Coupled model biases and extended‐range prediction skill during the onset phase of the Indian summer monsoon with different initializations related to land surface and number of observations

Abstract

In this study, we have analyzed the role of the initialization in the forecast of the monsoon onset phase beyond 10 days lead time (i.e., in the extended range) to understand the impact of displacement or shift in initial conditions in the extended‐range forecast. Two displacement errors are considered: (a) the initial error arising due to a change in land surface initial conditions and (b) the initial error arising due to a change in the number of observations. For the first part (a), we have analyzed and compared the difference in prediction skills in the United Kingdom Met Office (UKMO) GloSea5 forecasts run with two different land surface initial conditions (IC) configurations. In one configuration, the IC is prepared using a monthly land surface climatology; in the other configuration, it is based on daily land surface reanalysis. In the other part (b), we used the Indian Institute of Tropical Meteorology's Climate Forecast System (IITM_CFS) model with two different ICs (NCEP and NCMRWF differing in the number of observations over the Indian land region). Both runs indicate a shift in the initial condition, which manifests as displacement error. UKMO and IITM_CFS runs have the same land surface model when the corresponding twin experiments are compared in (a) and (b). Analysis of the initial displacement errors from these runs indicates that improving the realism in the land surface initial conditions can effectively modulate or change the surface meteorological fields in the prediction model during the onset phase. The result shows that the rotational and divergence components of the surface winds differ in the two sets of runs. Results also indicate that the difference in surface initialization manifests as differences in rotational and divergent kinetic energy. This could lead to a difference in the forecast of monsoon onset rain. Further analysis also suggests that the local land surface initial condition error, in addition to an error in large‐scale teleconnections, affects the monsoon onset forecast and its prediction skill in the extended‐range time‐scale.

Development of Indian summer monsoon precipitation biases in two seasonal forecasting systems and their response to large-scale drivers

“…ERA-interim reanalysis fields are used to provide the (unperturbed) initial conditions and perturbations between the members are produced through the use of a stochastic kinetic energy backscatter scheme (Bowler et al, 2009). An upgrade to the soil moisture initialisation (described by Gautam et al, 2023) was implemented in 2019 so GloSea6 includes this upgrade whereas the version of GloSea5 evaluated here does not.…”