Radar Rainfall Estimation for Ground Validation Studies of the Tropical Rainfall Measuring Mission

Author:

Ciach Grzegorz J.1,Krajewski Witold F.2,Anagnostou Emmanouil N.1,Baeck Mary L.1,Smith James A.3,McCollum Jeffrey R.1,Kruger Anton1

Affiliation:

1. Iowa Institute of Hydraulic Research, University of Iowa, Iowa City, Iowa

2. Iowa Institute of Hydraulic Research and Department of Civil Engineering, University of Iowa, Iowa City, Iowa

3. Department of Civil Engineering and Operations Research, Princeton University, Princeton, New Jersey

Abstract

Abstract This study presents a multicomponent rainfall estimation algorithm, based on weather radar and rain gauge network, that can be used as a ground-based reference in the satellite Tropical Rainfall Measuring Mission (TRMM). The essential steps are constructing a radar observable, its nonlinear transformation to rainfall, interpolation to rectangular grid, constructing several timescale accumulations, bias adjustment, and merging of the radar rainfall estimates and rain gauge data. Observations from a C-band radar in Darwin, Australia, and a local network of 54 rain gauges were used to calibrate and test the algorithm. A period of 25 days was selected, and the rain gauges were split into two subsamples to apply cross-validation techniques. A Z–R relationship with continuous range dependence and a temporal interpolation scheme that accounts for the advection effects is applied. An innovative methodology was used to estimate the algorithm controlling parameters. The model was globally optimized by using an objective function on the level of the final products. This is equivalent to comparing hundreds of Z–R relationships using a uniform and representative performance criterion. The algorithm performance is fairly insensitive to the parameter variations around the optimum. This suggests that the accuracy limit of the radar rainfall estimation based on power-law Z–R relationships has been reached. No improvement was achieved by using rain regime classification prior to estimation.

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference30 articles.

1. Atlas, D., and A. C. Chmela, 1957: Physical-synoptic variations of drop-size parameters. Preprints, Sixth Weather Radar Conf., Cambridge, MA, Amer. Meteor. Soc., 21–29.

2. Austin, P. M., 1987: Relation between measured radar reflectivity and surface rainfall. Mon. Wea. Rev., 115, 1053–1070.

3. Battan, L. J., 1973: Radar Observation of the Atmosphere. The University of Chicago Press, 324 pp.

4. Bellon, A., F. Fabry, and G. L. Austin, 1991: Errors due to space–time sampling strategies in high resolution radar data used in hydrology. Preprints, 25th Conf. on Radar Meteorology, Paris, France, Amer. Meteor. Soc., 2040–2048.

5. Bickel, P. J., and K. A. Doksum, 1977: Mathematical Statistics: Basic Ideas and Selected Topics. Holden-Day, 492 pp.

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