Supplementary material to "A Bayesian model to correct underestimated 3D wind speeds from sonic anemometers increases turbulent components of the surface energy balance"

2016 ◽  
Author(s):  
John M. Frank ◽  
William J. Massman ◽  
Brent E. Ewers
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Bayesian Model ◽  
Surface Energy Balance ◽  
Wind Speeds ◽  
Sonic Anemometers ◽  
Supplementary Material

scholarly journals Comparison of the meteorology and surface energy balance at Storbreen and Midtdalsbreen, two glaciers in southern Norway

2008 ◽  
Vol 2 (5) ◽  
pp. 873-916
Author(s):  
R. H. Giesen ◽  
L. M. Andreassen ◽  
M. R. van den Broeke ◽  
J. Oerlemans
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Turbulent Fluxes ◽  
Striking Difference ◽  
Net Radiation ◽  
Energy Fluxes ◽  
Wind Speeds ◽  
Weather Stations ◽  
Southern Norway

Abstract. We compare 5 years of meteorological records from automatic weather stations (AWSs) on Storbreen and Midtdalsbreen, two glaciers in southern Norway, located approximately 120 km apart. The records are obtained from identical AWSs with an altitude difference of 130 m and cover the period September 2001 to September 2006. Air temperature at the AWS locations is found to be highly correlated, even with the seasonal cycle removed. The most striking difference between the two sites is the difference in wind climate. Midtdalsbreen is much more under influence of the large-scale circulation with wind speeds on average a factor 1.75 higher. On Storbreen, weaker katabatic winds are dominant. The main melt season is from May to September at both locations. During the melt season, incoming and net solar radiation are larger on Midtdalsbreen, whereas incoming and net longwave radiation are larger on Storbreen, primarily caused by thicker clouds on the latter. The turbulent fluxes are a factor 1.7 larger on Midtdalsbreen, mainly due to the higher wind speeds. Inter-daily fluctuations in the surface energy fluxes are very similar at the AWS sites. On average, melt energy is a factor 1.3 larger on Midtdalsbreen, a result of both larger net radiation and larger turbulent fluxes. The relative contribution of net radiation to surface melt is larger on Storbreen (76%) than on Midtdalsbreen (66%). As winter snow depth at the two locations is comparable in most years, the larger amount of melt energy results in an earlier disappearance of the snowpack on Midtdalsbreen and 70% more ice melt than on Storbreen. We compare the relative and absolute values of the energy fluxes on Storbreen and Midtdalsbreen with reported values for glaciers at similar latitudes. Furthermore, a comparison is made with meteorological variables measured at two nearby weather stations, showing that on-site measurements are essential for an accurate calculation of the surface energy balance and melt rate.

scholarly journals Improving Estimation of Cropland Evapotranspiration by the Bayesian Model Averaging Method with Surface Energy Balance Models

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 188 ◽  
Author(s):  
Huaiwei Sun ◽  
Yong Yang ◽  
Ruiying Wu ◽  
Dongwei Gui ◽  
Jie Xue ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Bayesian Model ◽  
Surface Energy Balance ◽  
Bayesian Model Averaging ◽  
Model Averaging ◽  
Semiarid Region ◽  
Accurate Estimation ◽  
Landsat 8 ◽  
Efficiency Coefficient

Evapotranspiration (ET) is one of the key components of the global hydrological cycle. Many models have been established to obtain an accurate estimation of ET, but the uncertainty of each model has not been satisfactorily addressed, and the weight determination in multi-model simulation methods remains unclear. In this study, the Bayesian model averaging (BMA) method was adopted to tackle this issue. We explored the combination of four surface energy balance (SEB) models (SEBAL, SSEB, S-SEBI and SEBS) with the BMA method by using Landsat 8 images over two study areas in China, the Huailai flux station (semiarid region) and the Sidaoqiao flux station (arid/semiarid region), and the data from two stations were used as validation for this method. The performances of SEB models and different BMA methods is revealed by three statistical parameters (i.e., the coefficient of determination (R2), root mean squared error (RMSE), and the Nash-Sutcliffe efficiency coefficient (NSE)). We found the best performing SEB model was SEBAL, with an R2 of 0.609 (0.672), RMSE of 1.345 (0.876) mm/day, and NSE of 0.407 (0.563) at Huailai (Sidaoqiao) station. Compared with the four individual SEB models, each of the BMA methods (fixed, posterior inclusion probability, or random) can provide a more accurate and reliable simulation result. Similarly, in Huailai (Sidaoqiao) station, the best performing BMA random model provided an R2 of 0.750 (0.796), RMSE of 0.902 (0.602) mm/day, and NSE of 0.746 (0.793). We conclude that the BMA method outperformed the four SEB models alone and obtained a more accurate prediction of ET in two cropland areas, which provides important guidance for water resource allocation and management in arid and semiarid regions.

