Evaluating the performance of remote sensing precipitation products CMORPH,PERSIANN, and TMPA,in the arid region of northwest China

The arid region of northwest China is a large area with complex topography. Hydrological research is limited by scarcity and uneven distribution of rain gauges. Satellite precipitation products provide wide coverage and high spatial–temporal resolutions, but the accuracy needs to be evaluated before application. In this paper, the reliability of four satellite precipitation products (CMORPH [Climate Prediction Center’s morphing technique], PERSIANN [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks], TRMM [Tropical Rainfall Measuring Mission] 3B42, and TRMM 3B43) were evaluated through comparison with ground data or reported values on daily, monthly, and annual scales from 2003 to 2010. Indices including frequency bias index, probability of detection, and false alarm ratio were used to evaluate recorded precipitation occurrences; relative mean bias, the correlation coefficient, and the Nash coefficient were used to assess precipitation amount. Satellite precipitation products were more accurate in the warm than in the cold season, and performed better in northern Xinjiang than in other regions during the cold season. CMORPH and PERSIANN tended to overestimate precipitation. TRMM 3B42 and TRMM 3B43 performed best because the former most accurately detected precipitation occurrences on a daily scale, and both produced accurate space–time distribution of precipitation and the best consistency with rain gauge observations. Only a few monthly precipitation values for TRMM 3B42 and TRMM 3B43, and annual precipitation values for TRMM 3B42 were with satisfactory precision. TRMM3B42 and TRMM 3B43 are therefore recommended, but correction will be needed before application. Factors including elevation, relative relief, longitude, and latitude had significant effects on the performance of satellite precipitation products, and these factors may be helpful in correcting satellite precipitation.     

Influence of aerosol-radiative forcings on the diurnal and seasonal cycles of rainfall over West Africa and Eastern Atlantic Ocean using GCM simulations

Effects of aerosol radiative forcing on the diurnal and seasonal cycles of precipitation over West Africa and eastern Atlantic Ocean are investigated for the boreal summer season: June–July–August. An eight year (2000–2007) average of GCM simulated rainfall data is compared with the corresponding TRMM rainfall data. The comparison shows that the amplitude of the diurnal cycles of rainfall over land and ocean are reasonably well simulated. Over land, the phase of the simulated diurnal cycle of precipitation peaks several hours earlier than that of the TRMM data. Corresponding differences over the ocean(s) are relatively smaller. Some of the key features of the aerosol induced model simulated field anomalies are: (a) aerosol direct radiative forcing which increases the atmospheric stability and reduces the daytime moist convection and convective precipitation; (b) the aerosol induced changes in the diurnal cycle of precipitation are out of phase with those of the TRMM data over land, but are in-phase over the ocean; (c) aerosols reduce the amplitude of the diurnal cycle of precipitation over land and enhance it over ocean. However, the phase of the diurnal cycle is not affected much by the aerosol radiative forcing both over land and ocean. During the boreal summer, aerosol radiative forcing and induced circulation and precipitation cool the Sahel and the southern part of Sahara desert more than the adjacent areas to the north and south, thereby shifting the peak meridional temperature gradient northward. Consequently, an anomalous easterly jet is found north of its climatological location. This anomalous jet is associated with increased cyclonic circulation to the south of its axis, resulting in an anomalous monsoon rain belt in the Sahel.     

Diurnal phase of late-night against late-afternoon of stratiform and convective precipitation in summer southern contiguous China

Using the tropical rainfall measuring mission (TRMM) Precipitation Radar (PR) observations combined with the surface rain gauge data during 1998–2006, the robust diurnal features of summer stratiform and convective precipitation over the southern contiguous China are revealed by exploring the diurnal variations of rain rate and precipitation profile. The precipitation over the southern contiguous China exhibits two distinguishing diurnal phases: late-night (2200–0600 LST) and late-afternoon (1400–2200 LST), dependent on the location, precipitation type and duration time. Generally, the maximum rain rate and the highest profile of stratiform precipitation occur in the late-afternoon (late-night) over the southeastern (southwestern) China, while most of the stratiform short-duration rain rate tends to present late-afternoon peaks over the southern China. For convective precipitation, the maximum rain rate and the highest profile occur in the late-afternoon over most of the southern contiguous China, while the convective long-duration rain rate exhibits late-night peaks over the southwestern China. Without regional dependence, the convective precipitation exhibits much larger amplitude of diurnal variations in both near surface rain rate and vertical extension compared with stratiform precipitation and the convective rain top rises most rapidly between noon and afternoon. However, there are two distinctive sub-regions. The diurnal phases of precipitation there are very weakly dependent on precipitation type and duration time. Over the eastern periphery of the Tibetan Plateau, the maximum rain rate and the highest profile of either convective or stratiform precipitation occur in the late-night. Over the southeastern coastal regions, both the near surface rain rate and rain top of convective and stratiform precipitation peak in the late-afternoon.     

