scholarly journals Profiler Contributions to Tropical Rainfall Measuring Mission (TRMM) Ground Validation Field Campaigns

2002 ◽  
Vol 19 (6) ◽  
pp. 843-863 ◽  
Author(s):  
Kenneth S. Gage ◽  
Christopher R. Williams ◽  
Wallace L. Clark ◽  
Paul E. Johnston ◽  
David A. Carter
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Tropical Rainfall ◽  
Ground Validation ◽  
Field Campaigns

scholarly journals Ground Validation for the Tropical Rainfall Measuring Mission (TRMM)

2005 ◽  
Vol 22 (4) ◽  
pp. 365-380 ◽  
Author(s):  
David B. Wolff ◽  
D. A. Marks ◽  
E. Amitai ◽  
D. S. Silberstein ◽  
B. L. Fisher ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Marshall Islands ◽  
Error Statistics ◽  
Tropical Rainfall ◽  
Nasa Goddard Space ◽  
Ground Validation ◽  
Microwave Imager ◽  
Rain Rates ◽  
Good Agreement

Abstract An overview of the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) Program is presented. This ground validation (GV) program is based at NASA Goddard Space Flight Center in Greenbelt, Maryland, and is responsible for processing several TRMM science products for validating space-based rain estimates from the TRMM satellite. These products include gauge rain rates, and radar-estimated rain intensities, type, and accumulations, from four primary validation sites (Kwajalein Atoll, Republic of the Marshall Islands; Melbourne, Florida; Houston, Texas; and Darwin, Australia). Site descriptions of rain gauge networks and operational weather radar configurations are presented together with the unique processing methodologies employed within the Ground Validation System (GVS) software packages. Rainfall intensity estimates are derived using the Window Probability Matching Method (WPMM) and then integrated over specified time scales. Error statistics from both dependent and independent validation techniques show good agreement between gauge-measured and radar-estimated rainfall. A comparison of the NASA GV products and those developed independently by the University of Washington for a subset of data from the Kwajalein Atoll site also shows good agreement. A comparison of NASA GV rain intensities to satellite retrievals from the TRMM Microwave Imager (TMI), precipitation radar (PR), and Combined (COM) algorithms is presented, and it is shown that the GV and satellite estimates agree quite well over the open ocean.

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

1997 ◽  
Vol 36 (6) ◽  
pp. 735-747 ◽  
Author(s):  
Grzegorz J. Ciach ◽  
Witold F. Krajewski ◽  
Emmanouil N. Anagnostou ◽  
Mary L. Baeck ◽  
James A. Smith ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Estimation Algorithm ◽  
Rain Gauge ◽  
Performance Criterion ◽  
Local Network ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Tropical Rainfall ◽  
Rain Gauges ◽  
Ground Validation

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.

Overview of the Convection and Moisture Experiment (CAMEX)

2006 ◽  
Vol 63 (1) ◽  
pp. 5-18 ◽  
Author(s):  
Ramesh Kakar ◽  
Michael Goodman ◽  
Robbie Hood ◽  
Anthony Guillory
Keyword(s):  
Space Flight ◽  
Web Site ◽  
Tropical Rainfall Measuring Mission ◽  
Open Ocean ◽  
Intensity Change ◽  
Tropical Storms ◽  
Tropical Rainfall ◽  
Field Campaigns

Abstract This paper presents an overview of the Convection and Moisture Experiment (CAMEX), including the field operations, aircraft platforms and missions, instrumentation, and data acquired during 1998 and 2001 field campaigns. A total of eight tropical storms and hurricanes were investigated during the CAMEX field campaigns including Bonnie, Danielle, Earl, and Georges during 1998 and Chantal, Erin, Gabrielle, and Humberto during 2001. Most of these storms were sampled with aircraft over the open ocean, but Hurricanes Bonnie (1998), Georges (1998), and Gabrielle (2001) also provided opportunities to monitor landfalling impacts. A few of the storms were sampled on multiple occasions during a course of several days. Most notable of these was Hurricane Humberto, which was sampled on three consecutive days during a cycle of both increasing and decreasing intensity change. Information collected for each of the eight CAMEX tropical storms as well as the Tropical Rainfall Measuring Mission validation activities are accessible via the CAMEX Web site and archived at the National Aeronautics and Space Administration Marshall Space Flight Center.

Comparison Between Estimated Rainfall Estimated by the Tropical Rainfall Measuring Mission (TRMM) Satellite and Data Observed in the Lagoa Mirim/RS Basin, Brazil

INCREaSE 2019 ◽  
2019 ◽  
pp. 97-110
Author(s):  
Géri Eduardo Meneghello ◽  
Letícia Burkert Méllo ◽  
Ritâ De Cassia Fraga Damé ◽  
Francisco Amaral Villela ◽  
Maria Clotilde Carré Chagas Neta ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Tropical Rainfall
Sign in / Sign up

Export Citation Format

Share Document