IMDAA: High Resolution Satellite-era Reanalysis for the Indian Monsoon Region

Abstract

A high resolution regional reanalysis of the Indian Monsoon Data Assimilation and Analysis (IMDAA) project is made available to researchers for deeper understanding of the Indian monsoon and its variability. This 12 km resolution reanalysis covering the satellite-era from 1979 to 2018 using 4D-Var data assimilation method and the UK Met Unified Model is presently the highest resolution atmospheric reanalysis carried out for the Indian monsoon region. Conventional and satellite observations from different sources are used, including Indian surface and upper air observations, of which some were not used in any previous reanalyses. Various aspects of this reanalysis, like quality control and bias correction of observations, data assimilation system, land surface analysis, and verification of reanalysis products, are presented in this paper. Representation of important weather phenomena of each season over India in the IMDAA reanalysis verifies reasonably well against India Meteorological Department (IMD) observations and compares closely with ERA5. Salient features of the Indian summer monsoon are found to be well represented in the IMDAA reanalysis. Characteristics of major semi-permanent summer monsoon features (e.g., Low-level Jet and Tropical Easterly Jet) in IMDAA reanalysis are consistent with ERA5. The IMDAA reanalysis has captured the mean, inter-annual, and intra-seasonal variability of summer monsoon rainfall fairly well. IMDAA produces a slightly cooler winter and a hotter summer than the observations; the reverse for ERA5. IMDAA captured the fine-scale features associated with a notable heavy rainfall episode over complex terrain. In this study, the fine grid spacing nature of IMDAA is compromised due to the lack of comparable resolution observations for verification.

Katabatic and convective processes drive two preferred peaks in the precipitation diurnal cycle over the Central Himalaya

“…Over the Tibetan Plateau, ERA5 captures the broad mid‐to‐late‐afternoon peak, but IMDAA has significant difficulty, tending to place precipitation around local midnight, but with a large spatial variability. Model precipitation here is typically produced by the underlying large‐scale microphysics schemes (Sharma et al ., 2021), and so is perhaps not related to IMDAA's convective scheme, rather the fact that it assimilates substantially fewer observations from outside India than does ERA5 (Rani et al ., 2021).…”

Monthly Average Rainfall Forecasting Based On An Adaptive Neuro-Fuzzy Inference System in Upper Brahmani Basin, Odisha, India

“…The period of data, units, sources, and spatial resolutions are given in Table 1. IMDAA (Indian Monsoon Data Assimilation and Analysis) is a national atmospheric reanalysis that spans the Indian subcontinent (Indirarani et al 2021). The IMDAA is the outcome of a partnership between the United Kingdom's Met O ce (MO), India's National Centre for Medium-Range Weather Forecasting (NCMRWF), and the India Meteorological Department (IMD).…”

Numerical Simulation of a Clear Air Turbulence (CAT) Event Over Northern India Using WRF Modelling System

“…ECMWF ERA-Interim (ECMWF 2011), IMDAA (Rani et al 2021), and NGFS (Prasad et al 2016) data sets were also used in this study to analyze the CAT event. The specifications of all the data utilized in this study are stated in Table 1.…”