Influence of ASCAT soil moisture on prediction of track and intensity of landfall tropical cyclones

Abstract

ABSTRACT The current study attempted to evaluate the impact of Soil Moisture (SM) initial conditions in a regional NWP system on the simulation of land falling cyclones over North Indian Ocean region. SM initial conditions used in this study are created using a simplified EKF based LDAS, in which satellite derived SM information is also used. Here, two sets of numerical experiments using regional NWP system are performed with two different sets of SM initial conditions. The CTL (assimilated only surface level observations in LDAS) and ASCAT (assimilated satellite derived SM plus observations used in CTL) experiments are performed to understand the impact of SM initial conditions in NCUM-R NWP system. The atmospheric initial conditions for both experiments are prepared through 4DVAR assimilation technique. This study shows that high resolution regional model initialized with improved SM initial conditions created using satellite observations could improve structure, intensity, track and evolution of the storms. The positive values of humidity Jacobians are noticed over the regions affected by storms mainly in ASCAT. The evolution of vorticity tendency and convergence profiles is well differentiated in ASCAT as the system moved from higher to lower intensity stage or vice versa, but that pattern is not observed in CTL. The value of static stability indices is varying with strength of cyclones, which are well represented in ASCAT and are also well matched with observations. The evolution of magnitude of diabatic heating in and around the storm core region is more realistic in ASCAT than CTL. The moisture budget terms are improved in ASCAT, the contribution of moisture convergence (evaporation) to the precipitation is more over the oceanic (land) region before and after landfall of storm. The study deduced that accurate SM initial conditions are essential for better prediction of structure and intensity of high impact weather events.