1. NWS Forecast Office Assessment of GOES Sounder Atmospheric Instability
Summer 99 Forecaster assessment of usefulness of changes in hourly LI, CAPE, & CINH product for predicting location/timing of thunderstorms
There were 248 valid weather cases.
- Significant Positive Impact (30%)
- Slight Positive Impact (49%)
- No Discernible Impact (19%)
- Slight Negative Impact (2%)
- Significant Negative Impact (0)
From 19 July through 30 August 1999, the NWS Office of Meteorology conducted daily assessments of the operational value of the GOES-8 and GOES-10 sounder products. Thirty-seven NWS forecast offices, four national centers, and the NESDIS Satellite Analysis Branch participated in the evaluation, providing a total of 635 responses primarily via the World Wide Web. Forecasters used the sounder products to heighten their awareness of the potential of a wide variety of weather events, including severe thunderstorms, monsoon precipitation, and flash floods.
The figure summarizes some of the National Weather Service forecast responses obtained during the assessment period. Overall, forecasters found that the sounder products provided valuable information, especially with regard to moisture distributions. The products indicated temporal and spatial gradients unavailable from any other source. The forecasters indicated that in over 79% of all active weather situations, the use of GOES sounder products led to the issuance of improved forecasts.
Schmit et al. Weather and Forecasting. February 2002
Figure from the National Weather Service, Office of Services

2. Effect of GOES (sounder cloud) data on 3-h RUC cloud forecasts
3h 20km RUC cloud-top fcst
w/ GOES cloud assimilation
Verification
Cloud-top pressure
based on NESDIS product
Effect of GOES (sounder cloud)
data on 3-h RUC cloud forecasts
“much improved cloud forecasts”
1800 UTC
Tues 2 Oct 2001
These figures show the improve of short-term forecasts (in the Rapid Update Cycle model) when the GOES sounder cloud-top information product is assimilated.
The circles show 2 areas of improved cloud forecasts.
From Stan Benjamin:
Update to previous Notice of Intent to Change
- 20-km RUC
- Scheduled for implementation 16 April 2002
pending CAFTI approval
Stan Benjamin – NOAA/FSL
3h 40km RUC cloud-top fcst
No GOES cloud assimilation

3. Data Assimilation -- Satellite Data Improving Forecasts
The impact of five satellite data types and five in-situ data types in the Eta Data Assimilation/Forecast System (EDAS) was recently completed for 10-day time periods during three seasons (spring, summer and winter). A fall time period was not available due to a lack of consecutive data. The satellite data types included GOES clear air precipitable water (PW) as well as infrared cloud drift winds and water vapor cloud top winds, SSM/I marine vertically-integrated PW, and TOVS marine temperature retrievals down to cloud top. The in-situ data types included all the components of RAOB data, ACARS temperature and winds, and surface land observations. Overall, the results established that the satellite data types were of comparable importance to the in-situ data types for the time periods studied. During summer, satellite PW data were the most important data type in the EDAS, even for state variables other than moisture.
Having identified the impact of multiple satellite data types in the EDAS for several seasons, work began on identifying the impact of geostationary data versus polar orbiting data in the EDAS for multiple seasons. The case studies chosen include 15-day periods during the four seasons. Accumulated differences between the experimental runs (simulations with data denied) and control run (simulation with all available data) are then analyzed to demonstrate the forecast impact of these data types in the EDAS. The figure below illustrates the positive forecast impact (%) of GOES and POES data in the EDAS on standard meteorological state variables for the seasons thus far evaluated (fall 2001 and winter 2001/2002). The GOES data provides a more positive impact on the EDAS forecast for nearly all levels and fields.
Positive forecast impact (%) of both GOES and POES data in the EDAS (Eta Data Assimilation/Forecast System) on standard meteorological state variables for the seasons thus far evaluated (fall 2001 and winter 2001/2002).

4. Satellite winds on GFDL Forecasts
Hurricane examples.
Soden, Brian J., Christopher S. Velden, Robert E. Tuleya, 2001: The Impact of Satellite Winds on Experimental GFDL Hurricane Model Forecasts. Monthly Weather Review: Vol. 129, No. 4, pp. 835–852.
GFDL is Geophysical Fluid Dynamics Laboratory
GOES-8 1km visible
Soden et al.
Former National Hurricane Center director Robert Sheets once said that if he had only one tool to do his forecasting job, it would be the geostationary weather satellite.