Characterizing surface albedo of shallow fresh snow and its importance for snow ablation on the interior of the Tibetan Plateau

Snow depth on the interior of Tibetan Plateau (TP) in state-of-the-art reanalysis products is almost an order of magnitude higher than observed. This huge bias stems primarily from excessive snowfall, but inappropriate process representation of shallow snow also causes excessive snow depth and snow cover. This study investigated the issue with respect to the parametrization of fresh snow albedo. The characteristics of TP snowfall were investigated using ground truth data. Snow in the interior of the TP is usually only some centimeters in depth, and the albedo of fresh snow depends on snow depth, and is frequently less than 0.4. Such low albedo values contrast with the high values (~0.8) used in the existing snow schemes of land surface models. The SNICAR radiative transfer model can reproduce the observations that fresh shallow snow has a low albedo value, based on which a fresh snow albedo scheme was derived in this study. Finally, the impact of the fresh snow albedo on snow ablation was examined at 45 meteorological stations on TP using the land surface model Noah-MP which incorporated the new scheme. Allowing albedo to change with snow depth can produce quite realistic snow depths compared with observations. In contrast, the typically assumed fresh snow albedo of 0.82 leads to too large snow depths in the snow ablation period averaged across 45 stations. The shallow snow transparency impact on snow ablation is therefore particularly important in the TP interior, where snow is rather thin and radiation is strong.

Water Vapor from Western Eurasia Promotes Precipitation during the Snow Season in Northern Xinjiang, a Typical Arid Region in Central Asia

Atmospheric water vapor plays an important role in the water cycle, especially in arid Central Asia, where precipitation is invaluable to water resources. Understanding and quantifying the relationship between water vapor source regions and precipitation is a key problem in water resource research in typical arid Central Asia, Northern Xinjiang. However, the relationship between precipitation and water vapor sources is still unclear of snow season. This paper aimed at studying the role of water vapor source supply in the Northern Xinjiang precipitation trend, which was investigated using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The results showed that the total water vapor contributed from Western Eurasia and the North Polar area presented upward trends similar to the precipitation change trend, which indicated that the water vapor contribution from the two previous water vapor source regions supplied abundant water vapor and maintained the upward precipitation trend from 1980 to 2017 in Northern Xinjiang. From the climatology of water vapor transport, the region was controlled by midlatitude westerlies and major water vapor input from the western boundary, and the net water vapor flux of this region also showed an annual increasing trend. Western Eurasia had the largest moisture percentage contribution to Northern Xinjiang (48.11%) over the past 38 years. Northern Xinjiang precipitation was correlated with water vapor from Western Eurasia, the North Polar area, and Siberia, and the correlation coefficients were 0.66, 0.45, and 0.57, respectively. These results could aid in better understanding the water cycle process and climate change in this typical arid region of Central Asia.

Forward Simulation of Snow Albedo Based on Snicar Model

Integrated hydrometeorological – snow – frozen ground observations in the alpine region of the Heihe River Basin, China

<p><strong>Abstract.</strong> The alpine region is important in riverine and watershed ecosystems as a contributor of freshwater, providing and stimulating specific habitats for biodiversity. In parallel, recent climate change, human activities and other perturbations may disturb hydrological processes and eco-functions, creating the need for next-generation observational and modeling approaches to advance a predictive understanding of such processes in the alpine region. However, several formidable challenges, including the cold and harsh climate, high altitude and complex topography, inhibit complete and consistent data collection where/when needed, which hinders the development of remote sensing technologies and alpine hydrological models. The current study presents a suite of datasets consisting of long-term hydrometeorological, snow cover and frozen ground data for investigating watershed science and functions from an integrated, distributed and multiscale observation network in the upper reaches of the Heihe River Basin (HRB) in China. Gap-free meteorological and hydrological data were monitored from an observation network connecting a group of automatic meteorological stations (AMSs). In addition, to capture snow accumulation and ablation processes, snow cover properties were collected from a snow observation superstation using state-of-the-art techniques and instruments. High-resolution soil physics datasets were also obtained to capture the freeze-thaw processes from a frozen ground observation superstation. The updated datasets were released to scientists with multidisciplinary backgrounds (<i>i.e.</i>, cryosphere science, hydrology, and meteorology), and they are expected to serve as a testing platform to provide accurate forcing data and validate and evaluate remote sensing products and hydrological models for a broader community. The datasets are available from the Cold and Arid Regions Science Data Center at Lanzhou <a href="https://doi.org/doi:10.3972/hiwater.001.2019.db" target ="_blank">https://doi.org/10.3972/hiwater.001.2019.db</a>.</p>

Precipitation Change During the Snow Period in The Northern Xinjiang, a Typical Arid Region

Retrieval of Snow Water Equivalent by Gamma

Area Change of Snow and Ice in the Babao River Basin, Tibetan Plateau

Tracing Snowmelt Paths in an Integrated Hydrological Model for Understanding Seasonal Snowmelt Contribution at Basin Scale

Using Quantile Mapping to Correct WRF Precipitation for Improvement of Runoff Simulation in Manas River Basin

Spatiotemporal Variation of Snow Cover in Tianshan Mountains, Central Asia, Based on Cloud-Free MODIS Fractional Snow Cover Product, 2001–2015

Development and Evaluation of a River-Basin-Scale High Spatio-Temporal Precipitation Data Set Using the WRF Model: A Case Study of the Heihe River Basin

Remote sensing for snow hydrology in China: challenges and perspectives

Quantitative water resources assessment of Qinghai Lake basin using Snowmelt Runoff Model (SRM)

Extraction and assessment of snowline altitude over the Tibetan plateau using MODIS fractional snow cover data (2001 to 2013)

Spatiotemporal changes of snow cover over the Tibetan plateau based on cloud-removed moderate resolution imaging spectroradiometer fractional snow cover product from 2001 to 2011

Monitoring snow cover changes and their relationships with temperature over the Tibetan Plateau using MODIS data