Inter-comparison of satellite rainfall products for representing rainfall diurnal cycle over the Nile basin

In this study, the authors inter-compared the performance of three satellite-rainfall products in representing the diurnal cycle of rain occurrence and rain rate over the Nile basin in eastern Africa. These products are the real time (RT) and post-real-time (PRT) (bias adjusted) versions of Tropical Rainfall Measuring Mission (TRMM) and other sources product known as TRMM-3B42 and the National Oceanographic and Atmospheric Administration Climate Prediction Center (NOAA-CPC) product which is based on the CPC morphing technique (CMORPH). The rainfall diurnal cycles are re-produced using these products with specific focus on assessing effects of geographic location and topographic features. The performance of the satellite products in representing rainfall diurnal cycle shows large variation over the Nile basin. The products overestimate rain occurrence over the lakes, islands, and shores and underestimate occurrence over mountain tops. Overall, CMORPH performs better than TRMM-3B42 RT and TRMM-3B42 PRT in capturing the diurnal cycle of rain rate in Lake Tana basin. However, the difference between the two products is very small for Lake Victoria basin, where both products perform more favorably. Over most of the Nile basin areas, the use of fine versus coarse temporal and spatial resolution of the CMORPH product showed large differences for diurnal cycle of rain occurrence than that of rain rate. Results also show that the bias adjustment of TRMM-3B42 product does not necessarily bring improvements probably since the adjustments are not performed based on local rain gauge data.     

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.     

Satellite-derived rainfall thresholds for landslide early warning in Bogowonto Catchment,Central Java,Indonesia

Satellite rainfall products for landslide early warning prediction have been spotlighted by several researchers, in the last couple of decades. This study investigates the use of TRMM and ERA-Interim data, for the determination of rainfall thresholds and the prediction of precipitation, respectively, to be used for landslide early warning purposes at the Bogowonto catchment, Central Java, Indonesia. A landslide inventory of 218 landslides for the period of 2003–2016 was compiled, and rainfall data were retrieved for the landslide locations, as given by 6 ground stations, TRMM, and ERA-Interim data. First, rainfall data from the three different sources was compared in terms of correlation and extreme precipitation indices. Second, a procedure for the calculation of rainfall thresholds for landslide occurrence was followed consisting of four steps: i) the TRMM-based rainfall data was reconstructed for selected dates and locations characterized by landslide occurrence and non-occurrence; ii) the antecedent daily rainfall was calculated for 3, 5, 10, 15, 20 and 30 days for the selected dates and locations; iii) two-parameter daily rainfall-antecedent rainfall thresholds were calculated for the aforementioned dates; after analysis of the curves the optimum number of antecedent rainfall days was selected; and (iv) empirical rainfall thresholds for landslide occurrence were determined. The procedure was repeated for the entire landslide dataset, differentiating between forested and built-up areas, and between landslide occurrence in four temporal periods, in relation to the monsoon. The results indicated that TRMM performs well for the detection of very heavy precipitation and can be used to indicate the extreme rainfall events that trigger landslides. On the contrary, as ERA-Interim failed to detect those events, its applicability for LEWS remains limited. The 15-day antecedent rainfall was indicated to mostly affect the landslide occurrence in the area. The rainfall thresholds vary for forested and built-up areas, as well as for the beginning, middle and end of the rainy season.     

Rainfall Estimation from Combined Observations Using KALPANA-IR and TRMM- Precipitation Radar Measurements over Indian Region

In the present study an attempt has been made to improve the rainfall estimation technique developed recently by Mishra et al. (2009a, 2009b) based on KALPANA and Tropical Rainfall Measuring Mission (TRMM)-Precipitation Radar (PR) data over the Indian land and oceanic region. The algorithm for rainfall estimation was basically based on synergistically analyzing the thermal infra-red radiances from Kalpana/INSAT data along with the high resolution, horizontal and vertical rainfall estimates from PR. Presently the augmentation is based on the data base of precipitable water and relative humidity from National Centre for Environmental Prediction-Global forecast System (NCEP-GFS) data as a background field to correct for the biases in earlier algorithm. The algorithm is tested for many case studies of monsoon rainfall over India and adjoining oceanic regions. The rainfall from the present scheme is compared with the standard TRMM-3B42 rain product. The validation with the Automatic Weather Station (AWS) rain gauge and the Global Precipitation and Climatology Project (GPCP) version 2 rain products shows that the present scheme is able to retrieve the rainfall with a very good accuracy. These studies are aimed at the rainfall retrievals in near future from both INSAT-3D and Megha-Tropiques, IR and MW imagers respectively.     

