Simulation of the Ku-band Radar altimeter sea ice effective scattering surface

A radiative transfer model is used to simulate the sea ice radar altimeter effective scattering surface variability as a function of snow depth and density. Under dry snow conditions without layering these are the primary snow parameters affecting the scattering surface variability. The model is initialized with in situ data collected during the May 2004 GreenIce ice camp in the Lincoln Sea (73/spl deg/W; 85/spl deg/N). Our results show that the snow cover is important for the effective scattering surface depth in sea ice and thus for the range measurement, ice freeboard, and ice thickness estimation.     

High-resolution airborne infrared measurements of ocean skin temperature

Airborne measurements of ocean skin temperature T/sub s/ are presented from the Coupled Boundary Layers, Air-Sea Transfer in Low Winds (CBLAST-Low) Pilot Experiment in August 2001 off Martha's Vineyard, MA. We used an infrared (IR) camera with a spatial resolution of 1 m or less and temperature resolution of roughly 0.02/spl deg/C. Using subframe sampling of the IR imagery, we achieve lower noise and higher spatial resolution than reported by previous investigators using IR radiometers. Fine-scale maps of T/sub s/ exhibit horizontal variability over spatial scales ranging from O(10 km) down to O(1 m) that are related to atmospheric and subsurface phenomena under low to moderate wind conditions. Based on supporting measurements of wind and waves, we identify coherent ramp-like structures in T/sub s/ with stratification breakdown and meandering streaky features with internal waves. Regional maps of T/sub s/ show the standard deviation for the region is /spl plusmn/1.04/spl deg/C, while the meridional and zonal variability is 0.23/spl deg/C /spl middot/ km/sup -1/ and 0.27/spl deg/C /spl middot/ km/sup -1/, respectively. This temperature variability results in meridional and zonal scalar heat flux variability of 7.0 W /spl middot/ m/sup -2/ /spl middot/ km/sup -1/ and 7.6 W /spl middot/ m/sup -2/ /spl middot/ km/sup -1/, respectively. Our results demonstrate the potential for airborne IR imagery accompanied by high-quality ocean data to identify T/sub s/ features produced by subsurface circulation.     

Assessment of Kalpana-1 Rainfall Product over Indian Meteorological Sub-Divisions During the Summer Monsoon Season

In this paper, Kalpana-1 derived INSAT Multispectral Rainfall Algorithm (IMSRA) rainfall estimates are compared with two multisatellite rainfall products namely, TRMM Multisatellite Precipitation Analysis (TMPA)-3B42 and Global Satellite Mapping of Precipitation (GSMaP), and India Meteorological Department (IMD) surface rain gauge (SRG)-based rainfall at meteorological sub-divisional scale over India. The performance of the summer monsoon rainfall of 2013 over Indian meteorological sub-divisions is assessed at different temporal scales. Comparison of daily accumulated rainfall over India from IMSRA shows a linear correlation of 0.72 with TMPA-3B42 and 0.70 with GSMaP estimates. IMSRA is capable to pick up daily rainfall variability over the monsoon trough region as compared to TMPA-3B42 and GSMaP products, but underestimates moderate to heavy rainfall events. Satellite-derived rainfall maps at meteorological sub-divisional scales are in reasonably good agreement with IMD-SRG based rainfall maps with some exceptions. However, IMSRA performs better than GSMaP product at meteorological sub-divisional scale and comparable with TMPA data. All the satellite-derived rainfall products underestimate orographic rainfall along the west coast, the Himalayan foothills and over the northeast India and overestimate rainfall over the southeast peninsular India. Overall results suggest that IMSRA estimates have potential for monsoon rainfall monitoring over the Indian meteorological sub-divisions and can be used for various hydro-meteorological applications.     

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.     

