Rain Estimation Techniques Research Articles

Utilization of the AMSU high frequency measurements for improved coastal rain retrievals

This study describes a new rain estimation technique using Advanced Microwave Sounding Unit (AMSU) high frequency measurements and applicable over coastal regions. The existing operational AMSU rain retrieval algorithm utilizes the microwave window frequency measurements at 23, 31, 89 and 150 GHz. These measurements have limited applicability over coast due to ocean surface emissivity effects. This situation often leads to missing rain extent and thus rate retrievals over coastal regions. The new technique utilizes the higher window (89 and 150 GHz), opaque oxygen (53.6 GHz) and water vapor absorption (183 ± 1, ±3 and ±7 GHz) channels that are less impacted by surface emissivity variations. Rain extent is determined using a number of scattering measures computed from linear combinations of the brightness temperature at the selected high frequency channels. Next, the ice water path parameter is estimated from a quadratic relationship with the brightness temperature at the 183 ± 7 GHz water vapor absorption channel and the cosine of the local zenith angle. Rain rate is computed from ice water path. Evaluation and monitoring of the new technique integrated with the existing algorithm has indicated that the upgraded algorithm is robust and superior to the existing one over coast.

Overview of Overland Satellite Rainfall Estimation for Hydro-Meteorological Applications

This paper reviews current techniques on rainfall estimation from satellite sensor observations. The sensors considered in this study are the Precipitation Radar (PR) and radiometer (TMI) onboard TRMM (Tropical Rainfall Measuring Missio) satellite, the Special Sensor Microwave/Imager (SSM/I) onboard Defense Meteorological Satellite Program (DMSP) platforms, and infrared (IR) sensors onboard geostationary satellites. We present the physical basis and mathematical formulation of a newly developed combined radar-radiometer (PR/TMI) retrieval for TRMM and its application for overland rain estimation. Subsequently we discuss the current state-of-the-art in overland passive microwave (TMI and SSM/I) rain estimation techniques, and outstanding issues associated with the inverse problem. The significance of lightning information in advancing high-frequency rainfall estimation from passive microwave-calibrated IR retrieval techniques is discussed on the basis of newly developed techniques. Finally, current approaches are presented on merging the infrequent passive microwave-based rainfall estimates with the high-frequency, but lower accuracy, rainfall fields derived from proxy parameters (e.g., lightning and IR). The paper provides useful insights on satellite rainfall estimation and discusses issues and applications.

Rainfall estimation from infrared data using an improved version of the Auto-Estimator Technique

In order to apply a suitable procedure for now-casting application in the case of heavy precipitation events, we discuss possible improvements to the Auto-Estimator Technique (AET). The AET rain estimation technique identifies precipitating clouds by comparing two successive infrared satellite images. If the pixel in the second image is colder, then upward motion is assumed and the convective system is considered to be a precipitating cloud. If the pixel in the second image is warmer, then the convective system is likely to be in a weakening phase and no precipitation is assigned. In the case of horizontal movement of the convective system, for instance approaching and weakening, the pixel in the second image can be colder without any upward motion or rain. We propose an improvement of AET (IAET) that determines the cloud top temperature variation and the corresponding rain rate estimation, taking into account the effect of horizontal motion of clouds, obtained by optical flow techniques. Precipitation events over Sardinia during November 1999, May 2000 and June 2000 were analysed. Three-hour cumulated precipitation on one pixel size area were determined by infrared Meteosat data, using both AET and IAET. A comparison between satellite estimation and 49 corresponding ground data stations was made. Contingency tables and relative statistical indices (Bias, False Alarm Ratio, Probability of Detection, Hit Rate, Critical Success Index), and errors on 3 h precipitation (mean absolute error (MAE) and Bias) were computed. When no horizontal motion of the convective system is present, AET and IAET have the same performances. In the events of May 2000, with fast movement of the precipitation system, AET significantly overestimates the rain rate while IAET gives much better performances.

