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Mamoudou B. Ba
and
Arnold Gruber

Abstract

A multispectral approach is used to optimize the identification of raining clouds located at a given altitude estimated from the cloud-top temperature. The approach combines information from five channels on the National Oceanic and Atmospheric Administration Geostationary Operational Environmental Satellite (GOES): visible (0.65 μm), near infrared (3.9 μm), water vapor (6.7 μm), and window channels (11 and 12 μm). The screening of nonraining clouds includes the use of spatial gradient of cloud-top temperature for cirrus clouds (this screening is applied at all times) and the effective radius of cloud-top particles derived from the measurements at 3.9 μm during daytime. During nighttime, only clouds colder than 230 K are considered for the screening; during daytime, all clouds having a visible reflectance greater than 0.40 are considered for the screening, and a threshold of 15 μm in droplet effective radius is used as a low boundary of raining clouds. A GOES rain rate for each indicated raining cloud group referenced by its cloud-top temperature is obtained by the product of probability of rain (P b ) and mean rain rate (RRmean) and is adjusted by a moisture factor that is designed to modulate the evaporation effects on rain below cloud base for different moisture environments. The calibration of the algorithm for constants P b and RRmean is obtained using collocated instantaneous satellite and radar data and hourly gauge-adjusted radar products collected during 17 days in June and July 1998. A comparison of the combined visible and a temperature threshold of 230 K (e.g., previous infrared/visible algorithms) with the combined visible and a threshold of 15 μm demonstrates that the latter improves the detection of rain from warm clouds without lowering the skill of the algorithm. The quantitative validation shows that the algorithm performs well at daily and monthly scales. At monthly scales, a comparison with GOES Precipitation Index (GPI) shows that GOES Multispectral Rainfall Algorithm's performance against gauges is much better for September and October 1999.

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Istvan Laszlo
,
Arnold Gruber
, and
Herbert Jacobowitz

Abstract

Observations made with the current and proposed narrowband shortwave channels aboard the NOAA series of satellites were simulated for a number of different surfaces (ocean, vegetative land, desert, cloud and snow) using the ATRAD radiation model to study the relative merit of each channel and, in various combinations to predict the broadband albedo. Solar zenith angles were varied over the range from 0 to 60 degrees. The results indicated that for all of the surfaces considered there would be no significant difference in predicting the broadband albedo with either the current (0.58–0.68 μn) or proposed (0.58–0.68 μm) channel 1 of the AVHRR. The proposed narrower channel 2(0.84–0.87 μm), however, would be a better predictor than the current wider channel 2(0.725–1.0 μm). Channel 1 is better than channel 2 for surfaces of low or moderate reflectivity, while over snow, the error in using channel 2 would be less than half of that for channel 1. Combining channels 1 and 2 would reduce the error by about 50% for vegetation, ocean and snow. Adding the proposed channel 3A (1.58–1.64 μm) to channels 1 and 2 would further improve the prediction of the broadband albedo. Channel 20(0.65–0.73 μm) of the HIRS instrument was similarly studied to ascertain how well the broadband albedo would be predicted if the spectral filter was removed to widen the bandpass. Two different detectors (Si and InGaAs) with the current and a modified beamsplitter were considered. The results indicated that the modified beamsplitter was preferred. The use of this beamsplitter with the Si detector (0.46–1.04 μm) gave the best prediction for ocean, vegetative land, and desert scenes, while the InGaAs detector (0.64–1.74 μm) was best for cloud and snow scenes. Although the use of a widened channel 20 was shown to be less successful than the combination of channels 1, 2 and 3A of the AVHRR, flattening the response curve for the InGaAs detector using a compensating filter was comparable to using the AVHRR channels.

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Arnold Gruber
and
James J. O'Brien

Abstract

An objective technique for adjusting wind data, such that the total mass divergence in a volume of the atmosphere is zero, is developed. The adjustment is obtained by applying a least-squares smoothing with a Lagrangian multiplier to constrain the total mass divergence to a specified amount. The computational details are derived and the method is applied to several examples. Both for theoretical wind profiles and for actual data, a very satisfactory adjustment is achieved without destroying the physical information contained in the data.

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Arnold Gruber
and
Arthur F. Krueger

National Oceanic and Atmospheric Administration (NOAA) satellites have provided over eight years of observations from which estimates of the earth's total longwave emittance can be derived. Changes in satellite instrumentation, orbit, and algorithms used in obtaining these estimates are briefly summarized. The algorithms used by NOAA in obtaining a longwave radiation data set are provided.

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Arnold Gruber
and
Jay S. Winston

A brief description of an earth radiation budget data set, as determined from NOAA operational spacecraft, is presented. The data are continuous from June 1974 through February 1978. Some samples of the mapped outputs are shown, and information on the availability of these data is provided.

