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Traditional precipitation skill scores are affected by the well-known“double penalty”problem caused by the slight spatial or temporal mismatches between forecasts and observations. The fuzzy (neighborhood) method has been proposed for deterministic simulations and shown some ability to solve this problem. The increasing resolution of ensemble forecasts of precipitation means that they now have similar problems as deterministic forecasts. We developed an ensemble precipitation verification skill score, i.e., the Spatial Continuous Ranked Probability Score (SCRPS), and used it to extend spatial verification from deterministic into ensemble forecasts. The SCRPS is a spatial technique based on the Continuous Ranked Probability Score (CRPS) and the fuzzy method. A fast binomial random variation generator was used to obtain random indexes based on the climatological mean observed frequency, which were then used in the reference score to calculate the skill score of the SCRPS. The verification results obtained using daily forecast products from the ECMWF ensemble forecasts and quantitative precipitation estimation products from the OPERA datasets during June-August 2018 shows that the spatial score is not affected by the number of ensemble forecast members and that a consistent assessment can be obtained. The score can reflect the performance of ensemble forecasts in modeling precipitation and thus can be widely used. 相似文献
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By using the hourly data from surface meteorological stations in China, the 3-hour precipitation data from
CRA-Interim (Chinese Reanalysis-Interim), ERA5 (ECMWF Reanalysis 5) and JRA-55 (Japanese Reanalysis-55) are
compared, both on the spatial-temporal distributions and on bias with observation precipitation in China. The results
show that: (1) The three sets of reanalysis datasets can all reflect the basic spatial distribution characteristics of annual
average precipitation in China. The simulation of topographic forced precipitation in complex terrain by CRA-interim is
more detailed, while CRA-interim has larger negative bias in central and East China, and larger positive bias in
southwest China. (2) In terms of seasonal precipitation, the three sets of reanalysis datasets overestimate the precipitation
in the heavy rainfall zone of spring and summer, especially in southwest China. CRA interim’s location of the rain belt
in the First Rainy Season in South China is west by south, the summer precipitation has positive bias in southwest and
South China. (3) All of the reanalysis datasets can basically reflect the distribution difference of inter-annual variation of
drought and flood, but the overall the CRA-Interim generally shows negative bias, while the ERA5 and JRA-55 exhibit
positive bias. (4) For the diurnal variation of precipitation in summer, all the reanalysis datasets perform better in
simulating the daytime precipitation than in the night, and bias of CRA-interim is less in southeast and northeast than
elsewhere. (5) ERA5 generally performs the best on the evaluation of quantitative precipitation forecast, the JRA-55 is
the next, followed by the CRA-Interim. CRA-Interim has higher missing rate and lower threat score for heavy rains;
however, at the level of downpour, the CRA-Interim performs slightly better. 相似文献
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三江源地区是我国重要生态安全屏障,冻土是其高寒生态系统的重要组成部分,冻土的变化深刻影响高寒生态系统固碳及水源涵养。基于英国东英吉利大学（University of East Anglia,UEA）气候研究中心（Climatic Research Unit,CRU）月平均气温再分析资料,利用线性倾向法和滑动平均法并结合GIS空间分析和制图,计算并分析了三江源地区1901—2018年冻融指数变化趋势及其空间分布特征。结果表明：三江源地区冻结指数在1901—2018年整体以-1.1 ℃·d·a-1的斜率呈波动减少趋势,经历了三个波动变化阶段：1901—1943年的下降（-3.4 ℃·d·a-1）、1943—1966年的升高（8.8 ℃·d·a-1）、1966—2018年的再次下降（-4.3 ℃·d·a-1）。融化指数与冻结指数的变化相反,整体以0.34 ℃·d·a-1的斜率呈波动上升趋势,呈现升高（1901—1943年,3.3 ℃·d·a-1）、下降（1943—1981年,-3.1 ℃·d·a-1）、再次升高（1981—2018年,2.9 ℃·d·a-1）的趋势。在空间分布上,自西向东随海拔和多年冻土连续性降低,冻结指数由3 400 ℃·d递减到600 ℃·d,融化指数由接近0 ℃·d增加到1 800 ℃·d。长江源区冻结指数最大,融化指数最小;黄河源区冻结指数最小,融化指数最大。研究成果可为三江源地区冻土变化及其对高寒生态环境的影响研究提供科学借鉴。 相似文献
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The spatial and temporal consistency of seasonal air temperature and precipitation in eight widely used gridded observation-based climate datasets (CANGRD, CRU-TS3.1, CRUTEM4.1, GISTEMP, GPCC, GPCP, HadCRUT3, and UDEL) and eight reanalyses (20CR, CFSR, ERA-40, ERA-Interim, JRA25, MERRA, NARR, and NCEP2) was evaluated over the Canadian Arctic for the 1950–2010 period. The evaluation used the CANGRD dataset, which is based on homogenized temperature and adjusted precipitation from climate stations, as a reference. Dataset agreement and bias were observed to exhibit important spatial, seasonal, and temporal variability over the Canadian Arctic with the largest spread occurring between datasets over mountain and coastal regions and over the Canadian Arctic Archipelago. Reanalysis datasets were typically warmer and wetter than surface observation-based datasets, with CFSR and 20CR exhibiting biases in