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 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 Drivers and Projections of Global Surface Temperature Anomalies at Sub-City Scale

2021 ◽  
Author(s):  
Susanne A. Benz ◽  
Steven J. Davis ◽  
Jennifer Burney
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Rural Areas ◽  
Urban Areas ◽  
Surface Energy Balance ◽  
Urban Migration ◽  
Data Set ◽  
Surface Temperatures ◽  
Summer Temperatures ◽  
Surrounding Areas

More than half of the world’s population now lives in urban areas, and trends in rural-to-urban migration are expected to continue through the end of the century. Although cities create efficiencies that drive innovation and economic growth, they also alter the local surface energy balance, resulting in urban temperatures that can differ dramatically from surrounding areas. Here we introduce a global 1-km resolution data set of seasonal and diurnal anomalies in urban surface temperatures relative to their rural surroundings, and use satellite-observable parameters in a simple model informed by the surface energy balance to understand the dominant drivers of present urban heating, the heat-related impacts of projected future urbanization, and the potential for policies to mitigate those damages. At present, urban populations live in areas with daytime surface summer temperatures that are 3.21°C (-3.97 - 9.24, 5th-95th percentiles) warmer than surrounding rural areas, such that 1.2 billion people are exposed to average surface summer temperatures in excess of 35°C that might put them at risk of heat-related illness. If design and infrastructure of cities remain unchanged, increased urban heat anomalies will add 0.19°C (-0.01, 0.47) to the daytime summer surface temperatures in urban areas in 2100 -- in addition to warming due to climate change. Such urban heating will increase the number of urban population living under extreme and potentially health-threatening temperatures by approximately 20% compared to current numbers. However we also find a significant potential for mitigation: 82% of all urban areas can optimize vegetation and/or surface albedo and reduce urban daytime summer surface temperatures for the affected population on average by -0.81°C (-2.55, -0.05).

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 Near-surface meteorology during the Arctic Summer Cloud Ocean Study (ASCOS): evaluation of reanalyses and global climate models

2014 ◽  
Vol 14 (1) ◽  
pp. 427-445 ◽  
Author(s):  
G. de Boer ◽  
M. D. Shupe ◽  
P. M. Caldwell ◽  
S. E. Bauer ◽  
O. Persson ◽  
...  
Keyword(s):  
Surface Energy ◽  
Energy Budget ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Surface Energy Budget ◽  
The Arctic ◽  
Near Surface ◽  
Ocean Study ◽  
Arctic Summer

Abstract. Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)-Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

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 Surface temperatures and their influence on the permafrost thermal regime in high Arctic rock walls on Svalbard

2020 ◽  
Author(s):  
Juditha Undine Schmidt ◽  
Bernd Etzelmüller ◽  
Thomas Vikhamar Schuler ◽  
Florence Magnin ◽  
Julia Boike ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
High Arctic ◽  
Heat Fluxes ◽  
Wave Radiation ◽  
Rock Surface ◽  
Permafrost Degradation ◽  
Data Set ◽  
Surface Temperatures

Abstract. Permafrost degradation in steep rock walls and associated slope destabilization have been studied increasingly in recent years. While most studies focus on mountainous and sub-Arctic regions, the occurring thermo-mechanical processes play an important role also in the high Arctic. A more precise understanding is required to assess the risk of natural hazards enhanced by permafrost warming in high Arctic rock walls. This study presents rock surface temperature measurements of coastal and non-coastal rock walls in a high Arctic setting on Svalbard. We applied the surface energy balance model CryoGrid 3 for evaluation, including adjusted radiative forcing to account for vertical rock walls. Our measurements and model results show that rock surface temperatures at coastal cliffs are up to 1.5 °C higher than non-coastal rock walls when the fjord is ice-free in the winter season, resulting from additional energy input due to higher air temperatures at the coast and radiative warming by relatively warm seawater. An ice layer on the fjord counteracts this effect, leading to similar rock surface temperatures as in non-coastal settings. Our results include a simulated surface energy balance with short-wave radiation as the dominant energy source during spring and summer, and long-wave radiation being the main energy loss. While sensible heat fluxes can both warm and cool the surface, latent heat fluxes are mostly insignificant. Simulations for future climate conditions result in a warming of rock surface temperatures and a deepening of active layer thickness for both coastal and non-coastal rock walls. Our field data present a unique data set of rock surface temperatures in steep high Arctic rock walls, while our model can contribute towards the understanding of factors influencing coastal and non-coastal settings and the associated surface energy balance.

scholarly journals The influence of warm-season precipitation on the diel cycle of the surface energy balance and carbon dioxide at a Colorado subalpine forest site

2015 ◽  
Vol 12 (23) ◽  
pp. 7349-7377 ◽  
Author(s):  
S. P. Burns ◽  
P. D. Blanken ◽  
A. A. Turnipseed ◽  
J. Hu ◽  
R. K. Monson
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Warm Season ◽  
Specific Humidity ◽  
Diel Cycle ◽  
Subalpine Forest ◽  
Rain Event ◽  
Sensible Heat ◽  
Data Set

