A Moisture In-Flux Storm Tool for Tropical Cyclone Analysis and Forecasting

The negative impact of mid-level dry air is commonly monitored by operational centers for their forecasts of tropical cyclone (TC) formation and intensification. Dry air entering the TC environment inhibits convection, enhances cold downdrafts, and contributes to storm asymmetry, all of which are not favorable for TC intensification. The most common tools currently used by operational forecasters to detect dry-air intrusions are total precipitable water (TPW), layered precipitable water (LPW), and water vapor imagery. All of these provide some information about the location of dry air but do not provide quantitative measurements of dry air fluxes. Also, TPW is heavily influenced by low-level water vapor, and water vapor imagery does not provide moisture information from a consistent layer, thus both do not necessarily reflect moisture flux changes at mid-levels. The Moisture In-Flux Storm Tool (MIST) has been developed at CIRA to provide quantitative estimates of dry air intrusions in the TC near-environment. MIST uses mixing ratio profiles from the Advanced Technology Microwave Sounder (ATMS) on-board the Joint Polar Satellite System (JPSS) Suomi National Polar Orbiting Partnership (S-NPP) satellite, processed with Microwave Integrated Retrieval System (MiRS). MiRS is an all-weather retrieval system that is currently providing better temperature and moisture retrievals in TC environment than global numerical models. MIST winds are either derived from ATMS-MiRS temperature retrievals through balance constraints or taken from Global Forecast System (GFS) model. MIST is planned to be further expanded to run on all microwave sounders for which MiRS retrievals are produced operationally. That includes Advanced Microwave Sounding Units (AMSU) on NOAA-18 and -19, and MetOP-A and -B, as well as ATMS on-board JPSS-1. Several case studies demonstrating how MIST can provide additional information to forecasters will be presented together with a discussion of future application development and implementation. In addition, preliminary results of using ATMS-MiRS data to track warm core changes related to rapid intensification (RI) events and the possibility of using MIST-based predictors in statistical TC-intensity forecast models, including the Statistical Hurricane Intensity Prediction Scheme (SHIPS) and RI Index will be discussed.

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.