scholarly journals Sea water surface energy balance in the Arctic fjord (Hornsund, SW Spitsbergen) in May–November 2014

2016 ◽  
Vol 128 (3-4) ◽  
pp. 959-970 ◽  
Author(s):  
Krzysztof Fortuniak ◽  
Rajmund Przybylak ◽  
Andrzej Araźny ◽  
Włodzimierz Pawlak ◽  
Przemysław Wyszyński
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Water Surface ◽  
Surface Energy Balance ◽  
Sea Water ◽  
The Arctic ◽  
Arctic Fjord

scholarly journals The Arctic Summer Cloud Ocean Study (ASCOS): overview and experimental design

2014 ◽  
Vol 14 (6) ◽  
pp. 2823-2869 ◽  
Author(s):  
M. Tjernström ◽  
C. Leck ◽  
C. E. Birch ◽  
J. W. Bottenheim ◽  
B. J. Brooks ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Cloud Condensation Nuclei ◽  
The Arctic ◽  
Data Set ◽  
Arctic Clouds ◽  
Pack Ice ◽  
Ocean Study ◽  
Arctic Summer

Abstract. The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol–cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007–2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87°21' N, 01°29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations, and the balance between local and remote aerosols sources remains open. Lack of cloud condensation nuclei (CCN) was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets.

scholarly journals Surface Energy Balance on the Arctic Tundra: Measurements and Models

1999 ◽  
Vol 12 (8) ◽  
pp. 2585-2606 ◽  
Author(s):  
A. H. Lynch ◽  
F. S. Chapin ◽  
L. D. Hinzman ◽  
W. Wu ◽  
E. Lilly ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Arctic Tundra ◽  
The Arctic

scholarly journals The Arctic Summer Cloud-Ocean Study (ASCOS): overview and experimental design

2013 ◽  
Vol 13 (5) ◽  
pp. 13541-13652 ◽  
Author(s):  
M. Tjernström ◽  
C. Leck ◽  
C. E. Birch ◽  
B. J. Brooks ◽  
I. M. Brooks ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
The Arctic ◽  
Data Set ◽  
Arctic Clouds ◽  
Low Level ◽  
Pack Ice ◽  
Ocean Study ◽  
Arctic Summer

Abstract. The climate in the Arctic is changing faster than anywhere else on Earth. Poorly understood feedback processes relating to Arctic clouds and aerosol-cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in-situ in this difficult to reach region with logistically demanding environmental conditions. The Arctic Summer Cloud-Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007–2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait; two in open water and two in the marginal ice zone. After traversing the pack-ice northward an ice camp was set up on 12 August at 87°21' N 01°29' W and remained in operation through 1 September, drifting with the ice. During this time extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggest the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations and the balance between local and remote aerosols sources remains open. Lack of CCN was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets.

scholarly journals Surface Energy Balance Framework for Arctic Amplification of Climate Change

2012 ◽  
Vol 25 (23) ◽  
pp. 8277-8288 ◽  
Author(s):  
Glen Lesins ◽  
Thomas J. Duck ◽  
James R. Drummond
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
The Arctic ◽  
Arctic Amplification ◽  
Global Average ◽  
Inversion Strength

Abstract Using 22 Canadian radiosonde stations from 1971 to 2010, the annually averaged surface air temperature trend amplification ranged from 1.4 to 5.2 relative to the global average warming of 0.17°C decade−1. The amplification factors exhibit a strong latitudinal dependence varying from 2.6 to 5.2 as the latitude increases from 50° to 80°N. The warming trend has a strong seasonal dependence with the greatest warming taking place from September to April. The monthly variations in the warming trend are shown to be related to the surface-based temperature inversion strength and the mean monthly surface air temperatures. The surface energy balance (SEB) equation is used to relate the response of the surface temperature to changes in the surface energy fluxes. Based on the SEB analysis, there are four contributing factors to Arctic amplification: 1) a larger change in net downward radiation at the Arctic surface compared to the global average; 2) a larger snow and soil conductive heat flux change than the global average; 3) weaker sensible and latent heat flux responses that result in a larger surface temperature response in the Arctic; and 4) a colder skin temperature compared to the global average, which forces a larger surface warming to achieve the same increase in upward longwave radiation. The observed relationships between the Canadian station warming trends and both the surface-based inversion strength and the surface air temperature are shown to be consistent with the SEB analysis. Measurements of conductive flux were not available at these stations.

scholarly journals Observational Evidence Linking Arctic Supercooled Liquid Cloud Biases in CESM to Snowfall Processes

2017 ◽  
Vol 30 (12) ◽  
pp. 4477-4495 ◽  
Author(s):  
Elin A. McIlhattan ◽  
Tristan S. L’Ecuyer ◽  
Nathaniel B. Miller
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Climate Models ◽  
Global Climate ◽  
Longwave Radiation ◽  
Supercooled Liquid ◽  
Global Climate Models ◽  
The Arctic ◽  
Community Earth System Model

