Detecting change in UK extreme precipitation using results from the climateprediction.net BBC climate change experiment

We investigate a question posed by policy makers, namely, “when will changes in extreme precipitation due to climate change be detectable?” To answer this question we use climateprediction.net (CPDN) model simulations from the BBC Climate Change Experiment (CCE) over the UK. These provide us with the unique opportunity to compare 1-day extreme precipitation generated from climate altered by observed forcings (time period 1920–2000) and the SRES A1B emissions scenario (time period 2000–2080) (the Scenario) to extreme precipitation generated by a constant climate for year 1920 (the Control) for the HadCM3L General Circulation Model (GCM). We fit non-stationary Generalized Extreme Value (GEV) models to the Scenario output and compare these to stationary GEV models fit to the parallel Control. We define the time of detectable change as the time at which we would reject a hypothesis at the α = 0.05 significance level that the 20-year return level of the two runs is equal. We find that the time of detectable change depends on the season, with most model runs indicating that change to winter extreme precipitation may be detectable by the year 2010, and that change to summer extreme precipitation is not detectable by 2080. We also investigate which climate model parameters affect the weight of the tail of the precipitation distribution and which affect the time of detectable change for the winter season. We find that two climate model parameters have an important effect on the tail weight, and two others seem to affect the time of detection. Importantly, we find that climate model simulated extreme precipitation has a fundamentally different behavior to observations, perhaps due to the negative estimate of the GEV shape parameter, unlike observations which produce a slightly positive (∼0.0–0.2) estimate.

[1]  W. Hays Statistics for the social sciences , 1973 .

[2]  P. Rowntree,et al.  A Mass Flux Convection Scheme with Representation of Cloud Ensemble Characteristics and Stability-Dependent Closure , 1990 .

[3]  G. Oehlert A note on the delta method , 1992 .

[4]  M. Hulme,et al.  Development of a Relationship between Station and Grid-Box Rainday Frequencies for Climate Model Evaluation , 1997 .

[5]  R. Katz Extreme value theory for precipitation: sensitivity analysis for climate change , 1999 .

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

[7]  P. Jones,et al.  Observed trends in the daily intensity of United Kingdom precipitation. , 2000 .

[8]  Raquel V. Francisco,et al.  Evaluating uncertainties in the prediction of regional climate change , 2000 .

[9]  Alexei G. Sankovski,et al.  Special report on emissions scenarios , 2000 .

[10]  J. Räisänen,et al.  Changes in average and extreme precipitation in two regional climate model experiments , 2001 .

[11]  C. Schär,et al.  Detection Probability of Trends in Rare Events: Theory and Application to Heavy Precipitation in the Alpine Region , 2001 .

[12]  L. Bengtsson,et al.  Secular trends in daily precipitation characteristics: greenhouse gas simulation with a coupled AOGCM , 2002 .

[13]  Eric P. Smith,et al.  An Introduction to Statistical Modeling of Extreme Values , 2002, Technometrics.

[14]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[15]  J. Algina,et al.  Generalized eta and omega squared statistics: measures of effect size for some common research designs. , 2003, Psychological methods.

[16]  H. Fowler,et al.  A regional frequency analysis of United Kingdom extreme rainfall from 1961 to 2000 , 2003 .

[17]  Chris T. Jones A Fast Ocean GCM without Flux Adjustments , 2003 .

[18]  K. Taylor,et al.  An overview of results from the Coupled Model Intercomparison Project , 2003 .

[19]  H. Fowler,et al.  Implications of changes in seasonal and annual extreme rainfall , 2003 .

[20]  David M. H. Sexton,et al.  Comparison of Modeled and Observed Trends in Indices of Daily Climate Extremes , 2003 .

[21]  K. Trenberth,et al.  The changing character of precipitation , 2003 .

[22]  Francis W. Zwiers,et al.  Detectability of Anthropogenic Changes in Annual Temperature and Precipitation Extremes , 2004 .

[23]  P. Stott,et al.  Detection and attribution of changes in 20th century land precipitation , 2004 .

