2000—2016年基于WRF模式的0.05°×0.05°黑河流域近地表大气驱动数据
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摘要
黑河流域近地表大气驱动数据,是采用WRF(Weather Research and Forecasting)模式制备的黑河流域2000-2016年逐时0. 05°×0. 05°包括2 m气温、地表气压、2 m水汽混合比、辐射、10 m风场和累积降水量等近地表大气要素的驱动数据。通过与15个中国气象局常规自动气象站CMA站点逐日观测资料和两期黑河流域生态-水文过程综合遥感观测联合试验(WATER和Hi WATER)的站点逐时观测资料在不同时间尺度上进行验证。结果表明,2 m地表气温、地表气压和相对湿度都是比较可信的,尤其是2 m地表气温和地表气压,平均误差都很小且相关系数都达到0. 96以上;向下短波辐射与WATER站点观测数据的相关性均为0. 9以上,向下长波辐射的相关性达到0. 6; 10 m风速都与观测资料相差较大,相关性也比较弱。降水资料通过降雨和降雪两种相态与观测资料在不同时间尺度和空间尺度上进行验证,降雨与观测资料在年、月、日和时尺度上吻合得很好,与观测资料在年和月尺度上的相关系数高达0. 94和0. 84,在日尺度上相关系数达到0. 53;降雪与观测资料在月尺度上的相关性达到0. 78,与积雪覆盖率MODIS遥感产品的空间分布相当吻合,峰值分布也一致。液态和固态降水的验证表明WRF模式能够在地形复杂而干旱的黑河流域进行降尺度分析,所模拟的资料能够满足流域尺度水文建模和水资源平衡研究。
The near-surface atmospheric elements including air temperature,pressure,relative humility,wind,precipitation and radiation are called forcing data to drive hydrological,land surface,and ecological models.However,the spatial resolution of general circulation models( GCMs) is too coarse to represent regional climate variations at the regional,basin,and local scale. Weather research and forecasting model( WRF) is a next generation,fully compressible,Euler non-hydrostatic mesoscale forecast model with a run-time hydrostatic option.This model is useful for downscaling weather and climate at the scales from one kilometer to thousands of kilometers,and is useful for deriving meteorological parameters required for hydrological simulation too. The Heihe River Basin( HRB) is the second largest inland river in China. It is located in the middle part of the Hexi Corridor in the arid regions of northwest China and covers an area of approximately 140,000 km2. The HRB extends from the Qilian Mountain glaciers,passing through alpine meadows and forest areas( precipitation recharge area),through an arid region,In this paper,the near-surface atmospheric forcing data over the Heihe River Basin is introduced,which was produced by using WRF model from 2000 to 2016 at hourly,at 0. 05 deg. resolution,including the following variables: 2 m temperature,surface pressure,2 m specific humidity,downward shortwave radiation,downward longwave radiation,10 m wind field and precipitation. The forcing data was validated against daily data collected at 15 automatic weather stations of Chinese Meteorological Administration( CMA),and hourly data at a fewsites of Heihe River eco-hydrological process comprehensive remote sensing observation( WATER and Hi WATER). The following conclusions were drawn: 2 m surface temperature,surface pressure and 2 m specific humidity are more reliable,especially the average errors of 2 m surface temperature and surface pressure are very small and the correlation coefficients with observations are above 0. 96; correlation between downward shortwave radiation and WATER site observation data is more than 0. 9 either,and the correlation of downward longwave radiation is 0. 6; the error of 10 m wind speed from observational data is large,the correlation is relatively weak. The correlation coefficient between simulated and observed rainfall data at monthly and yearly time scales were up to 0. 94 and 0. 84,and the correlation coefficient reached 0. 53 at daily scale; the correlation between simulated and observed snowfall data at monthly scale reached 0. 78,the spatial distribution of snowfall agrees well with the snowfractional coverage rate of MODIS remote sensing product. So WRF model can be used for downscaling analysis in complex and arid terrain of Heihe River Basin,and the simulated data can meet the requirements of watershed scale hydrological modeling and water resources balance.
The near-surface atmospheric elements including air temperature,pressure,relative humility,wind,precipitation and radiation are called forcing data to drive hydrological,land surface,and ecological models.However,the spatial resolution of general circulation models( GCMs) is too coarse to represent regional climate variations at the regional,basin,and local scale. Weather research and forecasting model( WRF) is a next generation,fully compressible,Euler non-hydrostatic mesoscale forecast model with a run-time hydrostatic option.This model is useful for downscaling weather and climate at the scales from one kilometer to thousands of kilometers,and is useful for deriving meteorological parameters required for hydrological simulation too. The Heihe River Basin( HRB) is the second largest inland river in China. It is located in the middle part of the Hexi Corridor in the arid regions of northwest China and covers an area of approximately 140,000 km2. The HRB extends from the Qilian Mountain glaciers,passing through alpine meadows and forest areas( precipitation recharge area),through an arid region,In this paper,the near-surface atmospheric forcing data over the Heihe River Basin is introduced,which was produced by using WRF model from 2000 to 2016 at hourly,at 0. 05 deg. resolution,including the following variables: 2 m temperature,surface pressure,2 m specific humidity,downward shortwave radiation,downward longwave radiation,10 m wind field and precipitation. The forcing data was validated against daily data collected at 15 automatic weather stations of Chinese Meteorological Administration( CMA),and hourly data at a fewsites of Heihe River eco-hydrological process comprehensive remote sensing observation( WATER and Hi WATER). The following conclusions were drawn: 2 m surface temperature,surface pressure and 2 m specific humidity are more reliable,especially the average errors of 2 m surface temperature and surface pressure are very small and the correlation coefficients with observations are above 0. 96; correlation between downward shortwave radiation and WATER site observation data is more than 0. 9 either,and the correlation of downward longwave radiation is 0. 6; the error of 10 m wind speed from observational data is large,the correlation is relatively weak. The correlation coefficient between simulated and observed rainfall data at monthly and yearly time scales were up to 0. 94 and 0. 84,and the correlation coefficient reached 0. 53 at daily scale; the correlation between simulated and observed snowfall data at monthly scale reached 0. 78,the spatial distribution of snowfall agrees well with the snowfractional coverage rate of MODIS remote sensing product. So WRF model can be used for downscaling analysis in complex and arid terrain of Heihe River Basin,and the simulated data can meet the requirements of watershed scale hydrological modeling and water resources balance.
