Modeling the Water and Energy Balance of Vegetated Areas with Snow Accumulation

2009 ◽  
Vol 8 (4) ◽  
pp. 1013-1030 ◽  
Author(s):  
T. J. Kelleners ◽  
D. G. Chandler ◽  
J. P. McNamara ◽  
M. M. Gribb ◽  
M. S. Seyfried
2016 ◽  
Vol 10 (4) ◽  
pp. 1395-1413 ◽  
Author(s):  
Christian Stiegler ◽  
Magnus Lund ◽  
Torben Røjle Christensen ◽  
Mikhail Mastepanov ◽  
Anders Lindroth

Abstract. Snow cover is one of the key factors controlling Arctic ecosystem functioning and productivity. In this study we assess the impact of strong variability in snow accumulation during 2 subsequent years (2013–2014) on the land–atmosphere interactions and surface energy exchange in two high-Arctic tundra ecosystems (wet fen and dry heath) in Zackenberg, Northeast Greenland. We observed that record-low snow cover during the winter 2012/2013 resulted in a strong response of the heath ecosystem towards low evaporative capacity and substantial surface heat loss by sensible heat fluxes (H) during the subsequent snowmelt period and growing season. Above-average snow accumulation during the winter 2013/2014 promoted summertime ground heat fluxes (G) and latent heat fluxes (LE) at the cost of H. At the fen ecosystem a more muted response of LE, H and G was observed in response to the variability in snow accumulation. Overall, the differences in flux partitioning and in the length of the snowmelt periods and growing seasons during the 2 years had a strong impact on the total accumulation of the surface energy balance components. We suggest that in a changing climate with higher temperature and more precipitation the surface energy balance of this high-Arctic tundra ecosystem may experience a further increase in the variability of energy accumulation, partitioning and redistribution.


2013 ◽  
Vol 17 (12) ◽  
pp. 5127-5139 ◽  
Author(s):  
G. A. Artan ◽  
J. P. Verdin ◽  
R. Lietzow

Abstract. We illustrate the ability to monitor the status of snow water content over large areas by using a spatially distributed snow accumulation and ablation model that uses data from a weather forecast model in the upper Colorado Basin. The model was forced with precipitation fields from the National Weather Service (NWS) Multi-sensor Precipitation Estimator (MPE) and the Tropical Rainfall Measuring Mission (TRMM) data-sets; remaining meteorological model input data were from NOAA's Global Forecast System (GFS) model output fields. The simulated snow water equivalent (SWE) was compared to SWEs from the Snow Data Assimilation System (SNODAS) and SNOwpack TELemetry system (SNOTEL) over a region of the western US that covers parts of the upper Colorado Basin. We also compared the SWE product estimated from the special sensor microwave imager (SSM/I) and scanning multichannel microwave radiometer (SMMR) to the SNODAS and SNOTEL SWE data-sets. Agreement between the spatial distributions of the simulated SWE with MPE data was high with both SNODAS and SNOTEL. Model-simulated SWE with TRMM precipitation and SWE estimated from the passive microwave imagery were not significantly correlated spatially with either SNODAS or the SNOTEL SWE. Average basin-wide SWE simulated with the MPE and the TRMM data were highly correlated with both SNODAS (r = 0.94 and r = 0.64; d.f. = 14 – d.f. = degrees of freedom) and SNOTEL (r = 0.93 and r = 0.68; d.f. = 14). The SWE estimated from the passive microwave imagery was significantly correlated with the SNODAS SWE (r = 0.55, d.f. = 9, p = 0.05) but was not significantly correlated with the SNOTEL-reported SWE values (r = 0.45, d.f. = 9, p = 0.05).The results indicate the applicability of the snow energy balance model for monitoring snow water content at regional scales when coupled with meteorological data of acceptable quality. The two snow water contents from the microwave imagery (SMMR and SSM/I) and the Utah Energy Balance forced with the TRMM precipitation data were found to be unreliable sources for mapping SWE in the study area; both data sets lacked discernible variability of snow water content between sites as seen in the SNOTEL and SNODAS SWE data. This study will contribute to better understanding the adequacy of data from weather forecast models, TRMM, and microwave imagery for monitoring status of the snow water content.


Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1058 ◽  
Author(s):  
Yan Liu ◽  
Pu Zhang ◽  
Lei Nie ◽  
Jianhui Xu ◽  
Xinyu Lu ◽  
...  

