An improved estimate of daily precipitation from the ERA5 reanalysis

Abstract Precipitation is an essential climate variable and a fundamental part of the global water cycle. Given its importance to society, precipitation is often assessed in climate monitoring activities, such as in those led by the Copernicus Climate Change Service (C3S). To undertake these activit...

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Main Authors: David A. Lavers, Hans Hersbach, Mark J. Rodwell, Adrian Simmons
Format: Article
Language:English
Published: Wiley 2024-03-01
Series:Atmospheric Science Letters
Subjects:
Online Access:https://doi.org/10.1002/asl.1200
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author David A. Lavers
Hans Hersbach
Mark J. Rodwell
Adrian Simmons
author_facet David A. Lavers
Hans Hersbach
Mark J. Rodwell
Adrian Simmons
author_sort David A. Lavers
collection DOAJ
description Abstract Precipitation is an essential climate variable and a fundamental part of the global water cycle. Given its importance to society, precipitation is often assessed in climate monitoring activities, such as in those led by the Copernicus Climate Change Service (C3S). To undertake these activities, C3S predominantly uses ERA5 reanalysis precipitation. Research has shown that short‐range forecasts for precipitation made from this reanalysis can provide valuable estimates of the actual (observed) precipitation in extratropical regions but can be less useful in the tropics. While some of these limitations will be reduced with future reanalyses because of the latest advancements, there is potentially a more immediate way to improve the precipitation estimate. This is to use the precipitation modelled in the Four‐Dimensional Variational (4D‐Var) data assimilation window of the reanalysis, and it is the aim of this study to evaluate this approach. Using observed 24‐h precipitation accumulations at 5637 stations from 2001 to 2020, results show that smaller root‐mean‐square errors (RMSEs) and mean absolute errors are generally found by using the ERA5 4D‐Var precipitation. For example, for all available days from 2001 to 2020, 87.5% of stations have smaller RMSEs. These improvements are driven by reduced random errors in the 4D‐Var precipitation because it is better constrained by observations, which are themselves sensitive to or influence precipitation. However, there are regions (e.g., Europe) where larger biases occur, and via the decomposition of the Stable Equitable Error in Probability Space score, this is shown to be because the 4D‐Var precipitation has a wetter bias on ‘dry’ days than the standard ERA5 short‐range forecasts. The findings also highlight that the 4D‐Var precipitation does improve the discrimination of ‘heavy’ observed events. In conclusion, an improved ERA5 precipitation estimate is largely obtainable, and these results could prove useful for C3S activities and for future reanalyses, including ERA6.
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spelling doaj.art-2ecca0eb721c4e95a9cd4c0996d3d3072024-03-02T18:46:48ZengWileyAtmospheric Science Letters1530-261X2024-03-01253n/an/a10.1002/asl.1200An improved estimate of daily precipitation from the ERA5 reanalysisDavid A. Lavers0Hans Hersbach1Mark J. Rodwell2Adrian Simmons3European Centre for Medium‐Range Weather Forecasts (ECMWF) Reading UKEuropean Centre for Medium‐Range Weather Forecasts (ECMWF) Reading UKEuropean Centre for Medium‐Range Weather Forecasts (ECMWF) Reading UKEuropean Centre for Medium‐Range Weather Forecasts (ECMWF) Reading UKAbstract Precipitation is an essential climate variable and a fundamental part of the global water cycle. Given its importance to society, precipitation is often assessed in climate monitoring activities, such as in those led by the Copernicus Climate Change Service (C3S). To undertake these activities, C3S predominantly uses ERA5 reanalysis precipitation. Research has shown that short‐range forecasts for precipitation made from this reanalysis can provide valuable estimates of the actual (observed) precipitation in extratropical regions but can be less useful in the tropics. While some of these limitations will be reduced with future reanalyses because of the latest advancements, there is potentially a more immediate way to improve the precipitation estimate. This is to use the precipitation modelled in the Four‐Dimensional Variational (4D‐Var) data assimilation window of the reanalysis, and it is the aim of this study to evaluate this approach. Using observed 24‐h precipitation accumulations at 5637 stations from 2001 to 2020, results show that smaller root‐mean‐square errors (RMSEs) and mean absolute errors are generally found by using the ERA5 4D‐Var precipitation. For example, for all available days from 2001 to 2020, 87.5% of stations have smaller RMSEs. These improvements are driven by reduced random errors in the 4D‐Var precipitation because it is better constrained by observations, which are themselves sensitive to or influence precipitation. However, there are regions (e.g., Europe) where larger biases occur, and via the decomposition of the Stable Equitable Error in Probability Space score, this is shown to be because the 4D‐Var precipitation has a wetter bias on ‘dry’ days than the standard ERA5 short‐range forecasts. The findings also highlight that the 4D‐Var precipitation does improve the discrimination of ‘heavy’ observed events. In conclusion, an improved ERA5 precipitation estimate is largely obtainable, and these results could prove useful for C3S activities and for future reanalyses, including ERA6.https://doi.org/10.1002/asl.1200ERA5observationsprecipitation evaluation
spellingShingle David A. Lavers
Hans Hersbach
Mark J. Rodwell
Adrian Simmons
An improved estimate of daily precipitation from the ERA5 reanalysis
Atmospheric Science Letters
ERA5
observations
precipitation evaluation
title An improved estimate of daily precipitation from the ERA5 reanalysis
title_full An improved estimate of daily precipitation from the ERA5 reanalysis
title_fullStr An improved estimate of daily precipitation from the ERA5 reanalysis
title_full_unstemmed An improved estimate of daily precipitation from the ERA5 reanalysis
title_short An improved estimate of daily precipitation from the ERA5 reanalysis
title_sort improved estimate of daily precipitation from the era5 reanalysis
topic ERA5
observations
precipitation evaluation
url https://doi.org/10.1002/asl.1200
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