Application of regional climate models to the Indian winter monsoon over the western Himalayas

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Abstract

The Himalayan region is characterized by pronounced topographic heterogeneity and land use variability from west to east, with a large variation in regional climate patterns. Over the western part of the region, almost one-third of the annual precipitation is received in winter during cyclonic storms embedded in westerlies, known locally as the western disturbance. In the present paper, the regional winter climate over the western Himalayas is analyzed from simulations produced by two regional climate models (RCMs) forced with large-scale fields from ERA-Interim. The analysis was conducted by the composition of contrasting (wet and dry) winter precipitation years. The findings showed that RCMs could simulate the regional climate of the western Himalayas and represent the atmospheric circulation during extreme precipitation years in accordance with observations. The results suggest the important role of topography in moisture fluxes, transport and vertical flows. Dynamical downscaling with RCMs represented regional climates at the mountain or even event scale. However, uncertainties of precipitation scale and liquid–solid precipitation ratios within RCMs are still large for the purposes of hydrological and glaciological studies.

Highlights

► Study provide RCMs' sensitivity towards Indian Winter Monsoon. ► Uncertainty associated with RCMs towards Indian Winter Monsoon. ► Suitability for usage of hydrological/glaciological studies.

Introduction

Spatiotemporal distribution of precipitation due to orographic forcing and land use/land cover variability is important for assessing regional climates, water recharge, agriculture, and tourism over the western Himalayas (WH). Previous studies suggest that orographic forcing due to the elevation in mountainous regions has a fundamental role in determining the amount of precipitation. In such regions, land use (or land surface conditions) and topography are two key factors in defining the regional climate and its changes (Fyfe and Flato, 1999, Im et al., 2010). These are also some of the most sensitive and vulnerable areas for climate change (Beniston et al., 1997, Beniston, 2003). Altitudinal variations over mountains give rise to sharp gradients of vertical change in the temperature lapse rate (Barry, 2008, Thayyen et al., 2005). The role of land use and its impact on regional climates and associated precipitation regimes have been studied extensively (Steiner et al., 2009, Fairman et al., 2011, Nair et al., 2011, Przekurat et al., 2011). Precipitation over mountainous regions primarily depends on the source of the moisture that is advected into the region (Viste and Sorteberg, 2011) and the interaction with the prevailing land use (Steiner et al., 2009, Dimri and Niyogi, 2012, Dimri, 2012) and topography (Dimri, 2009, Im et al., 2010). Over mountainous regions, land use and topography can affect surface processes such as snow formation and melting, mostly due to local snow-albedo feedback mechanisms. Previous studies have recognized the complexity associated with precipitation over mountainous regions, which may aid our understanding of the spatial complexity of regional climate variabilities at fine resolutions in these areas. To deal with such a marked elevation dependency within the framework of regional model studies, explicitly representing the interactions between surface variables and the underlying topography is essential (Leung and Ghan, 1995, Qian et al., 2009).

Various analyses pertaining to the uncertainty/sensitivity of regional climate models (RCMs) in reproducing current climate and associated precipitation during the Indian summer monsoon have been undertaken (e.g., Bhaskaran et al., 1996, Bhaskaran et al., 1998, Bhaskaran et al., 2012, Saeed et al., 2012). The dependency of precipitation on topography forcing in RCM simulations has also been studied (Takahashi et al., 2010, Im and Ahn, 2011, Gutmann et al., 2012, Schomburg et al., 2012). However, no such studies on the complex topography of the WH during winter (December, January, and February: DJF; hereafter, Indian winter monsoon: IWM) are available. During the IWM, almost 30% of annual precipitation is received over the western Himalayan region. The main sources of this precipitation are eastward-moving synoptic weather systems, known locally as western disturbances (WDs) (Dimri and Mohanty, 2009). This accumulated precipitation, in the form of snow, is very important for the northern Indian region. It provides spring/summer snow melt as river discharge for northern Indian rivers, which support irrigation for agriculture across northern India. An understanding of the IWM is also important for various river-basin hydrological budgets and glacier studies. Therefore, the present study illustrates the role of two available RCM simulations over an eighteen year (1990–2007) period to assess the uncertainty/sensitivity of RCMs in defining the IWM. The downscaled fields were first compared against the corresponding observational reanalyses over the WH, and then a RCM simulation was verified to determine whether it could reproduce the interannual variability (IAV) over the WH. This was then followed by a case study of an active WD to illustrate the robustness of a RCM over a mountainous region for a WD event, and to illustrate the interaction of existing topography with large scale synoptic flow and subsequent precipitation.

In the present paper, the study area, model, and data sets used are discussed in Section 2 and the results are discussed in 3 Results and discussion, 4 Uncertainty associated with RCMs briefly introduces the issue of uncertainties associated with RCMs and, finally, Section 5 presents the salient findings of the study and our conclusions.

Section snippets

Model and observations

Due to the important and urgent issues regarding changes in the water budget/cycle associated with changes in Indian summer and winter monsoons and their impact on the recent retreat of Himalayan glaciers, the European Union (EU) has sponsored a multi-institutional research project, referred to as the Himalayan Glacier Retreat and Changing Monsoon Pattern (HighNOON). In this program, two RCM simulations were prepared: first, the Meteorological Office Hadley Centre Regional Climate Model version

Model sensitivity

For RCMs to be suitable tools for downscaling from global models and subsequent analyses, they must reproduce the climatology of the seasonal (DJF) circulation and its precipitation. The model biases in the wind and precipitation components are shown in Fig. 2. The zonal wind components for HadRM3 (Fig. 2a) and REMO (Fig. 2b) show different maxima zones of model bias. In the case of HadRM3, westerly biases dominate ~ 25°–35°N and persist up to the upper troposphere, and two zones of easterly

Uncertainty associated with RCMs

We concluded that the RCMs were robust in nature with good modeling outputs over a mountainous region at the event level. However, the results may not be accurate enough for use as an input for hydrological and glaciological studies, cloud burst analysis, or irrigation determination, given that we obtained differences in circulation patterns and precipitation compared to observations. Use of regional model outputs “without tuning” to evaluate glacier responses to climate change in the Himalayan

Conclusions

In this study, we analyzed the output of high-resolution RCM simulations forced at the boundaries by a coarser-resolution reanalysis data. From this output, winter precipitation arising from western disturbances across the WH is depicted. Dynamic downscaling resulting from the use of RCMs has not been discussed previously in terms of such heterogeneous topography and land use conditions. Two RCM simulations were analyzed with a corresponding verification reanalysis, and the regional climate and

Acknowledgments

This work was supported by HighNOON, funded by the European Union. A. P. Dimri acknowledges the support of JSPS for accomplishing the present study. C. Mathison and A. Wiltshire were partly supported by the Joint DECC/Defra Meteorological Office Hadley Centre Climate Programme (GA01101).

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