Understanding the snow accumulation and melting process is of great significance for the assessment and regulation of water resources and the prevention of meltwater flooding, especially for the semiarid region in the Manas River Basin. However, the lack of long snow measurement time series in this semiarid region prevents a full understanding of the detailed local-scale snow ablation process. Additionally, the modeling of snow accumulation and melting is challenging due to parameter uncertainty. In this study, the snow ablation process in the Manas River Basin was quantitatively explored with long time-series of 3-h measurements of snow depth, snow density and snow water equivalent (SWE) at the Wulanwusu (WLWS), Hanqiazi (HQZ), and Baiyanggou (BYG) sites. This study explored the ability of the Utah energy balance (UEB) snow accumulation and melt model to simulate SWE, energy flux and water loss in the study area. Furthermore, the uncertainty in the ground surface aerodynamic roughness index zos in the UEB model was also analyzed. The results showed that: (1) noticeable variations in snow depth, SWE and snow density occurred on seasonal and interannual time scales, and variations in melting time and melting ratios occurred on short time scales; (2) a rapid decrease in snow depth did not influence the variations in SWE, and snow melting occurred during all time periods, even winter, which is a typical characteristic of snow accumulation in arid environments; (3) the UEB model accurately simulated the snow ablation processes, including SWE, snow surface temperature, and energy flux, at WLWS, HQZ, and BYG sites; (4) the lowest contribution of net radiation to melting occurred in the piedmont clinoplain, followed by the mountain desert grassland belt and mountain forest belt, whereas the contributions of net turbulence exhibited the opposite pattern; (5) the optimal zos in the UEB model was experimentally determined to be 0.01 m, and the UEB model-simulated SWE based on this value was the most consistent with the measured SWE; and (6) the results may provide theoretical and data foundations for research on the snow accumulation process at the watershed scale.


2012 ◽  
Vol 6 (1) ◽  
pp. 199-209 ◽  
Author(s):  
D. van As ◽  
A. L. Hubbard ◽  
B. Hasholt ◽  
A. B. Mikkelsen ◽  
M. R. van den Broeke ◽  
...  

Abstract. This study uses data from six on-ice weather stations, calibrated MODIS-derived albedo and proglacial river gauging measurements to drive and validate an energy balance model. We aim to quantify the record-setting positive temperature anomaly in 2010 and its effect on mass balance and runoff from the Kangerlussuaq sector of the Greenland ice sheet. In 2010, the average temperature was 4.9 °C (2.7 standard deviations) above the 1974–2010 average in Kangerlussuaq. High temperatures were also observed over the ice sheet, with the magnitude of the positive anomaly increasing with altitude, particularly in August. Simultaneously, surface albedo was anomalously low in 2010, predominantly in the upper ablation zone. The low albedo was caused by high ablation, which in turn profited from high temperatures and low winter snowfall. Surface energy balance calculations show that the largest melt excess (∼170%) occurred in the upper ablation zone (above 1000 m), where higher temperatures and lower albedo contributed equally to the melt anomaly. At lower elevations the melt excess can be attributed to high atmospheric temperatures alone. In total, we calculate that 6.6 ± 1.0 km3 of surface meltwater ran off the ice sheet in the Kangerlussuaq catchment in 2010, exceeding the reference year 2009 (based on atmospheric temperature measurements) by ∼150%. During future warm episodes we can expect a melt response of at least the same magnitude, unless a larger wintertime snow accumulation delays and moderates the melt-albedo feedback. Due to the hypsometry of the ice sheet, yielding an increasing surface area with elevation, meltwater runoff will be further amplified by increases in melt forcings such as atmospheric heat.


2013 ◽  
Vol 7 (4) ◽  
pp. 1205-1225 ◽  
Author(s):  
L. I. Nicholson ◽  
R. Prinz ◽  
T. Mölg ◽  
G. Kaser

Abstract. The Lewis Glacier on Mt Kenya is one of the best-studied tropical glaciers, but full understanding of the interaction of the glacier mass balance and its climatic drivers has been hampered by a lack of long-term meteorological data. Here we present 2.5 yr of meteorological data collected from the glacier surface from October 2009 to February 2012. The location of measurements is in the upper portion of Lewis Glacier, but this location experiences negative annual mass balance, and the conditions are comparable to those experienced in the lower ablation zones of South American glaciers in the inner tropics. In the context of other glaciated mountains of equatorial East Africa, the summit zone of Mt Kenya shows strong diurnal cycles of convective cloud development as opposed to the Rwenzoris, where cloud cover persists throughout the diurnal cycle, and Kilimanjaro, where clear skies prevail. Surface energy fluxes were calculated for the meteorological station site using a physical mass- and energy-balance model driven by measured meteorological data and additional input parameters that were determined by Monte Carlo optimization. Sublimation rate was lower than those reported on other tropical glaciers, and melt rate was high throughout the year, with the glacier surface reaching the melting point on an almost daily basis. Surface mass balance is influenced by both solid precipitation and air temperature, with radiation providing the greatest net source of energy to the surface. Cloud cover typically reduces the net radiation balance compared to clear-sky conditions, and thus the frequent formation of convective clouds over the summit of Mt Kenya and the associated higher rate of snow accumulation are important in limiting the rate of mass loss from the glacier surface. The analyses shown here form the basis for future glacier-wide mass and energy balance modeling to determine the climate proxy offered by the glaciers of Mt Kenya.


