Improved rainfall estimation over the Indian region using satellite infrared technique

The GOES Precipitation Index (GPI) technique (Arkin, 1979) for rainfall estimation has been in operation for the last three decades. However, its applications are limited to the larger temporal and spatial scales. The present study focuses on the augmentation on GPI technique by incorporating a moisture factor for the environmental correction developed by Vicente et al. (1998). It consists of two steps; in the first step the GPI technique is applied to the Kalpana-IR data for rainfall estimation over the Indian land and oceanic region and in the second step an environmental moisture correction factor is applied to the GPI-based rainfall to estimate the final rainfall. Detailed validation with rain gauges and comparison with Tropical Rainfall Measuring Mission (TRMM) merged data product (3B42) are performed and it is found that the present technique is able to estimate the rainfall with better accuracy than the GPI technique over higher temporal and spatial domains for many operational applications in and around the Indian regions using Indian geostationary satellite data. Further comparison with the Doppler Weather Radar shows that the present technique is able to retrieve the rainfall with reasonably good accuracy.     

Global cloud water distribution derived from special sensor microwave imager/sounder and its comparison with GCM simulation

An SSM/I algorithm is developed for measuring cloud liquid water of raining and non-raining clouds. Cloud ice water corresponding to precipitation sized ice particles is obtained from the SSM/I scattering index which is calibrated against radar- derived ice water content. Smaller ice particles in upper level clouds are detected using scattering index based on SSM/T2 183±3 and 183±1 GHz channels which allow for removing water vapor emission. It is shown that SSM/I derived cloud liquid water distribution agrees well with GCM simulations, particularly in tropical latitudes.     

Potential of IRNSS/NavIC L5 signals for ionospheric studies

Indian Space Research Organization (ISRO) has developed an indigenous system named Indian Regional Navigation Satellite System (IRNSS) or NavIC (Navigation with Indian Constellation), that consists of 7 satellites and transmits navigation signal in L and S bands. ISRO, for validation of the system, has installed many IGS (IRNSS/GPS/SBAS) receivers scattered over the Indian region. Using preliminary data from two geographically widely separated stations over India, this paper presents the results on studies on parameters of IRNSS signal quality and discusses how these parameters may be used to study the ionospheric behavior over the Indian region. The results show the importance and advantages of using IRNSS data for such studies.     

Spatio-temporal variability of the wet component of the troposphere – Application to satellite altimetry

Due to the presence of water vapour and cloud liquid water in the atmosphere, the wet component of the troposphere is responsible for a delay in the propagation of the altimeter signals, the Wet Path Delay (WPD). The high space–time variability of the water vapour distribution makes the modelling of WPD difficult, its effect still being one of the main error sources in satellite altimetry applications, e.g. in the estimation of Mean Sea Level (MSL). The understanding and the quantification of the WPD variability on various spatial and temporal scales are the main purposes of this study, in view to improve the MSL error budget. The dominant timescales of WPD variability and its correlation with Sea Level Anomaly (SLA) are examined. In these analyses, the atmospheric reanalysis ERA-Interim model from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used to derive a global dataset of daily grids of WPD, spanning a 28-year period from January 1988 to December 2015. The Seasonal-Trend decomposition procedure based on Loess (STL) is used to extract precise WPD annual and interannual signals. Linear trends have been derived from the interannual time series and the contribution of each STL component was mapped globally, allowing the understanding of the WPD variability in spatial terms. The correlation between SLA and WPD is mapped and decomposed into seasons using monthly mean grids, for a period of 21-years, from January 1993 to December 2013.Aiming at inspecting the sensitivity of the results to the used data set, the WPD temporal analysis is extended to the data set provided by the Special Sensor Microwave Imager (SSM/I) and SSM/I Sounder (SSM/IS) Sensors. The WPD from SSM/I(S) is compared against those from the ERA-Interim and from the National Centers for Environmental Prediction (NCEP).Results show that climate phenomena, especially the El Niño Southern Oscillation (ENSO) are the cause for this high variability, since they affect the water vapour and temperature. The observed trends from ERA-Interim, computed globally and over ocean regions only, allow concluding that WPD is increasing with time by approximately 0.1?mm per year, and the maximum trends are observed for the Pacific North and Indian Oceans. High correlation between WPD and SLA is found over the western tropical Pacific.The comparison between WPD from SSM/I(S) and from ERA-Interim and NCEP, allows concluding that the trends computed using only the SSM/I(S) measurement points are substantially larger.     

