Coupled Model Biases during the Onset Phase of the Indian Summer Monsoon with Different Initializations Related to Land Surface and number of Observations
Abstract
Monsoon onset over Kerala (MOK) marks India's beginning of the rainy season. Prediction and outlooks of monsoon onset are crucial for agriculture planning. The MOK is associated with changes in the large-scale dynamical parameters and local moisture parameters. The differential heating of land and sea is the primary cause that drives the ISM. However, several studies show the sensitivity of onset to different meteorological and climatic factors. It is not well known how the land surface initial states impact the forecast of the onset in the operational forecast models.In this study, we have analyzed the role of the initialization in the forecast of the monsoon onset phase beyond ten 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 has 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 IITM_CFS model with two different ICs (NCEP and NCMRWF differing in the number of observations over Indian land region). Both runs indicate a shift in initial condition which manifests as displacement error. Both 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 the difference in the land surface initialization process 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 component 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. Reference- Joseph, Susmitha, et al. "Development and evaluation of an objective criterion for the real-time prediction of Indian summer monsoon onset in a coupled model framework." Journal of Climate 28.15 (2015): 6234-6248. Acknowledgment- The authors acknowledge the data support and research funding support for G Martin from the Met Office under the Weather and Climate Science for Service Partnership (WCSSP) India, a collaborative initiative between the Met Office, supported by the UK Government's Newton Fund, and the Indian Ministry of Earth Sciences (MoES).- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.A15B..07G