2012 ◽  
Vol 6 (6) ◽  
pp. 5181-5224 ◽  
Author(s):  
L. Nicholson ◽  
R. Prinz ◽  
T. Mölg ◽  
G. Kaser

Abstract. The Lewis Glacier on Mt Kenya is one of the best-studied tropical glaciers, but full understanding of the interaction of the glacier mass balance and climate forcing has been hampered by a lack of long term meteorological data. Here we present 2.5 yr of meteorological data collected from the glacier surface from October 2009–February 2012, which indicate that mean meteorological conditions in the upper zone of Lewis Glacier are comparable to those experienced in the ablation zones of South American tropical glaciers. In the context of other glaciated mountains of equatorial east Africa, the summit zone of Mt Kenya shows strong diurnal cycles of convective cloud development as opposed to the Rwenzoris where cloud cover persists throughout the diurnal cycle and Kilimanjaro where clear skies prevail. Surface energy fluxes were calculated for the meteorological station site using a physical mass- and energy-balance model driven by hourly measured meteorological data and additional input parameters that were determined by Monte Carlo optimization. Sublimation rate was lower than those reported on other tropical glaciers and melt rate was high throughout the year, with the glacier surface reaching the melting point on an almost daily basis. Surface mass balance is influenced by both solid precipitation and air temperature, with radiation providing the greatest net source of energy to the surface. Cloud cover typically reduces the net radiation balance compared to clear sky conditions, and thus the more frequent formation of convective clouds over the summit of Mt Kenya, and the associated higher rate of snow accumulation are important in limiting the rate of mass loss from the glacier surface. The analyses shown here are the basis for glacier-wide mass and energy balance modeling to determine the climate proxy offered by the glaciers of Mt Kenya.


2019 ◽  
Vol 13 (4) ◽  
pp. 1247-1265 ◽  
Author(s):  
Rebecca Mott ◽  
Andreas Wolf ◽  
Maximilian Kehl ◽  
Harald Kunstmann ◽  
Michael Warscher ◽  
...  

Abstract. The mass balance of very small glaciers is often governed by anomalous snow accumulation, winter precipitation being multiplied by snow redistribution processes (gravitationally or wind driven), or suppressed snow ablation driven by micrometeorological effects lowering net radiation and/or turbulent heat exchange. In this case study, we analysed the relative contribution of snow accumulation and ablation processes governing the long- and short-term mass balance of the lowest perennial ice field of the Alps, the Ice Chapel, located at 870 m a.s.l. in the Berchtesgaden National Park (Germany). This study emphasizes the importance of the local topographic setting for the survival of a perennial ice field located far below the climatic snow line. Although long-term mass balance measurements of the ice field surface showed a dramatic mass loss between 1973 and 2014, the ice field mass balance was rather stable between 2014 and 2017 and even showed a strong mass gain in 2017/2018 with an increase in surface height by 50 %–100 % relative to the ice field thickness. Measurements suggest that the winter mass balance clearly dominated the annual mass balance. At the Ice Chapel surface, 92 % of snow accumulation was gained by snow avalanching, thus clearly governing the 2017/2018 winter mass balance of the ice field with mean snow depths of 32 m at the end of the accumulation period. Avalanche deposition was amplified by preferential deposition of snowfall in the wind-sheltered rock face surrounding the ice field. Detailed micrometeorological measurements combined with a numerical analysis of the small-scale near-surface atmospheric flow field identified the micrometeorological processes driving the energy balance of the ice field. Measurements revealed a katabatic flow system draining down the ice field throughout the day, showing strong temporal and spatial dynamics. The spatial origin of the thermal flow system was shown to be of particular importance for the ice field surface energy balance. Numerical simulation indicates that deep katabatic flows, which developed at higher-elevation shaded areas of the rock face and drained down the ice field, enhance sensible heat exchange towards the ice field surface by enhancing turbulence close to the ice surface. Conversely, the shallow katabatic flow developing at the ice field surface appeared to laterally decouple the local near-surface atmosphere from the warmer adjacent air suppressing heat exchange. Numerical results thus suggest that shallow katabatic flows driven by the cooling effect of the ice field surface are especially efficient in lowering the climatic sensitivity of the ice field to the surrounding rising air temperatures. Such micrometeorological phenomena must be taken into account when calculating mass and energy balances of very small glaciers or perennial ice fields at elevations far below the climatic snow line.


