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Regional Climate Modeling in the Source Region of Yellow River with complex topography using the RegCM3: Model validation. Pinhong Hui, Jianping Tang School of Atmospheric Sciences Nanjing University, China. August 27-30, 2013 Katmandu, Nepal. Content. Introduction Experiment design

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Regional Climate Modeling in the Source Region of Yellow River with complex topography using the RegCM3: Model validation

Pinhong Hui, JianpingTang

School of Atmospheric Sciences

Nanjing University, China

August 27-30, 2013

Katmandu, Nepal


Content River with complex topography using the RegCM3: Model validation

  • Introduction

  • Experiment design

  • Observed data

  • Simulation result

    • Climatology

    • Variability

    • PDFs and quantiles

    • Extreme indices

  • Summary


Introduction
Introduction River with complex topography using the RegCM3: Model validation

  • The Tibet Plateau

    • The highest plateau all over the world

    • complex topography and fragile ecosystem

    • one of the most sensitive areas to climate change

  • The Source Region of Yellow River

    • located in the Tibet Plateau

    • climatology may have dramatic impact on hydrology and ecosystem over the whole Yellow River Basin

  • Spatial distribution of precipitation and temperature

    • displays a strong relationship with the topography in scale under 10km

    • However, most of this region lacks meteorological observations

  • Use of regional climate models(RCMs)

    • necessary for reproducing the main climatic features in complex terrain


Introduction1
Introduction River with complex topography using the RegCM3: Model validation

  • The regional climate models has been successfully applied in many regional climate studies around the world

    • Heikkila et al. (2011) did dynamical downscaling of the ERA-40 reanalysis with the WRFV

    • Afiesimama et al. (2006) use the RegCM3 to study the West African monsoon

    • Dimri and Ganju (2007) simulated wintertime Seasonal Scale over Western Himalaya Using RegCM3

    • Park et al. (2008) Characteristics of an East-Asian summer monsoon climatology simulated by the RegCM3

    • Caldwell et al. (2009) Evaluation of a WRF dynamical downscaling simulation over California

    • …...

  • There is little research work on regional climate modeling in the Source Region of Yellow River with high resolution using the RegCM3 model


Experiment design
Experiment design River with complex topography using the RegCM3: Model validation


Experiment design1
Experiment design River with complex topography using the RegCM3: Model validation

  • First figure: the larger domain with 45km resolution covering the whole China with a 15km nest covering the Source Region of Yellow River

  • Second figure

    • shaded color: terrain height in the nest

    • large red rectangle: analysis domain(92-106°E, 29-39°N)

    • black contour line: location of the Source Region of Yellow River

    • small red circles: surface observation stations


Observed data
Observed data River with complex topography using the RegCM3: Model validation

  • Daily surface observations from the China Meteorological Administration (CMA)

    • Precipitation

    • surface air temperature

    • daily maximum and minimum surface air temperature

  • Consists of 756 meteorological stations, covering the whole country and provides the best data available for China

  • 116 stations included in our analysis domain

  • Interpolated the model results onto the station locations and evaluated the quality of the simulations


Simulation result climatology
Simulation result River with complex topography using the RegCM3: Model validationClimatology


Precipitation bias
precipitation bias River with complex topography using the RegCM3: Model validation

  • high-resolution, remarkable improvement

  • 15km simulation

    • bias and RMSE, much smaller

    • spatial correlation coefficient, much higher

  • Overestimation , especially in winter

  • Source Region of Yellow River, better simulated

  • Largest bias, Qaidam Basin

  • Underestimation, Tanggula Mountain, Sichuan Basin


Surface air temperature bias
surface air temperature bias River with complex topography using the RegCM3: Model validation

  • 15km simulation outperforms the 45km simulation, especially in the Source Region of Yellow River

    • higher spatial correlation coefficient

    • lower bias and RMSE

  • cold bias

  • Maximum bias, surroundings of Tanggula Mountain

  • locations of cold bias are in good agreement with the wet bias regions



Simulation result surface elevationsVariability


Inter annual variability of precipitation and surface air temperature averaged over the whole analysis domain


Taylor Diagram of interannual variability in the 12 surface stations in the Source Region of Yellow River


Annual cycle of precipitation and surface air temperature averaged over the whole analysis domain



PDFs of daily mean precipitation over the whole analysis region and the Source Region of Yellow River


Quantiles region and the Source Region of Yellow River (0.025, 0.1, 0.25, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95 and 0.99) of daily mean precipitation


PDFs of daily mean surface air temperature over the whole analysis region and the Source Region of Yellow River


Quantiles analysis region and the Source Region of Yellow River (from 0.05 to 1 in steps of 0.05) of daily mean surface air temperature


  • Simulation result analysis region and the Source Region of Yellow RiverExtreme index


Precipitation extreme index definitions analysis region and the Source Region of Yellow River


Extreme precipitation index analysis region and the Source Region of Yellow River


Temperature extreme index definitions analysis region and the Source Region of Yellow River


Extreme temperature index analysis region and the Source Region of Yellow River


Summary
Summary analysis region and the Source Region of Yellow River

  • The RegCM3 model displays wet bias and cold bias with a better performance in the Source Region of Yellow River. And the wet bias is significantly larger in percent during winter

  • The model accurately captures the interannual variability and annual cycle of both precipitation and temperature averaging over the entire region with high correlation coefficients

  • It can also well simulate the probability distribution (PDFs) of precipitation but underestimate the extreme precipitation in summer and overestimate it in winter. The simulated temperature PDFs are shifted towards the lower temperatures

  • The RegCM3 model generally reproduces the spatial patterns of the extreme indices of precipitation and temperature but tends to overestimate the heavy rainfall and cold days

  • The simulation ability is improved in a great degree over Source Region of Yellow River by using higher resolution


Thank You! analysis region and the Source Region of Yellow River


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