Objective Calibration of Regional Climate Models: Application over Europe and North America

AbstractAn important source of model uncertainty in climate models arises from unconfined model parameters in physical parameterizations. These parameters are commonly estimated on the basis of manual adjustments (expert tuning), which carries the risk of overtuning the parameters for a specific climate region or time period. This issue is particularly germane in the case of regional climate models (RCMs), which are often developed and used in one or a few geographical regions only. This study addresses the role of objective parameter calibration in this context. Using a previously developed objective calibration methodology, an RCM is calibrated over two regions (Europe and North America) and is used to investigate the transferability of the results. A total of eight different model parameters are calibrated, using a metamodel to account for parameter interactions. The study demonstrates that the calibration is effective in reducing model biases in both domains. For Europe, this concerns in particular a ...

[1]  Lynn W. Gelhar,et al.  Stochastic subsurface hydrology from theory to applications , 1986 .

[2]  J. Curry,et al.  Comparing Arctic Regional Climate Model , 2002 .

[3]  H. Douville,et al.  European temperatures in CMIP5: origins of present-day biases and future uncertainties , 2013, Climate Dynamics.

[4]  D. Lüthi,et al.  Physical constraints for temperature biases in climate models , 2013 .

[5]  Omar Bellprat,et al.  Objective calibration of regional climate models: OBJECTIVE CALIBRATION OF RCMS , 2012 .

[6]  M. Castro,et al.  CLARIS Project: towards climate downscaling in South America , 2010 .

[7]  D. Lawrence,et al.  Regions of Strong Coupling Between Soil Moisture and Precipitation , 2004, Science.

[8]  M. Webb,et al.  Quantification of modelling uncertainties in a large ensemble of climate change simulations , 2004, Nature.

[9]  M. Webb,et al.  Structural similarities and differences in climate responses to CO2 increase between two perturbed physics ensembles. , 2010 .

[10]  E. Fischer,et al.  Changes in European summer temperature variability revisited , 2012 .

[11]  J. Christensen,et al.  A summary of the PRUDENCE model projections of changes in European climate by the end of this century , 2007 .

[12]  Myoung-Seok Suh,et al.  Regional Climate Model Intercomparison Project for Asia , 2005 .

[13]  A. Comrie,et al.  The North American Monsoon , 1997 .

[14]  Robert Pincus,et al.  On Constraining Estimates of Climate Sensitivity with Present-Day Observations through Model Weighting , 2011 .

[15]  B. Rockel,et al.  The performance of the regional climate model CLM in different climate regions, based on the example of precipitation , 2008 .

[16]  James C McWilliams,et al.  Considerations for parameter optimization and sensitivity in climate models , 2010, Proceedings of the National Academy of Sciences.

[17]  J. Christensen,et al.  Overestimation of Mediterranean summer temperature projections due to model deficiencies , 2012 .

[18]  M. D. McKay,et al.  A comparison of three methods for selecting values of input variables in the analysis of output from a computer code , 2000 .

[19]  R. Arritt,et al.  The Great Plains Low-Level Jet during the Warm Season of 1993 , 1997 .

[20]  René Laprise,et al.  Regional climate modelling , 2008, J. Comput. Phys..

[21]  J. Murphy,et al.  A methodology for probabilistic predictions of regional climate change from perturbed physics ensembles , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[22]  J. Gregory,et al.  Land/sea warming ratio in response to climate change: IPCC AR4 model results and comparison with observations , 2007 .

[23]  V. Brovkin,et al.  Impact of soil moisture‐climate feedbacks on CMIP5 projections: First results from the GLACE‐CMIP5 experiment , 2013 .

[24]  C. Schär,et al.  Evaluation of the convection‐resolving regional climate modeling approach in decade‐long simulations , 2014 .

[25]  S. Schubert,et al.  Climatology of the Simulated Great Plains Low-Level Jet and Its Contribution to the Continental Moisture Budget of the United States , 1995 .

[26]  S. Seneviratne,et al.  Investigating soil moisture-climate interactions in a changing climate: A review , 2010 .

[27]  M. Allen Do-it-yourself climate prediction , 1999, Nature.

[28]  L. Mearns,et al.  Towards Assessing NARCCAP Regional Climate Model Credibility for the North American Monsoon: Current Climate Simulations* , 2013 .

[29]  D. Klocke,et al.  Tuning the climate of a global model , 2012 .

[30]  D. Lüthi,et al.  The role of increasing temperature variability in European summer heatwaves , 2004, Nature.

[31]  Omar Bellprat,et al.  Exploring Perturbed Physics Ensembles in a Regional Climate Model , 2012 .

[32]  G. Balsamo,et al.  The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA‐Interim reanalysis data , 2014 .

[33]  S. Seneviratne,et al.  Analysis of ERA40-driven CLM simulations for Europe , 2008 .

