3. Research Capability
SMCD's Branches exploit a number of science and technology areas in fulfilling its broad mission of transforming raw satellite observations into the accurate, quantitative information that is needed to predict weather, monitor climate, and detect environmental hazards. The science and technology area of each of SMCD's branches are described here.
Operational Products Development Branch
The Operational Products Development Branch performs most of the Division's transition of research to operational products. This includes the sounding products for the POES ATOVS system and the GOES sounder, as well as the atmospheric motion vectors (winds) derived from tracking cloud and water vapor features in sequential satellite images. The Branch also develops GOES satellite products for use by weather service field meteorologists in nowcasting and short range weather forecasts, such as the Wet Microburst Severity Index (WMSI) and other atmospheric stability products. It also works closely with the NESDIS Office of Satellite Data Processing and Distribution to ensure reliable software for operational production of satellite products and provide timely science fixes for in- flight instrument problems.
Transition of Sounding Products to Operations
SMCD has supported the NESDIS POES sounding program since 1966 and the GOES sounders since 1994. SMCD has transitioned all new sounding systems and upgrades that STAR has developed into operations. It continues to monitor, validate, and improve the quality of the basic temperature and moisture profiles derived from the sounder observations, and provide science support and troubleshooting for many instrument anomalies. The soundings are distributed to weather services throughout the world via the World Meteorological Organization's (WMO) Global Telecommunications System (GTS). In October 2002, the GOES sounder retrieved products were added to the NWS Advanced Weather Interactive Processing System (AWIPS). SMCD is preparing for the next generation of sounders on the METOP, NPP, and NPOESS satellites.
Atmospheric Motion Vectors
Atmospheric motion vectors (AMVs) derived from a sequence of satellite images are an important source of global wind information, particularly over the world's oceans and more remote continental areas where conventional weather observations are lacking in time and space. These data are routinely used by the major NWP centers in the world and assimilated into regional and global NWP models. These data are also made routinely available to NWS forecasters responsible for providing the public with day-to-day weather forecasts. These products are distributed over the GTS and the NWS's AWIPS.
SMCD transitions to operational production the AMV algorithms developed by STAR scientists. AMVs have been typically derived from the GOES imagery providing approximately full disk coverage from 60S to 60N. The current operational GOES wind products include infrared (IR) cloud-drift winds, water vapor (WV) motion winds, and visible ( VIS) cloud-drift winds. More recently, SMCD has transitioned a MODIS wind algorithm to operations.
Precipitation information is critical for a wide variety of applications, ranging from predicting flash floods to analyzing long- term precipitation patterns for agriculture and water resource concerns. Rain gauges have traditionally been the primary source of precipitation data, but their coverage is quite poor, and radar observations have their own limitations.
To support operational forecasters in the US and the NOAA Weather and Water Goal, SMCD has developed and produces the Hydro-Estimator (H-E) - automated estimates of rainfall for the entire Continental United States (CONUS) based on infrared window cloud-top temperatures and supplementary information from numerical weather models. The H-E is available operationally to NWS forecasters via the AWIPS, and H-E fields are produced worldwide (using data from the three GOES satellites and the two Meteosat satellites) and distributed via the Internet on an experimental basis. In addition, a number of experimental algorithms are under development and/or evaluation at NESDIS, including the GOES Multi-Spectral Rainfall Algorithm (GMSRA), which uses data from four GOES Imager channels to extract additional information about cloud properties that are pertinent to rainfall, and the Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR) which also uses data from multiple GOES Imager channels and calibrates against microwave rain rate estimates in real-time.
Aviation hazards include volcanic ash, in-flight icing, and fog and low ceilings. An encounter with an airborne volcanic ash cloud can result in millions of dollars in damage to jet engines and the airframe, as well as the risk of engine stalls, so avoidance is critical. In-flight icing results in significant aerodynamic drag, and causes 5-10% of all fatal air crashes for smaller, general aviation and commuter class aircraft. Fog and low ceilings are a major reason for aviation delays, resulting in >$2B annual economic loss, and account for about 25% of fatal aviation and maritime accidents.
SMCD scientists have developed and continue to improve the following aviation hazards products:
Data, algorithms, and images presented on STAR websites are intended for experimental use only and are not supported on an operational basis. More information