scholarly journals Comparison of the meteorology and surface energy balance at Storbreen and Midtdalsbreen, two glaciers in southern Norway

2009 ◽  
Vol 3 (1) ◽  
pp. 57-74 ◽  
Author(s):  
R. H. Giesen ◽  
L. M. Andreassen ◽  
M. R. van den Broeke ◽  
J. Oerlemans
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Turbulent Fluxes ◽  
Striking Difference ◽  
Net Radiation ◽  
Energy Fluxes ◽  
Wind Speeds ◽  
Weather Stations ◽  
Southern Norway

Abstract. We compare 5 years of meteorological records from automatic weather stations (AWSs) on Storbreen and Midtdalsbreen, two glaciers in southern Norway, located approximately 120 km apart. The records are obtained from identical AWSs with an altitude difference of 120 m and cover the period September 2001 to September 2006. Air temperature at the AWS locations is found to be highly correlated, even with the seasonal cycle removed. The most striking difference between the two sites is the difference in wind climate. Midtdalsbreen is much more under influence of the large-scale circulation with wind speeds on average a factor 1.75 higher. On Storbreen, weaker katabatic winds are dominant. The main melt season is from May to September at both locations. During the melt season, incoming and net solar radiation are larger on Midtdalsbreen, whereas incoming and net longwave radiation are larger on Storbreen, primarily caused by thicker clouds on the latter. The turbulent fluxes are a factor 1.7 larger on Midtdalsbreen, mainly due to the higher wind speeds. Inter-daily fluctuations in the surface energy fluxes are very similar at the AWS sites. On average, melt energy is a factor 1.3 larger on Midtdalsbreen, a result of both larger net radiation and larger turbulent fluxes. The relative contribution of net radiation to surface melt is larger on Storbreen (76%) than on Midtdalsbreen (66%). As winter snow depth at the two locations is comparable in most years, the larger amount of melt energy results in an earlier disappearance of the snowpack on Midtdalsbreen and 70% more ice melt than on Storbreen. We compare the relative and absolute values of the energy fluxes on Storbreen and Midtdalsbreen with reported values for glaciers at similar latitudes. Furthermore, a comparison is made with meteorological variables measured at two nearby weather stations, showing that on-site measurements are essential for an accurate calculation of the surface energy balance and melt rate.

scholarly journals Using climate reanalysis data in conjunction with multi-temporal satellite thermal imagery to derive supraglacial debris thickness changes from energy-balance modelling

2021 ◽  
pp. 1-19
Author(s):  
Rebecca L. Stewart ◽  
Matthew Westoby ◽  
Francesca Pellicciotti ◽  
Ann Rowan ◽  
Darrel Swift ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Current Knowledge ◽  
Meteorological Data ◽  
Reanalysis Data ◽  
Balance Model ◽  
Thermal Imagery ◽  
Thickness Estimation ◽  
Miage Glacier

Abstract Surface energy-balance models are commonly used in conjunction with satellite thermal imagery to estimate supraglacial debris thickness. Removing the need for local meteorological data in the debris thickness estimation workflow could improve the versatility and spatiotemporal application of debris thickness estimation. We evaluate the use of regional reanalysis data to derive debris thickness for two mountain glaciers using a surface energy-balance model. Results forced using ERA-5 agree with AWS-derived estimates to within 0.01 ± 0.05 m for Miage Glacier, Italy, and 0.01 ± 0.02 m for Khumbu Glacier, Nepal. ERA-5 data were then used to estimate spatiotemporal changes in debris thickness over a ~20-year period for Miage Glacier, Khumbu Glacier and Haut Glacier d'Arolla, Switzerland. We observe significant increases in debris thickness at the terminus for Haut Glacier d'Arolla and at the margins of the expanding debris cover at all glaciers. While simulated debris thickness was underestimated compared to point measurements in areas of thick debris, our approach can reconstruct glacier-scale debris thickness distribution and its temporal evolution over multiple decades. We find significant changes in debris thickness over areas of thin debris, areas susceptible to high ablation rates, where current knowledge of debris evolution is limited.

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