An improved approach for rainfall estimation over Indian summer monsoon region using Kalpana-1 data

In this paper, an improved Kalpana-1 infrared (IR) based rainfall estimation algorithm, specific to Indian summer monsoon region is presented. This algorithm comprises of two parts: (i) development of Kalpana-1 IR based rainfall estimation algorithm with improvement for orographic warm rain underestimation generally suffered by IR based rainfall estimation methods and (ii) cooling index to take care of the growth and decay of clouds and thereby improving the precipitation estimation.     

Performance evaluation of some rain rate conversion models for microwave propagation studies

An important characteristic of rainfall levels at a particular place is the statistical distribution of rainfall rate. In this paper, 5-min integration time rainfall data for the Northcentral region of Nigeria was obtained from the Tropospheric Data Acquisition Network (TRODAN), Anyigba, Nigeria. Also, 1-min integration time rainfall was measured at Minna, Nigeria. In order to obtain the optimal rain rate model suitable for this region, two globally recognised rain rate models were critically evaluated and compared with the 1-min measurements. These are the ITU-R P.837-7 and Lavergnat-Gole (L-G) models. The results obtained showed that the ITU-R P.837-7 and L-G models respectively underestimated the measured rain rate by 7.3 mm/h and 9 mm/h at time percentage exceedance of 0.1%, while they underestimated the measured rain rate by 23.4 mm/h and 13 mm/h respectively at 0.01%. At 0.001%, the measured rain rate was overestimated by the ITU-R P.837-7 and L-G models by 27.4 mm/h and 3 mm/h respectively. Further performance evaluation of the predefined models was carried out using different error metrics such as sum of absolute error (SAE), mean absolute error (MAE), root mean square error (RMSE), standard deviation (STDEV) and Spearman’s rank correlation. The results obtained adjudged the Lavergnat-Gole model as the best rain rate prediction model for this region.     

Second order experimental statistics of rain attenuation at Ka band in a tropical location

Some second order rain attenuation statistics such as fade duration and fade slope are investigated on the basis of experimental measurements of received signals using the GSAT-14 satellite beacon signal at 20.2 GHz for three years (2014–2016) over the tropical location Ahmedabad (23.02 ⁰E, 72.51⁰N), India with an Elevation angle of 63⁰. Existing models of fade duration are compared with experimental data in this study and exponent of power law model of fade duration at Ka band is further explored. A new model for fade duration for Ka band for tropical locations is proposed where the constant of exponent of attenuation in the power law is found to be 0.143 instead of 0.055 used in ITU-R. Other relevant parameters for implementation of fade mitigation technique to prevent the link outage like cumulative distribution of signal fade rate, maximum and minimum fade rise and fade fall are also studied. Fade slope asymmetry over tropical region is also investigated. Keeping in view of exploiting the commercial launch of Ka band in Indian region there is an urgent need for validation of the existing models of fade slope (specially looking into fade symmetry) and fade duration. It will help the SATCOM (Satellite Communication) link designer to improve closed loop fade mitigation technique to minimize the possible link failure/link outage over the tropical region.     

Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.     

Ground validation of space-borne satellite rainfall products in Malaysia

Precipitation studies globally is not only important to hydrological cycling, but also very crucial to satellite and terrestrial communication system designs. This work presents the validation of ground based rainfall measurement with TRMM products and GPCC data. The result shows that an error bias of ±15 % exists between the ground and satellite rainfall measurements. The study also shows that the TRMM 3B43 V6 is in good agreement with the rain gauge rainfall measurement with highest and lowest correlation coefficient of 0.9721 and 0.7791 respectively. Therefore, TRMM 3B43 V6 is recommended for use in lieu of the ground measurement in Malaysia and its environs, most importantly for sea and remote areas where rain gauge cannot cover.     

气溶胶光学特性偏振遥感反演算法

陆地上空大气顶的辐射主要由大气散射和地表反射组成,一般地表反射的贡献要大于大气散射的贡献,使得陆地上空气溶胶的特性提取非常困难,而偏振信息只强烈依赖于散射粒子的特性,发展基于偏振信息的气溶胶反演方法是非常有效的. 通过对矢量辐射传输方程求解进行研究,基于倍加累加法矢量辐射传输模式分析影响气溶胶反演的主要因素,确定多维参数查找表建立方法,利用POLDER(Polarization and Directionality of the Earth-s Reflectances)提供的反射率和偏振反射率数据,发展了一种利用反射率和偏振反射率查找表迭代查找反演气溶胶光学参数和地表反射率的算法,实现了对北京、香河、Dalanzadgad观测站上空气溶胶光学厚度、粒子半径、折射指数和地表反射率的反演.用AERONET(Aerosol Robotic Network)地基数据对反演结果进行了验证.     