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Jerry Sullivan
,
Lev Gandin
,
Arnold Gruber
, and
Wayman Baker

Abstract

In 1988, the algorithm for retrieving temperature soundings from radiances measured by NOAA's polar-orbiting satellites was changed from a statistical to a “physical” retrieval system. Because of this change, the National Meteorological Center (NMC) wanted to update the satellite temperature error statistics used in the NMC analyses. The authors, therefore, updated the estimates of observational error variances, horizontal covariances, and vertical correlations for layer mean temperatures retrieved from NOAA-10 satellite radiance data. The temperature error statistics have also been used to estimate analogous error statistics for isobaric height.

The computations used radiosonde data as a substitute for true temperatures. Each “matchup” in the dataset consisted of a satellite retrieval close in space and time to a radiosonde sounding. The matchups were stratified into clear, partly cloudy, and cloudy cases, depending on the amount of cloud contamination in the satellite radiance data. In each of the nine mandatory pressure layers considered, from 1000–850 to 50–100 mb, the clear and partly cloudy matchup cases have nearly equal temperature error variances, while the variances for cloudy cases are substantially larger. Vertical error correlations for all three stratifications are similar. Root-mean-square height errors computed from satellite temperature errors are comparable to those computed from radiosonde errors in the clear and partly cloudy matchup cases, but larger in cloudy cases.

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Noah Wolfson
,
Albert Thomasell
,
Arnold Gruber
, and
George Ohring

Abstract

The impact of satellite sounding data on the systematic errors of the numerical weather prediction model of the Israel Meteorological Service has been investigated. In general, satellite data have been shown to reduce systematic error, and in particular, the greatest impact is near where the data have been introduced in the vicinity of low pressure systems.

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Arnold Gruber
,
Xiujuan Su
,
M. Kanamitsu
, and
J. Schemm

Two large-scale precipitation datasets, one produced by the Global Precipitation Climatology Project (GPCP) and the other by the Climate Prediction Center of the National Weather Service, and called Climate Prediction Center Merged Analysis of Precipitation (CMAP), were compared. Both datasets blend satellite and gauge estimates of precipitation. And while the latter has its heritage in the GPCP, different analysis procedures and some additional types of input data used by CMAP yielded different values. This study used the error characteristics of the data to assess the significance of the observed differences. Despite good spatial and temporal correlations between the two fields some of the observed differences were significant at the 95% level. These were traced to the use of some different input data such as the use by CMAP of atoll gauges in the tropical Pacific and gauges uncorrected for wetting evaporation and aerodynamic effects. The former impacts the tropical ocean rain amounts and the latter is particularly noticeable in the Northern Hemisphere land areas. Also, the application of these datasets to the validation of atmospheric general circulation models is discussed.

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ARNOLD GRUBER
,
LEROY HERMAN
, and
ARTHUR F. KRUEGER

Abstract

Resultant winds over the Pacific are derived from an Advanced Technology Satellite (ATS 1) for the month of November 1969. Since the method uses clouds as tracers, these resultant winds are biased toward cloud-producing circulation features. These biases appear to be smallest in the Tropics and, consequently, the winds here can be very useful for studies of the average circulation at low latitudes. Some of the important features of this circulation over the equatorial Pacific are clearly revealed.

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Jeffrey R. McCollum
,
Arnold Gruber
, and
Mamoudou B. Ba

Abstract

The Global Precipitation Climatology Project (GPCP) satellite estimates have approximately twice the magnitude of estimates produced from the rain gauges used by the GPCP in central equatorial Africa. Different possible explanations are identified and investigated. The first is that there may not be enough GPCP rain gauges in the area to provide accurate estimates of rainfall for comparisons with satellite estimates. A comparison of the time-averaged GPCP rain gauge estimate with a long-term (over 40 yr) climatology indicates that the GPCP gauge estimates are similar to long-term rainfall averages, suggesting that the GPCP rain gauge analysis is not underestimating rainfall. Two other possible explanations related to the physical properties of the air masses in this region are studied. Evidence from the literature and from estimates of the effective radii of cloud droplets suggests that there may be an abundance of aerosols in central Africa, resulting in an abundance of cloud condensation nuclei, small drops, and inefficient rain processes. The second explanation is that convective clouds forming under dry conditions generally have cloud bases considerably higher than those of clouds forming in moist environments. This leads to an increase in the evaporation rate of the falling rain, resulting in less precipitation reaching the ground. Analysis of the moisture distributions from both the National Centers for Environmental Prediction numerical weather prediction model reanalysis data and the National Aeronautics and Space Administration Water Vapor Project global moisture dataset reveals that the lower troposphere in this region of Africa is relatively dry, which suggests that cloud bases are high.

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