Hydrological modelling of a small watershed using satellite data and gis technique

A distributed parameter model Soil and Water Assessment Tool (SWAT) has been tested on daily and monthly basis for estimating surface runoff and sediment yield from a small watershed “Chhokeranala” in eastern India using satellite data and Geographical Information System (GIS). Several maps like watershed and sub-watershed boundaries, drainage network, landuse/cover and soil texture have been generated. The SWAT model has been verified for the initial phase of monsoon season in the year 2002 using daily rainfall and air temperature. Performance of the model has been also evaluated to simulate the surface runoff and sediment yield on sub-watershed basis for two months (July-August 2002). The results show a good agreement between observed and simulated runoff and sediment yield during the study period. Capability of the model for generating rainfall has been evaluated for 10 years (1992 - 2001) period. The model simulated daily rainfall shows close agreement with the observed rainfall. The present results show that the SWAT model can be used for satisfactory simulation of daily and monthly rainfall, runoff and sediment yield.     

Potential to estimate the canting angle of tilted structures in clouds from microwave radiances around 183 GHz

The effects of cloud structures on microwave radiances at frequencies from 89-190 GHz are investigated by simulations using the Goddard cumulus ensemble model data as input for a radiative transfer model. It was found that the brightness temperatures at these frequencies have different sensitivities to clouds with a tilted structure. The different sensitivities to altitude and amount of hydrometeors allow the estimation of the canting angle and tilt direction of tilted clouds using brightness temperatures at the water vapor channels at 183.3 /spl plusmn/ 1 and 183.3 /spl plusmn/ 7 GHz. The estimated canting angle and tilt direction are in agreement with the model situation. This method provides a potential to estimate tilted convective structures from microwave radiometric observations at 183.3 /spl plusmn/ 1 and 183.3 /spl plusmn/ 7 GHz. It is applied to a tilted storm observed from the National Aeronautics and Space Administration's ER-2 aircraft flying at about 20 km on August 26, 1998 during the third Convection and Moisture Experiment using the observed downlooking brightness temperatures at the water vapor channels of a Millimeter-wave Imaging Radiometer. The estimated results are in good agreement with the realistic storm situation obtained from the simultaneous observations of the ER-2 Doppler radar. This method also provides information about the vertical displacement of cloud structure and thereby to estimate the accurate location of surface rainfall. This is important when validating precipitation retrieval based on observations of the ice scattering above surface rainfall against surface rain observations using the microwave frequencies sensitive to high altitudes.     

Effect of raindrop size distribution variability in dual-frequency radar rain retrieval algorithms assessed from disdrometer measurements

The effect of natural variation of raindrop size distribution (DSD)on the retrieval of rainfall rate from the dual-frequency (13.6/35.5 GHz,as will be in the Global Precipitation Measurement Mission) Precipitation Radar (DPR) measurements is studied by utilizing a large set of disdrometer-measured DSD data through a simple simulation framework. A DPR inversion technique(DPR-IT) that focuses on the retrieval of DSD information from the non-Rayleigh backscattering characteristic of the hydrometeors and a conventional DPR technique(DPR-CT) that focuses on the independent retrieval of rainfall rate from the attenuation measurement are considered in this analysis. The preliminary results show that at different rainfall rate regions these methods have different responses to the DSD variability. For instance, it appears that DPR-IT suffers relatively less from the DSD variability in the regions of weak to moderate rainfall rate (/spl bsol/ mm /spl middot/ h/sup -1/),while in the strong rainfall rate (>/spl sim/10 mm /spl middot/ h/sup -1/) region the DPR-CT generally has less sensitivity to DSD variations than the DPR-IT.     

Use of high-resolution satellite data,GIS and NRCS-CN technique for the estimation of rainfall-induced run-off in small catchment of Jharkhand India

The present study demonstrates the use of NRCS-CN technique for rainfall-induced run-off estimation using high-resolution satellite data for small watershed of Palamu district, Jharkhand. The CN model was applied to the daily rainfall data of 15 years (1986–2000) along with use of large-scale thematic maps (1:10,000) pertaining to land use/land cover using IRS-P6 LISS-IV satellite data. The LU/LC map was spatially intersected with the hydrological soil group map to calculate the watershed area under different hydrological similar units for assigning CN values to compute discharge. The study showed that Daltonganj watershed exhibits an average run-off volume of 7,881,019 m³ from an average cumulative monsoon rainfall of 821 mm and the average actual direct run-off generated during the southwest monsoon season was 203 mm. The strong correlation between rainfall and run-off as well as between observed run-off and estimated run-off indicated high accuracy of run-off estimation by NRCS-CN technique.     

