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Christopher M. Hayden
and
Timothy J. Schmit

One aspect of the modernized observational capability of the National Weather Service will be geostationary sounding of temperature and moisture from GOES-I, currently scheduled for launch in 1992. The capability has evolved from ten years of research with the VISSR (Visible Infrared Spin Scan Radiometer) Atmospheric Sounder (VAS). This article summarizes that evolution and describes the initial operational sounder products expected of GOESI. The effect on products caused by problems in meeting performance specifications are discussed. The outlook for follow-on sounders in the next series (circa 2000) of GOES is also briefly treated.

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John F. Dostalek
and
Timothy J. Schmit

Abstract

Statistics are compiled comparing calculations of total precipitable water (TPW) as given by GOES sounder derived product imagery (DPI) to that computed from radiosonde data for the 12-month period March 1998–February 1999. In order to investigate the impact of the GOES sounder data, these results are evaluated against statistics generated from the comparison between the first guess fields used by the DPI (essentially Eta Model forecasts) and the radiosonde data. It is found that GOES data produce both positive and negative results. Biases in the first guess are reduced for moist atmospheres, but are increased in dry atmospheres. Time tendencies in TPW as measured by the DPI show a higher correlation to radiosonde data than does the first guess. Two specific examples demonstrating differences between the DPI and Eta Model forecasts are given.

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Robert M. Rabin
and
Timothy J. Schmit

Abstract

In this note, the relationship between the observed daytime rise in surface radiative temperature, derived from the Geostationary Operational Environmental Satellites (GOES) sounder clear-sky data, and modeled soil moisture is explored over the continental United States. The motivation is to provide an infrared (IR) satellite–based index for soil moisture, which has a higher resolution than possible with the microwave satellite data. The daytime temperature rise is negatively correlated with soil moisture in most areas. Anomalies in soil moisture and daytime temperature rise are also negatively correlated on monthly time scales. However, a number of exceptions to this correlation exist, particularly in the western states. In addition to soil moisture, the capacity of vegetation to generate evapotranspiration influences the amount of daytime temperature rise as sensed by the satellite. In general, regions of fair to poor vegetation health correspond to the relatively high temperature rise from the satellite. Regions of favorable vegetation match locations of lower-than-average temperature rise.

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Donald W. Hillger
and
Timothy J. Schmit

Abstract

No Abstract available.

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William H. Raymond
and
Timothy J. Schmit
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Jun Li
,
Chian-Yi Liu
,
Peng Zhang
, and
Timothy J. Schmit

Abstract

Advanced infrared (IR) sounders such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) provide atmospheric temperature and moisture profiles with high vertical resolution and high accuracy in preconvection environments. The derived atmospheric stability indices such as convective available potential energy (CAPE) and lifted index (LI) from advanced IR soundings can provide critical information 1 ~ 6 h before the development of severe convective storms. Three convective storms are selected for the evaluation of applying AIRS full spatial resolution soundings and the derived products on providing warning information in the preconvection environments. In the first case, the AIRS full spatial resolution soundings revealed local extremely high atmospheric instability 3 h ahead of the convection on the leading edge of a frontal system, while the second case demonstrates that the extremely high atmospheric instability is associated with the local development of severe thunderstorm in the following hours. The third case is a local severe storm that occurred on 7–8 August 2010 in Zhou Qu, China, which caused more than 1400 deaths and left another 300 or more people missing. The AIRS full spatial resolution LI product shows the atmospheric instability 3.5 h before the storm genesis. The CAPE and LI from AIRS full spatial resolution and operational AIRS/AMSU soundings along with Geostationary Operational Environmental Satellite (GOES) Sounder derived product image (DPI) products were analyzed and compared. Case studies show that full spatial resolution AIRS retrievals provide more useful warning information in the preconvection environments for determining favorable locations for convective initiation (CI) than do the coarser spatial resolution operational soundings and lower spectral resolution GOES Sounder retrievals.

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Mathew M. Gunshor
,
Timothy J. Schmit
, and
W. Paul Menzel

Abstract

The Cooperative Institute for Meteorological Satellite Studies (CIMSS) has been intercalibrating radiometers on five geostationary satellites (GOES-8, -10, Meteosat-5, -7, and GMS-5) using a single polar-orbiting or low-earth orbiting satellite [NOAA-14 High-Resolution Infrared Radiation Sounder (HIRS) and Advanced Very High Resolution Radiometer (AVHRR)] as a reference on a routine basis using temporally and spatially collocated measurements. This is being done for the 11-μm infrared window (IRW) channels as well as the 6.7-μm water vapor (WV) channels. IRW results between AVHRR or HIRS and all five geostationary instruments show relatively small differences, with all geostationary instruments vicariously comparing to within 0.6 K. The WV results between HIRS and all five geostationary instruments show larger differences, with geostationary instruments separating into two groups: GOES-8, -10, and GMS-5 comparing within 1 K; Meteosat-5 and -7 comparing within 0.1 K; and the two groups comparing within 2.7 K.

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Christopher M. Hayden
,
Gary S. Wade
, and
Timothy J. Schmit

Abstract

Derived product imagery (DPI) is a method of presenting quantitative meteorological information, derived from satellite measurements, as a color-coded image at single-pixel resolution. Its intended use is as animated sequences to observe trends in the displayed quantities, which for the GOES-8 are total precipitable water, lifted index, and surface skin temperature. Those products are produced once per hour, over the continental United States and the Gulf of Mexico. This paper reviews the development of the DPI and details the algorithm used for GOES-8. The quality of the products is discussed, and an example is given. The greatest value of the DPI probably lies in comparing a sequence of the satellite product with a sequence derived from a numerical forecast. In this way, deviation of the forecast from reality is readily exposed.

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Xia L. Ma
,
Timothy J. Schmit
, and
William L. Smith

Abstract

A nonlinear physical retrieval algorithm is developed and applied to the GOES-8/9 sounder radiance observations. The algorithm utilizes Newtonian iteration in which the maximum probability solution for temperature and water vapor profiles is achieved through the inverse solution of the nonlinear radiative transfer equation. The nonlinear physical retrieval algorithm has been tested for one year. It has also been implemented operationally by the National Oceanic and Atmospheric Administration National Environmental Satellite, Data and Information Service during February 1997. Results show that the GOES retrievals of temperature and moisture obtained with the nonlinear algorithm more closely agree with collocated radiosondes than the National Centers for Environmental Prediction (NCEP) forecast temperature and moisture profile used as the initial profile for the solution. The root-mean-square error of the total water vapor from the solution first guess, which is the NCEP 12-h forecast (referred to as the “background”), is reduced approximately 20% over the conventional data-rich North American region with the largest changes being achieved in areas of sparse radiosonde data coverage.

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Youri Plokhenko
,
W. Paul Menzel
,
Gail Bayler
, and
Timothy J. Schmit

Abstract

The spatial and temporal continuity of the infrared measurements from the Geostationary Operational Environmental Satellite (GOES)-8 sounder data are investigated, and an experimental processing approach is presented. Spatial filtering and cloud detection are performed in a joint algorithm: the preparation of the data for sounding analysis starts with spatial smoothing, followed by cloud detection, followed by averaging the clear-sky (cloud free) subsamples. Analysis of the sounder images reveals the presence of coherent noise on large spatial scales in some of the spectral bands. Analysis of a temporal sequence of spatially smoothed sounder images reveals regions of unphysical hourly change likely induced by instrument noise. A nonlinear temporal–spatial filtering algorithm is presented and tested that improves the noise filtering for the sounder spectral measurements and the thermodynamical spatial and temporal consistency of the sounding retrievals in the troposphere.

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