Introduction to downscaling Jess Fernndez Jesus.Fernandez@unican.es - PowerPoint PPT Presentation

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Santander Meteorology Group A multidisciplinary approach for weather & climate Introduction to downscaling Jesús Fernández Jesus.Fernandez@unican.es Grupo de Meteorología de Santander Universidad de Cantabria Dept. Matemática Aplicada y CC Comp. SPECS Workshop on seasonal forecasting: Data access, BC & DS 8-12 Sep 2014, Santander

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Outline Santander Meteorology Group A multidisciplinary approach for weather & climate Introduction to downscaling ● Downscaling: why? ● Approaches: dynamical and statistical DS ● Pros and cons ● Seasonal perspective ● Link to bias correction

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Outline Santander Meteorology Group A multidisciplinary approach for weather & climate Introduction to downscaling ● Downscaling: why? ● Approaches: dynamical and statistical DS ● Pros and cons FOCUS ● Seasonal perspective Lessons learnt from long-term RCM simulations ● Link to bias correction

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Downscaling: why? Santander Meteorology Group A multidisciplinary approach for weather & climate Global model Resolution: 3.75° x 3.75° (T30)

http://www.meteo.unican.es A multidisciplinary approach to weather & climate The World as seen by a GCM Santander Meteorology Group A multidisciplinary approach for weather & climate T30

http://www.meteo.unican.es A multidisciplinary approach to weather & climate The World as seen by a GCM Santander Meteorology Group A multidisciplinary approach for weather & climate Global model Resolution: 2.5° x 2.5° (T62)

http://www.meteo.unican.es A multidisciplinary approach to weather & climate The World as seen by a GCM Santander Meteorology Group A multidisciplinary approach for weather & climate T62

http://www.meteo.unican.es A multidisciplinary approach to weather & climate The World as seen by a GCM Santander Meteorology Group A multidisciplinary approach for weather & climate T62

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Santander Meteorology Group A multidisciplinary approach for weather & climate 75 km (~ERA-Interim / System4)

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Santander Meteorology Group A multidisciplinary approach for weather & climate 75 km (~ERA-Interim / System4)

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Santander Meteorology Group A multidisciplinary approach for weather & climate 75 km (~ERA-Interim / System4)

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Downscaling Santander Meteorology Group A multidisciplinary approach for weather & climate ● Downscaling techniques try to adapt the coarse global model output to the local features of a given region.

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Downscaling Santander Meteorology Group A multidisciplinary approach for weather & climate ● Downscaling techniques try to adapt the coarse global model output to the local features of a given region. ● This can be achieved through dynamical techniques, which solve numerically the governing equations of the atmosphere on a finer grid, The most common are nested RCMs

http://www.meteo.unican.es A multidisciplinary approach to weather & climate The World as seen by an RCM Santander Meteorology Group A multidisciplinary approach for weather & climate 45 km

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Not seen by a GCM / RCM Santander Meteorology Group A multidisciplinary approach for weather & climate

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Physical parameterizacions Santander Meteorology Group A multidisciplinary approach for weather & climate A parameterization is a statistical representation of the net effect of processes occurring on spatial scales smaller than the grid spacing of a dynamical model (GCM, RCM, CRM, LES, …) over mean variables at each grid cell. Parameterizations are based on the physics of the processes, plus simplifying (closure) assumptions to relate unknown variables to prognostic (mean) model variables. Theory (e.g. known physical constants) ● Parameters are obtained from: Field campaigns ● Higher resolution models (CRM, LES) ●

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Downscaling Santander Meteorology Group A multidisciplinary approach for weather & climate ● Downscaling techniques try to adapt the coarse global model output to the local features of a given region. ● This can be achieved through dynamical techniques, which solve numerically the governing equations of the atmosphere on a finer grid, ● or by statistical techniques, which seek empirical relationships between local and large-scale variables.

http://www.meteo.unican.es A multidisciplinary approach to weather & climate DS techniques Santander Meteorology Group A multidisciplinary approach for weather & climate General classes of downscaling Local climate = f (larger scale predictors) + locally forced variance Dynamical Empirical-statistical Perturbed observed Two approaches Three main classes RCM Hi-res GCM Weather Generators Transfer Functions Index / analogues Trained on long term Trained on time series Requires long term data time series and that spans range of sets and uses weather atmospheric re-analysis variability, and typing or historical data atmospheric re-analysis analogues data Source: Bruce Hewitson Conditioned by GCM Residual local scale (CSAG) parameters to capture variance added low frequency variance stochastically

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Statistical downscaling Santander Meteorology Group approaches A multidisciplinary approach for weather & climate Perfect Prognosis (PP) Calibrated in the training phase using observational data for both the predictands and predictors (reanalysis). Since different GCMs are used in the training and downscaling phases, large-scale circulation variables well-resolved by the models are typically chosen as predictors in this approach. Variables directly influenced by model parameterizations and orography are not suitable predictors in this approach. PP Training Downscaling Large scale Obs. GCM Local scale Obs. →

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Statistical downscaling Santander Meteorology Group (Perfect Prog) A multidisciplinary approach for weather & climate Present Climate Future … 2090 2020 2030 2070 2080 1960 1970 1980 1990 2000 2010 Observations Precip … ………………… Spain02, 20km … ………………… Precip = 0.8 MSLP + 1.2 Q850 Statistical model SDM GCM reanal. … ………………. MSLP, Q850, etc. ERA40, 250km • Assumption 1: Reanalysis choice • Assumption 2: Choosing consistent predictors: • Assumption 3: Stationarity/robustness: SDM SDM Precip = 0.8 MSLP + 1.2 Q850 Precip = 0.8 MSLP + 1.2 Q850 Projections … … ………………… ………………… Spain02, 20km SDM SDM GCM scen. … ………………. … ………………. AR4 ~250km Control scenario: 20c3m B1, A1B, A2

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Typical predictors Santander Meteorology Group A multidisciplinary approach for weather & climate

http://www.meteo.unican.es A multidisciplinary approach to weather & climate 1. Transfer functions Santander Meteorology Group A multidisciplinary approach for weather & climate Grids of atmospheric patterns Predictands: precip ., etc. for a given day n for a given day n Transfer Functions Y n ( T ( 1ooo mb ),..., T ( 500 mb ); Z ( 1ooo mb ),..., Z ( 500 mb ); Linear regression: .......; H ( 1ooo mb ),..., H ( 500 mb ) ) = X n Y n = a X n + b Logistic regression Y n = F( a X n + b) 1. Probabilistic prediction

http://www.meteo.unican.es A multidisciplinary approach to weather & climate Predictor selection Santander Meteorology Group A multidisciplinary approach for weather & climate Variable Nivel Hora Geopotencial 500 0 UTC Geopotencial 1000 0 UTC Temperatura 500 0 UTC Temperatura 850 0 UTC Humedad Relativa 850 0 UTC 140 parameters (5 variables, 28 gridboxes), n=16434 Redundancy (correlation): Principal Components (domain selection) Nearest grid-boxes Both (e.g. 15 CPs + values in 1 gridbox)