On the need for bias correction of regional climate change projections of temperature and precipitation

Jens Hesselbjerg Christensen; Fredrik Boberg; Ole Bøssing Christensen; Philippe Lucas-Picher

doi:10.1029/2008GL035694

On the need for bias correction of regional climate change projections of temperature and precipitation

Jens Hesselbjerg Christensen^*, Fredrik Boberg, Ole Bøssing Christensen, Philippe Lucas-Picher

^*Corresponding author for this work

426 Citations (Scopus)

Abstract

Within the framework of the European project ENSEMBLES (ensembles-based predictions of climate changes and their impacts) we explore the systematic bias in simulated monthly mean temperature and precipitation for an ensemble of thirteen regional climate models (RCMs). The models have been forced with the European Centre for Medium Range Weather Forecasting Reanalysis (ERA40) and are compared to a new high resolution gridded observational data set. We find that each model has a distinct systematic bias relating both temperature and precipitation bias to the observed mean. By excluding the twenty-five percent warmest and wettest months, respectively, we find that a derived second-order fit from the remaining months can be used to estimate the values of the excluded months. We demonstrate that the common assumption of bias cancellation (invariance) in climate change projections can have significant limitations when temperatures in the warmest months exceed 4-6 °C above present day conditions.

Original language	English
Article number	L20709
Journal	Geophysical Research Letters
Volume	35
Issue number	20
Number of pages	6
ISSN	0094-8276
DOIs	https://doi.org/10.1029/2008GL035694
Publication status	Published - 2008
Externally published	Yes

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10.1029/2008GL035694

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title = "On the need for bias correction of regional climate change projections of temperature and precipitation",

abstract = "Within the framework of the European project ENSEMBLES (ensembles-based predictions of climate changes and their impacts) we explore the systematic bias in simulated monthly mean temperature and precipitation for an ensemble of thirteen regional climate models (RCMs). The models have been forced with the European Centre for Medium Range Weather Forecasting Reanalysis (ERA40) and are compared to a new high resolution gridded observational data set. We find that each model has a distinct systematic bias relating both temperature and precipitation bias to the observed mean. By excluding the twenty-five percent warmest and wettest months, respectively, we find that a derived second-order fit from the remaining months can be used to estimate the values of the excluded months. We demonstrate that the common assumption of bias cancellation (invariance) in climate change projections can have significant limitations when temperatures in the warmest months exceed 4-6 °C above present day conditions.",

author = "Christensen, {Jens Hesselbjerg} and Fredrik Boberg and Christensen, {Ole B{\o}ssing} and Philippe Lucas-Picher",

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T1 - On the need for bias correction of regional climate change projections of temperature and precipitation

AU - Christensen, Jens Hesselbjerg

AU - Boberg, Fredrik

AU - Christensen, Ole Bøssing

AU - Lucas-Picher, Philippe

PY - 2008

Y1 - 2008

N2 - Within the framework of the European project ENSEMBLES (ensembles-based predictions of climate changes and their impacts) we explore the systematic bias in simulated monthly mean temperature and precipitation for an ensemble of thirteen regional climate models (RCMs). The models have been forced with the European Centre for Medium Range Weather Forecasting Reanalysis (ERA40) and are compared to a new high resolution gridded observational data set. We find that each model has a distinct systematic bias relating both temperature and precipitation bias to the observed mean. By excluding the twenty-five percent warmest and wettest months, respectively, we find that a derived second-order fit from the remaining months can be used to estimate the values of the excluded months. We demonstrate that the common assumption of bias cancellation (invariance) in climate change projections can have significant limitations when temperatures in the warmest months exceed 4-6 °C above present day conditions.

AB - Within the framework of the European project ENSEMBLES (ensembles-based predictions of climate changes and their impacts) we explore the systematic bias in simulated monthly mean temperature and precipitation for an ensemble of thirteen regional climate models (RCMs). The models have been forced with the European Centre for Medium Range Weather Forecasting Reanalysis (ERA40) and are compared to a new high resolution gridded observational data set. We find that each model has a distinct systematic bias relating both temperature and precipitation bias to the observed mean. By excluding the twenty-five percent warmest and wettest months, respectively, we find that a derived second-order fit from the remaining months can be used to estimate the values of the excluded months. We demonstrate that the common assumption of bias cancellation (invariance) in climate change projections can have significant limitations when temperatures in the warmest months exceed 4-6 °C above present day conditions.

U2 - 10.1029/2008GL035694

DO - 10.1029/2008GL035694

M3 - Journal article

AN - SCOPUS:58249085384

SN - 0094-8276

VL - 35

JO - Geophysical Research Letters

JF - Geophysical Research Letters

IS - 20

M1 - L20709

ER -

On the need for bias correction of regional climate change projections of temperature and precipitation

Abstract

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