Observed characteristics of the water and heat transfer of the soil–snow–atmosphere system through the snowpack in the eastern Tibetan Plateau

Li, Zhaoguo; Lyu, Shihua; Chen, Shiqiang; Ao, Yu‐Fei; Zhao, Lin; Chen, Hao; Meng, Xianhong

doi:10.1016/j.atmosres.2020.105195

Cited by 9 publications

(5 citation statements)

References 48 publications

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“…There are two stations in the Ngoring Lake basin, which is located in the Yellow River source area east of the TP (Li et al, 2017). One grassland station (NLGS) is located on a flat surface, and the other observation station (NLTS) is located 190 on the lakeside beside the lakeshore tower station Li et al, 2021). The in situ data of D105 and NPAM come from the Coordinated Enhanced Observing Period Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau (CAMP/Tibet) (Ma et al, 2009;Zhong et al, 2010;Ma et al, 2014).…”

Section: In Situ Observation Stationsmentioning

confidence: 99%

Estimation of 1 km downwelling shortwave radiation over the Tibetan Plateau under all-sky conditions

Zhong

et al. 2023

Preprint

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Abstract. Downwelling shortwave radiation (DSR) is the basic driving force for the energy and water cycles of the Earth’s climate system. As called the Third Pole of the Earth, the Tibetan Plateau (TP) absorbs a large amount of shortwave radiation and exert important impacts on global weather and climate change. However, due to coarse spatial resolution and insufficient consideration of factors influencing radiative transfer processes, DSR parameterization schemes are still need to be improved when applied to the TP. Based on satellite datasets and meteorological forcing data, all-sky DSR over the TP at a spatial resolution of 1 km was derived using an improved parameterization scheme. The influence of topography and different radiative attenuations were comprehensively taken into account. Specifically, the introduction of cloud multiscattering and topography factors further improves the DSR estimation accuracy. The validation results indicated that the developed parameterization scheme showed reasonable accuracy. By comparing with current widely used DSR products based on the same in situ observations, the derived DSR performed much better on different spatial and temporal scales. On instantaneous, ten-day, and monthly timescales, the root-mean-square errors (RMSEs) of the derived DSR are 132.8–158.2 W m−2, 70.8–76.5 W m−2, and 61.3–67.5 W m−2, respectively, which are much smaller than those of current DSR products. The derived DSR not only captured the temporal variation characteristics that are more consistent with the in situ measurements, but also provided reasonable spatial patterns. Meanwhile, the proposed parameterization scheme demonstrated its superiority in characterizing more details and high dynamics of the spatial pattern of DSR due to its terrain correction and high resolution. Moreover, this parameterization scheme does not need any local correction in advance and it has the potential to be extended to other regions in the world.

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Section: In Situ Observation Stationsmentioning

confidence: 99%

Estimation of 1 km downwelling shortwave radiation over the Tibetan Plateau under all-sky conditions

Zhong

et al. 2023

Preprint

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“…Data were collected at sites Maqu and Erlinghu (ELH), located in the east and west of SRYR, northeast of the Tibetan Plateau, China (Figure 1). In-situ observations, such as soil moisture and soil temperature, meteorological data (e.g., precipitation, wind speed, relative humidity, air temperature, air pressure) with 30 min observational time steps for 2015-2016 at Maqu and 2012-2019 at ELH were acquired (Li et al, 2017(Li et al, , 2021. Land cover at both sites was mainly alpine meadow; soil texture information for both sites was acquired and listed in Table 1.…”

Section: Field Site and Datamentioning

confidence: 99%

Soil Moisture Estimation by Assimilating In‐Situ and SMAP Surface Soil Moisture Using Unscented Weighted Ensemble Kalman Filter