华北地区夏季降水日变化的时空分布特征

利用2008~2014年间全国自动站观测降水和CMORPH[CPC（Climate Prediction Center）morphing technique]卫星反演降水资料融合而成的0.1°×0.1°小时降水产品揭示了华北夏季降水的日变化特征,发现华北多数地区夏季降水量和降水频率日变化呈现出明显的双峰特征且存在明显的区域性差异。在太行山以西地区,降水量和降水频率的日峰值出现在傍晚18:00左右（北京时）,规律性最强;而在太行山以东的平原和沿海地区,日峰值一般出现在上午。研究不同持续时间降水对总降水的贡献发现短时降水对傍晚的降水日峰值贡献较大,而长时降水则对凌晨的峰值影响更大。分析不同强度降水对总降水量的贡献结果表明,0.1~10 mm h-1强度降水较其它强度降水对夏季华北地区总降水量贡献更大,随着降水强度的增加降水量日变化的峰值个数增加。     

Are satellite products good proxies for gauge precipitation over Singapore?

The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000–2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate model simulated future projections, when information on precipitation extremes need to be reliable as they are highly crucial for adaptation and mitigation.     

Very high resolution rainfall patterns measured by TRMM precipitation radar: seasonal and diurnal cycles

The TRMM Precipitation Radar is used to construct a high resolution (0.05°?×?0.05°) climatology of rainfall over the latitude band extending to about 36° North and South. This study describes climatological patterns of rainfall frequency and intensity at high spatial resolution, with special focus on the seasonal and diurnal cycles in the frequency of rainfall events. We use this Tropics-wide dataset to highlight small-scale precipitation features that are too fine to be captured by the most widely used satellite-based rainfall datasets. The results shed light on the roles of changes in the wind direction, the land-sea thermal contrast, small-scale variations in sea surface temperature, and orography in shaping the seasonal and diurnal cycles of rainfall. In some regions of the tropics, diurnally locked local circulations are largely responsible for sharp gradients in the spatial distribution of seasonal mean precipitation. In other regions, we show that climatological rainfall frequency changes very sharply at coastlines, even though rainfall in these regions is expected to be controlled by relatively large scale weather systems.     

COMPARISON OF PERSIANN AND TMPA DAILY PRECIPITATION ESTIMATES OVER HUNAN PROVINCE OF CHINA

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.     

Validation of Daily Precipitation from Two High-Resolution Satellite Precipitation Datasets over the Tibetan Plateau and the Regions to Its East

Daily precipitation amounts and frequencies from the CMORPH (Climate Prediction Center Morphing Technique) and TRMM (Tropical Rainfall Measuring Mission) 3B42 precipitation products are validated against warm season in-situ precipitation observations from 2003 to 2008 over the Tibetan Plateau and the regions to its east. The results indicate that these two satellite datasets can better detect daily precipitation frequency than daily precipitation amount. The ability of CMORPH and TRMM 3B42 to accurately detect daily precipitation amount is dependent on the underlying terrain. Both datasets are more reliable over the relatively flat terrain of the northeastern Tibetan Plateau, the Sichuan basin, and the mid-lower reaches of the Yangtze River than over the complex terrain of the Tibetan Plateau. Both satellite products are able to detect the occurrence of daily rainfall events; however, their performance is worse in regions of complex topography, such as the Tibetan Plateau. Regional distributions of precipitation amount by precipitation intensity based on TRMM 3B42 are close to those based on rain gauge data. By contrast, similar distributions based on CMORPH differ substantially. CMORPH overestimates the amount of rain associated with the most intense precipitation events over the mid-lower reaches of the Yangtze River while underestimating the amount of rain associated with lighter precipitation events. CMORPH underestimates the amount of intense precipitation and overestimates the amount of lighter precipitation over the other analyzed regions. TRMM 3B42 underestimates the frequency of light precipitation over the Sichuan basin and the mid-lower reaches of the Yangtze River. CMORPH overestimates the frequencies of weak and intense precipitation over the mid-lower reaches of the Yangtze River, and underestimates the frequencies of moderate and heavy precipitation. CMORPH also overestimates the frequency of light precipitation and underestimates the frequency of intense precipitation over the other three regions. The TRMM 3B42 product provides better characterizations of the regional gamma distributions of daily precipitation amount than the CMORPH product, for which the cumulative distribution functions are biased toward lighter precipitation events.     

