TRMM卫星降雨数据在湖南省的精度和可靠性评定

卫星降雨数据的高时空分辨率使其在洪涝灾害监测、流域水文模型模拟等方面得以广泛应用,而对卫星降雨数据的精度评定和可靠性分析仍然是当前重要的研究课题。采用中低纬度旱涝灾害频发的湖南省23个国家基准气象站的降雨数据作为地面验证数据,对最新一代TRMM卫星降雨产品(3B42V7)的精度和误差特征进行了全面评估。从日、月、年和季节的不同时间尺度以及空间分布和高程等不同的空间要素方面对比分析了1999-2012年该卫星降雨产品在湖南地区的适应情况。研究表明:TRMM卫星反演降雨数据在日尺度上与地面气象站数据的匹配情况较差,相关系数仅为0.31;而在月尺度上有显著提高,相关系数为0.88。在干旱季节(11、12、1、2月)的表现要优于湿润季节(5、6、7、8月)。3B42卫星反演降雨数据存在比较明显的空间变异性,空间要素如高程、位置分布等对卫星降雨数据可靠性的影响强于降雨量的影响。     

TRMM卫星降水产品和SPDI在河南省干旱监测中的适用性

本文选取河南省15个具有代表性的气象站点,根据其1998—2019年的逐月气象观测资料和TRMM 3B43V7逐月卫星降水数据,运用多种统计指标评估TRMM 3B43V7卫星降水产品在河南省的适用性;采用卫星降水数据代替地面降水资料计算标准化帕尔默干旱指数(SPDI),并寻求最优时间尺度;结合历史干旱事件记载,评估SPDI指数在河南省干旱监测中的适用性。结果表明:TRMM3B43V7卫星降水数据与实测地面降水数据相比,精确度很高(Bias=-0.05)、相关性很强(CC>0.88);由TRMM卫星降水数据计算得到的SPDI指数用于评估河南省历史干旱表现良好,且12个月时间尺度的SPDI指数(SPDI12)适用性最好。鉴于以上结论,可以考虑基于TRMM卫星降水产品和SPDI12指数构建河南省的干旱监测业务化系统。     

GPM卫星降水产品在“7·21”河南极端暴雨过程中的误差评估

为评估卫星定量降水估测（Quantitative Precipitation Estimation, QPE）产品在气象预测以及灾害预警监测的能力,研究针对台风"烟花"给河南省带来的极端降水过程,以地面雨量站观测数据为参考,采用相关系数（CC）、相对偏差（RB）、均方根误差（RMSE）、分数标准误差（FSE）、探测率（POD）、误报率（FAR）以及临界成功指数（CSI）这7种精度评价指标和统计方法分析和评估全球降水测量计划（Global Precipitation Measurement, GPM）的多卫星融合降水产品中的IMERG（Integrated Multi-satellitE Retrievals for GPM） Version 06中的准实时产品IMERG_ER和近实时产品IMERG_LR,以及全球卫星降水制图（Global Satellite Mapping of Precipitation, GSMaP） Version 07中的准实时产品GSMaP_NRT和标准产品GSMaP_MVK。与...     

TRMM卫星降水产品在南流江流域的精度评估

为了评估TRMM 3B42-V7的两套卫星降水反演数据产品的精度,选取南流江流域的常乐水文站以上集水区域为研究区域,以雨量站点的观测资料为参考,采用相关系数、探测率等指标,以及绘制空间降雨量分布图,建立评价模型。结果表明,两套卫星降雨产品都存在高估降雨量的现象,日尺度降雨量相对偏差在5%左右,且流域内有区域性差别;整体上TRMM3B42V7降雨产品的精度优于TRMM3B42RTV7,前者TRMM3B42V7降雨产品存在一定误差,但在缺乏地面降雨资料的地区仍具有应用价值。     

卫星降雨数据与地面站点资料在水文模型中的融合应用

地面站点观测的降雨资料可以代表站点附近的降雨真实情况,具有单点高精度观测优势;卫星降雨数据则具有空间分配观测优势,对雨量空间分配规律刻画较准确,但精度不如地面站点观测值。以南流江流域为例,通过将卫星降雨数据与地面站点资料融合应用到水文模型中,以融合后的降雨数据驱动新安江模型得到的径流过程与水文站实测流量过程吻合程度有明显改善。可见将卫星降雨数据与地面站点资料相融合,可弥补地面站点分布不均匀的问题,保证降雨数据更好反映实际降雨特征,在水文模拟中具有很好的应用价值。     