total annual precipitation on the order of 300?mm. Warm bias in 20CR exceeded 12°C in winter over the western Arctic. Analysis of the temporal consistency of datasets over the 1950–2010 period showed evidence of discontinuities in several datasets as well as a noticeable increase in dataset spread in the period after approximately 2000. Declining station networks, increased automation, and the inclusion of new satellite data streams in reanalyses are potential contributing factors to this phenomenon. Evaluation of trends over the 1950–2010 period showed a relatively consistent picture of warming and increased precipitation over the Canadian Arctic from all datasets, with CANGRD giving moistening trends two times larger than the multi-dataset average related to the adjustment of the station precipitation data. The study results indicate that considerable care is needed when using gridded climate datasets in local or regional scale applications in the Canadian Arctic. 相似文献
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Takanori Shimizu Koji Tamai Ikuhiro Hosoda Shoji Noguchi Yuji Kominami Toshio Abe Kenzo Kitamura Ushio Kurokawa Delphis F. Levia Tayoko Kubota Naoki Kabeya Shin'ichi Iida Tatsuhiko Nobuhiro Shinji Sawano Sho Iwagami Akira Shimizu Yoshio Tsuboyama 《水文研究》2021,35(10):e14376
This data note introduces a database of long-term daily total precipitation and stream discharge data for seven forested watersheds in Japan that have been continuously monitored by the Forestry and Forest Products Research Institute. Three of the watersheds started data collection in the 1930s. Forest cover across the sites ranges from cool to warm temperate regions with the latitude spanning from 31 to 44° N and annual precipitation ranging from 1200 to 3000 mm yr−1. The effects of vegetation change via clearcutting, thinning and forest fire (among other stressors) on stream discharge can be analysed from the long-term observation sites. Moreover, this multi-site dataset allows for inter- and intra-site comparisons of annual water loss (difference of annual precipitation and stream discharge). These long-term datasets can provide comprehensive insights into the effects of climate change and other stressors on forested ecosystems, not only in Japan but across a spectrum of forest types, if combined with other long-term records from other forested watersheds across the world. 相似文献
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We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.
相似文献8.
Luis Andrés Guillén Mary Beth Adams Emily Elliot Jason Hubbart Charlene Kelly Brenden McNeil William Peterjohn Nicolas Zegre 《水文研究》2021,35(4):e14106
Long-term experimental watershed studies have significantly influenced our global understanding of hydrological processes. The discovery and characterization of how stream water quantity and quality respond to a changing environment (e.g. land-use change, acidic deposition) has only been possible due to the establishment of catchments devoted to long-term study. One such catchment is the Fernow Experimental Forest (FEF) located in the headwaters of the Appalachian Mountains in West Virginia, a region that provides essential freshwater ecosystem services to eastern and mid-western United States communities. Established in 1934, the FEF is among the earliest experimental watershed studies in the Eastern United States that continues to address emergent challenges to forest ecosystems, including climate change and other threats to forest health. This data note describes available data and presents some findings from more than 50 years of hydrologic research at the FEF. During the first few decades, research at the FEF focused on the relationship between forest management and hydrological processes—especially those related to the overall water balance. Later, research included the examination of interactions between hydrology and soil erosion, biogeochemistry, N-saturation, and acid deposition. Hydro-climatologic and water quality datasets from long-term measurements and data from short-duration studies are publicly available to provide new insights and foster collaborations that will continue to advance our understanding of hydrology in forested headwater catchments. As a result of its rich history of research and abundance of long-term data, the FEF is positioned to continue to advance understanding of forest ecosystems in a time of unprecedented change. 相似文献
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运用EOF分解、线性趋势分析、方差分析、小波分析、相关分析等方法,从均值、长期变化、年际和年代际变化特征等方面对NCEP/NCAR(N1T)、NCEP/DOE(N2T)、ERA-Interim(ET)、JRA-25(JT)4种再分析资料集和194站观测资料集中1979—2012年我国冬季最低气温(WTMIN)进行比较。结果表明:(1)ET在再现观测冬季最低气温多年平均时最优;(2)除新疆北部和西南部以及东北北部有降低趋势外,我国大部分地区WTMIN有升高的趋势,N1T对观测温度长期变化趋势再现能力优于其他3种资料;(3)观测WTMIN在中国北方和高原地区年际和年代际变化大于南方地区,四种再分析WTMIN对我国冬季最低气温的年际和年代际变化的再现在不同区域各有所长,总体上以ET为优。(4)再分析资料在再现观测WTMIN年代际时间尺度上的能力相当,以ET最优,尤其是在我国中东部地区和新疆北部地区。N1T和N2T对东北地区观测冬季最低气温年际变化的再现能力较好,ET再现观测WTMIN在1990s之前,2005年之后的3~4 a变化周期特征时能力略优于其他3种资料。 相似文献
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