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, ChinaAugust 27-30, 2013Katmandu, Nepal

ContentContent

IntroductionIntroductionExperiment designExperiment designObserved dataObserved data

Simulation resultSimulation resultClimatologyClimatologyVariabilityVariabilityPDFs and quantilesPDFs and quantilesExtreme indicesExtreme indices

SummarySummary

IntroductionIntroduction

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

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

IntroductionIntroduction

Experiment designExperiment design

Model Configuration

Model prototype RegCM3

Governing equations Hydrostatic

Grids and resolution 110×78, 45km &15km

Vertical layers (top)

18 sigma layers(50hPa)

Cumulus convection Grell

PBL Holtslag

Land Surface BATS

Initial and boundary conditions ERA-interim reanalysis

Simulation period

1989.1.1-2009.12.31

Experiment designExperiment design

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 dataObserved data

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 resultSimulation result

ClimatologyClimatology

precipitation bias

Statistical index

Whole region Source Region

Summer Winter Summer Winter

45km

BIAS(%) 19.770 268.322 14.760 122.096

Spatial R 0.865 0.768 0.786 0.842

RMSE(mm/day) 3.412 3.999 1.869 2.005

15km

BIAS(%) 13.368 227.880 12.055 80.987

Spatial R 0.883 0.792 0.873 0.880

RMSE(mm/day) 2.882 3.546 1.753 1.887

Overestimation , especially in winterSource Region of Yellow River, better simulatedLargest bias, Qaidam BasinUnderestimation, Tanggula Mountain, Sichuan Basin

high-resolution, remarkable improvement15km simulation

bias and RMSE, much smallerspatial correlation coefficient, much higher

surface air temperature bias

Statistical indexWhole region Source Region

Summer Winter Summ

er Winter

45km

BIAS(℃) -3.399 -3.961 -1.821 -1.713

Spatial R 0.703 0.544 0.687 0.313

RMSE(℃) 0.677 0.386 0.593 0.202

15km

BIAS(℃) -2.867 -3.506 -1.704 -1.594

Spatial R 0.786 0.594 0.899 0.787

RMSE(℃) 0.512 0.328 0.528 0.138

cold bias Maximum bias, surroundings of Tanggula Mountainlocations of cold bias are in good agreement with the wet bias regions

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

higher spatial correlation coefficient lower bias and RMSE

Precipitation and surface air temperature at different surface elevations

Simulation resultSimulation resultVariabilityVariability

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

Simulation resultSimulation result

PDFs and quantiles PDFs and quantiles

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

Quantiles (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 (from 0.05 to 1 in steps of 0.05) of daily mean surface air temperature

Simulation resultSimulation result

Extreme indexExtreme index

Variable name Definition

Consecutive dry days (CDD)

Maximum number of consecutive days with Precipitation < 1mm

Number of heavy precipitation days (R10)

Annual count of days when Precipitation >= 10mm

Maximum 5-day precipitation amount (Rx5 day)

Annual maximum consecutive 5-day precipitation

Very wet days (R95)Annual total precipitation when Pre. > 95th percentile

Precipitation extreme index definitions

Extreme precipitation index

Temperature extreme index definitions

Variable name Definition

Summer day (SU)Daily maximum temperature over 25℃

Consecutive frost days (CFD)Days with daily minimum temperature below 0℃

Growing season length (GSL)

The number of days between the first occurrence of at least 6 consecutive days with daily mean temperature above 5 ℃and the first occurrence after 1st July of at least 6 consecutive days with daily mean temperature below 5℃

Extreme temperature index

SummarySummary

a) 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

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

c) 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

d) 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

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

Thank You!Thank You!