observations. The changes in precipitation were consistent with simulations. Therefore, our downscaling method improved the evaluation of the climatic characteristics of extreme precipitation events and more comprehensively represented the influence of local factors, such as topography, which have been difficult to evaluate using previous methods.</jats:p>"}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1380021391873180034","@type":"Researcher","foaf:name":[{"@value":"Takao Yoshikane"}]},{"@id":"https://cir.nii.ac.jp/crid/1380021391873180183","@type":"Researcher","foaf:name":[{"@value":"Kei Yoshimura"}]}],"publication":{"publicationIdentifier":[{"@type":"EISSN","@value":"20452322"}],"prism:publicationName":[{"@value":"Scientific Reports"}],"dc:publisher":[{"@value":"Springer Science and Business Media LLC"}],"prism:publicationDate":"2023-06-09","prism:volume":"13","prism:number":"1"},"reviewed":"false","dcterms:accessRights":"http://purl.org/coar/access_right/c_abf2","dc:rights":["https://creativecommons.org/licenses/by/4.0","https://creativecommons.org/licenses/by/4.0"],"url":[{"@id":"https://www.nature.com/articles/s41598-023-36489-3.pdf"},{"@id":"https://www.nature.com/articles/s41598-023-36489-3"},{"@id":"https://www.researchsquare.com/article/rs-2601394/v1"},{"@id":"https://www.researchsquare.com/article/rs-2601394/v1.html"}],"createdAt":"2023-06-09","modifiedAt":"2023-06-09","foaf:topic":[{"@id":"https://cir.nii.ac.jp/all?q=Disasters","dc:title":"Disasters"},{"@id":"https://cir.nii.ac.jp/all?q=Bias","dc:title":"Bias"},{"@id":"https://cir.nii.ac.jp/all?q=Science","dc:title":"Science"},{"@id":"https://cir.nii.ac.jp/all?q=Climate%20Change","dc:title":"Climate Change"},{"@id":"https://cir.nii.ac.jp/all?q=Q","dc:title":"Q"},{"@id":"https://cir.nii.ac.jp/all?q=R","dc:title":"R"},{"@id":"https://cir.nii.ac.jp/all?q=Medicine","dc:title":"Medicine"},{"@id":"https://cir.nii.ac.jp/all?q=Climate%20Models","dc:title":"Climate Models"},{"@id":"https://cir.nii.ac.jp/all?q=Article","dc:title":"Article"}],"project":[{"@id":"https://cir.nii.ac.jp/crid/1040014327101598336","@type":"Project","projectIdentifier":[{"@type":"KAKEN","@value":"23H00351"},{"@type":"JGN","@value":"JP23H00351"},{"@type":"URI","@value":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-23H00351/"}],"notation":[{"@language":"ja","@value":"季節予報を用いた高解像度作物収量予報・早期警戒システムの開発"}]},{"@id":"https://cir.nii.ac.jp/crid/1040573407564713088","@type":"Project","projectIdentifier":[{"@type":"KAKEN","@value":"22H04938"},{"@type":"JGN","@value":"JP22H04938"},{"@type":"URI","@value":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-22H04938/"}],"notation":[{"@language":"ja","@value":"ミレニアム大気再解析プロダクトの創出"},{"@language":"en","@value":"Generation of Millennium Atmospheric Reanalysis Product"}]},{"@id":"https://cir.nii.ac.jp/crid/1040851641567621376","@type":"Project","projectIdentifier":[{"@type":"KAKEN","@value":"21H05002"},{"@type":"JGN","@value":"JP21H05002"},{"@type":"URI","@value":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21H05002/"}],"notation":[{"@language":"ja","@value":"衛星地球観測による新たな全球陸域水動態研究"},{"@language":"en","@value":"Study on global terrestrial hydrodynamics with satellite earth observations"}]}],"relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1050855656236280320","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["references"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Atmospheric driving mechanisms of extreme precipitation events in July of 2017 and 2018 in western Japan"}]},{"@id":"https://cir.nii.ac.jp/crid/1360002214439218304","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Classification and forecast of heavy rainfall in northern Kyushu during Baiu season using weather pattern recognition"}]},{"@id":"https://cir.nii.ac.jp/crid/1360011143984449280","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"DEVELOPMENT OF A NEXT-GENERATION REGIONAL WEATHER RESEARCH AND FORECAST MODEL"}]},{"@id":"https://cir.nii.ac.jp/crid/1360021393296337920","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"A comparison of three methods for downscaling daily precipitation in the Punjab region"}]},{"@id":"https://cir.nii.ac.jp/crid/1360021395479866368","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"A Machine Learning System for Precipitation Estimation Using Satellite and Ground Radar Network Observations"}]},{"@id":"https://cir.nii.ac.jp/crid/1360021396348998400","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"The role of topography on projected rainfall change in mid-latitude mountain regions"}]},{"@id":"https://cir.nii.ac.jp/crid/1360292617913801856","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Towards process-informed bias correction of climate change simulations"}]},{"@id":"https://cir.nii.ac.jp/crid/1360292619384530944","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Scaling of precipitation extremes with temperature in the French Mediterranean region: What explains the hook shape?"