GRAPES_GFS模式全球降水预报的主要偏差特征

利用2017年1、4、7、10月"全球降水观测(global precipitation measurement,GPM)计划"每日08时(北京时)的24 h累计降水量和逐30 min降水量观测产品,从降水量和频率等角度,对同期GRAPES全球模式(GRAPES_GFS)第1(D1)、3(D3)、5天(D5)的全球降水...     

Assessing the performance of satellite-based precipitation products and its dependence on topography over Poyang Lake basin

Satellite-based precipitation products (SPPs) have greatly improved their applicability and are expected to offer an alternative to ground-based precipitation estimates in the present and the foreseeable future. There is a strong need for a quantitative evaluation of the usefulness and limitations of SPPs in operational meteorology and hydrology. This study compared two widely used high-resolution SPPs, the Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN) in Poyang Lake basin which is located in the middle reach of the Yangtze River in China. The bias of rainfall amount and occurrence frequency under different rainfall intensities and the dependence of SPPs performance on elevation and slope were investigated using different statistical indices. The results revealed that (1) TRMM 3B42 usually underestimates the rainy days and overestimates the average rainfall as well as annual rainfall, while the PERSIANN data were markedly lower than rain gauge data; (2) the rainfall contribution rates were underestimated by TRMM 3B42 in the middle rainfall class but overestimated in the heavy rainfall class, while the opposite trend was observed for PERSIANN; (3) although the temporal distribution characteristics of monthly rainfall were correctly described by both SPPs, PERSIANN tended to suffer a systematic underestimation of rainfall in every month; and (4) the performances of both SPPs had clear dependence on elevation and slope, and their relationships can be fitted using quadratic equations.     

TRMM和CMORPH卫星资料对三峡库区降水的评估分析

利用1998—2016年TRMM和CMORPH两种遥感卫星资料降水和同期三峡库区气象观测站数据,通过比较干、支流和远、近库区气象站点的降水变化和蓄水前后降水量、雨日、降水强度和频率等变化特征,分析评估了基于两种卫星遥感降水和测站降水的三峡库区局地降水变化。结果表明:库区TRMM和CMORPH卫星降水年际变化特征总体上与气象观测站相符,反演效果在日尺度TRMM略逊于CMORPH,在季尺度CMORPH略逊于TRMM;两种卫星资料对冬季降水反演效果都偏弱。三峡库区干流和支流站点的降水变化总体一致,干、支流各站点降水量均具有较强的年际变化特征。TRMM相比CMORPH更能重现干、支流测站降水的年际变化特征,CMORPH降水年际波动振幅总体上比测站偏大。蓄水前后时段(1998—2003年与2004—2016年)对比,从不同等级降水的强度和雨日、季节降水频率和总量等变化反演效果来看,CMORPH资料分布相比TRMM更接近测站的变化趋势,反演效果略优于TRMM;但两种卫星资料的降水频率和降水量分布与测站的误差在蓄水前后变化都不明显。此外,气象测站、TRMM、CMORPH资料都表现出蓄水后三峡远、近库区年降水量的比值呈平稳波动状态,表明三峡水库蓄水后附近地区降水没有明显变化。     

高原低涡研究和TRMM卫星资料应用的相关进展

高原天气系统对青藏高原及其下游地区的降水有重要影响。高原低涡是活动于高原主体的重要天气系统之一。TRMM卫星的应用为研究高原天气系统提供了新方法。本文回顾了部分关于高原低涡和TRMM卫星资料应用的研究成果,包括高原低涡的定性认识、结构及其和背风坡浅薄天气系统的相互作用,TRMM卫星的基本资料、其在非高原地区和高原地区的应用。      