Abstract. Precipitation changes the physical and biological characteristics of an ecosystem. Using a precipitation-based conditional sampling technique and a 14 year data set from a 25 m micrometeorological tower in a high-elevation subalpine forest, we examined how warm-season precipitation affected the above-canopy diel cycle of wind and turbulence, net radiation Rnet, ecosystem eddy covariance fluxes (sensible heat H, latent heat LE, and CO2 net ecosystem exchange NEE) and vertical profiles of scalars (air temperature Ta, specific humidity q, and CO2 dry mole fraction χc). This analysis allowed us to examine how precipitation modified these variables from hourly (i.e., the diel cycle) to multi-day time-scales (i.e., typical of a weather-system frontal passage). During mid-day we found the following: (i) even though precipitation caused mean changes on the order of 50–70 % to Rnet, H, and LE, the surface energy balance (SEB) was relatively insensitive to precipitation with mid-day closure values ranging between 90 and 110 %, and (ii) compared to a typical dry day, a day following a rainy day was characterized by increased ecosystem uptake of CO2 (NEE increased by ≈ 10 %), enhanced evaporative cooling (mid-day LE increased by ≈ 30 W m−2), and a smaller amount of sensible heat transfer (mid-day H decreased by ≈ 70 W m−2). Based on the mean diel cycle, the evaporative contribution to total evapotranspiration was, on average, around 6 % in dry conditions and between 15 and 25 % in partially wet conditions. Furthermore, increased LE lasted at least 18 h following a rain event. At night, even though precipitation (and accompanying clouds) reduced the magnitude of Rnet, LE increased from ≈ 10 to over 20 W m−2 due to increased evaporation. Any effect of precipitation on the nocturnal SEB closure and NEE was overshadowed by atmospheric phenomena such as horizontal advection and decoupling that create measurement difficulties. Above-canopy mean χc during wet conditions was found to be about 2–3 μmol mol−1 larger than χc on dry days. This difference was fairly constant over the full diel cycle suggesting that it was due to synoptic weather patterns (different air masses and/or effects of barometric pressure). Finally, the effect of clouds on the timing and magnitude of daytime ecosystem fluxes is described.

scholarly journals Development of a 10-year (2001–2010) 0.1° data set of land-surface energy balance for mainland China

2014 ◽  
Vol 14 (23) ◽  
pp. 13097-13117 ◽  
Author(s):  
X. Chen ◽  
Z. Su ◽  
Y. Ma ◽  
S. Liu ◽  
Q. Yu ◽  
...  
Keyword(s):  
Energy Balance ◽  
High Resolution ◽  
Surface Energy ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Water Cycle ◽  
Surface Radiation ◽  
Wave Radiation ◽  
The Tibetan Plateau ◽  
Data Set

Abstract. In the absence of high-resolution estimates of the components of surface energy balance for China, we developed an algorithm based on the surface energy balance system (SEBS) to generate a data set of land-surface energy and water fluxes on a monthly timescale from 2001 to 2010 at a 0.1 × 0.1° spatial resolution by using multi-satellite and meteorological forcing data. A remote-sensing-based method was developed to estimate canopy height, which was used to calculate roughness length and flux dynamics. The land-surface flux data set was validated against "ground-truth" observations from 11 flux tower stations in China. The estimated fluxes correlate well with the stations' measurements for different vegetation types and climatic conditions (average bias = 11.2 Wm−2, RMSE = 22.7 Wm−2). The quality of the data product was also assessed against the GLDAS data set. The results show that our method is efficient for producing a high-resolution data set of surface energy flux for the Chinese landmass from satellite data. The validation results demonstrate that more accurate downward long-wave radiation data sets are needed to be able to estimate turbulent fluxes and evapotranspiration accurately when using the surface energy balance model. Trend analysis of land-surface radiation and energy exchange fluxes revealed that the Tibetan Plateau has undergone relatively stronger climatic change than other parts of China during the last 10 years. The capability of the data set to provide spatial and temporal information on water-cycle and land–atmosphere interactions for the Chinese landmass is examined. The product is free to download for studies of the water cycle and environmental change in China.

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 Near-surface meteorology during the Arctic Summer Cloud Ocean Study (ASCOS): evaluation of reanalyses and global climate models

2013 ◽  
Vol 13 (7) ◽  
pp. 19421-19470 ◽  
Author(s):  
G. de Boer ◽  
M. D. Shupe ◽  
P. M. Caldwell ◽  
S. E. Bauer ◽  
P. O. G. Persson ◽  
...  
Keyword(s):  
Surface Energy ◽  
Energy Budget ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Surface Energy Budget ◽  
The Arctic ◽  
Near Surface ◽  
Ocean Study ◽  
Arctic Summer

Abstract. Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three reanalyses (ERA-Interim, NCEP/NCAR and NCEP/DOE) and two global climate models (CAM5 and NASA GISS ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, is demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the need to evaluate individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms resulting in the best net energy budget.

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