Engineering topics

Haskins, Robert D.

Publications and source records attributed to Haskins, Robert D..

5 records

NASA NTRS1995

Comparison of cloud fields from atmospheric general circulation model, in situ and satellite measurements

This paper focuses on the comparison of cloud amounts derived from an atmospheric general circulation model (AGCM), Satellite-observed clouds, and Ground-based cloud observations. Unlike Earth Radiation Budget Experiment (ERBE)-type comparisons it does not mix potential errors in the cloud amount with those in the radiation code embedded in the model. Long term cloud climatologies were used to compare global cloud amounts and regional seasonal cycles. The AGCM successfully reproduced the signatures of the warm pool and North Pacific seasonal cycle cloudiness but failed in the low stratus region off the coast of South America, a known problem for AGCMs. The data sets also reproduced the anomaly signature associated with El Nino in the warm pool region, but the model amounts were lower. Global results had a similar success rate, with the model generally producing lower total cloud compared to the satellite and in situ measurements. To compare cloud vertical distributions the cloud height may need to be validated using the corresponding radiation fields. Unfortunately there were also some large discrepancies between the two observed cloud data sets. While tremendously improved over the last decade the character of the observed cloud data sets, must be substantially enhanced before they will be useful in validating AGCMs by any but the crudest levels of comparison.

Haskins, Robert D.↗

NASA NTRS1992

Validating a large geophysical data set: Experiences with satellite-derived cloud parameters

We are validating the global cloud parameters derived from the satellite-borne HIRS2 and MSU atmospheric sounding instrument measurements, and are using the analysis of these data as one prototype for studying large geophysical data sets in general. The HIRS2/MSU data set contains a total of 40 physical parameters, filling 25 MB/day; raw HIRS2/MSU data are available for a period exceeding 10 years. Validation involves developing a quantitative sense for the physical meaning of the derived parameters over the range of environmental conditions sampled. This is accomplished by comparing the spatial and temporal distributions of the derived quantities with similar measurements made using other techniques, and with model results. The data handling needed for this work is possible only with the help of a suite of interactive graphical and numerical analysis tools. Level 3 (gridded) data is the common form in which large data sets of this type are distributed for scientific analysis. We find that Level 3 data is inadequate for the data comparisons required for validation. Level 2 data (individual measurements in geophysical units) is needed. A sampling problem arises when individual measurements, which are not uniformly distributed in space or time, are used for the comparisons. Standard 'interpolation' methods involve fitting the measurements for each data set to surfaces, which are then compared. We are experimenting with formal criteria for selecting geographical regions, based upon the spatial frequency and variability of measurements, that allow us to quantify the uncertainty due to sampling. As part of this project, we are also dealing with ways to keep track of constraints placed on the output by assumptions made in the computer code. The need to work with Level 2 data introduces a number of other data handling issues, such as accessing data files across machine types, meeting large data storage requirements, accessing other validated data sets, processing speed and throughput for interactive graphical work, and problems relating to graphical interfaces.

Kahn, Ralph↗

NASA NTRS1992

Experience of the JPL Exploratory Data Analysis Team at validating HIRS2/MSU cloud parameters

Validation of the HIRS2/MSU cloud parameters began with the cloud/climate feedback problem. The derived effective cloud amount is less sensitive to surface temperature for higher clouds. This occurs because as the cloud elevation increases, the difference between surface temperature and cloud temperature increases, so only a small change in cloud amount is needed to effect a large change in radiance at the detector. By validating the cloud parameters it is meant 'developing a quantitative sense for the physical meaning of the measured parameters', by: (1) identifying the assumptions involved in deriving parameters from the measured radiances, (2) testing the input data and derived parameters for statistical error, sensitivity, and internal consistency, and (3) comparing with similar parameters obtained from other sources using other techniques.

Kahn, Ralph↗

NASA NTRS1991

Validating a large geophysical data set - Experiences with satellite-derived cloud parameters

The goal of this study is to validate the global cloud parameters derived from the satellite-borne HIRS2 and MSU atmospheric sounding instrument measurements, and to use the analysis of these data as one prototype for studying large geophysical data sets in general. The HIRS2/MSU data set contains a total of 40 physical parameters, filling 25 MB/day; raw HIRS2/MSU data are available for a period exceeding 10 years. Validation involves developing a quantitative sense for the physical meaning of the derived parameters over the range of environmental conditions sampled. This is accomplished by comparing the spatial and temporal distributions of the derived quantities with similar measurements made using other techniques, and with model results. The need to work with Level 2 (point) data, rather than Level 3 (gridded) data for validation purposes is discussed, and some techniques developed for charting the assumptions made in deriving an algorithm and generating a code to produce geophysical quantities from measured radiances are presented.

Kahn, Ralph↗

NASA NTRS1987

Satellite observation of atmosphere and surface interaction parameters

Atmosphere and ocean surface parameters are being derived from weather satellite data acquired by the High Resolution Infrared Sounder and the Microwave Sounding Unit. In this paper, the global distribution and accuracy of the derived parameters are described, and the satellite-derived skin surface temperature is compared with available shelter temperature. Seasonal and interannual changes are examined to study the response time of large-scale atmospheric changes to changes in surface conditions.

Chahine, Moustafa T.↗