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1.
本文在对比了TRMM多卫星降水分析TMPA(TRMM Multi-satellite Precipitation Analysis)资料和中国643个气象站观测降水量时空分布的基础上,采用2002~2006年夏季TMPA每小时降水量资料,用合成分析和谐波分析的方法研究了青藏高原及其周边地区夏季降水量和降水频率的日变化特征.分析结果表明,平均降水量和降水频率日变化谐波分析的标准振幅显示出青藏高原地区夏季降水具有显著的日变化特征,高原中部地区对流活动日变化最强,其次是高原西南方向的印度半岛地区.谐波分析的位相表明降水量和降水频率最大值出现的时间具有选择性,高原中部降水量最大值多集中在傍晚前后,高原以东的四川盆地通常在夜晚,尤其是在后半夜达到最大值,而长江上游和中下游地区对流活动则分别在上午和下午最为活跃.青藏高原以东地区降水量日变化的位相明显不同于其他陆地地区,也不同于高原中部,具有自西向东传播的信号,四川盆地的夜雨现象可能是高原地区对流活动日变化自西向东传播的结果. 相似文献
2.
The accurate measurement of precipitation is crucial for hydrological studies. This is especially true for the Hindu Kush–Karakoram–Himalaya (HKKH) mountain region, which is characterized by high spatiotemporal precipitation variability. The paucity of raingauges makes it difficult to measure precipitation in this region precisely. We conducted evaluation of TMPA 3B42V7 and APHRO 1101 in the HKKH area on a daily basis at a spatial resolution of 0.25°?×?0.25°, using 27 raingauges. Statistically, the largest error in the gridded data arose mainly from elevation, followed by volumetric error and Nash–Sutcliffe efficiency. Overall, the TMPA data have a poor correlation with ground observations in the HKKH area, especially for higher altitudes. The western areas are relatively more underestimated and the Karakoram shows higher frequency of bias in the TMPA retrievals. This method could help improve the satellite precipitation estimation algorithm as it considers local physiography and climatic factors. 相似文献
3.
This study presented a detailed comparison of daily
precipitation estimates from Precipitation Estimation from
Remote Sensing Information using Artificial Neural Network
(PERSIANN) and Tropical Rainfall Measuring Mission (TRMM) Multi
-satellite Precipitation Analysis (TMPA) over Hunan province of
China from 1998 to 2014. The ground gauge observations are taken
as the reference. It is found that overall TMPA clearly
outperforms PERSIANN, indicating by better statistical metrics
(including correlation coefficient, root mean square error and
relative bias). For the geospatial pattern, although both
products are able to capture the major precipitation features
(e.g., precipitation geospatial homogeneity) in Hunan, yet
PERSIANN largely underestimates the precipitation intensity
throughout all seasons. In contrast, there is no clear bias
tendency from TMPA estimates. Precipitation intensity analysis
showed that both the occurrence and amount histograms from TMPA
are closer to the gauge observations from spring to autumn.
However, in the winter season PERSIANN is closer to gauge
observation, which is likely due to the ground contamination
from the passive microwave sensors used by TMPA. 相似文献
4.
基于500个国家站雨量计的观测,从时空分布、不同地形条件、不同等级的降水强度及日变化角度,对比评估了2014—2016年夏季多星集成降水产品TMPA和IMERG在中国中东部的适用性。研究结果表明,与雨量计相比.TMPA和IMERG降水产品能较好地反映夏季中国中东部逐日降水量的变化规律,IMERG的平均误差更小。IMERG降水产品的日平均降水量与雨量计的相关性更高,相关系数超过0.9,而TMPA仅为0.8。在中国中东部的平原和山区,IMERG降水产品对弱降水(4 mm·d~(-1))强度和弱降水频次的表征能力,较TMPA降水产品有明显的改善;但IMERG降水产品对山区的强降水频次的探测较TMPA降水产品改进有限。从日变化来看,TMPA降水产品明显低估早晨的降水强度和降水频次,且高估了午后的降水强度和降水频次。IMERG降水产品作为高时空分辨率的准全球降水资料,在中国中东部有较高的精度,未来可应用于气象和水文模式中。 相似文献
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6.
中国大陆TMPA降水产品气候态的评估 总被引：3，自引：2，他引：1
利用逐日全国降水分析产品,对2012年12月下旬发布的最新版本的TRMM等多源卫星降水估算产品（TMPA）进行评估, 评估时间从2008年9月到2012年8月。从评估结果来看,研究产品3B42V7产品与CPAP产品具有高的相关性,两者的相关系数达到了0.94,相对误差在-0.11％左右,标准偏差约为0.53 mm·d-1。实时产品3B42RT产品与CPAP产品的相关性相对较差,相关系数为0.75,相对误差也上升到了39.3％,标准偏差为1.25 mm·d-1。3B42RT产品在我国西部高估了降水,全年的相对误差为116.60％（春夏秋冬四季分别为104.52%、 105.73%、117.64%和326.60%）;3B42V7产品的相对误差仅为0.82 %（春夏秋冬四季分别为2.25%、1.24%、-5.27%和-24.64%）。 相似文献
7.
