{"title":"泰迪工具v1.1:用于气候影响分析的每日气候模式数据的时间分解","authors":"Florian Zabel, Benjamin Poschlod","doi":"10.5194/gmd-16-5383-2023","DOIUrl":null,"url":null,"abstract":"Abstract. Climate models provide the required input data for global or regional climate impact analysis in temporally aggregated form, often in daily resolution to save space on data servers. Today, many impact models work with daily data; however, sub-daily climate information is becoming increasingly important for more and more models from different sectors, such as the agricultural, water, and energy sectors. Therefore, the open-source Teddy tool (temporal disaggregation of daily climate model data) has been developed to disaggregate (temporally downscale) daily climate data to sub-daily hourly values. Here, we describe and validate the temporal disaggregation, which is based on the choice of daily climate analogues. In this study, we apply the Teddy tool to disaggregate bias-corrected climate model data from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We choose to disaggregate temperature, precipitation, humidity, longwave radiation, shortwave radiation, surface pressure, and wind speed. As a reference, globally available bias-corrected hourly reanalysis WFDE5 (WATCH Forcing Data methodology applied to ERA5) data from 1980–2019 are used to take specific local and seasonal features of the empirical diurnal profiles into account. For a given location and day within the climate model data, the Teddy tool screens the reference data set to find the most similar meteorological day based on rank statistics. The diurnal profile of the reference data is then applied on the climate model. The physical dependency between variables is preserved, since the diurnal profile of all variables is taken from the same, most similar meteorological day of the historical reanalysis dataset. Mass and energy are strictly preserved by the Teddy tool to exactly reproduce the daily values from the climate models. For evaluation, we aggregate the hourly WFDE5 data to daily values and apply the Teddy tool for disaggregation. Thereby, we compare the original hourly data with the data disaggregated by Teddy. We perform a sensitivity analysis of different time window sizes used for finding the most similar meteorological day in the past. In addition, we perform a cross-validation and autocorrelation analysis for 30 globally distributed samples around the world that represent different climate zones. The validation shows that Teddy is able to reproduce historical diurnal courses with high correlations >0.9 for all variables, except for wind speed (>0.75) and precipitation (>0.5). We discuss the limitations of the method regarding the reproduction of precipitation extremes, interday connectivity, and disaggregation of end-of-century projections with strong warming. Depending on the use case, sub-daily data provided by the Teddy tool could make climate impact assessments more robust and reliable.","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":"399 1","pages":"0"},"PeriodicalIF":4.0000,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Teddy tool v1.1: temporal disaggregation of daily climate model data for climate impact analysis\",\"authors\":\"Florian Zabel, Benjamin Poschlod\",\"doi\":\"10.5194/gmd-16-5383-2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Climate models provide the required input data for global or regional climate impact analysis in temporally aggregated form, often in daily resolution to save space on data servers. Today, many impact models work with daily data; however, sub-daily climate information is becoming increasingly important for more and more models from different sectors, such as the agricultural, water, and energy sectors. Therefore, the open-source Teddy tool (temporal disaggregation of daily climate model data) has been developed to disaggregate (temporally downscale) daily climate data to sub-daily hourly values. Here, we describe and validate the temporal disaggregation, which is based on the choice of daily climate analogues. In this study, we apply the Teddy tool to disaggregate bias-corrected climate model data from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We choose to disaggregate temperature, precipitation, humidity, longwave radiation, shortwave radiation, surface pressure, and wind speed. As a reference, globally available bias-corrected hourly reanalysis WFDE5 (WATCH Forcing Data methodology applied to ERA5) data from 1980–2019 are used to take specific local and seasonal features of the empirical diurnal profiles into account. For a given location and day within the climate model data, the Teddy tool screens the reference data set to find the most similar meteorological day based on rank statistics. The diurnal profile of the reference data is then applied on the climate model. The physical dependency between variables is preserved, since the diurnal profile of all variables is taken from the same, most similar meteorological day of the historical reanalysis dataset. Mass and energy are strictly preserved by the Teddy tool to exactly reproduce the daily values from the climate models. For evaluation, we aggregate the hourly WFDE5 data to daily values and apply the Teddy tool for disaggregation. Thereby, we compare the original hourly data with the data disaggregated by Teddy. We perform a sensitivity analysis of different time window sizes used for finding the most similar meteorological day in the past. In addition, we perform a cross-validation and autocorrelation analysis for 30 globally distributed samples around the world that represent different climate zones. The validation shows that Teddy is able to reproduce historical diurnal courses with high correlations >0.9 for all variables, except for wind speed (>0.75) and precipitation (>0.5). We discuss the limitations of the method regarding the reproduction of precipitation extremes, interday connectivity, and disaggregation of end-of-century projections with strong warming. Depending on the use case, sub-daily data provided by the Teddy tool could make climate impact assessments more robust and reliable.\",\"PeriodicalId\":12799,\"journal\":{\"name\":\"Geoscientific Model Development\",\"volume\":\"399 1\",\"pages\":\"0\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2023-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geoscientific Model Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5194/gmd-16-5383-2023\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscientific Model Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/gmd-16-5383-2023","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
The Teddy tool v1.1: temporal disaggregation of daily climate model data for climate impact analysis
Abstract. Climate models provide the required input data for global or regional climate impact analysis in temporally aggregated form, often in daily resolution to save space on data servers. Today, many impact models work with daily data; however, sub-daily climate information is becoming increasingly important for more and more models from different sectors, such as the agricultural, water, and energy sectors. Therefore, the open-source Teddy tool (temporal disaggregation of daily climate model data) has been developed to disaggregate (temporally downscale) daily climate data to sub-daily hourly values. Here, we describe and validate the temporal disaggregation, which is based on the choice of daily climate analogues. In this study, we apply the Teddy tool to disaggregate bias-corrected climate model data from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We choose to disaggregate temperature, precipitation, humidity, longwave radiation, shortwave radiation, surface pressure, and wind speed. As a reference, globally available bias-corrected hourly reanalysis WFDE5 (WATCH Forcing Data methodology applied to ERA5) data from 1980–2019 are used to take specific local and seasonal features of the empirical diurnal profiles into account. For a given location and day within the climate model data, the Teddy tool screens the reference data set to find the most similar meteorological day based on rank statistics. The diurnal profile of the reference data is then applied on the climate model. The physical dependency between variables is preserved, since the diurnal profile of all variables is taken from the same, most similar meteorological day of the historical reanalysis dataset. Mass and energy are strictly preserved by the Teddy tool to exactly reproduce the daily values from the climate models. For evaluation, we aggregate the hourly WFDE5 data to daily values and apply the Teddy tool for disaggregation. Thereby, we compare the original hourly data with the data disaggregated by Teddy. We perform a sensitivity analysis of different time window sizes used for finding the most similar meteorological day in the past. In addition, we perform a cross-validation and autocorrelation analysis for 30 globally distributed samples around the world that represent different climate zones. The validation shows that Teddy is able to reproduce historical diurnal courses with high correlations >0.9 for all variables, except for wind speed (>0.75) and precipitation (>0.5). We discuss the limitations of the method regarding the reproduction of precipitation extremes, interday connectivity, and disaggregation of end-of-century projections with strong warming. Depending on the use case, sub-daily data provided by the Teddy tool could make climate impact assessments more robust and reliable.
期刊介绍:
Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication:
* geoscientific model descriptions, from statistical models to box models to GCMs;
* development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results;
* new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data;
* papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data;
* model experiment descriptions, including experimental details and project protocols;
* full evaluations of previously published models.