TRMM PR雷达与阜阳雷达降水资料的对比研究

选取了1998年与1999年HUBEX观测资料，将TRMM卫星上的星载降雨雷达PR与阜阳的713数字化天气雷达资料在以下3个方面做了比较：(1)强度场的分布；(2)平均反射率廓线；(3)灵敏度。分析、比较结果可知阜阳雷达在探测灵敏度和水平方向的分辨率要高于PR，但由于波束宽度、衰减和资料转化过程计算误差的原因，其远距离处的观测值与真实值有一定偏差。PR波长短，对衰减敏感，尤其是在垂直方向上经过强衰减后，订正值仍偏小。但由于探测方式的不同PR在水平方向上不存在衰减的问题，且其资料分布均匀，因此提出一种用PR     

TRMM PR雷达与阜阳雷达降水资料的对比研究

选取了1998年与1999年HUBEX观测资料，将TRMM卫星上的星载降雨雷达PR与阜阳的713数字化天气雷达资料在以下3个方面做了比较：(1)强度场的分布；(2)平均反射率廓线；(3)灵敏度。分析、比较结果可知阜阳雷达在探测灵敏度和水平方向的分辨率要高于PR，但由于波束宽度、衰减和资料转化过程计算误差的原因，其远距离处的观测值与真实值有一定偏差。PR波长短，对衰减敏感，尤其是在垂直方向上经过强衰减后，订正值仍偏小。但由于探测方式的不同PR在水平方向上不存在衰减的问题，且其资料分布均匀，因此提出一种用PR资料来订正地基雷达资料的方法用以提高地基雷达探测的精确度。     

降雨对Ku波段旋转扇形波束散射计影响

星载散射计测量的归一化后向散射截面是有关海面毛细重力波的大小和方向的函数:散射计的回波强度与海面毛细重力波的振幅成正比;风向对后向散射系数具有调制作用。因此,可以利用散射计的数据,根据地球物理模型反演出具有高精确度、无雨和中低风速条件下的海面风场矢量。然而高达10%的散射计测量数据会受到降雨影响(Nie,etal.,2008),尤其工作在Ku波段的散射计。降雨对海面散射幅度的影响主要包括:(1)降雨对雷达波的衰减和散射;(2)降雨改变海洋水面形态和海面粗糙度。     

Evaluation of Precipitation Features in High-Frequency SSM/I Measurements Over Indian Land and Oceanic Regions

Evaluation of the Special Sensor Microwave Imager (SSM/I) precipitation features is presented from various passes over Indian oceanic and land regions under the framework of radiative transfer simulations for both emission and scattering atmospheres. There is considerable uncertainty in the interpretation of the SSM/I high-frequency scattering features for development of rainfall algorithms. Specifically large areas of very low emissivity regimes showing false rain signatures due to the presence of low brightness temperatures (TBs) that are often present in the vicinity of colder sea surface areas in the 85-GHz TB from SSM/I. In this connection, the Polarization Corrected Temperature (PCT) defined by Spencer using the 85-GHz channels, vertical (V) and horizontal (H), has been studied to delineate these surface effects. These false scattering signatures, once corrected using PCT as a suitable parameter, significantly improve the quality of the SSM/I-derived precipitation areas. These results are also confirmed with the cloud optical depth data from the Moderate Resolution Imaging Spectroradiometer sensor onboard the Aqua satellite and the standard merged rain product (geostationary infrared and Tropical Rainfall Measuring Mission (TRMM) microwave data) 3B42 from TRMM. This letter is aimed for selecting PCT as one of the suitable predictor variables for the development of operational rainfall retrieval algorithm for the Indo-French Megha-Tropiques satellite's microwave radiometer at high frequencies.      

