Using a massive high‐resolution ensemble climate data set to examine dynamic and thermodynamic aspects of heavy precipitation change

Abstract This study investigated the relationship between extreme precipitation and near‐surface temperature (precipitation–temperature relation) from two different perspectives, the rate of change of precipitation with temperature and dynamic (i.e., effect of the change in atmospheric motion) and t...

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Autores principales:	Tomohito J. Yamada, Tsuyoshi Hoshino, Akihiro Suzuki
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Clausius‐Clapeyron relation d4PDF dynamic dynamical downscaling ensemble data high resolution Meteorology. Climatology QC851-999
Acceso en línea:	https://doaj.org/article/58f7aeb16d904de5b120d6b0cab10d06
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spelling	oai:doaj.org-article:58f7aeb16d904de5b120d6b0cab10d062021-12-01T20:00:13ZUsing a massive high‐resolution ensemble climate data set to examine dynamic and thermodynamic aspects of heavy precipitation change1530-261X10.1002/asl.1065https://doaj.org/article/58f7aeb16d904de5b120d6b0cab10d062021-12-01T00:00:00Zhttps://doi.org/10.1002/asl.1065https://doaj.org/toc/1530-261XAbstract This study investigated the relationship between extreme precipitation and near‐surface temperature (precipitation–temperature relation) from two different perspectives, the rate of change of precipitation with temperature and dynamic (i.e., effect of the change in atmospheric motion) and thermodynamic (i.e., effect of the change in atmospheric moisture content) aspects, using a 5‐km dynamical downscaled hundreds‐year data set for past climate condition (PAST; from 1951 to 2010) and future climate condition (FUTURE; 4°C warmer than the preindustrial condition). Initially, using the observation and the PAST and FUTURE data sets, it was found that the 99th and 99.9th percentile hourly precipitation for each temperature bin (P99 and P99.9, respectively) paralleled the slope of the Clausius–Clapeyron (C–C) relation for a certain temperature range over the Tokachi River basin in Hokkaido, the northern island of Japan; however, both P99 and P99.9 decreased in the high‐temperature range. Next, we examined the cause of the P99 and P99.9 differences between PAST and FUTURE for each temperature bin by classifying dynamic and thermodynamic factors. The result showed that the thermodynamic effect dominates the differences in P99 and P99.9 between PAST and FUTURE, which means that the thermodynamic effect is the main component of the precipitation–temperature relation. Similar analyses were applied to the whole river basin, including the mountainous area. The results showed that the differences in P99 and P99.9 between PAST and FUTURE are mainly due to the thermodynamic contribution, regardless of plain or mountain area. Using such large model data sets, we could make a robust assessment of the precipitation–temperature relation and the dynamic and thermodynamic contributions to precipitation changes. Moreover, using the 5‐km resolution hundreds‐year data set enabled us to quantify the spatial distribution of such precipitation characteristics over a thousands of square kilometer catchment.Tomohito J. YamadaTsuyoshi HoshinoAkihiro SuzukiWileyarticleClausius‐Clapeyron relationd4PDFdynamicdynamical downscalingensemble datahigh resolutionMeteorology. ClimatologyQC851-999ENAtmospheric Science Letters, Vol 22, Iss 12, Pp n/a-n/a (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Clausius‐Clapeyron relation d4PDF dynamic dynamical downscaling ensemble data high resolution Meteorology. Climatology QC851-999
spellingShingle	Clausius‐Clapeyron relation d4PDF dynamic dynamical downscaling ensemble data high resolution Meteorology. Climatology QC851-999 Tomohito J. Yamada Tsuyoshi Hoshino Akihiro Suzuki Using a massive high‐resolution ensemble climate data set to examine dynamic and thermodynamic aspects of heavy precipitation change
description	Abstract This study investigated the relationship between extreme precipitation and near‐surface temperature (precipitation–temperature relation) from two different perspectives, the rate of change of precipitation with temperature and dynamic (i.e., effect of the change in atmospheric motion) and thermodynamic (i.e., effect of the change in atmospheric moisture content) aspects, using a 5‐km dynamical downscaled hundreds‐year data set for past climate condition (PAST; from 1951 to 2010) and future climate condition (FUTURE; 4°C warmer than the preindustrial condition). Initially, using the observation and the PAST and FUTURE data sets, it was found that the 99th and 99.9th percentile hourly precipitation for each temperature bin (P99 and P99.9, respectively) paralleled the slope of the Clausius–Clapeyron (C–C) relation for a certain temperature range over the Tokachi River basin in Hokkaido, the northern island of Japan; however, both P99 and P99.9 decreased in the high‐temperature range. Next, we examined the cause of the P99 and P99.9 differences between PAST and FUTURE for each temperature bin by classifying dynamic and thermodynamic factors. The result showed that the thermodynamic effect dominates the differences in P99 and P99.9 between PAST and FUTURE, which means that the thermodynamic effect is the main component of the precipitation–temperature relation. Similar analyses were applied to the whole river basin, including the mountainous area. The results showed that the differences in P99 and P99.9 between PAST and FUTURE are mainly due to the thermodynamic contribution, regardless of plain or mountain area. Using such large model data sets, we could make a robust assessment of the precipitation–temperature relation and the dynamic and thermodynamic contributions to precipitation changes. Moreover, using the 5‐km resolution hundreds‐year data set enabled us to quantify the spatial distribution of such precipitation characteristics over a thousands of square kilometer catchment.
format	article
author	Tomohito J. Yamada Tsuyoshi Hoshino Akihiro Suzuki
author_facet	Tomohito J. Yamada Tsuyoshi Hoshino Akihiro Suzuki
author_sort	Tomohito J. Yamada
title	Using a massive high‐resolution ensemble climate data set to examine dynamic and thermodynamic aspects of heavy precipitation change
title_short	Using a massive high‐resolution ensemble climate data set to examine dynamic and thermodynamic aspects of heavy precipitation change
title_full	Using a massive high‐resolution ensemble climate data set to examine dynamic and thermodynamic aspects of heavy precipitation change
title_fullStr	Using a massive high‐resolution ensemble climate data set to examine dynamic and thermodynamic aspects of heavy precipitation change
title_full_unstemmed	Using a massive high‐resolution ensemble climate data set to examine dynamic and thermodynamic aspects of heavy precipitation change
title_sort	using a massive high‐resolution ensemble climate data set to examine dynamic and thermodynamic aspects of heavy precipitation change
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/58f7aeb16d904de5b120d6b0cab10d06
work_keys_str_mv	AT tomohitojyamada usingamassivehighresolutionensembleclimatedatasettoexaminedynamicandthermodynamicaspectsofheavyprecipitationchange AT tsuyoshihoshino usingamassivehighresolutionensembleclimatedatasettoexaminedynamicandthermodynamicaspectsofheavyprecipitationchange AT akihirosuzuki usingamassivehighresolutionensembleclimatedatasettoexaminedynamicandthermodynamicaspectsofheavyprecipitationchange
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Using a massive high‐resolution ensemble climate data set to examine dynamic and thermodynamic aspects of heavy precipitation change

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