引文
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Ran Y H,Li X,Cheng G D,et al,2012.Distribution of Permafrost in China-An Overview of Existing Permafrost Maps[J].Permafrost andPeriglacial Processes,23:322-333.DOI:10.1002/ppp.1756.
Wilby R L,Wigley T M,1997.Downscaling general circulation model output:a review of methods and limitations[J].Progress in Physical Geography,21:530-548.
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李新,吴立宗,马明国,等,2010.数字黑河的思考与实践2:数据集成[J].地球科学进展,25(3):306-316.
李艳,汤剑平,王元,等,2009.区域风能资源评价分析的动力降尺度研究[J].气候与环境变化,14(2):192-200.
潘小多,李新,冉有华,等,2012.下垫面对WRF模式模拟黑河流域区域气候精度影响研究[J].高原气象,31(3):657-667.
Cosgrove B A,Lohmann D,Mitchell K E,et al,2003.Real-time and retrospective forcing in the North American Land Data Assimilation System(NLDAS)project[J].Journal of Geophysical Research,108(D22):3-1~12.DOI:10.1029/2002JD003118.
Giorgi F,Mearns I,Oshields C,et al,1996.A regional model study of the importance of the 1998 drought and the l993 flood over the central Unite States[J].Climate,9:1150-1162.
Giorgi F,Bates T,1989.The climatological skill of a regional model over complex terrain[J].Monthly Weather Review,117:2325-2347.
Hong S Y,Juang H H,Lee D K,1999.Evaluation of a regional spectral model for the East Asian monsoon case studies for July 1987 and1988[J].Journal of the Meteorology Society of Japan,77:553-572.
Leung L R,Qian Y,Bian X,et al,2004.Mid-Century Ensemble Regional Climate Change Scenarios for the Western United States[J].Climate Change,62:75-113.
Li X,Cheng G D,Liu S M,et al,2013.Heihe Watershed Allied Telemetry Experimental Research(Hi WATER):Scientific objectives and experimental design[J].Bullet of American Meteorological Society,94:1145-1160.
Li X,Li X W,Li Z Y,et al,2009.Watershed Allied Telemetry Experimental Research[J].Journal of Geophysical Research,114(D22):D22103.DOI:10.1029/2008JD011590.
Lu L,Liu C,Li X,et al,2017.Mapping the soil texture in theHeihe River Basin based on fuzzy logic and data fusion[J].Sustainability,9(7):1246.doi:10.3390/su9071246.
Miller J,Russell G,Caliri G,1994.Continenta1 scale river flow in climate models[J].Journal of Climate,7:914-928.
National Center for Atmospheric Research(NCAR),2017.Weather Research And Forecasting Model System User’s Guide[EB/OL].https://www.mmm.ucar.edu/weather-research-and-forecastingmodel.
Nijssen B,O'Donnell G M,Lettenmaier D P,et al,2001.Predicting the discharge of global rivers[J].Journal of Climate,14:3307-3323.
Pan X D,Li X,2011.Validation of WRF model on simulating forcing data for Heihe River Basin[J].Sciences in Cold and Arid Regions,3(4):344-357.
Pan X D,Li X,Cheng G D,et al,2015.Development and evaluation of a river-basin-scale high spatio-temporal precipitation data set using the WRF model:a case study of the Heihe River Basin[J].Remote Sensing,7(7):9230-9252.
Pan X D,Li X,Cheng G D,et al,2017.Impact analysis of climate change on snowfall and fractional snow cover over a complex mountainous region using a numerical model and remote sensing products[J].Remote Sensing,9(8):774.DOI:10.3390/rs9080774.
Pan X D,Li X,Shi X K,et al,2012.Dynamic Downscaling of NearSurface Air Temperature at a basin scale using the WRF-with A Case Study in the Heihe River Basin,China[J].Frontier of Earth Science,6(3):314-323.
Ran Y H,Li X,Cheng G D,et al,2012.Distribution of Permafrost in China-An Overview of Existing Permafrost Maps[J].Permafrost andPeriglacial Processes,23:322-333.DOI:10.1002/ppp.1756.
Wilby R L,Wigley T M,1997.Downscaling general circulation model output:a review of methods and limitations[J].Progress in Physical Geography,21:530-548.
Wilby R L,Wigley T M,2000.Precipitation Predictors for downscaling:Observed and General Circulation Model Relationships[J].International Journal of Climatology,20(5):641-661.
Wilby R L,Dawson C W,Barrow E M,2002.SDSM-a decision support tool for the assessment of regional climate change impact[J].Environmental Modeling and Software,17:145-157.
李新,吴立宗,马明国,等,2010.数字黑河的思考与实践2:数据集成[J].地球科学进展,25(3):306-316.
李艳,汤剑平,王元,等,2009.区域风能资源评价分析的动力降尺度研究[J].气候与环境变化,14(2):192-200.
潘小多,李新,冉有华,等,2012.下垫面对WRF模式模拟黑河流域区域气候精度影响研究[J].高原气象,31(3):657-667.
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