Use of JPSS ATMS-MIRS Retrievals to Improve Tropical Cyclone Intensity Forecasting

The Suomi National Polar-Orbiting Partnership satellite (SNPP), launched in October 2011, is part of the Joint Polar Satellite System (JPSS), the next generation polar-orbiting operational environmental satellite system. SNPP carries five instruments, including the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Advanced Technology Microwave Sounder (ATMS). The time scale of tropical cyclones (TC) track and intensity changes is on the order of 12 hours, which makes JPSS instruments well suited for the forecasting of these parameters. Two basic methods exist for improving TC forecasts with SNPP. The first is to assimilate data in numerical forecast models, and the second is to improve analysis and statistical post-processing forecast products. Our group is developing the TC Maximum Potential Intensity (MPI) application using the second approach.

The MPI estimate algorithm uses temperature and moisture retrievals from ATMS in the near-storm environment to improve intensity analysis and forecasting. While tropical cyclone track errors have improved dramatically over the past few decades, the ability to forecast intensity changes has improved much more slowly. An especially difficult but very important forecast problem is predicting rapid changes in tropical cyclone intensity. Improving these forecasts is one of the highest priorities within NOAA. In the last 5 years statistical intensity forecast models, the Statistical Hurricane Intensity Prediction Scheme (SHIPS) and the Logistic Growth Equation Model (LGEM), have generally outperformed dynamical models in intensity prediction, especially for forecast times greater than 48 hours. The accuracy of both SHIPS and LGEM, as well as the Rapid Intensification Index (RII) tool, critically depends on the accuracy of the MPI estimate. Operational versions of LGEM and RII use statistical MPI calculated from sea surface temperature (SST) only. ATMS, the successor to the Advanced Microwave Sounding Unit (AMSU), provides high-resolution sounding data with very small gaps between consecutive orbits. In addition, ATMS data are processed with the new Microwave Integrated Retrieval System (MIRS) which provides simultaneous temperature and moisture profile retrievals. This makes it possible to obtain from the data MPI estimates which previously could only be done using model fields. We investigate the use of ATMS-MIRS retrievals as input into the MPI algorithm to improve RII and SHIPS/LGEM forecast. The MPI algorithm was adapted for use with ATMS temperature and moisture profiles, and the experimental version of MPI estimates is running in near real time and is available at the CIRA TC Real-Time page, http://rammb.cira.colostate.edu/products/tc_realtime/index.asp. Preliminary statistics show the improvement of the Brier Skill Score and bias for RII forecast for both Atlantic and West Pacific basins when using ATMS-based MPI, with up to 3.1% bias decrease for the Atlantic basin. In addition, the LGEM intensity forecast for the East Pacific basin is improved for 0-48 hr forecast times with the use of ATMS-based MPI. The results of global MPI estimates with ATMS-MIRS input, and the results of the comparison of ATMS temperature and moisture profiles to dropsondes and GFS profiles in the vicinity of TCs will be presented together with the discussion of the implications for SHIPS/LGEM and RII forecasts.

Disclaimer: The views, opinions, and findings contained in this article are those of the authors and should not be construed as an official National Oceanic and Atmospheric Administration (NOAA) or U.S. Government position, policy, or decision.