An empirical model for the variation of rain drop size distribution with rain rate at a few locations in southern India

A Joss–Waldvogel impact type disdrometer was installed at four different locations in the Indian peninsula during various periods from 2001 till date. The data are analysed to study the nature of rain drop size distribution (DSD) in this region. Out of the three well known distributions that describe DSD, namely, the Marshall–Palmer, Gamma and Lognormal, it has been found that Lognormal distribution fits the DSD in this region better than the other ones. Lognormal distributions for different rain rates were then derived by fitting the lognormal function to the data using a curve fitting software. Then the variation of fit parameters with rain rate was evaluated. Incorporating these variations, into the Lognormal distribution, an empirical equation that describes the DSD in this region for different rain rates was derived. Then this equation was tested with sample data from each of these stations. The data used for validation were not used for fitting lognormal equation to derive the fit parameters. The correlation between the DSD measured and derived using the empirical model was found to be quite good (0.9) except in some cases where the coefficient dropped to 0.75. The empirical model can be updated when more data are available.     

Optimum spectral bands for land cover discrimination

An experiment was undertaken to select the optimum spectral bands for the discrimination of land use/cover for proposed Indian Remote Sensing Satellite. A feature selection method was used for the discrimination analysis on the multiband data collected by Bendix 11-channel Modular Multiband Scanner over Tirupati test site of Chittoor district, Andhra Pradesh, South India. Of the various combinations of bands analysed, the optimum combination of four bands was defined as that one which provided the greatest divergence distances to discriminate the specific land covers in the test sites. On the basis of the above studies the optimum bands so chosen are 0.49–0.54 μm, 0.62–0.66 μm, 0.66–0.70 μm and 0.77–0.86 μm.     

Analysis of rain attenuation prediction models at Ku-band in Thailand

The performance of the existing rain attenuation models in tropical zones is still a debated issue due to the lack of measurements reported from these areas of the world to develop and validate prediction models. A three-year (2003–2005) campaign of rainfall rate and rain attenuation measurements was conducted on a satellite beacon link located in a tropical region of Thailand. The cumulative distributions of rain attenuation derived from the measured data are presented and compared with those obtained with existing prediction models.     

Total column water vapor estimation over land using radiometer data from SAC-D/Aquarius

The aim of this study is retrieving atmospheric total column water vapor (CWV) over land surfaces using a microwave radiometer (MWR) onboard the Scientific Argentine Satellite (SAC-D/Aquarius). To research this goal, a statistical algorithm is used for the purpose of filtering the study region according to the climate type.A log-linear relationship between the brightness temperatures of the MWR and CWV obtained from Global Navigation Satellite System (GNSS) measurements was used. In this statistical algorithm, the retrieved CWV is derived from the Argentinian radiometer’s brightness temperature which works at 23.8?GHz and 36.5?GHz, and taking into account CWVs observed from GNSS stations belonging to a region sharing the same climate type. We support this idea, having found a systematic effect when applying the algorithm; it was generated for one region using the previously mentioned criteria, however, it should be applied to additional regions, especially those with other climate types.The region we analyzed is in the Southeastern United States of America, where the climate type is Cfa (Köppen - Geiger classification); this climate type includes moist subtropical mid-latitude climates, with hot, muggy summers and frequent thunderstorms. However, MWR only contains measurements taken from over ocean surfaces; therefore the determination of water vapor over land is an important contribution to extend the use of the SAC-D/Aquarius radiometer measurements beyond the ocean surface. The CWVs computed by our algorithm are compared against radiosonde CWV observations and show a bias of about ?0.6?mm, a root mean square (rms) of about 6?mm and a correlation of 0.89.     

Investigation of vertical profile of rain microstructure at Ahmedabad in Indian tropical region

The microstructure of rain has been studied with observations using a vertical looking Micro Rain Radar (MRR) at Ahmedabad (23.06°N, 72.62°E), a tropical location in the Indian region. The rain height, derived from the bright band signature of melting layer of radar reflectivity profile, is found to be variable between the heights 4600 m and 5200 m. The change in the nature of rain, classified on the basis of radar reflectivity, is also observed through the MRR. It has been found that there are three types of rain, namely, convective, mixed and stratiform rain, prevailing with different vertical rain microstructures, such as, Drop Size Distribution (DSD), mean drop size, rain rate, liquid water content and average fall speed of the drops at different heights. It is observed that the vertical DSD profile is more inhomogeneous for mixed and stratiform type rain than for convective type rain. It is also found that the large number of drops of size <0.5 mm is present in convective rain whereas in stratiform rain, drops concentration is appreciable up to 1 mm. A comparison of measurements taken by ground based Disdrometer and that from the 200 m level obtained from MRR shows good agreement for rain rate and DSD at smaller rain rate values. The results may be useful for understanding rain structures over this region.     