Automatic P phase picking using maximum kurtosis and /spl kappa/-statistics criteria

The identification problem of P seismic phase onset has been addressed, based on the maximum-kurtosis assumption, /spl kappa/-statistics, and the Chebyshev inequality. Depending on two statistical decision criteria, the proposed approach provides either a single P onset peak or an interval in which the P onset exists, both with a confidence percentage. Results on real seismic data evaluated using a performance index justify the contribution of the proposed method toward an accurate and fully automated P onset identification.     

Validations of suspended sediment concentration (ssc) derived using ocean colour monitor (ocm) data off Chennai coast, India

Indian Remote Sensing Satellite (IRS) — P4 Ocean Colour Monitor (OCM) data were used to estimate Suspended Sediment Concentration (SSC) in the coastal waters off Chennai and to study the distribution along the coast. Surface water samples were collected during May and October 2000 synchronized with satellite overpass, and quantitative estimates of Suspended Sediment Concentration (SSC) were done. OCM — Data Analysis System (DAS) software developed by the Space Applications Centre, Ahmedabad was used for OCM data processing and analysis. The field data and OCM derived SSC showed a correlation of r = 0.85 and r = 0.95 for the months of May and October respectively.     

Soil moisture retrievals from biangular L-band passive microwave observations

A simple approach for correcting the effect of vegetation in the estimation of soil moisture (w/sub S/) from L-band passive microwave observations is presented in this study. The approach is based on statistical relationships, calibrated from simulated datasets, which requires only two observations made at distinct incidence angles (/spl theta//sub 1/,/spl theta//sub 2/). A sensitivity study was carried out, and best retrieval remote sensing configurations, in terms of polarization and couple of incidence angles (/spl theta//sub 1/,/spl theta//sub 2/), were investigated. Best estimations of w/sub S/ could be made at H polarization, for /spl theta//sub 1/ varying between 15/spl deg/ and 30/spl deg/, and with a difference (/spl theta//sub 2/-/spl theta//sub 1/) larger than 30/spl deg/. The method was tested against two experimental datasets acquired over crop fields (soybean and wheat). The average accuracy in the soil moisture retrievals during the whole crop cycle was found to be about 0.05 m/sup 3//m/sup 3/ for both crops.     

Analyzing the impact of thermal stress on vegetation health and agricultural drought – a case study from Gujarat,India

Although poor precipitation due to delayed arrival and/or early retreat of the southwest monsoon is considered the chief architect of drought in India, heat waves may also play a crucial role in the intensification of droughts. In the Indian subcontinent, occurrence of heat waves during the pre-monsoon and high air-temperature in the subsequent monsoon season imparts thermal stress on vegetation causing degradation of vegetation health (VH). In the present study, various vegetation indices and land-use/land-cover data derived from multi-sensor satellite have been used to assess VH and agricultural drought in Gujarat during 1981–2010. This Geographical Information Systems-based study has also used heat wave and temperature data to analyze the adverse effects of high temperature on VH. The time series of Vegetation Condition Index and Temperature Condition Index (TCI) has shown that the combined influence of moisture-stress and thermal stress determines the occurrence and severity of drought, which is reflected in the Vegetation Health Index (VHI). A strong correlation among aboveground air-temperature, the TCI and the VHI indicates definite influence of thermal stress on VH. Further, a systematic variation and strong resemblance between temperature, crop yield, TCI and VHI has established the impact of thermal stress on agricultural productivity.     

A hierarchical model for estimating methane emission from wetlands using MODIS data and ARIMA modeling

A three-step hierarchical Semi Automated Empirical Methane Emission Model (SEMEM) has been used to estimate methane emission from wetlands and waterlogged areas in India using Moderate Resolution Imagine Spectroradiometer (MODIS) sensor data onboard Terra satellite. Wetland Surface Temperature (WST), methane emission fluxes and wetland extent have been incorporated as parameters in order to model the methane emission. Analysis of monthly MODIS data covering the whole of India from November 2004 to April 2006 was carried out and monthly methane emissions have been estimated. Interpolation techniques were adopted to fill the data gaps due to cloudy conditions during the monsoon period. AutoRegressive Integrated Moving Average (ARIMA) model has been fitted to estimate the emitted methane for the months of May 2006 to August 2006 using SPSS software.     