Rebecca Lemons Andrea Hewitt Gehendra Kharel Cherie New Andrei Kirilenko Xiaodong Zhang 《国际地球制图》2013,28(8):613-626
The climate of the United States Northern Great Plains region is highly variable. Modelling of agriculture in this region and similar locations depends on the availability and quality of satellite and ground data for agro-climate variables. We evaluated tropical rainfall measuring mission (TRMM) multi-satellite preparation analysis (TMPA) precipitation, atmospheric infrared sounder (AIRS) surface air temperature, and AIRS relative air humidity (RH). A significant bias was found within the temperature and RH products and no bias but an insufficient rain event detection skill in the precipitation product (probability of detection ～0.3). A linear correction of the temperature product removed the bias as well as lowered the root mean square deviation (RMSD). The bias-corrections for RH led to increased RMSD or worse correlation. For precipitation, the correlation between the satellite product and ground data improved if cumulative precipitation or only precipitation during the growing season was used. 相似文献
8.
四套降水资料在喀喇昆仑山叶尔羌河上游流域的适用性分析 总被引：2，自引：2，他引：0
分析了2003-2009年基于卫星观测的降水数据CMORPH、 TMPA 3B42 v6、 中国科学院青藏高原研究所的融合数据ITPCAS和基于地面台站的APHRODITE (2003-2007)四套降水数据集在叶尔羌河上游流域的时空分布特征, 并以这四套降水数据为驱动, 利用VIC分布式水文模型对叶尔羌河上游流域的降水径流进行模拟.结果表明: 在空间分布上, 四套降水资料在叶尔羌河上游流域的差异较大, ITPCAS的空间分布与流域冰川的分布较一致, 基于冰川区即为大降水区的基本认知, 初步认为ITPCAS的空间分布比较合理; 其次是TMPA 3B42 v6和APHRODITE; 在流域的年降水量和季节分配量上, 由于缺乏高海拔地区的实测降水资料, 无法准确回答各套降水资料在量级上是否合理; 在时间序列上, 四套降水资料与流域站点降水(库鲁克栏杆站和塔什库尔干站的平均降水)存在着不同程度的差异.但从整体上看, CMORPH数据在一定程度上能够反映流域的月降水变化过程, 而APHRODITE和ITPCAS只能在个别年份对流域的降水描述较好; 在径流模拟上, 卫星降水数据CMORPH显示了作为水文模型输入数据的较大潜力; 而其他降水资料在叶尔羌河径流模拟中, 与实测径流在量和季节分配上可能存在较大偏差. 相似文献
9.
TMPA降水数据在澜沧江流域干旱监测中的评估(英文) 总被引：7，自引：1，他引：6
Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satellite precipitation analysis (TMPA; 3B43 V.6) product during the period 1998 to 2009 is an alternative precipitation data source with good accuracy. By using the standard precipitation index (SPI), at the grid point (0.25°×0.25°) and sub-basin spatial scales, this work assessed the effectiveness of TMPA in drought monitoring during the period 1998 to 2009 at the 1-month scale and 3-months scale; validated the monitoring accuracy of TMPA for two severe droughts happened in 2006 and 2009, respectively. Some conclusions are drawn as follows. (1) At the grid point spatial scale, in comparison with the monitoring results between rain gauges (SPI1g) and TMPA grid (SPI1s), both agreed well at the 1-month scale for most of the grid points and those grid points with the lowest critical success index (CSI) are distributed in the middle stream of the Lancang River Basin. (2) The same as SPI1s, the consistency between SPI3s and SPI3g is good for most of the grid points at the 3-months scale, those grid points with the lowest were concentrated in the middle stream and downstream of the Lancang River Basin. (3) At the 1-month scale and 3-months scale, CSI ranged from 50% to 76% for most of the grid points, which demonstrated high accuracy of TMPA in drought monitoring. (4) At the 3-months scale, based on TMPA basin-wide precipitation estimates, though we tended to overestimate (underestimate) the peaks of dry or wet events, SPI3s detected successfully the occurrence of them over the five sub-basins at the most time and captured the occurrence and development of the two severe droughts happened in 2006 and 2009. This analysis shows that TMPA has the potential for drought monitoring in data-sparse regions. 相似文献
10.
Norina Andres Fernando Vegas Galdos Waldo Sven Lavado Casimiro Massimiliano Zappa 《水文科学杂志》2013,58(11):2043-2059
AbstractEstimating water resources is important for adequate water management in the future, but suitable data are often scarce. We estimated water resources in the Vilcanota basin (Peru) for the 1998–2009 period with the semi-distributed hydrological model PREVAH using: (a) raingauge measurements; (b) satellite rainfall estimates from the TRMM Multi-satellite Precipitation Analysis (TMPA); and (c) ERA-Interim re-analysis data. Multiplicative shift and quantile mapping were applied to post-process the TMPA estimates and ERA-Interim data. This resulted in improved low-flow simulations. High-flow simulations could only be improved with quantile mapping. Furthermore, we adopted temperature and rainfall anomalies obtained from three GCMs for three future periods to make estimations of climate change impacts (Delta-change approach) on water resources. Our results show more total runoff during the rainy season from January to March, and temporary storages indicate that less water will be available in this Andean region, which has an effect on water supply, especially during dry season.Editor Z.W. Kundzewicz; Associate editor D. Gerten 相似文献