[34]  F. Giorgi,et al.  Addressing climate information needs at the regional level: the CORDEX framework , 2009 .

[35]  D. Jackson,et al.  Trends in Global Cloud Cover in Two Decades of HIRS Observations , 2005 .

[36]  Shaocheng Xie,et al.  Diagnosis of the summertime warm and dry bias over the U.S. Southern Great Plains in the GFDL climate model using a weather forecasting approach , 2006 .

[37]  Benjamin M. Sanderson,et al.  A Multimodel Study of Parametric Uncertainty in Predictions of Climate Response to Rising Greenhouse Gas Concentrations , 2011 .

[38]  P. Jones,et al.  Updated high‐resolution grids of monthly climatic observations – the CRU TS3.10 Dataset , 2014 .

[39]  S. Seneviratne,et al.  Systematic land climate and evapotranspiration biases in CMIP5 simulations , 2014, Geophysical research letters.

[40]  Ivan Güttler,et al.  RegCM4 : model description and preliminary tests over multiple CORDEX domains , 2012 .

[41]  E. Fischer,et al.  Soil Moisture–Atmosphere Interactions during the 2003 European Summer Heat Wave , 2007 .

[42]  P. Jones,et al.  Representing Twentieth-Century Space-Time Climate Variability. Part II: Development of 1901-96 Monthly Grids of Terrestrial Surface Climate , 2000 .

[43]  P. Jones,et al.  A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006 , 2008 .

[44]  D. Lüthi,et al.  European summer climate variability in a heterogeneous multi-model ensemble , 2007 .

[45]  D. Lüthi,et al.  Implementation and evaluation of aerosol and cloud microphysics in a regional climate model , 2011 .

[46]  C. Frei,et al.  High Resolution Sensitivity Studies with the Regional Climate Model CCLM in the Alpine Region , 2008 .

[47]  Renato Ramos da Silva,et al.  Project to Intercompare Regional Climate Simulations (PIRCS): Description and initial results , 1999 .

[48]  Van Genuchten,et al.  A closed-form equation for predicting the hydraulic conductivity of unsaturated soils , 1980 .

[49]  J. Christensen,et al.  On the need for bias correction of regional climate change projections of temperature and precipitation , 2008 .

[50]  F. Giorgi,et al.  The Effects of Domain Choice on Summer Precipitation Simulation and Sensitivity in a Regional Climate Model , 1998 .

[51]  Hans von Storch,et al.  Dynamical downscaling: Assessment of model system dependent retained and added variability for two different regional climate models , 2008 .

[52]  L. Terray,et al.  Land–sea contrast, soil-atmosphere and cloud-temperature interactions: interplays and roles in future summer European climate change , 2014, Climate Dynamics.

[53]  Ramón de Elía,et al.  Internal Variability in Regional Climate Downscaling at the Seasonal Scale , 2007 .

[54]  Fahad Saeed,et al.  Assessing the Transferability of the Regional Climate Model REMO to Different COordinated Regional Climate Downscaling EXperiment (CORDEX) Regions , 2012 .

[55]  A. Zadra,et al.  Transferability Intercomparison: An Opportunity for New Insight on the Global Water Cycle and Energy Budget , 2007 .

[56]  A. Lacis,et al.  Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data , 2004 .

[57]  S. Seneviratne,et al.  COSMO-CLM2: a new version of the COSMO-CLM model coupled to the Community Land Model , 2011 .

[58]  David P. Rowell,et al.  Causes and uncertainty of future summer drying over Europe , 2006 .

[59]  Hao Luo,et al.  High dimensional decision dilemmas in climate models , 2013 .

[60]  D. Lüthi,et al.  Elevation gradients of European climate change in the regional climate model COSMO-CLM , 2012, Climatic Change.

[61]  Paul J. Valdes,et al.  Optimal tuning of a GCM using modern and glacial constraints , 2010, Climate Dynamics.

[62]  Leonard A. Smith,et al.  Uncertainty in predictions of the climate response to rising levels of greenhouse gases , 2005, Nature.

[63]  R. Vautard,et al.  Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble , 2014 .

[64]  D. Cherkauer,et al.  Scale Dependency of Hydraulic Conductivity Measurements , 1995 .

[65]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[66]  R. Laprise,et al.  Challenging some tenets of Regional Climate Modelling , 2008 .

[67]  D. Lüthi,et al.  Interannual variability and regional climate simulations , 1996 .

[68]  Richard A. L. Jones,et al.  The North American Regional Climate Change Assessment Program: Overview of Phase I Results , 2012 .

[69]  Reto Knutti,et al.  Constraints on radiative forcing and future climate change from observations and climate model ensembles , 2002, Nature.

[70]  J. Steppeler,et al.  Meso-gamma scale forecasts using the nonhydrostatic model LM , 2003 .

[71]  S. Attinger,et al.  Multiscale parameter regionalization of a grid‐based hydrologic model at the mesoscale , 2010 .