利用TRMM／TMI资料提取地表层湿度信息试验

模拟分析了地表层湿度反演过程中地表及大气各种因素(卫星扫描角、地表粗糙度、地表植被覆盖和大气)对反演结果的影响情况;应用正演模拟技术得到了利用TMI低频10GHz通道微波极化比反演地表层湿度信息时,斜率和截距随像元植被覆盖度可调的反演方程;确定了反演方程中斜率、截距系数随像元植被覆盖度变化的对数关系和线性关系;反演技术中综合应用了多种途径获取到的被动微波像元中动态的植被覆盖信息;尝试了将这些因子用于地表层湿度反演的可行性;对于反演结果,研究工作中利用地表HUBEX外场观测资料进行了对比分析,得到了空间分布特征和时间演变趋势比较一致的对比分析结果。     

Mapping the Spatial and Temporal Pattern of Day-Night Temperature Difference in Greece from MODIS Imagery

The regional temporal and spatial multi-temporal land surface temperature (LST) MODIS dataset and elevation data are used to compute the day and night temperature variation in Greece in 2008. Clustering was applied and eight cluster centroids captured the temporal pattern of near-diurnal temperature (01:30 a.m. and 01:30 p.m.) variability while elevation statistics were computed per cluster. The spatial distribution of the clusters indicate that mean elevation, elevation variability, proximity to the sea, and the major inland water bodies were the key factors controlling the near-diurnal LST variability in Greece.     

ENSO影响下的西太平洋地区海陆水储量变化分析

利用2005-01-2016-12的GRACE卫星数据,结合测高、ARGO（array for real-time geostrophic oceanography）、TRMM（tropical rainfall measurement mission）降水数据和MEI（multivariate ENSO index）,从海平面、海水质量、海水比容和陆地水储量的非季节性变化分析了厄尔尼诺-南方涛动（El Ni?o/Southern Oscillation,ENSO）对西太平洋及其沿岸地区的影响。在GRACE数据处理过程中考虑了地震构造信号的影响,并采用正演模型法来恢复时变信号。结果表明,西太平洋地区平均海平面（western Pacific mean sea level,WPMSL）变化对ENSO的响应表现为:厄尔尼诺期间海平面下降,拉尼娜期间海平面上升;尤其在2014-2016年厄尔尼诺期间,WPMSL下降了近26.2 mm。比容变化为影响WPMSL非季节性变化的主导因素。澳大利亚和中南半岛水储量异常在年际变化上也较好响应了ENSO,与MEI的相关系数分别为-0.61（滞后3个月）和-0.65（滞后8个月）。长江流域对ENSO的响应主要在中下游区域,2014-2016年厄尔尼诺造成了该时期长江流域水储量达到近几年的极大值。     

Land surface temperature and its impact factors in Western Sichuan Plateau,China

The understanding influence of multiple factors variations on land surface temperature (LST) remains elusive. LST was retrieved by the atmospheric correction algorithms. Based on the correlation coefficients, stepwise regression analysis was developed to examine how multiple factors variability led to LST variations. The differences in LST between impact factors vary depending on time in a day. The elevation and land use types significantly affect the LST in sunny slope or shadow areas has a significantly quadratic curve correlation or a negative linear correlation with it, the influence of slope and aspect is not very significant. LST for forestland, grassland and bare land in the sunny slope and shadow area was the cubic polynomial related to its elevation. Normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) effectively express LST in mountainous. LST and NDMI or NDVI have a significantly negative correlation, NDMI is more effective and more applicable for the expression of LST.     

Sustainable fresh water resources management in northern Kuwait—A remote sensing view from Raudatain basin

The paper presents time and cost effective remote sensing technology to estimate recharge potential of fresh water shallow aquifers for their sustainable management of water resources in arid ecosystem. Precipitation measurement of Raudatain basin in Kuwait from TRMM data has been made and integrated with geological, geomorphological and hyrological data, to estimate the recharge potential of this basin. The total precipitation in the basin is estimated at 334 MCM for the year 2003. The initial losses are estimated at 78.43% and the transmission loss at 14.866% of the net precipitation.For sustainable management of the ground water resources, recharge wells have been proposed in the higher order streams to augment the Raudatain aquifer in Kuwait. If the available quantity of precipitation can be successfully utilized, it will reduce considerable pressure on desalination, which leads to increased salinity at the coast in Arabian Gulf.     

Assessment of the total lightning flash rate density (FRD) in northeast Brazil (NEB) based on TRMM orbital data from 1998 to 2013

