Characterizing Surface Albedo of Shallow Fresh Snow and Its Importance for Snow Ablation on the Interior of the Tibetan Plateau

AbstractSnow 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 parameterization 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. 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.

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Improved parameterization of snow albedo in WRF + Noah. Part II: Applicability to snow estimates for the Tibetan Plateau

10.5194/hess-2021-305 ◽

2021 ◽

Author(s):

Lian Liu ◽

Yaoming Ma ◽

Massimo Menenti ◽

Rongmingzhu Su ◽

Nan Yao ◽

...

Keyword(s):

Heat Flux ◽

Tibetan Plateau ◽

Air Temperature ◽

Land Surface ◽

Snow Depth ◽

Sensible Heat Flux ◽

Parameterization Scheme ◽

The Tibetan Plateau ◽

Sensible Heat ◽

Snow Albedo

Abstract. Snow albedo is important to the land surface energy balance and to the water cycle. During snowfall and subsequent snowmelt, snow albedo is usually parameterized as functions of snow related variables in land surface models. However, the default snow albedo scheme in the widely used Noah land surface model shows evident shortcomings in land-atmosphere interactions estimates during snow events on the Tibetan Plateau. Here, we demonstrate that our improved snow albedo scheme performs well after including snow depth as an additional factor. By coupling the WRF and Noah models, this study comprehensively evaluates the performance of the improved snow albedo scheme in simulating eight snow events on the Tibetan Plateau. The modeling results are compared with WRF run with the default Noah scheme and in situ observations. The improved snow albedo scheme significantly outperforms the default Noah scheme in relation to air temperature, albedo and sensible heat flux estimates, by alleviating cold bias estimates, albedo overestimates and sensible heat flux underestimates, respectively. This in turn contributes to more accurate reproductions of snow event evolution. The averaged RMSE relative reductions (and relative increase in correlation coefficients) for air temperature, albedo, sensible heat flux and snow depth reach 27 % (5 %), 32 % (69 %), 13 % (17 %) and 21 % (108 %) respectively. These results demonstrate the strong potential of our improved snow albedo parameterization scheme for snow event simulations on the Tibetan Plateau. Our study provides a theoretical reference for researchers committed to further improving the snow albedo parameterization scheme.

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Improved parameterization of snow albedo in Noah coupled with Weather Research and Forecasting: applicability to snow estimates for the Tibetan Plateau

Hydrology and Earth System Sciences ◽

10.5194/hess-25-4967-2021 ◽

2021 ◽

Vol 25 (9) ◽

pp. 4967-4981

Author(s):

Lian Liu ◽

Yaoming Ma ◽

Massimo Menenti ◽

Rongmingzhu Su ◽

Nan Yao ◽

...

Keyword(s):

Heat Flux ◽

Tibetan Plateau ◽

Air Temperature ◽

Land Surface ◽

Snow Depth ◽

Sensible Heat Flux ◽

Weather Research And Forecasting ◽

The Tibetan Plateau ◽

Sensible Heat ◽

Snow Albedo

Abstract. Snow albedo is important to the land surface energy balance and to the water cycle. During snowfall and subsequent snowmelt, snow albedo is usually parameterized as functions of snow-related variables in land surface models. However, the default snow albedo scheme in the widely used Noah land surface model shows evident shortcomings in land–atmosphere interaction estimates during snow events on the Tibetan Plateau. Here, we demonstrate that our improved snow albedo scheme performs well after including snow depth as an additional factor. By coupling the Weather Research and Forecasting (WRF) and Noah models, this study comprehensively evaluates the performance of the improved snow albedo scheme in simulating eight snow events on the Tibetan Plateau. The modeling results are compared with WRF run with the default Noah scheme and in situ observations. The improved snow albedo scheme significantly outperforms the default Noah scheme in relation to air temperature, albedo and sensible heat flux estimates by alleviating cold bias estimates, albedo overestimates and sensible heat flux underestimates, respectively. This in turn contributes to more accurate reproductions of snow event evolution. The averaged root mean square error (RMSE) relative reductions (and relative increase in correlation coefficients) for air temperature, albedo, sensible heat flux and snow depth reach 27 % (5 %), 32 % (69 %), 13 % (17 %) and 21 % (108 %), respectively. These results demonstrate the strong potential of our improved snow albedo parameterization scheme for snow event simulations on the Tibetan Plateau. Our study provides a theoretical reference for researchers committed to further improving the snow albedo parameterization scheme.