2016 ◽  
Vol 20 (1) ◽  
pp. 411-430 ◽  
Author(s):  
E. Cornwell ◽  
N. P. Molotch ◽  
J. McPhee

Abstract. Seasonal snow cover is the primary water source for human use and ecosystems along the extratropical Andes Cordillera. Despite its importance, relatively little research has been devoted to understanding the properties, distribution and variability of this natural resource. This research provides high-resolution (500 m), daily distributed estimates of end-of-winter and spring snow water equivalent over a 152 000 km2 domain that includes the mountainous reaches of central Chile and Argentina. Remotely sensed fractional snow-covered area and other relevant forcings are combined with extrapolated data from meteorological stations and a simplified physically based energy balance model in order to obtain melt-season melt fluxes that are then aggregated to estimate the end-of-winter (or peak) snow water equivalent (SWE). Peak SWE estimates show an overall coefficient of determination R2 of 0.68 and RMSE of 274 mm compared to observations at 12 automatic snow water equivalent sensors distributed across the model domain, with R2 values between 0.32 and 0.88. Regional estimates of peak SWE accumulation show differential patterns strongly modulated by elevation, latitude and position relative to the continental divide. The spatial distribution of peak SWE shows that the 4000–5000 m a.s.l. elevation band is significant for snow accumulation, despite having a smaller surface area than the 3000–4000 m a.s.l. band. On average, maximum snow accumulation is observed in early September in the western Andes, and in early October on the eastern side of the continental divide. The results presented here have the potential of informing applications such as seasonal forecast model assessment and improvement, regional climate model validation, as well as evaluation of observational networks and water resource infrastructure development.


2014 ◽  
Vol 18 (9) ◽  
pp. 3553-3570 ◽  
Author(s):  
R. Sultana ◽  
K.-L. Hsu ◽  
J. Li ◽  
S. Sorooshian

Abstract. Noah (version 2.7.1), the community land-surface model (LSM) of National Centers for Environmental Predictions-National Center for Atmospheric Research (NCEP-NCAR), which is widely used to describe the land-surface processes either in stand-alone or in coupled land-atmospheric model systems, is recognized to underestimate snow–water equivalent (SWE). Noah's SWE bias can be attributed to its simple snow sub-model, which does not effectively describe the physical processes during snow accumulation and melt period. To improve SWE simulation in the Noah LSM, the Utah Energy Balance (UEB) snow model is implemented in Noah to test alternate snow surface temperature and snowmelt outflow schemes. Snow surface temperature was estimated using the force-restore method and snowmelt event is regulated by accounting for the internal energy of the snowpack. The modified Noah's SWE simulations are compared with the SWE observed at California's NRCS SNOTEL stations for 7 water years: 2002–2008, while the model's snow surface temperature is verified with observed surface-temperature data at an observation site in Utah. The experiments show that modification in Noah's snow process substantially reduced SWE estimation bias while keeping the simplicity of the Noah LSM. The results suggest that the model did not benefit from the alternate temperature representation but primary improvement can be attributed to the substituted snowmelt process.


2016 ◽  
Vol 9 (2) ◽  
pp. 633-646 ◽  
Author(s):  
T. Marke ◽  
E. Mair ◽  
K. Förster ◽  
F. Hanzer ◽  
J. Garvelmann ◽  
...  

Abstract. This article describes the extension of the ESCIMO.spread spreadsheet-based point energy balance snow model by (i) an advanced approach for precipitation phase detection, (ii) a method for cold content and liquid water storage consideration and (iii) a canopy sub-model that allows the quantification of canopy effects on the meteorological conditions inside the forest as well as the simulation of snow accumulation and ablation inside a forest stand. To provide the data for model application and evaluation, innovative low-cost snow monitoring systems (SnoMoS) have been utilized that allow the collection of important meteorological and snow information inside and outside the canopy. The model performance with respect to both, the modification of meteorological conditions as well as the subsequent calculation of the snow cover evolution, are evaluated using inside- and outside-canopy observations of meteorological variables and snow cover evolution as provided by a pair of SnoMoS for a site in the Black Forest mountain range (southwestern Germany). The validation results for the simulated snow water equivalent with Nash–Sutcliffe model efficiency values of 0.81 and 0.71 and root mean square errors of 8.26 and 18.07 mm indicate a good overall model performance inside and outside the forest canopy, respectively. The newly developed version of the model referred to as ESCIMO.spread (v2) is provided free of charge together with 1 year of sample data including the meteorological data and snow observations used in this study.


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