}]},{"@id":"https://cir.nii.ac.jp/crid/1360302867633904768","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Evaluation and improvement of tail behaviour in the cumulative distribution function transform downscaling method"}]},{"@id":"https://cir.nii.ac.jp/crid/1360302867633960064","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"The influence of convection-permitting regional climate modeling on future projections of extreme precipitation: dependency on topography and timescale"}]},{"@id":"https://cir.nii.ac.jp/crid/1360302868287715584","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Overview of Observed Clausius-Clapeyron Scaling of Extreme Precipitation in Midlatitudes"}]},{"@id":"https://cir.nii.ac.jp/crid/1360302871123105664","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Intercomparison of machine learning methods for statistical downscaling: the case of daily and extreme precipitation"}]},{"@id":"https://cir.nii.ac.jp/crid/1360302871124104960","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Statistical Downscaling of Precipitation Using Machine Learning with Optimal Predictor Selection"}]},{"@id":"https://cir.nii.ac.jp/crid/1360302871124395008","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Machine Learning Enhancement of Storm-Scale Ensemble Probabilistic Quantitative Precipitation Forecasts"}]},{"@id":"https://cir.nii.ac.jp/crid/1360565168765082240","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Over 5,000 Years of Ensemble Future Climate Simulations by 60-km Global and 20-km Regional Atmospheric Models"}]},{"@id":"https://cir.nii.ac.jp/crid/1360567183245161728","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Precipitation Changes in a Climate With 2‐K Surface Warming From Large Ensemble Simulations Using 60‐km Global and 20‐km Regional Atmospheric Models"}]},{"@id":"https://cir.nii.ac.jp/crid/1360567183378209920","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Towards predictive understanding of regional climate change"}]},{"@id":"https://cir.nii.ac.jp/crid/1360583650219619328","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"A bias correction method for precipitation through recognizing mesoscale precipitation systems corresponding to weather conditions"}]},{"@id":"https://cir.nii.ac.jp/crid/1360584343748293248","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Comparing Area Probability Forecasts of (Extreme) Local Precipitation Using Parametric and Machine Learning Statistical Postprocessing Methods"}]},{"@id":"https://cir.nii.ac.jp/crid/1360584344423532800","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Support vector regression to predict porosity and permeability: Effect of sample size"}]},{"@id":"https://cir.nii.ac.jp/crid/1360584344424374912","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Evaluation of Performance Measures for SVR Hyperparameter Selection"}]},{"@id":"https://cir.nii.ac.jp/crid/1360584346471176960","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Stochastic Model Output Statistics for Bias Correcting and Downscaling Precipitation Including Extremes"}]},{"@id":"https://cir.nii.ac.jp/crid/1360584346483114752","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Downscaling GCMs using the Smooth Support Vector Machine method to predict daily precipitation in the Hanjiang Basin"}]},{"@id":"https://cir.nii.ac.jp/crid/1360855571529101696","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Structure of an Evolving Hailstorm Part V: Synthesis and implications for Hail Growth and Hail Suppression"}]},{"@id":"https://cir.nii.ac.jp/crid/1360861292738714368","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Class Imbalance Learning Methods for Support Vector