基于Sentinel-3A SRAL 2级产品的鄱阳湖水位评估与校准

Sentinel-3A卫星合成孔径雷达高度计（SRAL）因其时空分辨率优势在水位监测上应用潜力较大。基于2016—2018年Landsat-8 与Sentinel-2 光学遥感获取鄱阳湖星子站邻近水域，提取湖上Sentinel-3A SRAL 2级产品卫星测高点，提出一种卫星测高水位计算与校准方法，并结合实测水位进行评估。结果表明:Sentinel-3A SRAL 2级产品在鄱阳湖的过境数据有效率为64%，3—9月有连续覆盖数据，12月至次年2月受水位低或湖滩出露影响无有效数据；不同高程系统下的卫星观测水位与实测水位序列的一致性极显著，皮尔逊相关系数为0.999，在0.001水平上显著相关，实测水位变化量与卫星观测水位变化量的皮尔逊相关系数为1，二者的平均偏差为?0.175 m，标准差为0.084 m，其中降轨统计指标值优于升轨，枯水期则优于丰水期，以降轨枯水期指标值为最优:平均偏差、均方根误差、标准差分别为?0.082、0.107和0.076 m。以2016—2017年、2017—2018年、2016—2018年卫星测高水位与实测数据的平均偏差作为校准参数，校准水位的平均绝对偏差都为0.073 m，皮尔逊相关系数为1。研究验证了卫星测高数据计算和校准河湖水位方法的有效性，该类数据可应用于水文、气候变化研究与洪旱监测等。     

不同卫星遥感降水产品在辽东山区的适用性及修正方法研究

文章对比分析CMA和JMA两种卫星遥感降雨产品在辽东山区降水量应用效果,并对其降水量进行修正。结果表明:CMA卫星降雨产品在大雨量级的总体应用效果好于JMA降雨产品。采用卡尔曼滤波方法对卫星遥感降水产品进行修正后,修正降水量和气象站实测降水量之间的误差10%。研究成果对于卫星遥感降水产品在辽东山区的应用具有重要参考价值。     

干旱类型转化机理及预警体系框架研究

为了明晰不同干旱类型之间的转化机理以构建科学系统化的干旱预警体系框架,在系统化分析气象干旱、水文干旱、农业干旱和社会经济干旱的产生过程及其相互关系的同时,探讨了干旱监测指标内涵及干旱事件识别,在此基础上,基于大尺度水循环过程分析了水循环过程的干旱产生,进而深入分析了不同类型干旱之间转化的机理,确定了不同类型干旱转化的关键指标和条件因素,最后,以基于多源遥感数据和地面数据库为基础,利用多源数据融合的方法,通过构建综合干旱指数,建立了干旱预警体系框架。研究表明:从系统角度全面研究干旱类型之间的演进过程、干旱指标内涵及干旱事件的识别,建立干旱动态监测与评估综合分析模型或指标,明晰不同类型干旱转化机理,开展定量监测与评估干旱事件的动态演进过程及其影响,构建干旱预警体系框架,是开展干旱监测、预测、预警、评估和进一步开展旱灾研究的基础。     

卫星与地面观测融合降雨产品精度与径流模拟评估

虽然近年来卫星反演降雨产品逐渐成熟,但精度仍较差,不能满足现代水文气象业务和科研的需求,因此需要地面观测资料对其进行订正。文中采用的卫星与地面站融合数据是基于中国3万多个自动站降雨观测数据和CMORPH卫星反演降雨资料,采用PDF(probability density function)和OI(optimal interpolation)两步融合方法生成的中国区域高时空分辨率(0.1°/1h)的降雨量融合产品。通过在汉江丹江口水库以上流域建立分布式水文模型,对2008～2012年的融合降雨数据进行水文模拟适用性分析。结果表明:在日尺度上,CMORPH卫星降雨与地面站点融合数据具有较好的相关性,但存在一定的系统偏差;该降雨产品能较好地捕捉到强度小于25 mm的中小降雨,其模拟的径流与流域下部高峰流量的观测结果有较好的一致性,但总水量比实测值低15.7%,NSE达0.723。研究成果为基于高时空分辨率的卫星雨量计融合降雨产品在分布式水文模型的水文适用性提供了新的见解和经验,并为该数据在流域洪水模拟的水文预报应用提供参考与借鉴。     

