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Large-scale atmospheric circulation characteristics and their relations to local daily precipitation extremes in Hesse, central Germany Anahita Amiri Department.

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Presentation on theme: "Large-scale atmospheric circulation characteristics and their relations to local daily precipitation extremes in Hesse, central Germany Anahita Amiri Department."— Presentation transcript:

1 Large-scale atmospheric circulation characteristics and their relations to local daily precipitation extremes in Hesse, central Germany Anahita Amiri Department of Geography Justus Liebig University Giessen

2 2 Objective Challenges  Coarse resolution of global climate models (GCMs)  Doubt about the reliability of some GCM output variables  scale mismatch between the reliable outputs of GCM and climate change impact needs

3 3 Outline Downscaling Selecting predictors Finding statistical relationship between predictors and predictand Validating the model

4 4 Downscaling What is downscaling?  A method for obtaining high-resolution climate or climate change information from coarse-resolution GCMs Downscaling techniques  Regional climate models  Weather classification and re–sampling  Mixtures of stochastic processes, weather generators  Linear and non–linear regression

5 5 Statistical Downscaling Approaches

6 6 Practical Considerations Predictors and Predictand Selecting best set of Predictors for each domain (size and location) Transform Function (or model type) Seasonal Variability Calibration and Validation

7 7 Types of Predictors 1- Synoptic predictors (MSLP, 500 hPa Geopotential heights) 2- Temperature predictors (T850, Tmax, Tmin) 3- Moisture predictors (specific and relative humidity, precipitation) 4- Air flow predictors (u, v)

8 8 Predictor Selection Considerations: An “ideal” Predictor should be:  Strongly correlated with the Predictand  Physically and/or conceptually sensible  Able to preserve covariance between local variables  Accurately described by the GCM  Archived at the same temporal resolution as the local variable(s)

9 9 Steps for selecting downscaling predictor variables 1- Calculating correlation between predictors and daily precipitation monthly /seasonal maxima 2- Calculating PCA1 and average for high correlated areas 3- Fitting GEV and finding confidence interval for location parameter 4- Finding correlation between predictors 5- Using AIC to find the best combination of predictors

10 10 Correlation between specific humidity at 850hPa and maximum precipitation for winter

11 11 Correlation between relative vorticity at 850hPa and maximum precipitation for winter

12 12 Correlation between temperature at surface level and maximum precipitation for winter

13 13 Model Selection Model Derivation for the statistical relations between selected set of predictors and the monthly/seasonal maxima of Percipitation Calculate AIC for each model Validate model by cross validation methods

14 14 Summary Station data Select predictand Select predictors Set model structure Calibrate model ERA40 data Screen variables Downscale predictand GCM predictors ERA40 predictors Synthesize Observed data Generate scenario Analyse results Impact assessment

15 15 Asking For your Suggestions Thank you for your suggestions


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