1901~2013年GPCC和CRU降水资料在中国大陆的适用性评估

利用1901~2013年中国大陆地区的气象台站实测降水资料,对东英吉利（East Anglia）大学气候研究中心（Climatic Research Unit,CRU）和全球降水气候中心（Global Precipitation Climatology Centre,GPCC）的降水资料分别从季节、年际和年代际尺度上进行了评估。结果表明：1961~2013年CRU与GPCC降水资料均能较准确地描述中国大陆地区的降水特征,且在东部较西部地区、夏季较冬季与站点实测降水情况更为一致。将中国大陆划分为不同区域并在其季节、年际和年代际时间尺度上通过比较降水偏差绝对值的百分比、均方根误差和相关系数等统计量后发现：CRU在青藏高原和其它较大的山脉附近与站点实测降水的差别较大,且年均降水趋势在西北一带的阿尔金山脉、黄土高原、东南地区和长江下游地区,比实测降水的年均趋势小、甚至出现趋势相反的情况。此外,CRU降水的年代际变化趋势也偏小。而GPCC数据不论是降水量还是降水趋势都更接近实际情况。在1901~1961年,通过与65个长期气象观测站点的降水时间序列比较发现,CRU在110°E以西地区与站点观测的降水资料间的差别较大,而GPCC与站点观测资料的吻合较好。最后,利用1961~2013年两套降水资料和站点实测资料分别计算了标准化降水指数（SPI）,简单分析了中国大陆地区的干旱变化,发现GPCC对旱涝的时空变化特征的描述比CRU更接近站点实际观测;并且CRU也没有反映出1997年夏季中国地区出现的严重干旱情况,而GPCC较为准确地反映出了这一干旱事件特征。因此,本文的研究结果认为,就中国大陆地区长时期降水资料而言,GPCC的适用性优于CRU。     

Evaluation of five gridded rainfall datasets in simulating streamflow in the upper Dong Nai river basin,Vietnam

Rainfall data with an appropriate spatial resolution is a key input to hydrological models. However, networks of rain gauges are often sparsely and unevenly distributed in large catchments, especially in developing countries. High-resolution rainfall datasets, such as the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), the Climate Forecast System Reanalysis (CFSR), the Climatic Research Unit Time Series (CRU-TS), the Global Precipitation Climatology Centre (GPCC) and the Tropical Rainfall Measuring Mission (TRMM), have become available to overcome such limitations. The objective of this study was to evaluate the impacts of four land-based rainfall products (APHRODITE, CFSR, CRU-TS, and GPCC) and a satellite-based rainfall product (TRMM) on streamflow of the upper catchment of Tri An reservoir in Vietnam using the Hydrological Modeling System (HEC-HMS). In addition, the available rain gauges data were used for comparison purpose. Result indicates that the TRMM and GPCC data show their best match to rain gauges data in simulating the streamflow in the period 1999–2007. Generally, the results indicate that the TRMM and GPCC data could be alternative solutions.     

Comparison of precipitation products to observations in Tibet during the rainy season

Precipitation is an important component of global water and energy transport and a major aspect of climate change. Due to the scarcity of meteorological observations, the precipitation climate over Tibet has been insufficiently documented. In this study, the distribution of precipitation during the rainy season over Tibet from 1980 to 2013 is described on monthly to annual time scales with meteorological observations. Furthermore, four precipitation products are compared to observations over Tibet. These datasets include products derived from the Asian Precipitation-Highly-Resolved Observational Data(APHRO), the Global Precipitation Climatology Centre(GPCC), the University of Delaware(UDel), and the China Meteorological Administration(CMA). The error, relative error, standard deviation, root-mean-square error, correlations and trends between these products for the same period are analyzed with in situ precipitation during the rainy season from May to September. The results indicate that these datasets can broadly capture the temporal and spatial precipitation distribution over Tibet. The precipitation gradually increases from northwest to southeast. The spatial precipitation in GPCC and CMA are similar and positively correlated to observations. Areas with the largest deviations are located in southwestern Tibet along the Himalayas. The APHRO product underestimates, while the UDel, GPCC, and CMA datasets overestimates precipitation on the basis of monthly and inter-annual variation. The biases in GPCC and CMA are smaller than those in APHRO and UDel with a mean relative error lower than 10% during the same periods. The linear trend of precipitation indicates that the increase in precipitation has accelerated extensively during the last 30 years in most regions of Tibet. The CMA generally achieves the best performance of these four precipitation products. Data uncertainty in Tibet might be caused by the low density of stations, complex topography between the grid points and stations, and the interpolation methods, which can also produce an obvious difference between the gridded data and observations.     

基于SPEI的近百年天津地区气象干旱时空演变特征

基于1921—2016年天津地区降水、气温观测数据,对全球降水气候中心降水(GPCC-P)、东英吉利大学气候研究中心气温(CRU-T)进行适用性评估后发现GPCC-P和CRU-T均能较好地反映天津地区降水和气温的变化。在此基础上,进一步利用GPCC-P、CRU-T计算的标准化降水蒸散指数(SPEI)分析天津地区近百年干旱时空演变特征并判断其未来变化趋势。结果表明：(1)天津干旱主要发生于1940年代初期、1990年代末和2000年代初期,四季均以轻旱和中旱为主,干旱高频季节由秋、冬季逐渐转为春、夏季。(2)天津全区SPEI气候趋势在6个时期除秋季整体呈“升、降、升”分布特征外,春、夏、冬季均表现为“升、降”的分布特征,且夏季下降趋势最为显著,1961—2010年宁河每10 a下降0.30。(3)1921—1970、1931—1980、1941—1990年天津春、冬季湿润化趋势由降水主导,而夏、秋季则由气温和降水协同影响;1951—2000、1961—2010、1971—2016年春季干旱趋势主要受气温影响,夏、冬季则为气温和降水协同影响,随着全球变暖,气温升高对干旱的影响逐渐增强。(4...