Eric C. Barrett

Algorithms for the Retrieval of Rainfall from Passive Microwave Measurements.

The retrieval of rainfall intensity from radiances measured by spaceborne microwave radiometers can be understood in terms of well established physics. At frequencies below about 40 GHz over an ocean background the relationship between the rainfall and the observations is particularly well understood. In this part of the spectrum, the radiances are principally determined by the liquid hydrometeors with only a modest amount of ambiguity. In very intense convection, ice aloft may increase this ambiguity somewhat. At high frequencies, such as the 85.5 GHz channel of the SSM/I, scattering by the frozen hydrometeors becomes more significant and quantitative rainfall retrieval becomes more problematic. In spite of the ambiguities, the use of the higher frequencies is desirable on a number of counts including: applicability over land, spatial resolution and dynamic range. A total of 16 algorithms were submitted for the PIP‐1. These include algorithms that are based on high frequency (scattering) measurements and low frequency (emission) measurements with a few combinations and variations on these themes. The calibration of the algorithms varies from mostly empirical to essentially first principles with most falling somewhere in‐between. All of the algorithms retrieved rainfall and one also retrieved a profile of the liquid and frozen hydrometeors.

Satellite Identification of Rain Days over the Upper Nile River Basin Using an Optimum Infrared Rain/No-Rain Threshold Temperature Model

Abstract As part of the U.S. Agency for International Development/National Oceanic and Atmospheric Administration project to develop an improved monitoring, forecasting, and simulation system for the river Nile, the Remote Sensing Unit of the University of Bristol has been investigating and developing satellite infrared techniques for small-scale estimation of rainfall over the region of the upper Nile basin. In this paper, the need for variable IR rain/no-rain temperature thresholds as a basis for reliable satellite identification of rain areas over small scales is explained, and the spatially and temporally variable nature of optimum IR rain/no-rain threshold temperatures is examined. Meteosat IR data covering a period of 17 months have been analyzed along with daily rain gauge reports for calibration and validation. Analyses have been carried out on a monthly basis. Optimum IR rain/no rain threshold temperatures over the study area in the east Africa region are shown to have exhibited a marked seasonal...

Estimation of daily rainfall over the upper Nile river basin using a continuously calibrated satellite infrared technique

A continuously calibrated infrared (IR) geostationary satellite rainfall estimation technique (CCB4) is introduced, in the context of the Nile River Forecast System, an operational system for hydrological modelling and forecasting. The CCB4 incorporates near-real-time rain gauge data to continuously calibrate optimum IR rain/no-rain thresholds and daily rain rates on a daily time step. The ability of the CCB4 and two comparative techniques to estimate daily rainfall at the regional and pixel scales is assessed, using Meteosat IR imagery and gauge data from six wet season months covering three years. The CCB4 shows improved skill in identifying rain days and estimating daily rain amounts at a range of spatial scales, from regional to pixel scales. At the pixel scale, however, improved root mean square errors remain relatively high, ranging between 66% and 84% of the mean unconditional rain rate. Copyright

Toward an Objective Nephanalysis

Abstract A method is presented for the automatic construction of a cloud-type and cloud-amount nephanalysis. The uses to which such a nephanalysis could be put are first considered, and then a combination of brightness and texture measurements is used to characterize cloud types on DMSP satellite imagery. Texture is evaluated by measuring the standard deviation and vector dispersion of the density values within small window areas of the whole satellite picture, and then by a discriminant analysis scheme window areas are allocated to one of three cloud categories and a no-cloud category. The automatic nephanalysis is constructed by analyzing all the adjacent window areas on the image. The results of the analysis of visible and infrared images show accuracies of greater than 72% for each automatic nephanalysis. Finally, the use of multispectral cloud image analysis is considered in contrast to the unispectral brightness and texture approach.

Retrieval of land and sea brightness temperatures from mixed coastal pixels in passive microwave data

A technique is presented to separate uncontaminated land and sea brightness temperatures from mixed coastal pixels in 37-GHz vertically polarized passive microwave data from the Special Sensor Microwave Imager (SSM/I) instrument. Combining a mathematical model of the instrument response over several neighboring footprints with a GIS representation of the coastline yields a relationship between land and sea brightness temperatures and radiation measurements made at the satellite. Inverting this relationship allows separate land and sea brightness temperature values to be derived for each mixed coastal pixel in the original image. The technique has been successfully applied to 37-GHz vertically polarized SSM/I imagery for test areas covering the Gulf of Aden and the British Isles. Errors in the retrieved brightness temperatures were estimated to be of the order of 1-2 K.