海表温度对中法海洋卫星散射计测量的影响

卫星散射计通过测量海表粗糙度反演全球海面风场。对于Ku波段散射计,海表粗糙不仅和海面风场相关,还受海表温度的二阶效应调制。定量研究了海表温度对中法海洋卫星（CFOSAT）散射计（CSCAT）反演风速和后向散射测量的影响。结果表明,CSCAT两种极化方式测量的后向散射系数都会受到海表温度的影响,但是垂直极化中低入射角（θ <36°）测量的后向散射系数几乎不随温度变化。因此CSCAT的风速偏差也随海表温度的变化而变化,且随着入射角的增大和风速的减小,海表温度对风速偏差的影响程度增大。在数据分析的基础上提出了一种考虑海表温度影响机制的地球物理模式函数,为未来CFOSAT散射计风场反演的海温校正提供参考。     

Rainfall estimation over a Mediterranean region using a method based on various spectral parameters of SEVIRI-MSG

The ultimate objective of this paper is the estimation of rainfall over an area in Algeria using data from the SEVIRI radiometer (Spinning Enhanced Visible and Infrared Imager). To achieve this aim, we use a new Convective/Stratiform Rain Area Delineation Technique (CS-RADT). The satellite rainfall retrieval technique is based on various spectral parameters of SEVIRI that express microphysical and optical cloud properties. It uses a multispectral thresholding technique to distinguish between stratiform and convective clouds. This technique (CS-RADT) is applied to the complex situation of the Mediterranean climate of this region. The tests have been conducted during the rainy seasons of 2006/2007 and 2010/2011 where stratiform and convective precipitation is recorded. The developed scheme (CS-RADT) is calibrated by instantaneous meteorological radar data to determine thresholds, and then rain rates are assigned to each cloud type by using radar and rain gauge data. These calibration data are collocated with SEVIRI data in time and space.     

Future U.S. ocean color missions—OCI,MODIS and HIRIS

The Coastal Zone Color Scanner (CZCS) launched by the National Aeronautics and Space Administration (NASA) on the Nimbus-7 Satellite in 1978 has provided exceptionally valuable data for studies of the productivity of the ocean, fisheries, the detection of oceanic fronts and currents, and the optical properties of the ocean. NASA has been working with the scientific community, the National Oceanographic and Atmospheric Administration (NOAA), France's Centre National d'Etudes Spatiales (CNES), and industry to develop an Ocean Color Imager (OCI), a follow-on instrument which would provide the near real-time and global data necessary to fill these needs in the 1990's. The Earth Observing Satellite Company (EOSAT) is considering flying an ocean and land wide-field color instrument which would meet these needs on Landsat 6 or 7 planned for launch in 1989 and 1991, respectively. It would provide eight ocean color channels for improved atmospheric correction and in-water algorithms, global coverage and near real-time data for operational uses. In the mid 1990's NASA is planning to fly a Moderate Resolution Imaging Spectrometer (MODIS) and a High Resolution Imaging Spectrometer (HIRIS) as part of the Earth Observing System (Eos) on the Polar Platform of the Space Station. These instruments are array spectrometers which would provide full spectral resolution in the visible and infrared. This opens the possibility of separating different groups of phytoplankton, suspended sediments and other substances in the water. Also, HIRIS would have across track pointing ability which will allow high resolution rapid sampling of dynamic coastal areas and estuaries.     

Impact of four dimensional assimilation of satellite data on long-range simulations over the Indian region during monsoon 2006

A number of experiments were conducted to study the impact of updating model basic fields by satellite data (Quick Scatterometer (QSCAT) surface winds and Atmospheric Infrared Sounder (AIRS) temperature and humidity profiles) on long-range simulation during the Indian summer monsoon 2006. The Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) mesoscale model version5 (MM5) and its four dimensional data assimilation (FDDA) technique was used for the numerical simulations. The spatial distribution and temporal variation in model simulated basic meteorological parameters and rainfall were verified against the observed fields from National Center for Environmental Prediction (NCEP) analysis and Tropical Rainfall Measuring Mission (TRMM), respectively. The overall analysis of the results from QSCAT surface wind assimilation as compared to control simulation (CNT; without the satellite data assimilation) suggest that a better representation of a single level wind field during model integration fail to make significant improvement in the model simulation both in the basic meteorological parameters and rainfall. The assimilation of temperature and humidity profiles from the AIRS during model integration significantly improved the rainfall prediction during monsoon period. It is found that the improvement in rainfall prediction is attributed to improved thermodynamics structure due to AIRS profile assimilation and the degree of improvement is more in temperature prediction as compared to humidity prediction. It is also found that the prediction over the regions, such as south west part of India and foothills of Himalaya, where a complex orography exists, is not significantly benefited from satellite data assimilation which highlights the need of improvement in the model in addition to a better representation of atmospheric state.