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Assimilation of Satellite-Observed Snow Albedo in a Land Surface Model

Journal of Hydrometeorology ◽

10.1175/jhm-d-11-0125.1 ◽

2012 ◽

Vol 13 (3) ◽

pp. 1119-1130 ◽

Cited By ~ 19

Author(s):

M. Jahanzeb Malik ◽

Rogier van der Velde ◽

Zoltan Vekerdy ◽

Zhongbo Su

Keyword(s):

Land Surface ◽

Snow Depth ◽

Prediction Models ◽

Weather Prediction ◽

Land Surface Model ◽

Surface Energy Budget ◽

Shortwave Radiation ◽

Surface Model ◽

Snow Albedo ◽

The Impact

Abstract This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado) that are part of the 2002/03 Cold Land Processes Field Experiment (CLPX). The assimilated snow albedo products are 1) the standard Moderate Resolution Imaging Spectrometer (MODIS) product (MOD10A1) and 2) retrievals from MODIS observations with the recently developed Pattern-Based Semiempirical (PASS) approach. The performance of the Noah simulations, with and without assimilation, is evaluated using the in situ measurements of snow albedo, upward shortwave radiation, and snow depth. The results show that simulations with albedo assimilation agree better with the measurements. However, because of the limited impact of snow albedo updates after subsequent snowfall, the mean (or seasonal) error statistics decrease significantly for only two of the three CLPX sites. Though the simulated snow depth and duration for the snow season benefit from the assimilation, the greatest improvements are found in the simulated upward shortwave radiation, with root mean squared errors reduced by about 30%. As such, this study demonstrates that assimilation of satellite-observed snow albedo can improve LSM simulations, which may positively affect the representation of hydrological and surface energy budget processes in runoff and numerical weather prediction models.

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Spatio-Temporal Variation Characteristics of Snow Depth and Snow Cover Days over the Tibetan Plateau

Water ◽

10.3390/w13030307 ◽

2021 ◽

Vol 13 (3) ◽

pp. 307

Author(s):

Chi Zhang ◽

Naixia Mou ◽

Jiqiang Niu ◽

Lingxian Zhang ◽

Feng Liu

Keyword(s):

Tibetan Plateau ◽

Snow Cover ◽

Snow Depth ◽

Feedback Effect ◽

Effect Of Temperature ◽

The Tibetan Plateau ◽

Reanalysis Dataset ◽

Spatio Temporal ◽

The Impact ◽

Main Factor

Changes in snow cover over the Tibetan Plateau (TP) have a significant impact on agriculture, hydrology, and ecological environment of surrounding areas. This study investigates the spatio-temporal pattern of snow depth (SD) and snow cover days (SCD), as well as the impact of temperature and precipitation on snow cover over TP from 1979 to 2018 by using the ERA5 reanalysis dataset, and uses the Mann–Kendall test for significance. The results indicate that (1) the average annual SD and SCD in the southern and western edge areas of TP are relatively high, reaching 10 cm and 120 d or more, respectively. (2) In the past 40 years, SD (s = 0.04 cm decade−1, p = 0.81) and SCD (s = −2.3 d decade−1, p = 0.10) over TP did not change significantly. (3) The positive feedback effect of precipitation is the main factor affecting SD, while the negative feedback effect of temperature is the main factor affecting SCD. This study improves the understanding of snow cover change and is conducive to the further study of climate change on TP.

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Influence of thermodynamic soil and vegetation parameterizations on the simulation of soil temperature states and surface fluxes by the Noah LSm over a Tibetan plateau site

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-6-455-2009 ◽

2009 ◽

Vol 6 (1) ◽

pp. 455-499 ◽

Cited By ~ 3

Author(s):

R. van der Velde ◽

Z. Su ◽

M. Ek ◽

M. Rodell ◽

Y. Ma

Keyword(s):