Remote Sensing of suspended sediments along the Tamil Nadu coastal waters

Indian Remote Sensing satellite (IRS) 1A & 1B digital data in combination with field measurement were used to map distribution and concentration of suspended sediments along the Tamil Nadu coastal waters for monsoon and non-monsoon periods. Qualitative suspended sediment mapping was done for entire Tamil Nadu coast while quantitative studies were taken at two selected sites (eg. Tuticorin and Ennore). For qualitative mapping both monsoon (17-12-90) and non-monsoon (18-4-90) season data were analysed by level slicing technique and a qualitative scale was assigned to different sediment classes based on tonal variations. The suspended sediment concentration (SSC) samples were collected on April 15, 1992 and March 10, 1992 around Ennore and Tuticorin coastal waters respectively, synchronous to IRS-1A satellite overpass. This data was used for quantitative estimation of SSC using digital chromaticity technique. The study shows that the plumes of high suspended sediment concentration are contributed from the nearshore wetlands and river mouths and were finally dispersing towards Jaffna coast. Different classes of high to low SSC values ranging from less than 5 mg/L in offshore areas to 21 mg/L in nearshore of Tuticorin were also delineated. The dispersal pattern of the sediments on different is discussed.     

Simultaneous measurements of ku- and ka-band sea surface cross sections by an airborne Radar

The dual-frequency Airborne Precipitation Radar-2 (APR-2) was deployed during the Wakasa Bay Experiment in 2003, for validation of the Advanced Microwave Scanning Radiometer-EOS. Besides providing extensive observations of diverse precipitating systems, this Ku-(13.4 GHz) and Ka-band (35.6 GHz) cross-track scanning radar measured sea surface backscatter simultaneously. While the characteristics of the normalized sea surface cross section /spl sigma//sup 0/ at Ku-band are well understood and widely published, the existing experimental data concerning /spl sigma//sup 0/ at Ka-band are scarce and results are inconsistent. In this letter, the Ku/Ka-band /spl sigma//sup 0/ measurements collected by APR-2, together with the estimated uncertainties, are discussed. In general, the measured /spl sigma//sup 0/ at Ka-band at around 10/spl deg/ incidence angle appears to be close to that at Ku-band /spl sigma//sup 0/, and Ka-band exhibits a nonnegligible difference in wind dependence with respect to Ku-band for moderate to high winds.     

Characterization and quantification of data voids in the shuttle Radar topography mission data

The goal of this study was to characterize and quantify the occurrence of data voids in data from the Shuttle Radar Topography Mission (SRTM) for the conterminous United States. For this purpose, SRTM data and corresponding data from the national elevation data were downloaded in 21 samples spatially organized to cover the main topography of the U.S. Void locations in SRTM data were compared to terrain attributes and subsequently the area of individual data voids to the same attributes. It was found that data voids amounted to 0.3% of the total dataset. Data voids were found in all topographic settings but more often in slopes steeper than approximately 20/spl deg/ that face south (170/spl deg/), and also in flat areas such as lakes and rivers. It was also found that more than 50% of all data voids were composed of connected pixels in groups less than six pixels. The largest data voids could be attributed to water bodies, while the rest could be explained by terrain-radar interaction characteristics.     

