Importance of the Resolution of Surface Topography in Indian Monsoon Simulation

Abstract

The influence of surface topography resolution in Indian summer monsoon simulation is investigated. Three sets of six-member ensemble simulations with climatological sea surface temperature are conducted with the Community Atmospheric Model, version 5.1 (CAM5.1): COARSE simulation at 1.9° × 2.5° latitude–longitude resolution, FINE simulation at 0.47° × 0.63° resolution, and HYBRID simulation, that is, using COARSE surface topography imposed on the FINE configuration. With regard to the representation of the surface topography, substantial differences occur at the regional scales between the simulations, especially over the foothills and steep flanks of the mountains. In the COARSE and HYBRID simulations, the orographic height of the foothills is overestimated whereas that of the steep flanks adjacent to the foothills is underestimated. The biases are severe (up to 1 km) over the Himalayas and Tibet and have detrimental effects on regional climate through barrier effects on the low-level flow, and the lapse rate and elevated heat source effects. Overall, the simulations show remarkable improvement with an increase in resolution, mainly because of the improved representation of atmospheric and surface processes. However, local climate—surface air temperature, sea level pressure, precipitable water, and wind—of the orographic regions, particularly where large orographic biases exist in COARSE, is found to benefit substantially from increased resolution of surface topography. Local precipitation and evaporation are exceptions, although, as they are negligibly sensitive to topographic resolution, showing strong dependence on the resolution of surface and atmospheric processes. Moreover, resolution of surface topography generally does not have notable remote impacts.

Competing Topographic Mechanisms for the Summer Indo‐Asian Monsoon

“…Since our work primarily highlights the importance of topography using high‐resolution modeling, we enviably sacrifice any potential response and feedback of the ocean to topographic changes. Thus, accurately modeling the coupling between ocean‐atmosphere conditions (Annamalai et al, ; Wang et al, ) and topographic forcings (Acosta & Huber, ; Jain et al, ; Mishra et al, ) using high‐resolution modeling is a necessary condition to fully depict the Indo‐Asian monsoon dynamics and presents direction for future research.…”

“…One limitation of such studies is that they are often difficult to interpret because many factors are changed simultaneously in the name of realism. Another limitation is that such studies are run at resolutions that do not accurately capture monsoon dynamics (Acosta & Huber, 2017) and thermodynamics (Jain et al, 2019;Mishra et al, 2018) due to the necessity of performing long simulations for paleoclimate context. An alternative approach is using idealized modeling methods in which topography is carved out from modern Park et al, 2012;, which has identified mechanisms that are crucial for the IAM.…”

“…One limitation of such studies is that they are often difficult to interpret because many factors are changed simultaneously in the name of realism. Another limitation is that such studies are run at resolutions that do not accurately capture monsoon dynamics (Acosta & Huber, ) and thermodynamics (Jain et al, ; Mishra et al, ) due to the necessity of performing long simulations for paleoclimate context.…”

Uncertainty quantification based cloud parameterization sensitivity analysis in the NCAR community atmosphere model

“…It is, therefore, crucial to systematically characterize the sensitivity of climate simulations at global and regional scales during different seasons (especially for different monsoon and storm track regions), as well as the characteristics of South Asian summer monsoon (SASM) to cloud microphysics and macrophysics parameters to reduce uncertainty in climate simulations. The quantification and reduction of uncertainty in climate simulations due to parameter sensitivity over the SASM region are also one of the main objectives of the DST CoE in Climate Modeling, IIT Delhi, India, for the improvement of SASM simulations 5 – 8 , 54 . In this paper, we examine the GSA for the majority of physical parameters in microphysics and macrophysics parameterizations used in the NCAR CAM5, using MOAT sensitivity analysis for different simulated climate variables.…”

Impact of Stochastic Entrainment in the NCAR CAM Deep Convection Parameterization on the Simulation of South Asian Summer Monsoon

“…4). This is advantageous to the model because the total precipitation biases over South Asia have been a longstanding problem in CAM5 and its predecessors (e.g., Wang et al 2016a;Anand et al 2018;Mishra et al 2018), as well as in CMIP5 (e.g., Sperber et al 2013). It was not greatly alleviated, even after including stochasticity in the generation of convective clouds (Wang et al 2016a) and linking it to large-scale vertical velocity (Wang et al 2018).…”