Investigating moist dynamics on sub-seasonal scales in the IMDAA reanalysis

The study aims to investigate the moist dynamics that govern tropical precipitation variability at sub-seasonal timescales during the boreal summer monsoon season over the Indian region. For this purpose, we have used indigenously generated long-term (1981-2020) regional reanalysis data from the National Center for Medium-Range Weather Forecasting (NCMRWF) known as Indian Monsoon Data Assimilation and Analysis (IMDAA). Several process-oriented diagnostics (PODs) (e.g. column water vapor (CWV)-rainfall association; moist static energy budget (MSE), and Gross Moist stability (GMS)) are employed to examine the role of the vertical structure of specific humidity (q) and large-scale vertical motion (w) in representing some of the crucial moist processes necessary for tropical convection. Results are validated using the ERA5 reanalysis and the relative roles are quantified. Our examination suggests that despite having systematic biases in key variables responsible for monsoon convection, several aspects (mean state, vertical and space-time structures) of the sub-seasonal variability are captured well in the regional reanalysis system, which is encouraging. Nevertheless, diagnostics also reveal that the moisture-convection feedback mechanism is relatively weaker in IMDAA reanalysis, which is evident from the weak CWV-rainfall association. For instance, for lower CWV thresholds (<55 mm), IMDAA overestimates and produces excess rainfall over CI. Applying the vertical MSE budget to the IMDAA data demonstrates that the moisture and MSE advection terms act as leading components, suggesting strong predictability (∼7-10 days) signals in horizontal advection of moisture and MSE. The study underscores the limitation of IMDAA reanalysis vertical distribution of moisture in the time evolution of active and break monsoon phases. Further, study emphasizes the need for PODs in examining the fidelity of IMDAA reanalysis. It indicates the merits and demerits of IMDAA for a better understanding of the monsoon processes and model development.