Although the Climate Forecast System version‐2 model simulates an overall dry bias in boreal summer mean rainfall over Indian land, the deficiency is particularly prominent over northwest India. The prevailing dryness limits the interannual prediction skill of the Indian summer monsoon rainfall and its subseasonal variability because of poor representation of latent heating due to weak moist convection and the resulting circulation. Here, we show that land‐surface vegetation plays a crucial role in determining the dry bias in the Climate Forecast System version‐2 model. We replaced the land‐surface model's existing vegetation type over India with that derived from recent satellite‐based observations. The modifications helped improve the seasonal mean rainfall over northwest India by 6%. The improvements are especially noticeable during the monsoon season's onset (14%) and withdrawal (10%) phases. Simulations with modified vegetation advanced the onset dates over Kerala, central India, and northwest India closer to that observed. This improvement in the mean onset dates is most prominent over northwest India. Such an improvement was possible owing to a substantial reduction of long rainfall hiatus after onset over Kerala in the simulation with modified vegetation. The modification makes the spatial orientation of monsoon onset isochrones more realistic. We found that although the vertically integrated moisture flux is eastward over most of the Indian monsoon region during its onset phase, its intraseasonal components are westward. In other words, at the intraseasonal time‐scale, moisture propagates against the prevailing low‐level westerlies. This intraseasonal eddy moisture transport advances onset from the Bay of Bengal toward the far northwest parts of the Indian land. The representation of such intraseasonal moisture seepage in the model updated with satellite‐derived vegetation types was improved. Our study indicates the necessity of greater attention to land‐surface representations for improved predictions of onset dates.

Land surface utilization in the Indian subcontinent has undergone
dramatic transformations over the years, altering the region’s surface energy flux
partitioning. The resulting changes in moisture availability and atmospheric stability
can be critical in determining the season’s monsoon rainfall. This study uses fully
coupled global climate model (GCM) simulations with idealized land cover to elucidate
the consequences of land surface alterations. We find that an increase in forest cover, in
general, increases precipitation in India. However, precipitation is not a linear function
of forest-covered-area due to the spatially heterogeneous nature of the impact. A fully
forest-covered India receives less precipitation than when the forest covers only the
eastern side of India, occupying just about half the area. This signifies the importance
of the east-west gradient in vegetation cover observed over India. Using an energy
balance model, we diagnose that the diverse nature of this precipitation response results
from three different pathways: evaporation from the surface, the net energy input into
the atmosphere, and moist stability. Evaporation exhibits a linear relationship with
forest-covered-area and reveals minimal spatial heterogeneity. On the contrary, the
influence through the other two pathways is found to be region specific. Rainfall
modulation via changes in net energy input is dominant in the head Bay of Bengal
region, which is susceptible to convective systems. Whereas impact through stability
changes is particularly significant south of 20 N . In addition, we find that moisture
advection modulates the significance of these pathways over northwest India. Thus,
the impact of land cover changes act via three effective mechanisms and are region
dependent. The findings in this study have broader ramifications since the dominant
region-specific mechanisms identified are expected to be valid for other forcings and
are not just limited to the scenarios considered here.

<p>The heterogeneities arising out of surface variabilities, land-sea contrasts, aerosol concentrations, and the influence of orography define the intricate characteristics of regional monsoon systems. The amount of precipitation India receives during the boreal summer monsoon season can be modulated by land surface processes due to its influence on moisture availability and atmospheric stability. This study investigates the impact of vegetation changes on the seasonal mean precipitation over Indian land using fully coupled global climate model (GCM) simulations with idealized land cover. In addition, an  energetics framework is employed to unravel the physical mechanisms/pathways connecting vegetation and rainfall. In general, evaporation enhances with an increase in forest cover. However, this does not translate to a similar increase in all-India averaged precipitation. Using the energetics approach, we find that precipitation changes primarily happens via three different thermodynamic pathways. We also find the regions where each pathway is dominant. The relative dominance of these pathways in various areas leads to spatial inhomogeneities in the precipitation response due to vegetation changes. Human intervention, including agricultural expansion, has reshaped the landscape of India in the last century, altering the nature of land-atmosphere interactions. The results from this study, that land cover plays a significant role in modulating the regional characteristics of seasonal monsoon precipitation, are particularly important in this context. The findings in this study also have broader ramifications since the dominant region-specific mechanisms identified are expected to be valid for other forcings and are not just limited to the scenarios considered here. A unified framework connecting these various forcings with monsoon variability would be of great practical importance, and the present study is an advancement in this regard.</p>