基于TRMM/FY降雨数据的台风“海葵”监测分析

台风灾害往往都是由暴雨引起的,台风暴雨的研究对台风天气预报具有重要意义。在RS/GIS技术的支持下,以2012年8月发生的台风"海葵"为例,基于TRMM 3B42和FY-2D降水数据,在对两种卫星降雨数据有效性分析的基础上,对此次台风引起的强降雨过程进行了重现和分析。结果表明:二者与实测降雨数据一致性较好,分别达到了0.944 8和0.914 5;两种卫星降雨数据都较好地抓住了强降水中心的位置;对比地面站点、TRMM 3B42和FY-2D这3种数据绘制的强降水中心区域平均降水随时间序列变化,可以发现两种卫星与地面观测数据有较为相似的时间演变特征,能较为清楚的分辨出台风的螺旋结构,并且与台风发展路径具有较高的一致性。因此,两种卫星数据在对台风路径、强降雨中心的预测上具有较大的应用潜力。     

An Application of GPCC and NCEP/NCAR Datasets for Drought Variability Analysis in Iran

The lack of reliable and updated precipitation datasets is the most important limitation that hinders establishing a drought monitoring and early warning system in Iran. To overcome this obstacle, we have evaluated the applicability of GPCC and NCEP/NCAR precipitation datasets for drought analysis in Iran. For this purpose, drought variability across the country has been analyzed through the standardized precipitation index (SPI) on 12-month time scale based on the common period 1951?C2005. For each dataset, by applying the principal component analysis (PCA) to the SPI field and Varimax rotation, the studied area has been regionalized into a few distinctive sub-regions characterized by independent climatic variability. Results have been checked against observations at 32 rain gauge stations having reliable data for the study period. Both GPCC and NCEP/NCAR datasets identify the same sub-regions of drought variability and they are in good agreement with observations. However, the NCEP rotated principal component scores associated with the sub-regions show different time variability with respect to the behaviours captured by GPCC, on one hand, and observations, on the other hand. It seems that, in central Iran such differences concern mainly the period before the seventies. Thus, the results suggest that GPCC dataset is a useful tool for drought monitoring in Iran and it can be used to complement the information provided by rain gauge observations. The NCEP/NCAR reanalysis dataset shows a better agreement with observations for the period 1970?C2005 than for 1951?C2005, and its discrepancies in the regional time variability of drought with respect to GPCC and observations should be taken into account when periods before the seventies are considered.     

标准化降水指数与有效干旱指数在新疆干旱监测中的应用

基于干旱监测理论,根据新疆测站1961—2010年逐日降水资料,对比分析了基于不同时间尺度(1、3、6、9、12、24个月)标准化降水指标(SPI)与有效干旱指数(EDI)对干旱监测的有效性与实用性。结果表明:不论针对短期干旱还是长期干旱,EDI监测能力均明显优于SPI。短时间尺度的SPI受短时间降水影响较大,能反映短时间新疆地区的干旱变化特征;随时间尺度的增加,SPI对短时间降水的响应能力较差,但仍可反映长时间序列下明显的干旱变化趋势。与SPI相比,EDI能够很好地反映出短期干旱和当时降水量的影响;同时能够随时间迁移,给每日降水量分配以不同权重,考虑前期降水量对当前干湿状况的影响。相关研究结果可为湿润区及其他气候区洪旱灾害监测提供重要理论依据。     

ＲCPs 情景下贵州省干旱趋势分析

为探究贵州省未来干旱变化趋势,基于 CMIP5 全球气候模式预估的降水月值数据,利用标准化降水指数(SPI)分析了 2016—2050 年 ＲCPs 情景下贵州省干旱趋势。结果表明: 2016—2050 年间ＲCP2. 6、ＲCP4. 5 和 ＲCP8. 5 情景下贵州省 SPI 指数均呈现增加趋势。除特旱外,ＲCP8. 5 情景下轻旱、中旱、重旱发生频次高于 ＲCP2. 6 和 ＲCP4. 5 情景。2016—2030 年各情景下各干旱等级发生频次较高。不同情景下各干旱等级的干旱频率空间异质性突出。各情景下贵州省干旱站次比和干旱强度均呈现下降趋势,发生全域性干旱年份较多,发生区域性干旱和局域性干旱年份较少。发生轻度干旱强度年份较多,发生中度干旱强度和重度干旱强度年份较少。ＲCPs 情景下贵州省降水增加导致干旱风险降低。研究结果可为干旱监测和农业生产提供参考依据。     

