Towards process-informed bias correction of climate change simulations

[1]  T. Shepherd,et al.  The modulation of stationary waves, and their response to climate change, by parameterized orographic drag , 2017 .

[2]  Hannah M. Christensen,et al.  Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model , 2017 .

[3]  Mathieu Vrac,et al.  A combined statistical bias correction and stochastic downscaling method for precipitation , 2016 .

[4]  C. Castro,et al.  Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes , 2016 .

[5]  T. Shepherd,et al.  Climate model biases in jet streams, blocking and storm tracks resulting from missing orographic drag , 2016 .

[6]  R. Furrer,et al.  Propagation of biases in climate models from the synoptic to the regional scale: Implications for bias adjustment , 2016 .

[7]  C. Schär,et al.  Does Quantile Mapping of Simulated Precipitation Correct for Biases in Transition Probabilities and Spell Lengths , 2016 .

[8]  T. Shepherd,et al.  Missing orographic drag leads to climate model biases in jet streams, blocking and storm tracks , 2016 .

[9]  Isla R. Simpson,et al.  Causes of change in Northern Hemisphere winter meridional winds and regional hydroclimate , 2016 .

[10]  Vladimir A. Semenov,et al.  Evidence for added value of convection‐permitting models for studying changes in extreme precipitation , 2015 .

[11]  B. Hewitson,et al.  Toward an Ethical Framework for Climate Services , 2015 .

[12]  J. Abatzoglou,et al.  Improved Bias Correction Techniques for Hydrological Simulations of Climate Change , 2015 .

[13]  A. Gobiet,et al.  The effect of empirical-statistical correction of intensity-dependent model errors on the temperature climate change signal , 2015 .

[14]  B. Goswami,et al.  Drying of Indian subcontinent by rapid Indian Ocean warming and a weakening land-sea thermal gradient , 2015, Nature Communications.

[15]  Daniel Walton,et al.  A Hybrid Dynamical–Statistical Downscaling Technique. Part I: Development and Validation of the Technique , 2015 .

[16]  W. Robinson,et al.  North Atlantic Storm-Track Sensitivity to Warming Increases with Model Resolution , 2015 .

[17]  R. Leung,et al.  A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges , 2015, Reviews of geophysics.

[18]  Tim Li,et al.  Causes of Strengthening and Weakening of ENSO Amplitude under Global Warming in Four CMIP5 Models , 2015 .

[19]  D. Maraun,et al.  The representation of location by a regional climate model in complex terrain , 2015 .

[20]  Leonard A. Smith,et al.  Tales of future weather , 2015 .

[21]  P. Friederichs,et al.  Multivariate—Intervariable, Spatial, and Temporal—Bias Correction* , 2015 .

[22]  M. Meredith,et al.  Circulation, retention, and mixing of waters within the Weddell‐Scotia Confluence, Southern Ocean: The role of stratified Taylor columns , 2015 .

[23]  S. Kotlarski,et al.  VALUE: A framework to validate downscaling approaches for climate change studies , 2015 .

[24]  A. Hall Projecting regional change , 2014, Science.

[25]  T. Shepherd Atmospheric circulation as a source of uncertainty in climate change projections , 2014 .

[26]  M. Dettinger,et al.  An Enhanced Archive Facilitating Climate Impacts and Adaptation Analysis , 2014 .

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

[28]  H. Fowler,et al.  Heavier summer downpours with climate change revealed by weather forecast resolution model , 2014 .

[29]  C. Mechoso,et al.  A global perspective on CMIP5 climate model biases , 2014 .

[30]  G. Yohe,et al.  Climate Change Impacts in the United States: The Third National Climate Assessment , 2014 .

[31]  Joseph Daron,et al.  Interrogating empirical-statistical downscaling , 2014, Climatic Change.

[32]  F. Piontek,et al.  The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework , 2013, Proceedings of the National Academy of Sciences.

[33]  Linda O. Mearns,et al.  The Practitioner's Dilemma: How to Assess the Credibility of Downscaled Climate Projections , 2013 .

[34]  D. Pierce,et al.  Bias correction can modify climate model simulated precipitation changes without adverse effect on the ensemble mean , 2013 .

[35]  Brian J. Hoskins,et al.  Winter and Summer Northern Hemisphere Blocking in CMIP5 Models , 2013 .

[36]  D. Wuebbles,et al.  An asynchronous regional regression model for statistical downscaling of daily climate variables , 2013 .

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

[38]  F. Piontek,et al.  A trend-preserving bias correction – the ISI-MIP approach , 2013 .

[39]  Kevin I. Hodges,et al.  The Ability of CMIP5 Models to Simulate North Atlantic Extratropical Cyclones , 2013 .

[40]  Jakob Runge,et al.  Turn down the heat : climate extremes, regional impacts, and the case for resilience - full report , 2013 .

[41]  Gregg M. Garfin,et al.  Assessment of Climate Change in the Southwest United States: A Report Prepared for the National Climate Assessment , 2013 .

[42]  J. Hafner,et al.  Global Warming Shifts the Monsoon Circulation, Drying South Asia , 2013 .

[43]  E. Guilyardi,et al.  ENSO representation in climate models: from CMIP3 to CMIP5 , 2013, Climate Dynamics.

