Engineering topics

Haines, S. L.

Publications and source records attributed to Haines, S. L..

5 records

NASA NTRS2004

The Geostationary Operational Environmental Satellite (GOES) Product Generation System

The Geostationary Operational Environmental Satellite (GOES) Product Generation System (GPGS) is introduced and described. GPGS is a set of computer programs developed and maintained at the Global Hydrology and Climate Center and is designed to generate meteorological data products using visible and infrared measurements from the GOES-East Imager and Sounder instruments. The products that are produced by GPGS are skin temperature, total precipitable water, cloud top pressure, cloud albedo, surface albedo, and surface insolation. A robust cloud mask is also generated. The retrieval methodology for each product is described to include algorithm descriptions and required inputs and outputs for the programs. Validation is supplied where applicable.

Haines, S. L.↗

NASA NTRS2004

Application of Satellite-Derived Land Surface Temperature to Minimum Temperature Forecasting

Satellite-derived land surface temperature (LST) is studied for the purpose of understanding regional skin temperature dependency and variability, and its relationship to corresponding, site-specific air temperature. Skin temperature is highly correlated with surface-air temperature although it differs depending on land surface characteristics, terrain, and atmospheric conditions on a diurnal and seasonal scale. The high temporal resolution of the Geostationary Operational Environmental Satellite (GOES) -12 sounder is used to compare the diurnal cycles of LST and surface-air temperature. The minimum for both temperatures occurs near sunrise and LST is found to agree closely with surface-air temperatures a period of hours before sunrise on clear sky nights. The Moderate Resolution Imaging Spectroradiometer (MODIS)-derived LST renders more horizontal temperature structure - with its high spatial resolution (1 km at nadir) compared to the GOES-12 sounder (10 km). Nighttime MODIS-derived LST is extrapolated to the time of minimum temperature for a number of case study days and these are grouped by season and atmospheric conditions. These composites show that the variation in LST mirror the variation in minimum surface-air temperature under similar conditions.

Jones, P. R.↗

NASA NTRS2004

Spatially Varying Spectrally Thresholds for MODIS Cloud Detection

The EOS science team has developed an elaborate global MODIS cloud detection procedure, and the resulting MODIS product (MOD35) is used in the retrieval process of several geophysical parameters to mask out clouds. While the global application of the cloud detection approach appears quite robust, the product has some shortcomings on the regional scale, often over determining clouds in a variety of settings, particularly at night. This over-determination of clouds can cause a reduction in the spatial coverage of MODIS derived clear-sky products. To minimize this problem, a new regional cloud detection method for use with MODIS data has been developed at NASA's Global Hydrology and Climate Center (GHCC). The approach is similar to that used by the GHCC for GOES data over the continental United States. Several spatially varying thresholds are applied to MODIS spectral data to produce a set of tests for detecting clouds. The thresholds are valid for each MODIS orbital pass, and are derived from 20-day composites of GOES channels with similar wavelengths to MODIS. This paper and accompanying poster will introduce the GHCC MODIS cloud mask, provide some examples, and present some preliminary validation.

Haines, S. L.↗

NASA NTRS2000

Comparison of Daily Total Precipitable Water From Satellite and Model Reanalysis Fields

Previous studies have shown that there is fairly good agreement between the monthly values of total precipitable water (TPW) from the NVAP data set, a multi satellite and radiosonde merged data product, and the NCEP reanalysis TPW data. However, there are regions and time periods where significant differences between the data sets are found in the monthly mean TPW time series and period of record trends. To better understand these differences seen in the monthly data values, the daily mean TPW data are examined. Possible contributions to the TPW differences such as data quality of the individual NVAP data set components associated with missing or irregular daily values are addressed. Also, effects associated with the weighting of the individual NVAP data set components to form a merged product are considered. The daily variations in TPW exhibited by each data set are also quantified and compared between the data sets.

Jedlovec, Gary J.↗

NASA NTRS2000

Evaluation of Skin Temperatures Retrieved from GOES-8

Skin temperatures derived from geostationary satellites have the potential of providing the temporal and spatial resolution needed for model assimilation. To adequately assess the potential improvements in numerical model forecasts that can be made by assimilating satellite data, an estimate of the accuracy of the skin temperature product is necessary. A particular skin temperature algorithm, the Physical Split Window Technique, that uses the longwave infrared channels of the GOES Imager has shown promise in recent model assimilation studies to provide land surface temperatures with reasonable accuracy. A comparison of retrieved GOES-8 skin temperatures from this algorithm with in situ measurements is presented. Various retrieval algorithm issues are addressed including surface emissivity

Suggs, Ronnie, J.↗