Clouds are a key regulator of Earth’s surface energy balance. The presence or absence of clouds, along with their macroscale and microscale characteristics, is the primary factor modulating the amount of radiation incident on the surface. Recent observational studies in the Arctic highlight the ubiquity of supercooled liquid-containing clouds (LCCs) and their disproportionately large impact on surface melt. Global climate models (GCMs) do not simulate enough Arctic LCCs compared to observations, and thus fail to represent the surface energy balance correctly. This work utilizes spaceborne observations from NASA’s A-Train satellite constellation to explore physical processes behind LCCs and surface energy biases in the Community Earth System Model Large Ensemble (CESM-LE) project output. On average CESM-LE underestimates LCC frequency by ~18% over the Arctic, resulting in a ~20 W m−2 bias in downwelling longwave radiation (DLR) over the ~18 × 106 km2 area examined. Collocated observations of falling snow and LCCs indicate that Arctic LCCs produce precipitation ~13% of the time. Conversely, CESM-LE generates snow in ~70% of LCCs. This result indicates that the Wegener–Bergeron–Findeisen (WBF) process—the growth of ice at the expense of supercooled liquid—may be too strong in the model, causing ice to scavenge polar supercooled cloud liquid too efficiently. Ground-based observations from Summit Station, Greenland, provide further evidence of these biases on a more local scale, suggesting that CESM-LE overestimates snow frequency in LCCs by ~52% at the center of the ice sheet leading to ~21% too few LCCs and ~24 W m−2 too little DLR.

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.

scholarly journals Application of an improved surface energy balance model to two large valley glaciers in the St. Elias Mountains, Yukon

2020 ◽  
pp. 1-16
Author(s):  
Tim Hill ◽  
Christine F. Dow ◽  
Eleanor A. Bash ◽  
Luke Copland
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Shortwave Radiation ◽  
Balance Model ◽  
Landsat 8 ◽  
Glacier Surface ◽  
Ice Dynamics ◽  
Surface Melt

Abstract Glacier surficial melt rates are commonly modelled using surface energy balance (SEB) models, with outputs applied to extend point-based mass-balance measurements to regional scales, assess water resource availability, examine supraglacial hydrology and to investigate the relationship between surface melt and ice dynamics. We present an improved SEB model that addresses the primary limitations of existing models by: (1) deriving high-resolution (30 m) surface albedo from Landsat 8 imagery, (2) calculating shadows cast onto the glacier surface by high-relief topography to model incident shortwave radiation, (3) developing an algorithm to map debris sufficiently thick to insulate the glacier surface and (4) presenting a formulation of the SEB model coupled to a subsurface heat conduction model. We drive the model with 6 years of in situ meteorological data from Kaskawulsh Glacier and Nàłùdäy (Lowell) Glacier in the St. Elias Mountains, Yukon, Canada, and validate outputs against in situ measurements. Modelled seasonal melt agrees with observations within 9% across a range of elevations on both glaciers in years with high-quality in situ observations. We recommend applying the model to investigate the impacts of surface melt for individual glaciers when sufficient input data are available.

scholarly journals A Semiempirical Microscale Model of the Surface Energy Balance and Its Application to Two Urban Rooftops

2008 ◽  
Vol 47 (3) ◽  
pp. 819-834 ◽  
Author(s):  
Timothy M. Barzyk ◽  
John E. Frederick
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Balance Model ◽  
Site Specific ◽  
City Hall ◽  
Microscale Model ◽  
Dry Conditions ◽  
Stone Concrete ◽  
The City

Abstract Individual structures within the same local-scale (102–104 m) environment may experience different microscale (<103 m) climates. Urban microclimate variations are often a result of site-specific features, including spatial and material characteristics of surfaces and surrounding structures. A semiempirical surface energy balance model is presented that incorporates radiative and meteorological measurements to statistically parameterize energy fluxes that are not measured directly, including sensible heat transport, storage heat flux through conduction, and evaporation (assumed to be negligible under dry conditions). Two Chicago rooftops were chosen for detailed study. The City Hall site was located in an intensely developed urban area characterized by close-set high-rise buildings. The University rooftop was in a highly developed area characterized by three- to seven-story buildings of stone, concrete, and brick construction. Two identical sets of instruments recorded measurements contemporaneously from these rooftops during summer 2005, and results from the week of 29 July to 5 August are presented here. The model explains 83.7% and 96% of the variance for the City Hall and University sites, respectively. Results apply to a surface area of approximately 1260 m2, at length scales similar to the dimensions of built structures and other urban elements. A site intercomparison revealed variations in surface energy balance components caused by site-specific features and demonstrated the relevance of the model to urban applications.

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