Engineering topics

Amitai, E.

Publications and source records attributed to Amitai, E..

7 records

NASA NTRS2011

Toward a Framework for Systematic Error Modeling of NASA Spaceborne Radar with NOAA/NSSL Ground Radar-Based National Mosaic QPE

Characterization of the error associated to satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving space-born passive and active microwave measurement") for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. We focus here on the error structure of NASA's Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements using NOAA/NSSL ground radar-based National Mosaic and QPE system (NMQ/Q2). A preliminary investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) using a three-month data sample in the southern part of US. The primary contribution of this study is the presentation of the detailed steps required to derive trustworthy reference rainfall dataset from Q2 at the PR pixel resolution. It relics on a bias correction and a radar quality index, both of which provide a basis to filter out the less trustworthy Q2 values. Several aspects of PR errors arc revealed and quantified including sensitivity to the processing steps with the reference rainfall, comparisons of rainfall detectability and rainfall rate distributions, spatial representativeness of error, and separation of systematic biases and random errors. The methodology and framework developed herein applies more generally to rainfall rate estimates from other sensors onboard low-earth orbiting satellites such as microwave imagers and dual-wavelength radars such as with the Global Precipitation Measurement (GPM) mission.

Kirstettier, Pierre-Emmanual↗

NASA NTRS2005

Validation for the Tropical Rainfall Measuring Mission: Lessons Learned and Future Plans

The Tropical Rainfall Measuring Mission (TRMM) was launched in November 1997 and is a highly regarded and successful mission. A major component of the TRMM program was its Ground Validation (GV) program. Through dedicated research and hard work by many groups, both the GV and satellite-retrieved rain estimates have shown a convergence at key GV sites, lending credibility to the global TRMM estimates. To be sure, there are some regional differences between the various satellite estimates themselves, which still need to be addressed; however, it can be said with some certainty that TRMM has provided a high-quality, long-term climatological data set for researchers that provides errors on the order of 10-20%, rather than pre-TRMM era error estimates on the order of 50-100%. The TRMM GV program's main operational task is to provide rainfall products for four sites: Darwin, Australia (DARW); Houston, Texas (HSTN); Kwajalein, Republic of the Marshall Islands (KWAJ); and, Melbourne, Florida (MELB). A comparison between TRMM Ground Validation (Version 5) and Satellite (Version 6) rain intensity estimates is presented. The gridded satellite product (3668) will be compared to GV Level II rain-intensity and -type maps (2A53 and 2A54, respectively). The 3G68 product represents a 0.5 deg x 0.5 deg data grid providing estimates of rain intensities from the TRMM Precipitation Radar (PR), Microwave Imager (TMI) and Combined (COM) algorithms. The comparisons will be sub-setted according to geographical type (land, coast and ocean). The convergence of the GV and satellite estimates bodes well for expectations for the proposed Global Precipitation Measurement (GPM) program and this study and others are being leveraged towards planning GV goals for GPM. A discussion of lessons learned and future plans for TRMM GV in planning for GPM will also be provided.

Wolff, David B.↗

NASA NTRS2004

Status of TRMM Ground Validation Program at NASA GSFC

The TRMM Ground Validation (GV) program at NASA GSFC has made considerable progress: over the last several years. The GV program now has a Complete record of Level I-HI products from the Kwajaiein and Melbourne, Florida sites. Current emphasis is to eliminate the remaining backlog for the Houston, Texas and Darwin, Australia sites. This paper provides details on the status of our data processing efforts, defines accuracy estimates of the various GV rain products, end shows comparisons between GV rain intensities and accumulations to satellite retrievals over the GV sites. We will show that the Version 6a TRMM TMI and PR, at leas! over ocean areas of the GV sites, are within +/- 10% of the Version 5 GV estimates at least over open Ocean areas, away from contaminating effects of land and coastal regions.

Wolff, David B.↗

NASA NTRS2003

Uniting Space, Ground and Underwater Measurements for Improved Estimates of Rain Rate

Global precipitation is monitored from a variety of platforms including space-borne, ground- and ocean-based platforms. Intercomparisons of these observations are crucial to validating the measurements and providing confidence for each measurement technique. Probability distribution functions of rain rates are used to compare satellite and ground-based radar observations. A preferred adjustment technique for improving rain rate distribution estimates is identified using measurements from ground-based radar and radar and rain gauges within the coverage area of the radar. The underwater measurement of rainfall shows similarities to radar measurements, but with intermediate spatial resolution and high temporal resolution. Reconciling these different measurement techniques provides understanding and confidence for all of the methods.