Fu,

Zhang,

Zhong

et al. 2023

Water Resources Research

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Highly accurate soil moisture information is necessary to understand land surface processes. However, observational techniques do not produce adequately accurate spatial‐temporal continuous regional soil moisture data. The data assimilation method can be used to improve the soil moisture estimations by merging multi‐source observed data, but its performance is affected by error covariance and the quality of assimilated data. We designed eight numerical experiments to analyze how to improve the filter performance through soil moisture assimilation using the unscented weighted ensemble Kalman filter (UWEnKF) and 1‐D Richards equation at Maqu and Erlinghu (ELH) observational sites in the source region of Yellow River (SRYR), China. The experimental results show that the filter performance improves as the quality of assimilated data increases in the soil moisture assimilation experiment when assimilating in‐situ surface soil moisture (SSM) observations, SMAP SSM data and downscaled SMAP SSM data. In other aspects, filter performance is readily affected by model and observation error covariances in soil moisture assimilation. If the SMAP SSM data are taken to be perfect (i.e., small bias), UWEnKF performs differently between different sites because of the underestimation or overestimation of SMAP SSM and model simulations compared to the in‐situ observations. Additionally, different soil moisture assimilation results can be obtained with different initial values at the beginning of the assimilation period. Overall, filter performance can be improved primarily by improving the quality of assimilated data (e.g., downscaling the remote sensing data), and by creating a reasonable and effective method for determining error covariance.This article is protected by copyright. All rights reserved.

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“…There are two stations in the Ngoring Lake basin, which is located in the Yellow River source area east of the TP (Li et al, 2017). One grassland station (NLGS) is located on a flat surface, and the other observation station (NLTS) is located on the lakeside beside the lakeshore tower station (Li et al, 2020(Li et al, , 2021. The in situ data of D105 and NPAM come from the Coordinated Enhanced Observing Period Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau (CAMP/Tibet) (Ma et al, 2009(Ma et al, , 2014Zhong et al, 2010).…”

Section: In Situ Observation Stationsmentioning

confidence: 99%

Estimation of 1 km downwelling shortwave radiation over the Tibetan Plateau under all-sky conditions

Li,

Zhong,

et al. 2023

Atmos. Chem. Phys.

View full text Add to dashboard Cite

Abstract. Downwelling shortwave radiation (DSR) is the basic driving force for the energy and water cycles of the Earth's climate system. Called the Third Pole of the Earth, the Tibetan Plateau (TP) absorbs a large amount of shortwave radiation and exerts important impacts on global weather and climate change. However, due to coarse spatial resolution and insufficient consideration of factors influencing radiative transfer processes, DSR parameterization schemes still need to be improved when applied to the TP. Based on satellite datasets and meteorological forcing data, all-sky DSR over the TP at a spatial resolution of 1 km was derived using an improved parameterization scheme. The influence of topography and different radiative attenuations were comprehensively taken into account. Specifically, the introduction of cloud multiscattering and topography factors further improves the DSR estimation accuracy. The validation results indicated that the developed parameterization scheme showed reasonable accuracy. By comparing with current, widely used DSR products based on the same in situ observations, the derived DSR performed much better on different spatial and temporal scales. On instantaneous, 10 d and monthly timescales, the root-mean-square errors (RMSEs) of the derived DSR are 132.8–158.2, 70.8–76.5 and 61.3–67.5 W m−2, respectively, which are much smaller than those of current DSR products. The derived DSR not only captured the temporal-variation characteristics that are more consistent with the in situ measurements, but also provided reasonable spatial patterns. Meanwhile, the proposed parameterization scheme demonstrated its superiority in characterizing more details and high dynamics of the spatial pattern of DSR due to its terrain correction and high resolution. Moreover, this parameterization scheme does not need any local correction in advance and has the potential to be extended to other regions in the world.

show abstract

Observed characteristics of the water and heat transfer of the soil–snow–atmosphere system through the snowpack in the eastern Tibetan Plateau

Cited by 9 publications

References 48 publications

Estimation of 1 km downwelling shortwave radiation over the Tibetan Plateau under all-sky conditions

Estimation of 1 km downwelling shortwave radiation over the Tibetan Plateau under all-sky conditions

Soil Moisture Estimation by Assimilating In‐Situ and SMAP Surface Soil Moisture Using Unscented Weighted Ensemble Kalman Filter

Estimation of 1 km downwelling shortwave radiation over the Tibetan Plateau under all-sky conditions

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