Validating infrared-based rainfall retrieval algorithms with 1-minute spatially dense raingage measurements over Korean peninsula

¶This study compares and contrasts six infrared-based satellite rain estimation techniques and their validation during a 2-month period from June 20–August 20, 1998 over the Korean peninsula. Two probability matching techniques (PMM1, PMM2), a look-up table technique (LUT), a convective-stratiform technique (CST), the Negri-Adler-Wetzel technique (NAWT), and the Arkin technique (ARKT) are applied to hourly infrared GMS imagery. Retrieved rainrates are compared against one-minute reporting raingage observations from the dense Automated Weather Station (AWS) network of Korea. The high spatial resolution and fine temporal resolution of the AWS measurements provide a unique and effective means to validate rain estimates derived from instantaneous space measurements, which is a main scientific focus of this study.

Precipitation and Attenuation Measurements at a 10-cm Wavelength

Abstract On 9 June 1993, a squall line passed over the National Severe Storms Laboratory Cimarron radar and polarimetric data of this event were recorded. The line produced heavy rain and at one time was oriented north-south, extending over the radar site. At that time intense rainfall occurred over the radar. Polarimetric radar data from this event are examined to explore the utility of polarization radar techniques for rainfall monitoring and to evaluate the rain accumulation algorithm of the National Weather Services WSR-88D radar. The Twin Lakes WSR-88D radar observed the same squall line but from a different viewing angle. An unexpectedly large attenuation was experienced by the 10-cm-wavelength radiation, leading to large errors in conventional rain estimation techniques. An independent assessment of the rain measurements is made using rain accumulation in a dense network of surface rain gauges.

The Role of Visible Data in Improving Satellite Rain-Rate Estimates

Abstract Data from the first Algorithm Intercomparison Project(AIP/1) collected over Japan and surrounding waters in June, July, and August 1989 are used in this study to assess the importance of visible data in satellite rain estimation techniques. The purpose of the project was to compare different methods for estimating rainfall using satellite measurements. Radar and surface gauge data provided the validation set. RAINSAT, an estimation technique using both visible (VIS) and infrared (IR) data, achieved the highest correlation with the validation data. In this paper rainfall estimates from RAINSAT (VIS+IR) am compared with two IR-only techniques to deduce the effectiveness of VIS data. Some estimates are also made using a VIS-only technique. Comparisons am made on both a spatial and diurnal basis. Cloud climatologies for a subset of the AIP/1 data and the southern Ontario data on which RAINSAT was trained showed a marked similarity. It is found that the total volume of rain as a function of albedo is very similar for both Japanese and Ontario data. The VIS data generally produced higher correlations with the validation data than did the IR data. This was especially the case when rain fell from warm, orogaphically induced rainfall. When rain fell from cold bright clouds. especially over the ocean, the correlations of the two types of data with the validation data were similar. It is also shown that normalization of VIS data by the cosine of solar zenith data was inadequate to remove diurnal variations in apparent brightness.

A non‐linear algorithm for estimating three‐hourly rain rates over Amazonia from GOES/VISSR observations

Abstract Recent work has suggested that infrared window brightness temperatures can be regressed in a non‐linear formulation to estimate three‐hourly rain rates. We describe an Infrared Power law Rain rate (IPR) algorithm, which is based on such a formulation. Because it is continuous, IPR preserves the structure present in colder regions of an infrared image. In a test over Amazonia, IPR performed as well as three other infrared rain estimation techniques.

Rain-rate classification of INSAT—VHRR images through statistical methods

This study describes a procedure to determine rain rates using INSAT visible and infrared data by means of statistical methods. Satellite rain estimation techniques are more sensitive to spatial degradation than to temporal degradation. In the present study, visible and infrared samples selected from the VHRR images are used in the training process to achieve good spatial correspondence between satellite and ground estimates. Brightness features which are providing the best separability among the selected rainrate categories are extracted from the images. By locating all the 560 rain gauge stations maintained by the India Meteorological Department (IMD), the maximum likelihood decision rule was employed to classify the 8 km × 8 km window centered at a rain gauge station into one of the four selected rainfall rate categories. The training process used the rainfall data obtained from IMD daily weather reports for verification. The INSAT data for sample dates, representing different seasons has been used for the study. Classification accuracy, defined as the percentage of samples correctly classified out of all the samples in the selected class, was found to be above 80%.