The Northeast region of Brazil (NEB) concentrates on average 18 % of the total deaths associated with lightning strikes in Brazil. When considering population, the state of Piauí had the highest mortality rate in the region (1.8 deaths million⁻¹), much higher than the national rate (0.8) and the NEB rate (0.5). This work aimed to evaluate the space-time distribution of total lightning (intracloud, cloud-to-cloud and cloud-to-ground) in NEB, covering the period from 1998 to 2013. For this purpose, we used data from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite, which provided information on the occurrence of total lightning, and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor aboard on TERRA satellite, which provided the terrain elevation data to verify the influence of topography on the flash rate density (FRD). The full distribution was used to identify the hotspots (cities with the highest FRD), while the monthly distribution helped in the cluster analysis. NEB has great spatial and temporal variability of the recorded lightning rates, with average of 0–44.5 flash km^-2 year⁻¹. The regions with high total lightning rates are located in the states of Piauí, Maranhão and west of Bahia. The topography of the region seems to act as a facilitator of the convective process, leading to the formation of intense upward currents, essential for the generation of electric charges inside thunderstorms. CAPE values showed good relationship with lightning occurrence in the region. The cluster with the highest occurrence of lightning and hotspots is in the region of influence of the Intertropical Convergence Zone (ITCZ) and Mesoscale Convective Systems, suggesting an important relationship with large organized cloud systems.     

Evaluation of satellite-derived agro-climate variables in the Northern Great Plains of the United States

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.     

Characterization of Surface Geological Material in Northwest India and Adjoining Areas of Pakistan Using Normalized Difference Water Index,Land Surface Temperature and Silica Index

Land surface temperature (LST) shows negative correlation with the Normalized Difference Water Index (NDWI). Variability in the degree of correlation between LST and NDWI is ascribed to the physical character of specific geological material. Northwest India exhibits various landforms with different geological materials and has been broadly classified into four zones. Structural ridges of Aravalli Mountain of different rock compositions show strong variability both in NDWI (range 1.154, SD?=?0.0599) and in LST (range 24 °C and SD?=?2.54). Negative LST–NDWI correlation in this sector is partially linear. Western Thar Desert, having homogenous silica sand of lower emissivity shows least variability in its NDWI (range 0.88, SD?=?0.027) and moderate variability in its LST (20 °C, SD?=?2.389). Strong negative correlation of LST with NDWI is exhibited here. Band ratio Silica map in this sector shows strong positive correlation with LST. The eastern part of the Thar desert with mixed rocky knobs, and wind-blown sand shows low variability in NDWI (range 0.85) as well as LST (range 15 °C). Area in Indus–Bias–Sutlej River basin, dominated with fluvial sediments with lesser amount of windblown sediments, show low variability of NDWI (0.85) and moderate variability of LST (range 23 °C). In the areas, around Luni river higher NDWI trend is recorded, which is unrelated to present drainage trends indicating presence of palaeo-drainage. In addition, high NDWI and high LST bearing linear zones at places are interpreted as structural lineaments/faults based on pattern, moisture content and thermal high.     

Normalised difference spectral indices and urban land cover as indicators of land surface temperature (LST)

Land cover changes associated with urbanisation modify microclimate, leading to urban heat islands, whereby cities are warmer than the surrounding countryside. Understanding the factors causing this phenomenon could help urban areas adapt to climate change and improve living conditions of inhabitants. In this study, land surface temperatures (LST) of Aarhus, a city in the high latitudes, are estimated from the reflectance of a thermal band (TIRS1; Band 10; 10.60–11.19 μm) of Landsat 8 on five dates in the summer months (one in 2015, and four in 2018). Spectral indices, modelled on the normalised difference vegetation index (NDVI), using all combinations of the first seven bands of Landsat 8 are calculated and their relationships with LST, analysed. Land cover characteristics, in terms of the percentages of tree cover, building cover and overall vegetation cover are estimated from airborne LiDAR data, building footprints and 4-band aerial imagery, respectively. The correlations between LST, the spectral indices and land cover are estimated.The difference in mean temperature between the rural and urban parts of Aarhus is up to 3.96 °C, while the difference between the warmer and colder zones (based on the mean and SD of LST) is up to 13.26 °C. The spectral index using the near infrared band (NIR; Band 5; 0.85-0.88 μm) and a short-wave infrared band (SWIR2; Band 7; 2.11–2.29 μm) has the strongest correlations (r: 0.62 to 0.89) with LST for the whole study area. This index is the inverse of normalised burn ratio (NBR), which has been used for mapping burnt areas. Spectral indices using different combinations of the infrared bands have stronger correlations with LST than the more widely used vegetation indices such as NDVI. The percentage of tree cover has a higher negative correlation (Pearson’s r: -0.68 to -0.75) with LST than overall vegetation cover (r: -0.45 to -0.63). Tree cover and building cover (r: 0.53 to 0.71) together explain up to 68 % of the variation in LST. Modification of tree and building cover may therefore have the potential to regulate urban LST.     

