Advanced IR measurements improve hurricane forecasts
Using numerical modeling, scientists can improve hurricane forecasts and provide more accurate path and intensity predictions to save lives and prevent property damage. One factor limiting forecast quality is the lack of information about the amount of water vapor in the atmosphere. Varying greatly over short distances and time periods, water vapor travels rapidly and provides energy in storm development. Atmospheric-water-vapor information is one of the key parameters needed in the regional numerical-weather-prediction (NWP) model for accurate hurricane forecasting.
Today's hyperspectral IR sounders (which allow data collection in hundreds or even thousands of spectral bands), such as the Atmospheric Infrared Sounder (AIRS)1 onboard NASA's Earth Observing System (EOS) Aqua platform and the Infrared Atmospheric Sounding Interferometer (IASI) onboard the European Space Agency's Meteorological Operational Platform (METOP)-A satellite, provide unprecedented global, vertical atmospheric temperature and moisture distributions with high accuracy. Through an advanced retrieval technique,2 critical information can be extracted from AIRS radiance measurements by assimilation of the spatial and vertical water-vapor distribution around a hurricane into a regional NWP model, thereby improving path and intensity forecasts.3,4
We explored assimilation by employing the high-spatial-resolution (~13.5km) moisture profiles retrieved from AIRS to initialize and analyze hurricane development. We used a recently developed, advanced ensemble-data-assimilation system to combine vertical atmospheric-water-vapor profiles from AIRS with the Weather Research and Forecast model developed by the National Center for Atmospheric Research. This technique has unique advantages in terms of initialization of the environment of tropical cyclones, including the use of weather-dependent multivariate-forecast error estimates to correct for ‘unobserved variables.’ We subsequently examined hurricane-path and intensity forecasts with and without inclusion of the AIRS water-vapor profiles. We found that using the latter significantly improves hurricane-path forecasts (see Figure 1) as well as intensity predictions. We also demonstrated the relative importance of water-vapor with respect to temperature measurements in hurricane modeling.
We are currently examining additional hurricane cases to better document the improvements. We will also study IR data from other satellite platforms (e.g., IASI). With an advanced IR sounder in a geostationary orbit, the large-scale spatial and temporal variability of water-vapor distributions can be captured,5 which is critical for further improvements of hurricane forecasts, particularly of their genesis, rapid intensification, path, and intensity.
Jun Li researches advanced imager/sounder data processing and product generation. He received several international scientific awards during his career. He has authored or co-authored more than 60 science papers in peer-reviewed journals, as well as more than 100 proceedings papers.