[44]  D. Maraun Reply to “Comment on ‘Bias Correction, Quantile Mapping, and Downscaling: Revisiting the Inflation Issue’” , 2013 .

[45]  M. Jenkinson,et al.  Can correcting feature location in simulated mean climate improve agreement on projected changes? , 2013 .

[46]  A. Hall,et al.  On the persistent spread in snow-albedo feedback , 2012, Climate Dynamics.

[47]  E. Maurer,et al.  Making Climate Data Relevant to Decision Making: The important details of Spatial and Temporal Downscaling , 2013 .

[48]  J. Overpeck,et al.  Future Climate: Projected Average , 2013 .

[49]  J. Christensen,et al.  Temperature dependent climate projection deficiencies in CMIP5 models , 2012 .

[50]  S. Hagemann,et al.  Climate change impact on available water resources obtained using multiple global climate and hydrology models , 2012 .

[51]  J. Seibert,et al.  Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions? , 2012 .

[52]  Andrew Dawson,et al.  Simulating regime structures in weather and climate prediction models , 2012 .

[53]  C. Piani,et al.  Two dimensional bias correction of temperature and precipitation copulas in climate models , 2012 .

[54]  Rowan Sutton,et al.  The impact of North Atlantic sea surface temperature errors on the simulation of North Atlantic European region climate , 2012 .

[55]  Lukas Gudmundsson,et al.  Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations – a comparison of methods , 2012 .

[56]  Volker Wulfmeyer,et al.  HESS Opinions "Should we apply bias correction to global and regional climate model data?" , 2012 .

[57]  P. Paruolo,et al.  Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: Analysis of the climate change signal , 2012 .

[58]  J. Seibert,et al.  Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods , 2012 .

[59]  P. Berg,et al.  Bias correction of high resolution regional climate model data , 2012 .

[60]  R. Vautard,et al.  Regional climate downscaling with prior statistical correction of the global climate forcing , 2012 .

[61]  Sebastian Rast,et al.  Skill, Correction, and Downscaling of GCM-Simulated Precipitation , 2012 .

[62]  P. Cox,et al.  Quantifying future climate change , 2012 .

[63]  Douglas Maraun,et al.  Nonstationarities of regional climate model biases in European seasonal mean temperature and precipitation sums , 2012 .

[64]  Ashish Sharma,et al.  A nesting model for bias correction of variability at multiple time scales in general circulation model precipitation simulations , 2012 .

[65]  S. Vannitsem,et al.  Bias correction and post-processing under climate change , 2011 .

[66]  Chris Harris,et al.  Improved Atlantic winter blocking in a climate model , 2011 .

[67]  Hydrologic projections for the western United States , 2011 .

[68]  S. Hagemann,et al.  On the contribution of statistical bias correction to the uncertainty in the projected hydrological cycle , 2011 .

[69]  P. Paruolo,et al.  Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models , 2011 .

[70]  A. Thomson,et al.  The representative concentration pathways: an overview , 2011 .

[71]  Dieter Gerten,et al.  Impact of a Statistical Bias Correction on the Projected Hydrological Changes Obtained from Three GCMs and Two Hydrology Models , 2011 .

[72]  A. Gobiet,et al.  Empirical‐statistical downscaling and error correction of daily precipitation from regional climate models , 2011 .

[73]  C. Skinner,et al.  Influence of SST biases on future climate change projections , 2011 .

[74]  Ashish Sharma,et al.  Accounting for interannual variability: A comparison of options for water resources climate change impact assessments , 2011 .

[75]  Gauss M. Cordeiro,et al.  Bias Correction , 2011, International Encyclopedia of Statistical Science.

[76]  Christopher Moseley,et al.  Climate model bias correction and the role of timescales , 2010 .

[77]  R. Wilby,et al.  Scenario-neutral approach to climate change impact studies: Application to flood risk , 2010 .

[78]  D. Maraun,et al.  Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user , 2010 .

[79]  T. Woollings Dynamical influences on European climate: an uncertain future , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[80]  E. Wood,et al.  Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching , 2010 .

[81]  C. Piani,et al.  Statistical bias correction for daily precipitation in regional climate models over Europe , 2010 .

[82]  Ping Liu,et al.  An MJO Simulated by the NICAM at 14- and 7-km Resolutions , 2009 .

[83]  Paul-Antoine Michelangeli,et al.  Probabilistic downscaling approaches: Application to wind cumulative distribution functions , 2009 .

[84]  H. Künsch,et al.  Bayesian multi-model projection of climate: bias assumptions and interannual variability , 2009 .

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

[86]  A. Hall,et al.  Improving predictions of summer climate change in the United States , 2008 .

[87]  E. Maurer,et al.  Fine‐resolution climate projections enhance regional climate change impact studies , 2007 .

[88]  C. Sordo,et al.  Analysis and downscaling multi-model seasonal forecasts in Peru using self-organizing maps , 2005 .

[89]  José Manuel Gutiérrez Llorente,et al.  Analysis and downscaling multi-model seasonal forecasts in Peru using self-organizing maps , 2005 .

[90]  Eric A. Rosenberg,et al.  A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States: Update and Extensions* , 2002 .

[91]  Anders Moberg,et al.  Daily dataset of 20th‐century surface air temperature and precipitation series for the European Climate Assessment , 2002 .

[92]  D. Lüthi,et al.  Surrogate climate-change scenarios for regional climate models , 1996 .