Investigating flash floods potential areas using ASCAT and TRMM satellites in the Western Cape Province,South Africa

The aim of the study was to evaluate flash flood potential areas in the Western Cape Province of South Africa, by integrating remote sensing products of high rainfall intensity, antecedent soil moisture and topographic wetness index (TWI). Rainfall has high spatial and temporal variability, thus needs to be quantified at an area in real time from remote sensing techniques unlike from sparsely distributed, point gauge network measurements. Western Cape Province has high spatial variation in topography which results in major differences in received rainfall within areas not far from each other. Although high rainfall was considered as the major cause of flash flood, also other contributing factors such as topography and antecedent soil moisture were considered. Areas of high flash flood potential were found to be associated with high rainfall, antecedent precipitation and TWI. Although TRMM 3B42 was found to have better rainfall intensity accuracy, the product is not available in near real time but rather at a rolling archive of three months; therefore, Multi- sensor precipitation estimate rainfall estimates available in near real time are opted for flash flood events. Advanced Scatterometer (ASCAT) soil moisture observations were found to have a reasonable r value of 0.58 and relatively low MAE of 3.8 when validated with in situ soil moisture measurements. The results of this study underscore the importance of ASCAT and TRMM satellite datasets in mapping areas at risk of flooding.     

Using remote sensing to monitor the influence of river discharge on watershed outlets and adjacent coral Reefs: Magdalena River and Rosario Islands,Colombia

Worldwide, coral reef ecosystems are being increasingly threatened by sediments loads from river discharges, which in turn are influenced by changing rainfall patterns due to climate change and by growing human activity in their watersheds. In this case study, we explored the applicability of using remote sensing (RS) technology to estimate and monitor the relationship between water quality at the coral reefs around the Rosario Islands, in the Caribbean Sea, and the rainfall patterns in the Magdalena River watershed. From the Moderate Resolution Imaging Spectroradiometer (MODIS), this study used the water surface reflectance product (MOD09GQ) to estimate water surface reflectance as a proxy for sediment concentration and the land cover product (MCD12Q1 V51) to characterize land cover of the watershed. Rainfall was estimated by using the 3B43 V7 product from the Tropical Rainforest Measuring Mission (TRMM). For the first trimester of each year, we investigated the inter-annual temporal variation in water surface reflectance at the Rosario Islands and at the three main mouths of the Magdalena River watershed. No increasing or decreasing trends of water surface reflectance were detected for any of the sites for the study period 2001–2014 (p > 0.05) but significant correlations were detected among the trends of each site at the watershed mouths (r = 0.57–0.90, p < 0.05) and between them and the inter-annual variation in rainfall on the watershed (r = 0.63–0.67, p < 0.05). Those trimesters with above-normal water surface reflectance at the mouths and above-normal rainfall at the watershed coincided with La Niña conditions while the opposite was the case during El Niño conditions. Although, a preliminary analysis of inter-annual land cover trends found only cropland cover in the watershed to be significantly correlated with water surface reflectance at two of the watershed mouths (r = 0.58 and 0.63, p < 0.05), the validation analysis draw only a 40.7% of accuracy in this land cover classification. This requires further analysis to confirm the impact of the cropland on the water quality at the watershed outlets. Spatial analysis with MOD09GQ imagery detected the overpass of river plumes from Barbacoas Bay over the Rosario Islands waters.     

A comparison of MODIS, NCEP, and TMI sea surface temperature datasets

The monthly average sea surface temperature (SST) datasets of MODIS (Moderate Resolution Imaging Spectroradiometer), NCEP (National Center for Environmental Prediction) and TMI (Tropical Rainfall Measuring Mission (TRMM) Microwave Imager) are compared for the period March 2000 to June 2003. Large discrepancies (0.5 K->1 K) are found over extensive areas: the tropical Atlantic, tropical western Pacific, Bay of Bengal, Arabian Sea and the storm tracks. Many of these discrepancies are related to the biases inherent in the infrared and microwave retrieval methods. Probable causes for these biases include cirrus contamination, insufficient corrections for water vapor absorption and aerosol attenuation in infrared retrieval as well as uncertainty in surface emissivity in microwave retrieval. The SST difference patterns bear close resemblance to the patterns of distribution of aerosols, cirrus, atmospheric water vapor and surface wind speed at certain regions. Correlations between SST difference and aerosol optical depth, column water vapor and surface wind speed in some areas are high (>0.75). These biases have to be adjusted in order for the SST datasets to be more useful for climate studies.