Amitai, E.↗

NASA NTRS2000

Climatological Processing and Product Development for the TRMM Ground Validation Program

The Tropical Rainfall Measuring Mission (TRMM) satellite was successfully launched in November 1997.The main purpose of TRMM is to sample tropical rainfall using the first active spaceborne precipitation radar. To validate TRMM satellite observations, a comprehensive Ground Validation (GV) Program has been implemented. The primary goal of TRMM GV is to provide basic validation of satellite-derived precipitation measurements over monthly climatologies for the following primary sites: Melbourne, FL; Houston, TX; Darwin, Australia- and Kwajalein Atoll, RMI As part of the TRMM GV effort, research analysts at NASA Goddard Space Flight Center (GSFC) generate standardized rainfall products using quality-controlled ground-based radar data from the four primary GV sites. This presentation will provide an overview of TRMM GV climatological processing and product generation. A description of the data flow between the primary GV sites, NASA GSFC, and the TRMM Science and Data Information System (TSDIS) will be presented. The radar quality control algorithm, which features eight adjustable height and reflectivity parameters, and its effect on monthly rainfall maps, will be described. The methodology used to create monthly, gauge-adjusted rainfall products for each primary site will also be summarized. The standardized monthly rainfall products are developed in discrete, modular steps with distinct intermediate products. A summary of recently reprocessed official GV rainfall products available for TRMM science users will be presented. Updated basic standardized product results involving monthly accumulation, Z-R relationship, and gauge statistics for each primary GV site will also be displayed.

Marks, D. A.↗

NASA NTRS2000

Evolving Improvements to TRMM Ground Validation Rainfall Estimates

The primary function of the TRMM Ground Validation (GV) Program is to create GV rainfall products that provide basic validation of satellite-derived precipitation measurements for select primary sites. Since the successful 1997 launch of the TRMM satellite, GV rainfall estimates have demonstrated systematic improvements directly related to improved radar and rain gauge data, modified science techniques, and software revisions. Improved rainfall estimates have resulted in higher quality GV rainfall products and subsequently, much improved evaluation products for the satellite-based precipitation estimates from TRMM. This presentation will demonstrate how TRMM GV rainfall products created in a semi-automated, operational environment have evolved and improved through successive generations. Monthly rainfall maps and rainfall accumulation statistics for each primary site will be presented for each stage of GV product development. Contributions from individual product modifications involving radar reflectivity (Ze)-rain rate (R) relationship refinements, improvements in rain gauge bulk-adjustment and data quality control processes, and improved radar and gauge data will be discussed. Finally, it will be demonstrated that as GV rainfall products have improved, rainfall estimation comparisons between GV and satellite have converged, lending confidence to the satellite-derived precipitation measurements from TRMM.

Robinson, M.↗

NASA NTRS2000

Rainfall Product Evaluation for the TRMM Ground Validation Program

Evaluation of the Tropical Rainfall Measuring Mission (TRMM) satellite observations is conducted through a comprehensive Ground Validation (GV) Program. Standardized instantaneous and monthly rainfall products are routinely generated using quality-controlled ground based radar data from four primary GV sites. As part of the TRMM GV program, effort is being made to evaluate these GV products and to determine the uncertainties of the rainfall estimates. The evaluation effort is based on comparison to rain gauge data. The variance between the gauge measurement and the true averaged rain amount within the radar pixel is a limiting factor in the evaluation process. While monthly estimates are relatively simple to evaluate, the evaluation of the instantaneous products are much more of a challenge. Scattegrams of point comparisons between radar and rain gauges are extremely noisy for several reasons (e.g. sample volume discrepancies, timing and navigation mismatches, variability of Z(sub e)-R relationships), and therefore useless for evaluating the estimates. Several alternative methods, such as the analysis of the distribution of rain volume by rain rate as derived from gauge intensities and from reflectivities above the gauge network will be presented. Alternative procedures to increase the accuracy of the estimates and to reduce their uncertainties also will be discussed.

Amitai, E.↗