Thermal Properties ◽

Tibetan Plateau ◽

Land Surface ◽

Land Surface Model ◽

Soil Heat Flux ◽

Stomatal Resistance ◽

Surface Fluxes ◽

Surface Model ◽

The Tibetan Plateau ◽

Soil Thermal Properties

Abstract. In this paper, we investigate the ability of the Noah Land Surface model (LSm) to simulate temperature states in the soil profile and surface fluxes measured during a 7-day dry period at a micrometeorological station on the Tibetan Plateau. Adjustments in soil and vegetation parameterizations required to ameliorate the Noah simulation on these two aspects are presented, which include: (1) Differentiating the soil thermal properties of top- and subsoils, (2) Investigation of the different numerical soil discretizations and (3) Calibration of the parameters utilized to describe the transpiration dynamics of the Plateau vegetation. Through the adjustments in the parameterization of the soil thermal properties (STP) simulation of the soil heat transfer is improved, which results in a reduction of Root Mean Squared Differences (RMSD's) by 14%, 18% and 49% between measured and simulated skin, 5-cm and 25-cm soil temperatures, respectively. Further, decreasing the minimum stomatal resistance (Rc, min) and the optimum temperature for transpiration (Topt) of the vegetation parameterization reduces RMSD's between measured and simulated energy balance components by 30%, 20% and 5% for the sensible, latent and soil heat flux, respectively.

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Developing the soil texture effects on the surface resistance to bare soil based on MOD16 algorithm to estimate evapotranspiration over the Tibetan Plateau

10.5194/egusphere-egu2020-3833 ◽

2020 ◽

Author(s):

Ling Yuan ◽

Yaoming Ma ◽

Xuelong Chen

Keyword(s):

Tibetan Plateau ◽

Soil Texture ◽

Land Surface ◽

Bare Soil ◽

The Other ◽

Accurate Estimation ◽

Surface Model ◽

The Tibetan Plateau ◽

The Mean ◽

Modified Algorithm

Evapotranspiration (ET), composed of evaporation (ETs) and transpiration (ETc) and intercept water (ETw), plays an indispensable role in the water cycle and energy balance of land surface processes. A more accurate estimation of ET variations is essential for natural hazard monitoring and water resource management. For the cold, arid, and semi-arid regions of the Tibetan Plateau (TP), previous studies often overlooked the decisive role of soil properties in ETs rates. In this paper, an improved algorithm for ETs in bare soil and an optimized parameter for ETc over meadow based on MOD16 model are proposed for the TP. The nonlinear relationship between surface evaporation resistance (rss) and soil surface hydration state in different soil texture is redefined by ground-based measurements over the TP. Wind speed and vegetation height were integrated to estimate aerodynamic resistance by Yang et al. (2008). The validated value of the mean potential stomatal conductance per unit leaf area (CL) is 0.0038m s-1. And the algorithm was then compared with the original MOD16 algorithm and a soil water index&#8211;based Priestley-Taylor algorithm (SWI&#8211;PT). After examining the performance of the three models at 5 grass flux tower sites in different soil texture over the TP, East Asia, and America, the validation results showed that the half-hour estimates from the improved-MOD16 were closer to observations than those of the other models under the all-weather in each site. The average correlation coefficient(R2) of the improved-MOD16 model was 0.83, compared with 0.75 in the original MOD16 model and 0.78 in SWI-PT model. The average values of the root mean square error (RMSE) are 35.77W m-2, 79.46 W m-2, and 73.88W m-2 respectively. The average values of the mean bias (MB) are -4.08W m-2, -52.36W m-2, and -11.74 W m-2 overall sites, respectively. The performance of these algorithms are better achieved on daily (R2=0.81, RMSE=17.22W m-2, MB=-4.12W m-2; R2=0.64, RMSE=56.55W m-2, MB=-48.74W m-2; R2=0.78, RMSE=22.3W m-2, MB=-9.82W m-2) and monthly (R2=0.93, RMSE=23.35W m-2, MB=-2.8W m-2; R2=0.86, RMSE=69.11W m-2, MB=-39.5W m-2; R2=0.79, RMSE=62.8W m-2, MB=-9.7W m-2) scales. Overall, the results showed that the newly developed MOD16 model captured ET more accurately than the other two models. The comparisons between the modified algorithm and two mainstream methods suggested that the modified algorithm could produce high accuracy ET over the meadow sites and has great potential for land surface model improvements and remote sensing ET promotion for the ET region.