Machines"}]},{"@id":"https://cir.nii.ac.jp/crid/1360865815496708736","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"A support vector machine-based method for improving real-time hourly precipitation forecast in Japan"}]},{"@id":"https://cir.nii.ac.jp/crid/1360865817573773568","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Multi-model ensemble predictions of precipitation and temperature using machine learning algorithms"}]},{"@id":"https://cir.nii.ac.jp/crid/1360865818227360384","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"SVM or deep learning? A comparative study on remote sensing image classification"}]},{"@id":"https://cir.nii.ac.jp/crid/1360865821268023808","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory"}]},{"@id":"https://cir.nii.ac.jp/crid/1360865821268536448","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Rainfall and runoff forecasting with SSA–SVM approach"}]},{"@id":"https://cir.nii.ac.jp/crid/1361418520878865152","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Responses and impacts of atmospheric rivers to climate change"}]},{"@id":"https://cir.nii.ac.jp/crid/1361981468719258496","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Accurate precipitation prediction with support vector classifiers: A study including novel predictive variables and observational data"}]},{"@id":"https://cir.nii.ac.jp/crid/1362262943437731968","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Predictions of climate change over Europe using statistical and dynamical downscaling techniques"}]},{"@id":"https://cir.nii.ac.jp/crid/1362262945839089152","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Practical selection of SVM parameters and noise estimation for SVM regression"}]},{"@id":"https://cir.nii.ac.jp/crid/1362544418371196160","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Comparison of Support Vector Machine and Extreme Gradient Boosting for predicting daily global solar radiation using temperature and precipitation in humid subtropical climates: A case study in China"}]},{"@id":"https://cir.nii.ac.jp/crid/1363107368864297472","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Statistical downscaling of precipitation using machine learning techniques"}]},{"@id":"https://cir.nii.ac.jp/crid/1363107369861365760","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Dynamics and Prediction of a Mesoscale Extreme Rain Event in the Baiu Front over Kyushu, Japan"}]},{"@id":"https://cir.nii.ac.jp/crid/1363107369968027264","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Constraints on future changes in climate and the hydrologic cycle"}]},{"@id":"https://cir.nii.ac.jp/crid/1363388844279295872","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Formation of Mesoscale Lines of Precipitation: Nonsevere Squall Lines in Oklahoma during the Spring"}]},{"@id":"https://cir.nii.ac.jp/crid/1363388844388577920","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Secular Trends of Precipitation Amount, Frequency, and Intensity in the United States"}]},{"@id":"https://cir.nii.ac.jp/crid/1363670319618428544","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"OROGRAPHIC PRECIPITATION"}]},{"@id":"https://cir.nii.ac.jp/crid/1363951796047439232","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Testing the Clausius–Clapeyron constraint on changes in extreme precipitation under CO2 warming"}]},{"@id":"https://cir.nii.ac.jp/crid/1363951796087188608","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"The Operational JMA Nonhydrostatic Mesoscale Model"}]},{"@id":"https://cir.nii.ac.jp/crid/1364233268152041472","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"A tutorial on support vector regression"}]},{"@id":"https://cir.nii.ac.jp/crid/1370585257124968704","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"A study on time and space distribution of heavy rainfalls (2). Analysis of correlative structures based on great-sphere data of hourly rainfall"}]},{"@id":"https://cir.nii.ac.jp/crid/1370585257124968706","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Accuracy of radar-AMeDAS precipitation"}]},{"@id":"https://cir.nii.ac.jp/crid/1370585257124968714","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Effective spectral resolution of ECMWF atmospheric forecast models"}]},{"@id":"https://cir.nii.ac.jp/crid/1370585257124968715","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Guidance