[24]  M. Ekströma,et al.  New estimates of future changes in extreme rainfall across the UK using regional climate model integrations . 2 . Future estimates and use in impact studies , 2004 .

[25]  P. Jones,et al.  New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 1. Assessment of control climate , 2005 .

[26]  D. Stainforth,et al.  The challenge of volunteer computing with lengthy climate model simulations , 2005, First International Conference on e-Science and Grid Computing (e-Science'05).

[27]  D. Easterling,et al.  Trends in Intense Precipitation in the Climate Record , 2005 .

[28]  Nicole A. Lazar,et al.  Statistics of Extremes: Theory and Applications , 2005, Technometrics.

[29]  A. Davison,et al.  Generalized additive modelling of sample extremes , 2005 .

[30]  P. Jones,et al.  New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 2. Future estimates and use in impact studies , 2005 .

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

[32]  Claudia Tebaldi,et al.  Understanding future patterns of increased precipitation intensity in climate model simulations , 2005 .

[33]  Francis W. Zwiers,et al.  Estimating Extremes in Transient Climate Change Simulations , 2005 .

[34]  M. Allen,et al.  Constraints on climate change from a multi‐thousand member ensemble of simulations , 2005 .

[35]  Ralf Toumi,et al.  A fundamental probability distribution for heavy rainfall , 2005 .

[36]  Francis W. Zwiers,et al.  Climate Change Detection and Attribution: Beyond Mean Temperature Signals , 2006 .

[37]  L. Haan,et al.  Extreme value theory : an introduction , 2006 .

[38]  J. V. Revadekar,et al.  Global observed changes in daily climate extremes of temperature and precipitation , 2006 .

[39]  L. Haan,et al.  Extreme value theory , 2006 .

[40]  Jonathan M. Gregory,et al.  The impact of natural and anthropogenic forcings on climate and hydrology since 1550 , 2006 .

[41]  G. Hegerl,et al.  Detection of human influence on twentieth-century precipitation trends , 2007, Nature.

[42]  Claudia Tebaldi,et al.  Going to the extremes , 2007 .

[43]  G. Hegerl,et al.  Changes in temperature and precipitation extremes in the IPCC ensemble of global coupled model simulations , 2007 .

[44]  G. Hegerl,et al.  Understanding and Attributing Climate Change , 2007 .

[45]  Chris G. Knight,et al.  Association of parameter, software, and hardware variation with large-scale behavior across 57,000 climate models , 2007, Proceedings of the National Academy of Sciences.

[46]  H. Fowler,et al.  Estimating change in extreme European precipitation using a multimodel ensemble , 2007 .

[47]  Reto Knutti,et al.  The use of the multi-model ensemble in probabilistic climate projections , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[48]  K. Trenberth,et al.  Observations: Surface and Atmospheric Climate Change , 2007 .

[49]  G. Meehl,et al.  An intercomparison of model-simulated historical and future changes in extreme events , 2007 .

[50]  Jeffrey T. Kiehl,et al.  Twentieth century climate model response and climate sensitivity , 2007 .

[51]  C. Piani,et al.  The climateprediction.net BBC climate change experiment: design of the coupled model ensemble , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[52]  J. Gregory,et al.  Dependence of the land‐sea contrast in surface climate response on the nature of the forcing , 2008 .

[53]  D. Stone,et al.  Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations , 2008 .

[54]  Reto Knutti,et al.  Constraints on Model Response to Greenhouse Gas Forcing and the Role of Subgrid-Scale Processes , 2008 .

[55]  H. Fowler,et al.  Multi‐model ensemble estimates of climate change impacts on UK seasonal precipitation extremes , 2009 .

[56]  D. Frame,et al.  Quantifying the effects of perturbing the physics of an interactive sulfur scheme using an ensemble of GCMs on the climateprediction.net platform , 2009 .

[57]  B. Booth,et al.  Changes in the Global Sulfate Burden due to Perturbations in Global CO2 Concentrations , 2009 .

[58]  H. Fowler,et al.  Detecting changes in seasonal precipitation extremes using regional climate model projections: Implications for managing fluvial flood risk , 2010 .