基于SPI的辽宁省庄河市近35年干旱演变特性研究

庄河市是辽南地区的重要水源地,分析其干旱演变特性有利于该地区水资源的合理开发与利用,对于防旱减灾、合理布局产业结构具有重要的现实意义。本文根据庄河市1984年1月1日至2018年12月31日的逐日降水数据计算了1个月、3个月、6个月、12个月共4个不同时间尺度下的标准化降水指数(SPI),并基于SPI对该地区近35年的年际与季节干旱演变特征进行了分析。结果表明:在年际变化方面,庄河市的SPI在2000年以前波动幅度较小,说明该地区的降水在时间上分布较为均匀;但自2000年以来,SPI序列出现较大的波峰与波谷,说明降雨的分布不均匀性有所增强;SPI的时间序列趋势线斜率为负值,说明该地区整体上呈现偏旱趋势,因此其水资源压力不断增大。在季节演变特征方面,夏季干旱和秋季干旱呈现增强趋势;秋旱的发生频率最高,而夏旱的出现频率最低。本研究结果可为庄河地区的抗旱减灾与水资源规划提供科学依据。     

Effect of Air Temperature on Historical Trend of Long-Term Droughts in Different Climates of Iran

Effective monitoring of drought plays an important role in water resources planning and management, especially under global warming effect. The aim of this paper is to study the effect of air temperature on historical long-term droughts in regions with diverse climates in Iran. To this end, monthly air temperature (T) and precipitation (P) data were gathered from 15 longest record meteorological stations in Iran covering the period 1951–2014. Long-term meteorological droughts behavior was quantified using two different drought indices, i.e. the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Linear and non-linear trends in T, P, SPI and SPEI were evaluated using non-parametric and parametric statistical approaches such as non-modified and modified Mann-Kendall Test, Theil-Sen approach, and simple regression. The results indicated that the significant trends for temperature are approximately all increasing (0.2 °C to 0.5 °C per decade), and for precipitation are mostly decreasing (?7.2 mm to ?14.8 mm per decade). It was also indicated that long-term drought intensities monitored by the SPI and SPEI have had significant downward trend (drought intensification with time) at most stations of interest. The observed trends in the SPI series can be worsen if air temperature (in addition to precipitation) participates in drought monitoring as SPEI. In arid and extra arid climates, it was observed that temperature has strong effects on historical drought characteristics when comparing the SPI and SPEI series. Due to the determinative role of temperature in mostly dry regions like Iran, the study suggests using the SPEI rather than SPI for more effective monitoring of droughts.     

基于贝叶斯模式平均方法融合多源数据的水文模拟研究

可靠的长系列气象数据是开展流域水文模拟、水旱灾害防治和水资源综合管理的基本依据,但是我国气象站网布设不均、地面观测资料系列相对较短,难以满足工程应用需要。本文融合有限的地面气象观测数据,长系列高精度MSWEP-V2卫星集成降水数据集和欧洲中期天气预报中心的ERA5气温数据,首先通过基于分位数映射的日偏差校正（DBC）、基于月尺度的回归校正（LRBC）和等率校正（RBC）等3种方法,对遥测栅格降水和再分析气温日系列进行偏差校正,再采用季节性贝叶斯模式平均（BMA）方法描述各偏差校正系列的后验分布优选相应权重,从而得到融合多种偏差校正模式的长系列日降水、气温过程。以巢湖流域为例,采用174个自动气象站2015—2019年的观测数据和7个国家基本气象台站1979—2019年的长系列资料检验校正效果,并在2个子流域分别驱动新安江、GR4J和HMETS水文模型验证水文模拟的适用性。结果表明：BMA方法能够综合考虑各偏差校正方法的优势,校正后的日降水和气温数据偏差较小,与实测系列的相关性系数接近0.8;水文模型率定期及检验期的KGE系数超过0.67,校正后的气象数据满足水文模拟要求。     

