Engineering topics
Publications and source records attributed to Haskins, R..
Spectral Empirical Orhtogonal Functions (EOFs) derived from the covariance of satellite radiance spectra may be interpreted in terms of the vertical distribution of the covariance of temperature, water vapor, and clouds. The purpose of the investigation is to demonstrate the important constraints that resolved spectral radiances can place upon climate models.
We compare the performance of broadband radiometers with spectrally-dispersed measurements.
An intercomparison is made between vertically integrated water vapor flux estimates from the NASA reanalysis product, and from two versions of an atmospheric general circulation model (AGCM) forced only by observed sea surface temperature (SST). The period of comparison was from March 1985-February 1991 plus data from the U.S. flood in 1993.
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.
The spatial distribution of the expected changes in the atmospheric water vapor content and cloud cover, as predicted by the transient greenhouse gas (GHG) simulation of Hansen et al. (1988), are examined to determine whether the signals would be large enough and unique enough to be useful in a GHG detection study. The nature of the predicted GHG signal was first examined using the transient CO2 run from the GISS ocean/atmosphere general circulation model. Next, the remotely sensed irradiance characteristics data (as the measure of water vapor content) supplied by the HIRS/MSU sensors for the area of the equatorial cold tongue region (the region in which there are no measurement stations). It is shown that HIRS/MSU signals can provide data necessary for detecting GHS signals in atmospheric moisture for regions where ground observations are not possible.
A relaxation algorithm which permits meteorological parameters to be obtained from satellite data, without a priori assumptions about the properties of the other unknowns in the field of view, was developed. Atmospheric temperature profiles, atmospheric humidity, cloud cover, cloud top height, cloud top temperature, sea-surface temperature, land-surface temperature, snow cover, and ice cover are derived. Simultaneous determination of atmospheric and surface thermal structure and the cloud distribution provides information on heat sources and sinks, storage rates, and transport phenomena in the atmosphere. Such information is critical in determining the driving mechanisms for motions in the atmosphere and oceans and in improving numerical weather prediction.
Examples are given of the accuracy of the results obtained from the HIRS 2/MSU (High Resolution Infrared Sounder and Microwave Sounding Unit) analysis of ocean, atmosphere, and land parameters. Sea surface temperatures are compared with available ship and buoy radiosonde data, and land surface temperatures are compared with shelter temperatures. The seasonal change in land and ocean skin surface temperature is reviewed. The distribution of clouds is examined and their opacities in the visible and infrared parts of the spectrum are compared.
The fundamental problem in deriving weather and climate procedures from satellite data lies in the proper selection of sets of sounding frequencies, and in the derivation of accurate algorithms that are capable of uncoupling the effects of these variables to retrieve the true value of each unknown parameter separately. This uncoupling is presently based on the relaxation principle of Chahine (1968, 1970), which allows each parameter to be retrieved analytically without a priori assumptions as to the properties of the other unknowns in the field of view. Attention is given to work conducted with the High Resolution IR Sounder and the Microwave Sounding Unit instruments carried by the NOAA Weather Satellite.