The role of the Himalaya and the Tibetan Plateau for the Indian Monsoon

Transcription

1 June, 7 th June, 14 th 2009 The role of the Himalaya and the Tibetan Plateau for the Indian Monsoon Prof. Dr. Klaus Dethloff (AWI Potsdam) Stefan Polanski (AWI Potsdam ) Dr. Annette Rinke (AWI Potsdam) Prof. Dr. Manfred Strecker (Uni Potsdam)

2 1 Domain of the regional climate model HIRHAM4 Orography [50 km] 100 grid points = 5000 km 110 grid points = 5500 km

3 2 Methods simulation with regional climate model HIRHAM4 (HIRLAM+ECHAM4) - spatial resolution: 0.5 º x 0.5 º = 50 x 50 km (horizontal), 19 level (vertical) - temporal resolution: 300 s - boundary forcing by ERA40 Data (ECMWF) - simulation-period: 44 years ( ) calculation of spatial and temporal variability (seasonal, interannual and decadal) for temperature, precipitation and circulation patterns validation of model results with observation data sets aim: description and quantification of regional coupling between monsoon circulation and orographic as well as thermal processes in Himalaya and Tibetan Plateau

4 1. HIRHAM vs. ERA40: Mean sea level pressure in hpa (colours) Geopotential height [500hPa] in m (isolines) (summer monsoon JJAS ) HIRHAM4 ERA40 ERA40 HIRHAM4

5 1. HIRHAM vs. ERA40: Temperature in ºC (summer monsoon JJAS ) HIRHAM4 ERA40 ERA40 HIRHAM4

6 1. HIRHAM vs. ERA40: Stdev_Temperature in ºC (summer monsoon JJAS ) HIRHAM4 ERA40

7 1. HIRHAM vs. ERA40: Precipitation in mm (summer monsoon JJAS ) HIRHAM4 ERA40 ERA40 HIRHAM4

8 2. HIRHAM vs. TRMM + GPCC4 + ERA40: Precipitation in mm (summer monsoon JJAS ) HIRHAM4 TRMM GPCC4 ERA40 correlation coefficient (summer monsoon JJAS ): TRMM HIRHAM4 GPCC4 ERA

9 2. HIRHAM vs. TRMM + GPCC4 + ERA40: Stdev_Precipitation in mm (summer monsoon JJAS ) HIRHAM4 TRMM GPCC4 ERA40

10 3. Central Asia Station - Dataset (NSIDC) source: parameter: temperature (monthly means), precipitation (monthly totals) number of stations: 194 (temperature), 262 (precipitation)

11 3. Central Asia Station - Dataset : Temperature in K The need for a correction of model temperature because of elevation bias HIRHAM - OBSERVATION Jan July blue - original red - corrected blue - original red - corrected elevation bias in m elevation bias in m temperature bias in K temperature bias in K constant lapse rate = 0.65K / 100m

12 3. Central Asia Station - Dataset : Temperature in ºC Absolute frequency of occurrence of bias HIRHAM - OBSERVATION Jan July absolute frequency of bias absolute frequency of bias temperature bias temperature bias

13 3. Central Asia Station - Dataset : Temperature in ºC Mean annual cycle HIRHAM vs. OBSERVATION (ERA40 + Stations) Stations = 7.5º C temperature in ºC

14 3. Central Asia Station - Dataset : Precipitation Relative frequency of occurrence of bias HIRHAM - OBSERVATION Jan July relative frequency of bias in % relative frequency of bias in % relative precipitation bias (HIR-OBS)/OBS (%) relative precipitation bias (HIR-OBS)/OBS (%)

15 3. Central Asia Station - Dataset : Precipitation in mm Mean annual cycle HIRHAM vs. OBSERVATION (ERA40 + GPCC4 + Stations) Stations = 25.9 mm Stations = mm

16 4. Sub domains (HIRHAM4) all continent water mountains >1500 m Tibetan Plateau >3000 m glacier deserts India (continent)

17 continent 4. Sub domains Mean annual cycle T2m in C Precip in mm Tibetan Plateau >3000 m

18 4 Summary model simulation run model validation with observation data - station data: - Central Asia Temperature Data Central Asia Precipitation Data gridded data: - ERA40 Data GPCC4 Full Data Reanalysis (Precipitation) TRMM PR (Precipitation) IMD RF (Precipitation) case studies: - Siberian High - wet and dry monsoons -SST

19 THANK YOU!