Last Decade Progress in Understanding and Modeling the Land Surface Processes on the Tibetan Plateau

Abstract

Abstract. The Land Surface Model (LSM) that simulates water and energy exchanges at the land-atmosphere interface is a key component of the Earth system model. The Tibetan Plateau (TP) drives the Asian monsoon through surface heating and thus plays a key role in regulating the climate system in the Northern Hemisphere. Therefore, it's vital to understand and represent well the land surface processes on the TP. After an early review that identified key issues in the understanding and modelling of land surface processes on the TP in 2009, several progress have been made in the last decade in developing new land surface schemes and supporting datasets. This review summarizes the major advances, including (i) An enthalpy-based approach was adopted to enhance the description of cryosphere processes such as glacier/snow mass balance and soil freeze-thaw transition. (ii) Parameterization of the vertical mixing process was improved in lake models to ensure reasonable heat transfer to the deep water and to the near-surface atmosphere. (iii) New schemes were proposed for modelling water flow and heat transfer in soils accounting for the effects of vertical soil heterogeneity due to the presence of high soil organic matter content and dense vegetation roots in surface soils, or gravel in soil columns. (iv) Supporting datasets of meteorological forcing and soil parameters were developed by integrating multi-source datasets including ground-based observations. Perspectives on the further improvement of land surface modelling on the TP are provided, including the continuous updating of supporting datasets, parameter estimation through assimilation of satellite observations, improvement of snow and lake processes, and the development of an integrated LSM for the TP.

Different responses of soil respiration to climate change in permafrost and non‐permafrost regions of the Tibetan plateau from 1979 to 2018

“…The dataset has a horizontal resolution of 0.1° and available at 3‐hourly intervals from 1979 to 2018. Several studies have evaluated the CMFD and suggested that the dataset is highly accurate and suitable for land surface simulation on the TP (Lu et al, 2020; Yang et al, 2021).…”

An Enhanced MOD16 Evapotranspiration Model for the Tibetan Plateau During the Unfrozen Season

“…This study is also based on empirical fitting relationships. Furthermore, empirical formulations of r s s have developed to estimate evaporation from bare soil in LSMs for long‐term ET simulation with large spatial scale (Chang et al., 2019; Dong et al., 2020; Lu et al., 2020; J. Tang & Riley, 2013; Yang et al., 2011). Although the MOD16‐STM algorithm based on empirical parameters performs better at five independent grassland sites, it is still necessary to improve the proposed algorithm by considering the physical processes of soil evaporation and with the help of more observations to enhance the performance of the model in the future studies.…”

QRF4P‐NRT: Probabilistic Post‐Processing of Near‐Real‐Time Satellite Precipitation Estimates Using Quantile Regression Forests

“…He et al., 2020). This data set has been validated and widely used in many studies in China (e.g., Gou et al., 2021; Huang et al., 2020; Lu et al., 2020). These reanalysis data with a temporal resolution of 3 hr and a spatial resolution of 0.1° were aggregated to a daily scale and a spatial resolution of 0.5° using daily and spatial averaging.…”