Estimates of daily rainfall over the Amazon Basin

Five geostationary satellite rain estimation techniques were tested over Amazonia. Individually, the techniques explained ¼ to ⅓ of the variance of daily gage rainfall. Based in large part on cost, one technique, which involves a nonlinear relation in temperature, was selected to provide a mapping of daily Amazonia rainfall between May 6 and 12, 1987. Accumulated over the 7 days, rainfall by this technique averaged 40 mm. It varied from zero in the southeast to more than 150 mm in the northwest. To the southwest the predominantly convective pattern of the rain image was overlaid by a streakiness, implying some baroclinic influence. In maps combining gage observations with satellite estimates, rainfall varied significantly from day to day. Only over the largest scale did a trend emerge: a tendency for rain to withdraw from south to north.

Exploration of Extended-Area Treatment Effects in FACE-2 Using Satellite Imagery

Abstract The second phase of the Florida Area Cumulus Experiment (FACE-2) has been completed and an exploratory analysis has been conducted to investigate the possibility that cloud seeding may have affected the rainfall outside the intended target. Rainfall was estimated over a 3.5×105 km2 area centered on the target using geosynchronous, infrared satellite imagery and the Griffith-Woodley rain estimation technique. This technique was derived in South Florida by calibrating infrared images using raingage and radar observations to produce an empirical, diagnostic (a posteriori), satellite rain estimation technique. The satellite rain estimates for the extended area were adjusted based on comparisons of raingage and satellite rainfall estimates for the entire FACE target (1.3×104 km2). All daily rainfall estimates were composited in two ways: 1) in the original coordinate system and 2) in a relative coordinate system that rotates the research area as a function of wind direction. After compositing, seeding...

Insights into Errors of SMS-Inferred GATE Convective Rainfall

In the mean the Griffith/Woodley rain estimation technique underestimated the radar-measured rain of each of the three phases (a total of 56 days) of GATE, to varying degrees, and the satellite-derived isohyets were generally too extensive relative to radar-measured patterns. Three possible error sources are investigated in the present paper: 1) the method of apportionment of satellite-derived rain at the surface; 2) resolution degradation of the digital satellite imagery; and 3) anomalous behavior of convective clouds in the tropical Atlantic relative to those of the Florida derivation data set. To correct the satellite-derived rain patterns, a new method of apportionment was tested by recomputing the GATE satellite rain estimates. Better volumetric comparisons between radar and satellite estimates were observed for 24 h and phase periods, and comparisons of isohyetal patterns improved on all time scales. The relative error caused by resolution degradation was quantified by comparing rain estimates produced from full resolution imagery to estimates derived from degraded imagery for an 8° latitude by 12° longitude area in the eastern tropical Pacific ocean over a 54 h period. Results showed that the volumetric rainfall estimates made at 1/3° spatial and 1 h temporal resolution would be on the order of 10% lower than estimates made with the full resolution data (1/15° and 30 min). The remaining differences between the GATE satellite and radar estimates are attributable to different conditions prevailing in Florida and in GATE. These include significant rain from clouds that do not grow above the −20°C level (“warm rain”) and very long-lived anvils.

Satellite Rain Estimation in the U.S. High Plains

A satellite rain-estimation technique, derived in Florida for convective rainfall, was used to estimate areal rainfall in the U.S. High Plains. Raingages in dense and sparse networks provided the verification data. Unadjusted satellite-inferred rainfalls exceeded the corresponding gage estimates by a factor of 3–5, depending on the area size. This was expected and it is the result of treating convective clouds in arid regions as tropical clouds. Two objective methods were derived to adjust the technique for use in the High Plains. The first involved gage and satellite comparisons for a small area and then extrapolation of this comparison to satellite rain estimates for large areas. The second involved calculation of an adjustment factor using the output of a one-dimensional cumulus cloud model. Accuracy of the adjusted rainfalls are discussed in terms of bias, mean error factor, root mean square error and linear regression analyses. These preliminary results suggest that the satellite convective rain estimation technique can provide rain estimates of considerable utility once the estimates are adjusted for regional differences.