A new instrument with rainfall monitoring potential

Abstract The new Special Sensor Microwave Imager (SSM/I) is introduced, and its global data acquisition pattern illustrated. Through an image for the morning of 29 July 1987 covering north-western Europe in general, and southern Britain in particular, its rainfall monitoring potential is illustrated and explained. An initial comparison with digital outputs from the FRONTIERS radar system of the U.K. Meteorological Office is presented, revealing very promising spatial correspondences between SSM/I and radar-derived rain areas.

A statistical modelling approach to passive microwave rainfall retrieval

Abstract A new empirical algorithm for retrieving rainfall rates from passive microwave (particularly Special Sensor Microwave/Imager) data is presented. Errors caused by spatial and temporal variation of surface temperature, emissivity, and atmospheric effects are minimized by modeling the nonraining brightness temperatures within 0.5° latitude by 0.5° longitude regions based on the statistics of the satellite data from the whole of the month prior to the date of interest. Displacement of data away from the modeled relationship by more than a threshold value, calculated from the standard deviation of the nonraining data, is detected as rainfall. The algorithm is able to detect rainfall over land, sea, and coasts. An initial calibration and validation is performed using data from WetNet Precipitation Intercomparison Project 2 over the British Isles. To overcome collocation errors during calibration and validation, techniques are presented for matching radar rain pixels with appropriate satellite data. The...

Sea-ice type classification from ERS-1 SAR data based on grey level and texture information

This paper describes the development of a practical algorithm for the classification of sea-ice types from ERS-1 synthetic aperture radar (SAR) data. The algorithm was based on a combination of grey level and texture information in order to overcome ambiguous grey level values of different ice types. The problem of calculating texture parameters for windows containing more than one ice type was overcome by first segmenting the image so that only pixels from the same segment were included in the calculation of the texture measure. The segmentation procedure was based on the iterative application of a speckle noise reduction filter, and was thus crucially dependent on the ability of such a filter to smooth out noise without destroying edges and fine features. In order to achieve this, a modification to the sigma filter of Lee (1983b) was developed; it out-performed the sigma filter for a model problem. Two ERS-1 SAR scenes of the marginal ice zone east of Spitsbergen in March 1992 were analysed by calculating values of grey level and range for different ice types contained within raw data extracts. Although the grey levels of some of the ice types overlapped, most of the ambiguity was removed through the additional use of range. It was also necessary to test for the wave-like appearance of open water. The classification scheme was demonstrated to identify correctly most of the grease/new ice, first-year ice, multiyear ice, rough ice, pancake ice, and open water in the two SAR scenes, although there was some misclassification of open water as first-year ice.

Potentialities and problems of satellite remote sensing with special reference to arid and semiarid regions

Although satellite remote sensing of the atmosphere and Earths surface has been pursued now for many years, it has not been applied widely in detailed or systematic investigations of the atmospheric and land surface climates of arid and semiarid regions. This paper briefly surveys characteristics of satellite systems that should be considered when evaluating the present and potential roles of satellite remote sensing in arid and semiarid zone research, and in studies of desertification. Actual and potential applications of satellite data in these research areas are then reviewed. It is concluded that satellite data available for arid and semiarid areas have been used in a very fragmentary and unsystematic manner. Proposals are made for exploiting more fully satellite data, especially in investigations of desertification.

Microwave monitoring of rainfall: Intercomparisons of data from the Chilbolton radar and the DMSP‐SSM/I

Ground-based multi-parameter radar is used to validate and evaluate satellite passive microwave parameters related to rainfall over land. Light precipitation over the southern part of England is considered. The issues of diverse resolutions of radar and satellite data in space and time are investigated, as well as the satellite beam-filling problem, in relation to present passive microwave satellite algorithms related to rainfall over land, and their perceived behaviour. Several statistical analyses are applied and their sensitivities to data integration problems are quantified. Passive microwave parameters are evaluated and compared with each other. It is concluded that for radar passive microwave satellite data intercomparisons, calibrations and validations the time resolution seems to be more important than the spatial resolution, and high-resolution radar can be used operationally to tackle the satellite beam-filling problem. It is found that several passive microwave algorithms have performances very similar to each other. Copyright