中国区域逐日融合降水数据集与国际降水产品的对比评估

中国国家气象信息中心基于2400多个国家级台站观测日降水量和CMORPH卫星反演降水产品,采用概率密度匹配和最优插值相结合的两步数据融合方法,研制了中国区域1998年以来的0.25°×0.25°分辨率的逐日融合降水产品(CMPA_Daily)。通过该数据集与广泛应用于中国天气气候领域的两种国际上降水融合产品TRMM 3B42(Tropical Rainfall Measuring Mission, 3B42)和GPCP(Global Precipitation Climatology Project, 1 degree daily)的对比评估,考察CMPA_Daily产品的质量,评价其能否合理体现中国降水的天气气候特征。首先利用2008—2010年5—9月独立检验数据定量对比了CMPA_Daily、TRMM 3B42和GPCP 三种降水产品的误差,结果表明,在误差的时间变化和空间分布上,CMPA_Daily均具有最高的相关系数和最小的平均偏差及均方根误差,TRMM 3B42其次,GPCP的误差相对较大。CMPA_Daily只低估了大暴雨,TRMM 3B42低估了大雨以上量级的降水,而GPCP低估了除小雨以外的所有降水。CMPA_Daily产品因融入了更多的站点观测信息,不论在中国东部沿海,还是中西部地形复杂区,其精度均优于TRMM 3B42和GPCP产品,即使在站点稀疏的青藏高原地区,CMPA_Daily降水量也更加接近站点观测,呈现明显的高相关。CMPA_Daily与独立检验数据的高相关在地形起伏时效果也较稳定,TRMM和GPCP的相关系数则随着地形变化幅度陡变而非常明显地降低。进一步通过对比分析各降水产品1998—2012年的气候平均降水特征表明,3种资料对中国区域气候平均降水量、降水强度、频率分布以及年际变化的总体描述基本一致,因有效融入了更多的中国站点观测信息,不论降水空间分布还是降水量,CMPA_Daily与地面观测均最为接近,在中国的中东部大部分地区对降水的估计精度明显更高,而在站点分布较稀疏的青藏高原地区,CMPA_Daily的降水分布型与TRMM、GPCP卫星融合资料类似,较地面站点插值产品更能体现出合理的降水分布。对中国强降水事件监测对比表明,CMPA_Daily产品可以更加准确地描述降水的强度变化,细致刻画降水空间分布,在把握降水小尺度特征上具有明显的优势,体现出高分辨率、高精度降水产品的特点。     

基于TRMM卫星的近10a甘肃临夏降水变化特征

基于2001~2010年TRMM 3B43降水资料和数字高程模型（DEM）数据,采用回归模型＋残差的方法,对甘肃临夏回族自治州近10 a的TRMM 3B43降水数据进行降尺度运算,并结合研究区6个雨量站的观测值,对TRMM 3B43降尺度结果进行精度检验,在此基础上定量研究了临夏回族自治州近10 a的降水量时空变化特征。结果表明：TRMM 3B43降尺度降水量数据整体上具有一定的可信度,但比地面台站的观测值偏小;甘肃临夏州年降水量呈现出由西南向东北递减的趋势,且降水量随着海拔高度的升高而逐渐增加,两者相关系数为0.82;年内降水主要集中在5~9月,基本占全年降水量的70%以上,其中6月降水量最大,12月降水量最小。     

Modeled Chaco low-level jets and related precipitation patterns during the 1997–1998 warm season

Summary Chaco jet events (CJEs) are a subset of South American low-level jet events to the east of the Andes, characterized by enhanced poleward penetration and by a strong impact on precipitation over southeastern South America. The present study uses the Eta model short range weather forecasts produced operationally in the Brazilian Center for Weather Forecasts and Climate Studies (Centro de Previs?o de Tempo e Estudos Climáticos, CPTEC) to characterize the CJEs and the related precipitation during the 1997–1998 warm season. An enhanced diurnal cycle in precipitation with respect to that found during the warm season mean can be recognized during CJEs in Eta/CPTEC model output, with preference for a nocturnal maximum over southern Brazil, Uruguay, and the central part of northern Argentina, and a daytime maximum near high topography (northwestern Argentina, the Brazilian Planalto). The analysis of thermodynamic and dynamic forcing appearing during CJEs, helps to explain the modeled precipitation cycle: the nocturnal maximum is mostly explained by enhanced low-level convergence at night, while the diurnal one is mainly a response to radiative warming. Boundary-layer convergence, and convective instability, present within the CJEs environment, work together to provide both dynamic forcing and potential for convection. The simulated precipitation cycle is complemented with surface observations of “current weather” that corroborate the main oscillations found in simulated precipitation.     

Climatological characteristics of summer precipitation over East Asia measured by TRMM PR: A review

Precipitation is an important indicator of climate change and a critical process in the hydrological cycle, on both the global and regional scales. Methods of precipitation observation and associated analyses are of strategic importance in global climate change research. As the first space-based radar, the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) has been in operation for almost 17 years and has acquired a huge amount of cloud and precipitation data that provide a distinctive view to help expose the nature of cloud and precipitation in the tropics and subtropics. In this paper we review recent advances in summer East Asian precipitation climatology studies based on long-term TRMM PR measurements in the following three aspects: (1) the three-dimensional structure of precipitation, (2) the diurnal variation of precipitation, and (3) the recent precipitation trend. Additionally, some important prospects regarding satellite remote sensing of precipitation and its application in the near future are discussed.     