Operational feasibility of neural-network-based radar rainfall estimation

An operational radar rainfall estimation system based on the adaptive radial basis function (RBF) neural network is developed. During the process of training and cross validation, the rainfall estimation was computed only at the gauge locations. Once the training is done, the radar rainfall estimation based on neural networks is applied to the full coverage area of the radar. Such large-scale application of the rainfall estimate poses several questions in the context of operational applications. This letter addresses two of those questions, namely: 1) the feasibility of adaptively updating RBF neural network models on a daily basis and 2) the ability of neural network radar rainfall estimation at high spatial resolution within reasonable and practical time frame for operational applications. Using the datasets collected by WSR-88D radar located in Melbourne, FL, it is demonstrated that radar-based rainfall estimation using an adaptive RBF neural network is feasible. The results show that 73% of overnight updating for the RBF neural network can be completed within 2 h, and the estimation over an area of 100 km/spl times/100 km can be generated within the time frame (a few tens of seconds-150 s), which is much smaller than the average radar volume scan time.     

1979年—2019年兴凯湖湖冰物候变化的被动微波遥感监测

季节性冻结与消融的湖冰是气候变化的重要指示器。本文以兴凯湖为例,基于1979年—2019年的被动微波遥感数据获取了兴凯湖的冻融日期,用2000年—2019年的中等分辨率成像光谱仪MODIS(Moderate-resolution Imaging Spectroradiometer)数据进行了验证,并用气候数据分析了湖冰物候变化的原因。结果表明被动微波与MODIS遥感数据在湖冰物候提取方面具有较好的一致性,也即MODIS的验证结果表明用低频被动微波亮度温度数据获取湖冰物候的方法是可行的,结果也是可靠的。平均而言,兴凯湖湖冰每年11-13左右开始冻结,11-23左右完全冻结,湖冰冻结持续时间9.80 d;次年04-23左右湖冰开始消融,04-30左右湖冰完全消融,消融持续时间8.03 d;湖冰完全封冻时间150.50 d,湖冰覆盖时间168.03 d。过去41 a,兴凯湖开始冻结日期没有明显变化,完全冻结日期平均推后了0.19 d/a,开始消融日期和完全消融日期分别提前了0.16 d/a和0.13 d/a,湖泊完全封冻时间和湖冰覆盖时间分别缩短了12.71 d和2.87 d。湖冰冻结日期推后与风速增大密切相关,消融日期提前和湖冰持续时间缩短与气温升高显著相关。     

Detecting Drought-Prone Areas of Rice Agriculture Using a MODIS-Derived Soil Moisture Index

This study examined the use of remote sensing in detecting and assessing drought in Iloilo Province, Philippines. A remote sensing-based soil moisture index (SMI), rainfall anomaly data from the Tropical Rainfall Measuring Mission (TRMM), and rice production departure (P_d ) data were used for drought detection and validation. The study was conducted using two drought years (2001, 2005) and one non-drought year (2002). According to SMI data, the drought distribution was classified into four major groups. SMI values > 0.3 were considered not to be drought and SMI values ≤ 0.3 were classified as slight, moderate, and severe drought. Results based on SMI revealed that the study area experienced drought in 2001 and 2005, while 2002 exhibited no drought. On the other hand, TRMM-based rainfall anomaly data revealed negative values in 2001 and 2005 and positive values in 2002. Below-normal P_d values were observed in 2005 and above-normal values in 2002, whereas nearly normal values prevailed in 2001. Yield indicator data were crucial for the assessment of drought impacts on rice production. In most cases, the pattern of rice production and productivity revealed that the decline in the production or productivity of rice for a particular year coincided with lower SMI values and greater rainfall departure or negative anomaly.     

GPS反演的可降水量与降水的对比分析研究

本文以秦皇岛为例,分析GPS可降水量与降水实况的关系。2007年5月~8月期间发生16次降水过程,每次水汽的增加,都对应着一次降水过程和降水峰值的出现;16次降水事件中,GPS可降水量序列峰值超前降水发生时间1h和2h分别各为6次,两者占到总降水次数的75%,也就是说GPS可降水量序列峰值超前降水发生时间约为1~2h;降水出现的时间一般发生在大气可降水量迅速增加之后,在2h或3h的大气可降水量的增幅迅速增加达到5mm后,2h内出现降水占68.75%,3~4h出现降水占18.75%,5~6 h出现降水占6.25%;而大气可降水量迅速增加前2h内出现降水的仅占6.25%,即GPS可降水量迅速增加后4h内出现降水的比率占到87.5%。GPS可降水量可作为降水短期预报的指标之一。