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Recent Changes in the Moisture Source of Precipitation over the Tibetan Plateau

Journal of Climate ◽

10.1175/jcli-d-15-0842.1 ◽

2017 ◽

Vol 30 (5) ◽

pp. 1807-1819 ◽

Cited By ~ 58

Author(s):

Chi Zhang ◽

Qiuhong Tang ◽

Deliang Chen

Keyword(s):

Tibetan Plateau ◽

Land Surface ◽

Hydrological Cycle ◽

Land Surface Model ◽

Water Vapor Transport ◽

Surface Model ◽

The Tibetan Plateau ◽

Precipitation Trend ◽

Moisture Source ◽

Moisture Supply

Abstract Evidence has suggested a wetting trend over part of the Tibetan Plateau (TP) in recent decades, although there are large uncertainties in this trend due to sparse observations. Examining the change in the moisture source for precipitation over a region in the TP with the most obvious increasing precipitation trend may help understand the precipitation change. This study applied the modified Water Accounting Model with two atmospheric reanalyses, ground-observed precipitation, and evaporation from a land surface model to investigate the change in moisture source of the precipitation over the targeted region. The study estimated that on average more than 69% and more than 21% of the moisture supply to precipitation over the targeted region came from land and ocean, respectively. The moisture transports from the west of the TP by the westerlies and from the southwest by the Indian summer monsoon likely contributed the most to precipitation over the targeted region. The moisture from inside the region may have contributed about 18% of the total precipitation. Most of the increased moisture supply to the precipitation during 1979–2013 was attributed to the enhanced influx from the southwest and the local moisture supply. The precipitation recycling ratio over the targeted region increased significantly, suggesting an intensified hydrological cycle. Further analysis at monthly scale and with wet–dry-year composites indicates that the increased moisture contribution was mainly from the southwest and the targeted region during May and September. The enhanced water vapor transport from the Indian Ocean during July and September and the intensified local hydrological recycling seem to be the primary reasons behind the recent precipitation increase over the targeted region.

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Investigating basin-scale water budget dynamics in 18 rivers across Tibetan Plateau through multiple datasets

10.5194/hess-2017-429 ◽

2017 ◽

Author(s):

Wenbin Liu ◽

Fubao Sun ◽

Yanzhong Li ◽

Guoqing Zhang ◽

Yan-Fang Sang ◽

...

Keyword(s):

Tibetan Plateau ◽

Land Surface ◽

Water Budget ◽

Water Resource Management ◽

Management Practices ◽

Yellow River ◽

Aridity Index ◽

Surface Model ◽

The Tibetan Plateau ◽

Basin Scale

Abstract. The dynamics of basin-scale water budgets are not well understood nowadays over the Tibetan Plateau (TP) due to the lack of hydro-climatic observations. In this study, we investigate seasonal cycles and trends of water budget components (e.g., precipitation-P, evapotranspiration-ET and runoff-Q) in eighteen TP river basins during the period 1982–2011 through the use of multi-source datasets (e.g., in situ observations, satellite retrievals, reanalysis outputs and land surface model simulations). A water balance-based two-step procedure, which considers the changes in basin-scale water storage at the annual scale, is also adopted to calculate actual ET. The results indicated that precipitation (mainly snowfall from mid-autumn to next spring), which mainly concentrated during June–October (varied among different monsoons-impacted basins), was the major contributor to the runoff in TP basins. Increased P, ET and Q were found in most TP basins during the past 30 years except for the upper Yellow River basin and some sub-basins of Yalong River, which were mainly affected by the weakening East Asian Monsoon. Moreover, the aridity index (PET/P) and runoff coefficient (Q/P) decreased in most basins, which were in agreement with the warming and moistening climate in the Tibetan Plateau. The results obtained demonstrated the usefulness of integrating multi-source datasets to hydrological applications in the data-sparse regions. More generally, such approach might offer helpful insights towards understanding the water and energy budgets and sustainability of water resource management practices of data-sparse regions in a changing environment.