Drought Characterisation Based on Water Surplus Variability Index

Drought assessment, characterisation and monitoring increasingly requires considering not only precipitation but also the other meteorological parameters such as an evapotranspiration. Thus, some new drought indices based on precipitation and evapotranspiration have been developed. This study introduces a new drought index named the water surplus variability index (WSVI). The procedure to estimate the index involves accumulation water surplus at different time scales. To approve the proposed procedure, the WSVI is compared with the standardized precipitation index (SPI), the reconnaissance drought index (RDI) and the standardized precipitation evapotranspiration index (SPEI) based on 1-, 3-, 6- and 12-month timescales using data from several weather stations located in regions with different aridity index. Near perfect agreement (d?~?1) between WSVI and SPI, RDI and SPEI was indicated in humid and sub-humid locations. The results also showed that the correlation coefficients between WSVI and SPI, RDI and SPEI were higher for semi-arid stations than for arid ones.     

Influence of Precipitation Changes on the SPI and Related Drought Severity. An Analysis Using Long-Term Data Series

Drought indices, such as the Standardized Precipitation Index (SPI) are used to quantify drought severity. Due to the SPI probabilistic and standardized nature, a given value of SPI computed in distinct time periods or locations indicates the same relative drought severity but corresponds to different amounts of precipitation. Thus, the present study aims at contributing for a comprehensive analysis of the influence of long-term precipitation variability on drought assessment by the SPI. Long records of monthly precipitation, spanning from 1863 to 2007 in several locations across Portugal, were divided into 30 years sub-periods and the SPI with 12-month time scale (SPI-12) was computed for each sub-period and for the entire period of records. The probability distributions adjusted to precipitation in those different time periods were compared envisaging to detect the SPI sensitivity to the reference period and, therefore, to changes in precipitation. Precipitation thresholds relative to the upper limits of SPI-12 drought categories were obtained and the influence of the time period was investigated. Results have shown that when SPI values derived from the full data record for a recent time period are lower/higher than the SPI values derived from data of the considered time period a recent downward/upward shift of precipitation has occurred. Coherently, a common pattern of drought aggravation from the initial until the more recent period was not detected. However, in southern locations, lower precipitation thresholds of the SPI drought categories were generally found in the more recent period, particularly for more severe drought categories, whereas in the northern locations Porto and Montalegre, an increase was detected. The impacts of the reference period on the computed SPI drought severity and frequency are shown, bringing to discussion the need for updating ´normal´ conditions when long term precipitation records are available and precipitation changes are observed.     

Identification of Drought Occurrences Using Ensemble Predictions up to 20-Days in Advance

In the present study, skill of an extended range forecast system has been evaluated for identifying droughts over central India 20-days in advance. Rainfall forecasts from 44 ensemble members of the forecast system developed Indian Institute of Tropical Meteorology (IITM), Pune have been used to prepare probabilistic rainfall forecasts. It is seen that the uncertainties in the forecasts (in terms of ensemble spread) increases from day-5 to day 20. As the focus of the study is for drought predictions, forecasts in the bins 0-5 mm/5 day and 5-25 mm/5 day (no rain or less rain) were studied in detail. It is found that the modeling system has a tendency to over-forecast rainfall probabilities. With bias correction, the forecasts become more reliable. Various drought indices were computed using the mean of the forecast distribution up to 20-days in advance. Standardized precipitation index (SPI) computed using Gamma and Pearson type-III distributions are similar in the study region. It was found that these are in reasonable agreement with those from observations. Probabilistic forecasts of standardized precipitation index (SPI) were made and the relative operating characteristics (ROC) scores indicate that the forecasted SPI values are suitable for application.     

Computation of Drought Index SPI with Alternative Distribution Functions

The Standardized Precipitation Index (SPI) is widely used as drought meteorological index, to identify the duration and/or severity of a drought. The SPI is usually computed by fitting the gamma probability distribution to the observed precipitation data. In this work, the possibility to calculate SPI by fitting to the precipitation data the normal and the log-normal probability distributions was studied. For this purpose, 19 time series of monthly precipitation of 76?years were used, and the assumption that the gamma probability distribution would provide better representation of the precipitation data than log-normal and normal distributions, at various time scales (1, 3, 6, 12 and 24?months) was tested. It is concluded that for SPI of 12 or 24?months, the log-normal or the normal probability distribution can be used for simplicity, instead of gamma, producing almost the same results.