To improve weather forecasts and public safety, the NSF supports basic research on observational systems, analysis techniques, and understanding of phenomena. Ongoing research on new observational systems includes techniques for using cosmic ray data to derive soil moisture and using distributed, short-wavelength radar systems for small-scale severe weather observations. Major efforts to understand tornadoes and hurricane genesis are ongoing, and aim to improve the ability of weather forecasters to relay high-impact weather information to the public.
Continually improving the accuracy, timeliness, and accessibility to prediction services is largely a result of research and development both within the NWS and externally from universities and private corporations. NCEP's Environmental Modeling Center (EMC) develops, enhances, and maintains complex data assimilation and numerical modeling software systems that span the globe. The computer models and other numerical forecast products developed by the EMC provide the basic guidance that NCEP and WFO meteorologists use in making weather and climate predictions. The EMC uses advanced modeling methods developed both internally and cooperatively with universities, the international scientific community, NESDIS, NOAA laboratories, and other government agencies. As an example, EMC is a partner in the National Aeronautics and Space Administration (NASA)/NOAA Joint Center for Satellite Data Assimilation (JCSDA), designed to accelerate the use of research and operational satellite data in NCEP operational models. The EMC integrates research and technology through collaborative model development projects. These interactions serve as an efficient and effective interface between NCEP and the scientific community that develop ideas, numerical models, and forecast techniques to implement model improvements and improve NWS products. The EMC conducts applied research and technology transfers and publishes research results in various media for dissemination to the world meteorological, oceanographic, and climate community. EMC also participates in ongoing interactive research programs such as NOAA’s Hurricane Forecast Improvement Project (HFIP) and the community Weather Research and Forecast (WRF) model. Furthermore, EMC is participating in the Winter Storm Reconnaissance Program in the Pacific through targeted observations aimed at improving forecasts across the country. In addition, at NCEP, led by the EMC, the ensemble approach has been applied operationally at the short, medium and extended range. EMC efforts with collaborative development resulted in improvements to mesoscale and global models, as well as advancements in hurricane track forecasts, climate forecasts, and air quality forecasts.
Center for Satellite Applications and Research (STAR)
STAR is the science arm of NESDIS. Its mission is to create satellite data products using observations of the land, atmosphere, and ocean and transfer those products from research into routine operations. In addition, STAR supports the assimilation of the data from new satellite instruments into NOAA’s numerical prediction models. STAR also calibrates the Earth-observing instruments of all NOAA satellites to provide reliable measurements for assessing the current conditions on Earth in a timely manner, predicting changes in conditions and studying long-term trends in the environment.
STAR investigates how to develop satellite datasets that can be used to assess conditions on the Earth in a timely manner, predict changes, and study long-term trends in the environment. STAR works to create products that monitor atmospheric, oceanic, and environmental hazards; enhance NOAA’s infrastructure for remote sensing; reduce the risk of launching new, untested, and very expensive satellites and sensors; and expand its support to users.
Hurricane Applications of Lightning Measurements. The next-generation NOAA geostationary satellites, starting with the GOES-R, will be capable of measuring total lightning. Lightning causes between $4 and $5 billion in losses each year in the civilian sector with about 47 deaths and 303 injuries per year. Although ground-based lightning measurements have been available for several years, this will be the first time that these data are available with high time resolution over the open oceans where hurricanes form and grow. The improvements in the prediction of hurricane genesis and intensification have not kept pace with those for track forecasting. The lightning observations have the potential to provide a new source of information for tropical cyclone forecasting.
Research in FY 2011 will continue to focus on the continued use of a new ground-based lightning network that can provide some information of lightning activity over the tropical oceans. The World Wide Lightning Locator Network (WWLLN) provides estimates of only about 25 percent of the lightning activity compared to what will be available from GOES-R, but it provides a first look at the forecast potential of this new data source. The WWLLN data is being used to examine the relationship between lightning distributions and hurricane formation and intensification in combination with other factors known to be important such as sea surface temperature and atmospheric vertical wind shear. Preliminary results for the Atlantic are very encouraging and show the potential to use lightning information to improve the prediction of rapid intensity change, which is an especially challenging forecast problem. Ongoing research will generalize this study to tropical cyclones in other ocean basins outside of the Atlantic and the development of experimental rapid intensification forecast algorithms that utilize the WWLLN data.
This work has the potential to help improve hurricane forecasts. The ability to better forecast how strong a storm will be when it reaches the coast will help to improve the reliability of hurricane watches and warnings, which are important for evacuations and other mitigation activities.
Precipitation Estimation from Satellites. Precipitation estimation data from satellites provide a critical supplement to other sources of rainfall information for flood and flash flood forecasting, water resources applications, and myriad other uses—in many parts of the world, satellites represent the only reliable source of rainfall information. Infrared and visible data from geostationary weather satellites provide high-resolution, rapidly updated rainfall information for hazardous weather applications. More accurate estimates of rainfall can be derived from microwave-frequency data onboard polar-orbiting satellites, but their less-frequent updating makes them more suitable for longer-term water monitoring.
In FY 2010 and into FY 2011, NOAA expects to complete the transition of three research products to operational status and will develop the algorithms for the next generation of NOAA’s GOES. The three products are current rainfall rate, which will build on a nearly 20-year legacy of automated satellite rain rate products; three-hour rainfall potential, which will be a brand new product predicting rainfall from satellite data; and three-hour rainfall probability—the probability of measurable rainfall during the next three hours. In addition, modifications to the current-generational algorithms will be explored in order to better serve the users of these data.
Microburst Assessment from Satellites. A suite of products was developed and evaluated to assess hazards presented by convective storms and associated high winds to aircraft in flight derived from the current generation of GOES. The existing suite of GOES microburst products employs the GOES sounder to calculate risk based on conceptual models of favorable environmental profiles for convective wind generation. Large output values of the microburst index algorithms indicate that the ambient thermodynamic structure of the troposphere fits the prototypical environment for each respective microburst type (i.e. Wet, Hybrid, Dry, etc.). In accordance with new diagnostic nowcasting products, the Microburst Windspeed Potential Index (MWPI), and a multichannel GOES imager microburst risk product were recently developed and experimentally implemented. These products are designed to infer attributes of a favorable microburst environment that include large temperature and moisture changes with height in the atmosphere. These conditions foster intense convective downdrafts due to evaporational cooling as precipitation descends in the sub-cloud layer.
The GOES imager microburst risk product is based on a multichannel algorithm in which output brightness temperature difference is proportional to microburst potential. This product provides a higher spatial (4 km) and temporal (30 minutes) resolution than is currently offered by the GOES sounder microburst products (10 km, 60 minutes) and thus, provides useful information to supplement the sounder products in the convective storm nowcasting process. In addition, this imager product provides microburst risk guidance in high latitude regions, especially north of latitude 50°N, where existing sounder coverage is not available. FY 2011 research will continue to focus on intercomparison, validation, and refinement of the GOES microburst products as well as training in the operational use of the products.