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Donald P. Wylie

Abstract

The use of geostationary satellite data for estimating precipitation in non-tropical areas was explored with data taken in Montreal, Canada. The previous studies using geostationary images for rain estimation have concentrated primarily on tropical clouds (Griffith et al., 1978; Stout, et al., 1979). The intent of this study was to evaluate the applicability of using these data and techniques in other geographical areas. The Montreal area provided a wide range of weather situations common to midlatitudes for which the techniques could be tested. Because of the many variables in this area (different cloud types, moisture availability, temperature vertical structure and others) the rain rates of the cloud areas varied. Large differences in rain rates between the days studies in Montreal were found. The Montreal data also had rain rates that were considerably smaller than found in the tropical studies.

To explain these differences the environments of the clouds were investigated using sounding data. By applying a cumulus model (Simpson and Wiggert, 1969) to the soundings most of the daily differences in rain rates were explained. The large differences between the tropical studies and Montreal also were described by the model. It is proposed that future rain estimation schemes combine satellite image with sounding data through a cloud model to form a technique applicable to a wide variety of weather situations and geographical areas.

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Donald P. Wylie
and
Denise Laitsch

Abstract

Rain estimates for the Great Plains States were made for a one-month period, August 1979, using different combinations of satellite and other data. The data tested were as follows: 1) two satellite images per day without any other data, 2) four satellite images per day, 3) 24 images per day, 4) 24 images per day with hourly surface observations and two per day radiosonde soundings (excluding the 6 h raingage reports), 5) two images per day with the Service A 6 h raingage reports, 6) 24 images per day with the Service A raingage reports, and 7) an automatic rain estimate made from infrared temperatures without human intervention.

Each method was applied to the same geographic area by the same meteorologists. Estimates produced from the seven data combinations were compared to a withheld data set of 538 hourly recording raingages.

The rain estimates from all methods tested were very similar in their ability to locate rainfall and estimate the monthly patterns. The first two methods tested, using only satellite imagery at low-frequency sampling rates, gave slightly poorer skill scores than the more data-rich methods. Best scores were found for methods using the Service A raingage reports (Methods 5 and 6). The frequency of satellite imagery did not change the quality ofthe estimates when the raingages were included.

The rain estimates made without the judgment of a meteorologist (Method 7) scored surprisingly close to the other methods tested. The additional effort of a meteorologist improved the rain estimates in all cases, but the level of improvement was small beyond that produced by a simple automated scheme.

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Donald P. Wylie
and
Harold M. Woolf

Abstract

An analysis technique for Geostationary Operational Environmental Satellite-VISSR (Visible and Infrared Spin Scan Radiometer) Atmospheric Sounder (GOES-VAS) sounder data was developed to extract cloud and clear radiance information. This technique employed many of the concepts used in the International Satellite Cloud Climatology Project (ISCCP) such as spatial and time comparisons of neighboring satellite pixels. It improved upon the previous studies that used VAS data by using all available VAS data at full time and space resolution. The previous studies utilized <10% of the original data.

The GOES-VAS cloud and clear radiance statistics compared well with rawinsondes and the ISCCP cloud analysis. The best agreement between the ISCCP and this GOES-VAS cloud analysis was for upper-tropospheric clouds (<440 hPa) in both cloud frequency and infrared emissivity. The two cloud datasets agreed to within 2% for both parameters. A comparison of the GOES-VAS clear radiance data to National Weather Service (NWS) rawinsondes showed agreement within 1.7 K (blackbody radiances). The upper-tropospheric VAS channels were warmer than the rawinsondes. The VAS water vapor channels suggested that the NWS rawinsondes have a dry bias in the upper troposphere.

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Donald P. Wylie
,
Barry B. Hinton
, and
Kellie M. Millett

Abstract

The feasibility of using satellites for providing surface winds or wind stress data was explored. Three popular methods were compared using nearly colocated data to assess the accuracies of each and the coverage that each could provide. The three methods tested were 1) the use of the sun glitter reflection seen on visible images of the ocean surface; 2) the use of active microwave sensors (flown on SEASAT) which reflect microwaves off the ocean surface; and 3) the use of cloud motions as indicators of the surface winds.

Close agreement in wind speed estimates was found among the three methods. The biases were <0.6 m s−1 for comparisons between comparable methods of estimating surface winds (1 and 2). Cloud motion comparisons to the other methods exhibited biases of <3.0 m s−1. Individual point-by-point comparisons between wind measurements had an average scatter of 2.0 m s−1 (rms) or less after the mean biases were removed. Atmospheric variability caused as many of the differences as the instrumental errors indicating that meaningful wind information could be obtained from all three methods.

Very detailed spacial coverage was obtained with the sun-glitter method for wind speeds. However, the coverage was restricted to a narrow band 5° of latitude wide in the tropics. SEASAT also provided good coverage for two swaths (4° longitude wide) on each side of the satellite's orbit. Gaps between the swaths and orbits (polar non-synchronous orbits) were left unsampled. Both methods required external data on the wind directions which were obtained from cloud motions. The cloud motions provided coverage over larger areas than the other two methods because of the abundance of low-level cumuli.

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Donald P. Wylie
,
David Santek
, and
David O’C. Starr

Abstract

Operational satellite data from GOES-8 and GOES-9 were used to make stereoscopic measurements of cloud heights during the National Aeronautics and Space Administration’s Subsonic Aircraft: Contrail and Cloud Effects Special Study program. The stereoscopic data were used to differentiate between boundary layer wave clouds and cirrus in the mid- and upper troposphere. This separation was difficult to evaluate from radiometric data alone. Stereographic cloud height analysis provided a definitive result. The technique used for calculating cloud heights is described. GOES-8 and -9 data were better suited for stereoscopic measurements than data from previous satellites.

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W. Paul Menzel
,
Richard A. Frey
,
Hong Zhang
,
Donald P. Wylie
,
Chris C. Moeller
,
Robert E. Holz
,
Brent Maddux
,
Bryan A. Baum
,
Kathy I. Strabala
, and
Liam E. Gumley

Abstract

The Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System (EOS) Terra and Aqua platforms provides unique measurements for deriving global and regional cloud properties. MODIS has spectral coverage combined with spatial resolution in key atmospheric bands, which is not available on previous imagers and sounders. This increased spectral coverage/spatial resolution, along with improved onboard calibration, enhances the capability for global cloud property retrievals. MODIS operational cloud products are derived globally at spatial resolutions of 5 km (referred to as level-2 products) and are aggregated to a 1° equal-angle grid (referred to as level-3 product), available for daily, 8-day, and monthly time periods. The MODIS cloud algorithm produces cloud-top pressures that are found to be within 50 hPa of lidar determinations in single-layer cloud situations. In multilayer clouds, where the upper-layer cloud is semitransparent, the MODIS cloud pressure is representative of the radiative mean between the two cloud layers. In atmospheres prone to temperature inversions, the MODIS cloud algorithm places the cloud above the inversion and hence is as much as 200 hPa off its true location. The wealth of new information available from the MODIS operational cloud products offers the promise of improved cloud climatologies. This paper 1) describes the cloud-top pressure and amount algorithm that has evolved through collection 5 as experience has been gained with in-flight data from NASA Terra and Aqua platforms; 2) compares the MODIS cloud-top pressures, converted to cloud-top heights, with similar measurements from airborne and space-based lidars; and 3) introduces global maps of MODIS and High Resolution Infrared Sounder (HIRS) cloud-top products.

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