on Mesoscale Wind Mapping"}]},{"@id":"https://cir.nii.ac.jp/crid/1370585257124968719","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching"}]},{"@id":"https://cir.nii.ac.jp/crid/1370585257124968835","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Random search for hyper-parameter optimization"}]},{"@id":"https://cir.nii.ac.jp/crid/1370585257124968837","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Structure of the band-shaped precipitation system inducing the heavy rainfall observed over northern Kyushu, Japan on 29 June 1999"}]},{"@id":"https://cir.nii.ac.jp/crid/1370585257124968843","@type":"Product","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Dynamics of widespread extreme precipitation events and the associated large-scale environment using AMeDAS and JRA-55 data"}]},{"@id":"https://cir.nii.ac.jp/crid/1390001205221821952","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Climatology of Extreme Precipitation in Japan for Different Time Scales"}]},{"@id":"https://cir.nii.ac.jp/crid/1390001206504257664","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Structure of the Band-Shaped Precipitation System Inducing the Heavy Rainfall Observed over Northern Kyushu, Japan on 29 June 1999"},{"@value":"A one-dimensional entraining/detraining plume model and its application in convective parameterization"},{"@value":"Structure of the band-shaped precipitation system inducing the heavy rainfall observed over the northern Kyushu, Japan on 29 June 1999"}]},{"@id":"https://cir.nii.ac.jp/crid/1390001206507125248","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@language":"ja","@value":"1991年7月1～10日の強い降雨を伴う梅雨前線の大規模及びメソ-α-規模の様相"},{"@language":"en","@value":"Large- and Meso-α-scale Characteristics of Meiyu/Baiu Front Associated with Intense Rainfalls in 1-10 July 1991"},{"@language":"ja-Kana","@value":"Large and Meso アルファ scale Characteristics of Meiyu Baiu Front Associated with Intense Rainfalls in 1 10 July 1991"},{"@value":"Large- and Meso-&alpha;-scale Characteristics of Meiyu/Baiu Front Associated with Intense Rainfalls in 1-10 July 1991"}]},{"@id":"https://cir.nii.ac.jp/crid/1390282681480967680","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@language":"en","@value":"20-km-Mesh Global Climate Simulations Using JMA-GSM Model<br>—Mean Climate States—"},{"@value":"20-km-Mesh Global Climate Simulations Using JMA-GSM Model--Mean Climate States"},{"@value":"20-km-Mesh Global Climate Simulations Using JMA-GSM Model<br>&mdash;Mean Climate States&mdash;"},{"@value":"20-km-mesh global climate simulations using JMA-GSM model—Mean climate states"},{"@value":"20 km-mesh global climate simulations using JMA-GSM model—Mean climate state"},{"@value":"20-km-mesh global climate simulations using JMA-GSM model—mean climate states—"},{"@value":"20-km-Mesh global climate simulations using JMA-GSM Model<br>—Mean climate States&mdash;"},{"@value":"20km-Mesh global climate simulations using JMA-GSM model"}]},{"@id":"https://cir.nii.ac.jp/crid/1390588767007093376","@type":"Article","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"ja","@value":"大アンサンブル気候予測情報を用いた水害リスク評価への超解像活用可能性"},{"@language":"en","@value":"POTENTIAL OF SUPER-RESOLUTION FOR FLOOD IMPACT ASSESSMENT OF CLIMATE CHANGE"}]},{"@id":"https://cir.nii.ac.jp/crid/1572261550686743936","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Scikit-learn : Machine learning in python"},{"@value":"Scikit‐learn: Machine learning in Python"}]},{"@id":"https://cir.nii.ac.jp/crid/2051433317028481664","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"d4PDF : large-ensemble and high-resolution climate simulations for global warming risk assessment"}]}],"dataSourceIdentifier":[{"@type":"CROSSREF","@value":"10.1038/s41598-023-36489-3"},{"@type":"CROSSREF","@value":"10.21203/rs.3.rs-2601394/v1"},{"@type":"KAKEN","@value":"PRODUCT-25219462"},{"@type":"KAKEN","@value":"PRODUCT-25344282"},{"@type":"KAKEN","@value":"PRODUCT-25345124"},{"@type":"OPENAIRE","@value":"doi_dedup___::413315eb54d4936616ea61a1452d30aa"},{"@type":"CROSSREF","@value":"10.21203/rs.3.rs-2601394/v1_isPreprintOf_DOI_JHWVOLaptrhfpzAXrjl72Wjgl0M"},{"@type":"CROSSREF","@value":"10.2208/jscejj.25-16127_references_DOI_JHWVOLaptrhfpzAXrjl72Wjgl0M"},{"@type":"CROSSREF","@value":"10.1038/s41598-023-36489-3_hasPreprint_DOI_54d20SWCfDHEegJe7D7EimiyRMn"}]}