An Examination of Temperature Trends at High Elevations Across the Tibetan Plateau: The Use of MODIS LST to Understand Patterns of Elevation‐Dependent Warming

Abstract

Research has revealed systematic changes in warming rates with elevation (EDW) in mountain regions. However, weather stations on the Tibetan plateau are mostly located at lower elevations (3,000‐4,000 m) and are nonexistent above 5,000 m, leaving critical temperature changes unknown. Satellite LST (Land Surface Temperature) can fill this gap but needs calibrating against in situ air temperatures (Tair). We develop a novel statistical model to convert LST to Tair, developed at 87 high‐elevation Chinese Meteorological Administration stations. Tair (daily maximum/minimum temperatures) is compared with Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua LST (1330 and 0130 local time) for 8‐day composites during 2002‐2017. Typically, 80‐95% of the difference between LST and Tair (ΔT) is explained using predictors including LST diurnal range, morning heating/nighttime cooling rates, the number of cloud free days/nights, and season (solar angle). LST is corrected to more closely represent Tair by subtracting modeled ΔT. We validate the model using an AWS on Zhadang Glacier (5800 m). Trend analysis at the 87 stations (2002‐2017) shows corrected LST trends to be similar to original Tair trends. To examine regional contrasts in EDW patterns, elevation profiles of corrected LST trends are derived for three ranges (Qilian Mountains, NyenchenTanglha, and Himalaya). There is limited EDW in the Qilian mountains. Maximum warming is observed around 4,500‐5,500 m in NyenchenTanglha, consistent with snowline retreat. In common with other studies, there is stabilization of warming at very high elevations in the Himalaya, including absolute cooling above 6,000 m, but data there are compromised by frequent cloud.

Satellite data reveal southwestern Tibetan plateau cooling since 2001 due to snow‐albedo feedback

“…Guo et al (2019) used SBAT to reveal a reversal in elevation dependent warming above 4,500 m on the TP in recent years. Pepin et al (2019) corrected MODIS LST data to more closely represent air temperature, and analysed patterns of warming in three mountain ranges across the plateau for 2002-2017. Although some enhanced warming at high elevations was found in the Nyenchen Tanglha and Qilian Mountains, in the central Himalayas the warming changed predominantly to cooling above 6,000 m.…”

Quantifying the Congruence between Air and Land Surface Temperatures for Various Climatic and Elevation Zones of Western Himalaya

“…The daily, and 8-day night-and day-time T s from MODIS satellites on Terra (MOD11A1 and MOD11A2 available from February, 2000) and Aqua (MYD11A1 and MYD11A2 available from July, 2002) satellites [23,24] was downloaded from NASA Earthdata portal (https://earthdata.nasa.gov/) [38] and was used to calculate average of daily and 8-day T s ( Table 2). The remotely-sensed T s from MODIS (version 006) has been observed to have RMSD of less than 0.5 K in comparison to the in situ measurements of the T s [39] and therefore has been widely used for multiple scientific applications [18,19,22,[25][26][27][28]40]. The local time for the pass over the study area for Terra is around 10:30 and 22:30 and for Aqua is around 13:30 and 01:30 during day and night, respectively.…”

“…The root mean square difference (RMSD) between T a from meteorological stations and T s from Moderate Resolution Imagining Spectroradiometer (MODIS) on Terra [23] and Aqua [24] satellites was estimated to be ±2.20 • C in Indo-Gangetic plain [25], ±1.33 • C in Portugal [18], ±5.48 • C in mountainous regions of Nevada, United states of America [19], ±2.97 to ±7.45 • C in northern Tibetan Plateau, China [26], ±4.09 to ±4.53 • C in a mountainous region of sub-Arctic Canada [27], and ±1.51 to ±3.74 • C over different ecosystems in Africa [22]. A recent study attempted to analyze the temperature trend using the 8-day T s corrected using the difference between T s and T a calculated for 87 meteorological stations in the Chinese part of Himalaya and Tibetan Plateau [28]. Most of these published studies have compared the T a and T s at monthly or 8-day scales while several prominently used ecological and glacio-hydrological models in Himalaya that require daily temperature data as input parameter [4,29].…”

Variations in Winter Surface Temperature of the Purog Kangri Ice Field, Qinghai–Tibetan Plateau, 2001–2018, Using MODIS Data

“…Many studies have been performed to estimate temperature variations on the Antarctic and Greenland ice sheets using MODIS LST, revealing a warming trend and extreme melting events (LST extremes) in recent years [17][18][19][20]. For the Qinghai-Tibetan Plateau, the MODIS LST product has been applied to the lower-altitude regions (<5000 m) with meteorological observation station data in terms of near-surface temperature estimation, delimitation of permafrost extent, and lake surface temperature analysis [21][22][23][24].…”