Climatological Characteristics of Summer Precipitation over East Asia Measured by TRMM PR:A Review

Precipitation is an important indicator of climate change and a critical process in the hydrological cycle, on both the global and regional scales. Methods of precipitation observation and associated analyses are of strategic importance in global climate change research. As the first space-based radar, the Tropical Rainfall Measuring Mission(TRMM)Precipitation Radar(PR) has been in operation for almost 17 years and has acquired a huge amount of cloud and precipitation data that provide a distinctive view to help expose the nature of cloud and precipitation in the tropics and subtropics. In this paper we review recent advances in summer East Asian precipitation climatology studies based on long-term TRMM PR measurements in the following three aspects:(1) the three-dimensional structure of precipitation,(2) the diurnal variation of precipitation, and(3) the recent precipitation trend. Additionally, some important prospects regarding satellite remote sensing of precipitation and its application in the near future are discussed.     

基于TIGGE多模式降水量预报的统计降尺度研究

利用TIGGE资料中欧洲中期天气预报中心、美国国家环境预报中心、英国气象局以及日本气象厅4个中心,1~7 d预报时效的降水量预报资料,以TRMM/3B42RT降水量作为"观测值",对东亚地区降水量进行统计降尺度处理。首先利用逻辑回归方法将天气分为有雨和无雨,再对有雨的情况,利用线性回归方法对插值后的预报结果进行降尺度订正,最后将4个中心的预报值进行消除偏差集合平均,得到多模式集成的降水量预报场。结果表明:逻辑回归能够有效地改善预报中小雨的空报情况,统计降尺度订正后的预报结果比直接插值更加准确,多模式集成的预报效果优于单模式结果,其改进效果随预报时效的延长逐渐减小。     

湖南夏季降水日变化特征

利用湖南96个测站13年的逐时自记降水资料, 分析了夏季（6~8月）降水日变化特征。结果表明, 湖南夏季降水日变化呈现显著的区域差异。湘东南降水量、 降水频次峰值主要出现在午后到傍晚, 而其它地区的降水峰值一般出现在清晨。进一步分析显示, 降水频次峰值出现时次分布更集中, 区域特征更鲜明。湘西北、 湘东南区域平均的累积降水量、 降水频次及降水强度的日变化在清晨和午后均呈双峰型特征。湘西北主（次）峰值出现的时间大致与湘东南次（主）峰值出现的时间对应。同时, 降水日变化与降水持续时间密切相关。持续5~10 h降水事件是持续1~4 h事件与持续10 h以上事件降水量峰值出现时间发生显著变化的过渡降水事件。持续1~4 h（10 h以上）的降水事件的极值降水始发时间为午后至傍晚（夜间）。在不同持续时间的降水事件中, 持续2 h降水的累积量最大。     

A new method to compare hourly rainfall between station observations and satellite products over central-eastern China

This study employs a newly defined regional-rainfall-event (RRE) concept to compare the hourly characteristics of warm-season (May-September) rainfall among rain gauge observations, China merged hourly precipitation analysis (CMPA-Hourly), and two commonly used satellite products (TRMM 3B42 and CMORPH). By considering the rainfall characteristics in a given limited area rather than a single point or grid, this method largely eliminates the differences in rainfall characteristics among different observations or measurements over central-eastern China. The results show that the spatial distribution and diurnal variation of RRE frequency and intensity are quite consistent among different datasets, and the performance of CMPA-Hourly is better than the satellite products when compared with station observations. A regional rainfall coefficient (RRC), which can be used to classify local rain and regional rain, is employed to represent the spatial spread of rainfall in the limited region defining the RRE. It is found that rainfall spread in the selected grid box is more uniform during the nocturnal to morning hours over central-eastern China. The RRC tends to reach its diurnal maximum several hours after the RRE intensity peaks, implying an intermediate transition stage from convective to stratiform rainfall. In the afternoon, the RRC reaches its minimum, implying the dominance of local convections on small spatial scale in those hours, which could cause large differences in rain gauge and satellite observations. Since the RRE method reflects the overall features of rainfall in a limited region rather than at a fixed point or in a single grid, the widely recognized overestimation of afternoon rainfall in satellite products is not obvious, and thus the satellite estimates are more reliable in representing sub-daily variation of rainfall from the RRE perspective. This study proposes a reasonable method to compare satellite products with rain gauge observations on the sub-daily scale, which also has great potential to be used in evaluating the spatiotemporal variation of cloud and rainfall in numerical models.