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The impact of the Westerlies on the PBL growth and land surface energy balance on the north of the central Himalaya

10.5194/egusphere-egu2020-1329 ◽

2020 ◽

Author(s):

Xuelong Chen ◽

Yue Lai ◽

Yaoming Ma

Keyword(s):

Energy Balance ◽

Tibetan Plateau ◽

Surface Energy ◽

Land Surface ◽

Surface Energy Balance ◽

The Tibetan Plateau ◽

Central Himalaya ◽

Mountainous Areas ◽

The North ◽

The Impact

The spatial-temporal structure of the Planetary Boundary Layer (PBL) over mountainous areas can be strongly modified by topography. The PBL over the mountainous terrain of the Tibetan Plateau (TP) is more complex than that observed over its flat areas. To date, there have been no detailed analyses which have taken into account the topography effects exerted on PBL growth over the Tibetan Plateau (TP). A clear understanding of the processes involved in the PBL growth and depth over the TP&#8217;s mountainous areas is therefore long overdue. The PBL in the Himalayan region of the Tibetan Plateau (TP) is important to the study of interaction between the area&#8217;s topography and synoptic circulation. This study used radiosonde, in-situ measurements and ECMWF ERA5 reanalysis dataset to investigate the vertical structure of the PBL and the land surface energy balance in the Rongbuk Valley on the north of the central Himalaya, and their association with the Westerlies, which control the climate of the Himalaya in winters. Measurements show that the altitude of the PBL&#8217;s top in November was the highest of three intensive observation periods (i.e., June, August and November). The PBLs in November appeared to have been influenced by the Westerlies which prevails in this region during the non-monsoon season. We discovered that the deep PBLs seen in November correlate with the downward transmission of the Westerlies to the valley floor (DTWTV). It was found that DTWTV happened in the direction of southwest when the synoptic wind above the valley ridges height blow from southwest, which is parallel to the valley axis. DTWTV happened in the direction of southwest promotes a stronger near-surface wind, smaller aerodynamic resistance, and larger sensible heat flux, which cause PBLs grow high.

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Evaluation of WRF coupled with Noah using an improved albedo parameterization scheme during a severe snow event over the Tibetan Plateau

10.5194/egusphere-egu2020-4000 ◽

2020 ◽

Author(s):

Lian Liu ◽

Massimo Menenti ◽

Yaoming Ma ◽

Weiqiang Ma

Keyword(s):

Tibetan Plateau ◽

Air Temperature ◽

Land Surface ◽

Large Impact ◽

Parameterization Scheme ◽

Surface Model ◽

The Tibetan Plateau ◽

Vegetation Fraction ◽

Green Vegetation ◽

Heavy Snow

Snow falls frequently over the Tibetan Plateau, and is a vital component of the widespread cryosphere which has vital feedback to climate change. Snowfall and the subsequent evolution of the snowpack have a large effect on surface energy balance and water cycle. Albedo, the main determinant of net radiation flux, is a major driver of land surface processes. However, the current widely used Noah land surface model does not describe snow albedo correctly, although it keeps snow-related variables i.e. snow cover and age into account. In our study, the impact of an improved albedo parameterization scheme in WRF coupled with Noah was investigated. In the improved albedo scheme, albedo was parameterized as functions of snow depth and age which was developed using remote sensing retrievals of albedo. Numerical experiments were conducted to model a severe snow event in March 2017. The performance of WRF coupled with Noah applying the improved albedo scheme was compared with that of applying the default albedo scheme and with that of WRF coupled with CLM applying CLM&#8217;s complex albedo scheme. First, the improved albedo scheme largely reduces the WRF coupled with Noah albedo overestimation in the southeastern Tibetan Plateau, remarkably reducing the large cold bias estimates by 0.7 &#8451; air temperature RMSE. Second, the improved albedo scheme gives the highest correlationship between the satellite-derived and the model estimated albedo, contributing to achieve the SWE spatial pattern, heavy snow belt and maximum SWE estimates in eastern Tibetan Plateau. Remarkable underestimation of albedo in WRF coupled with CLM contributes to regional maximum SWE underestimation and failure in heavy snow belt estimates.In addition, WRF default land cover and green vegetation fraction were out of date but played a large impact on estimates of air temperature, albedo and SWE. Updated land parameters led to improve the model performance in simulating the severe snow event, by reducing albedo RMSE by 1%-4%. The choice of the algorithm to retrieve green vegetation fraction had a large impact on the accuracy of green vegetation fraction retrievals. It remains open to debate the optimal algorithm to estimate land surface properties in the complex topographic Tibetan Plateau.

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