Abstract

The interplay of moisture, temperature and precipitation forced through the orographic processes sustain and regulate the Himalayan cryospheric system. However, factors influencing the Slope Environmental Lapse Rate (SELR) of temperature along the Himalayan mountain slopes and an appropriate modeling solution remain as a key knowledge gaps. The present study evaulates the SELR variations in the monsoon regime of the western Himalaya and proposes a modeling solution for the valley scale SELR assessment. SELR of selected station pairs in the Sutlej and Beas basins ranging between the elevation of 662 m a.s.l. to 3130 m a.s.l. and that of Garhwal Himalaya between 770 m a.s.l. and 3820 m a.s.l. were assessed in this study. Results suggest that the moisture-temperature interplay is not only forcing the seasonal variations, but also the elevation - depended variability of the temperature SELR. Temperature lapse rate constrianed to the nival-glacier regime is found to be comparable to the saturated adiabatic lapse rate (SALR) and lower than the valley scale SELR. The study also suggests that the bi-modal pattern of the annual temperature lapse rates earlier observed in the Nepal Himalaya is extended up to upper Ganga, Sutlej and Beas basins in the western Himalaya. This seasonal variability of SELR is found to be closly linked with the seasonal variations in the lifting condensation levels (LCLs) over the region. Inter-annual variation in SELR of the nival-glacier regime are found to be significant while that of the valley scale SELR are more stable. We propose a simple preliminary but robust model for deriving the valley scale SELR of monsoon regime modifying the equation governing pseudo adiabatic lapse rate. The SELR modeling solution is achieved by deriving monthly SELR indices using the data of two station pairs in the Sutlej and Beas basins during the 1986-2005 period through K-fold cross validation. The model sucessfully captures seasonal SELR variations, and was tested compared to the station pairs in the upper Ganga basin as well and showed significant improvement over the standard environmental lapse rate of 6.5K/km.

Highlights

  • The Hindu-Kush-Himalayan (HKH) mountain ranges play a very important role in regulating the climate and hydrology of the South-Asian region (Dey and Bhanu Kumar, 1983; Kumar et al, 1999; Zhao and Moore, 2004; Ye and Bao, 2005)

  • Seasonal variations of valley scale Slope Environmental Lapse Rate (SELR) observed for Beas, Sutlej and upper Ganga basins in the present study is comparable with the observations reported from Neaplease Himalaya (Kattel et al, 2013; Heynen et al, 2016) and suggest that the processes controlling the SELR are similar across the monsoon regime of the central and western Himalayan region

  • We propose that the rate of re-evaporation of water droplet, governed by the seasonal variations in the lifting condensation levels (LCLs) could be playing an important role in determining the seasonal variations in the valley scale SELR

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Summary

Introduction

The Hindu-Kush-Himalayan (HKH) mountain ranges play a very important role in regulating the climate and hydrology of the South-Asian region (Dey and Bhanu Kumar, 1983; Kumar et al, 1999; Zhao and Moore, 2004; Ye and Bao, 2005). Sustenance of the large population in the region depends on the health of the rivers fed by this mighty mountain chain (Cruz et al, 2007; Bookhagen and Burbank, 2010; Bolch et al, 2012; Immerzeel et al, 2013) Acknowledgment of these facts have resulted in an increased focus on the Himalayan cryospheric systems, their response to changing climate, and ensuing impact on downstream flow regimes in recent years (Bookhagen and Burbank, 2010; Immerzeel et al, 2010, 2013; Kaser et al, 2010; Thayyen and Gergan, 2010). As mountain climate is a balance between free air advective processes and surface radiative effects (Whiteman et al, 2004; Pepin and Lundquist, 2008), understanding the complex nuances of orographic controls on the Himalayan climate system is a priority for this region with limited data sets

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