Analysis of the atmospheric energy budget: A consistency study of available data sets

1999 ◽  
Vol 104 (D8) ◽  
pp. 9655-9661 ◽  
Author(s):  
Rucong Yu ◽  
Minghua Zhang ◽  
Robert D. Cess
Keyword(s):  
Energy Budget ◽  
Data Sets ◽  
Atmospheric Energy

Impact of time sampling on atmospheric energy budget residuals

2001 ◽  
Vol 77 (1-4) ◽  
pp. 167-184 ◽  
Author(s):  
L. Haimberger ◽  
B. Ahrens ◽  
F. Hamelbeck ◽  
M. Hantel
Keyword(s):  
Energy Budget ◽  
Time Sampling ◽  
Atmospheric Energy

scholarly journals New estimates of the large-scale Arctic atmospheric energy budget

2010 ◽  
Vol 115 (D8) ◽  
Author(s):  
David F. Porter ◽  
John J. Cassano ◽  
Mark C. Serreze ◽  
David N. Kindig
Keyword(s):  
Energy Budget ◽  
Large Scale ◽  
Atmospheric Energy

scholarly journals The Energy Budget of the Polar Atmosphere in MERRA

2012 ◽  
Vol 25 (1) ◽  
pp. 5-24 ◽  
Author(s):  
Richard I. Cullather ◽  
Michael G. Bosilovich
Keyword(s):  
Energy Budget ◽  
The Arctic ◽  
Polar Regions ◽  
Polar Cap ◽  
The South ◽  
Atmospheric Energy ◽  
In Situ Observations ◽  
Energy Convergence ◽  
South Polar

Abstract Components of the atmospheric energy budget from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) are evaluated in polar regions for the period 1979–2005 and compared with previous estimates, in situ observations, and contemporary reanalyses. Closure of the budget is reflected by the analysis increments term, which indicates an energy surplus of 11 W m−2 over the North Polar cap (70°–90°N) and 22 W m−2 over the South Polar cap (70°–90°S). Total atmospheric energy convergence from MERRA compares favorably with previous studies for northern high latitudes but exceeds the available previous estimate for the South Polar cap by 46%. Discrepancies with the Southern Hemisphere energy transport are largest in autumn and may be related to differences in topography with earlier reanalyses. For the Arctic, differences between MERRA and other sources in top of atmosphere (TOA) and surface radiative fluxes are largest in May. These differences are concurrent with the largest discrepancies between MERRA parameterized and observed surface albedo. For May, in situ observations of the upwelling shortwave flux in the Arctic are 80 W m−2 larger than MERRA, while the MERRA downwelling longwave flux is underestimated by 12 W m−2 throughout the year. Over grounded ice sheets, the annual mean net surface energy flux in MERRA is erroneously nonzero. Contemporary reanalyses from the Climate Forecast Center (CFSR) and the Interim Re-Analyses of the European Centre for Medium-Range Weather Forecasts (ERA-I) are found to have better surface parameterizations; however, these reanalyses also disagree with observed surface and TOA energy fluxes. Discrepancies among available reanalyses underscore the challenge of reproducing credible estimates of the atmospheric energy budget in polar regions.

scholarly journals How Well Do the CMIP5 Models Simulate the Antarctic Atmospheric Energy Budget?

2015 ◽  
Vol 28 (20) ◽  
pp. 7933-7942 ◽  
Author(s):  
Michael Previdi ◽  
Karen L. Smith ◽  
Lorenzo M. Polvani
Keyword(s):  
Sea Ice ◽  
Energy Budget ◽  
General Circulation ◽  
Climate Model ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Secondary Importance ◽  
Sea Ice Extent ◽  
Atmospheric Energy ◽  
The Antarctic

Abstract The authors evaluate 23 coupled atmosphere–ocean general circulation models from phase 5 of CMIP (CMIP5) in terms of their ability to simulate the observed climatological mean energy budget of the Antarctic atmosphere. While the models are shown to capture the gross features of the energy budget well [e.g., the observed two-way balance between the top-of-atmosphere (TOA) net radiation and horizontal convergence of atmospheric energy transport], the simulated TOA absorbed shortwave (SW) radiation is too large during austral summer. In the multimodel mean, this excessive absorption reaches approximately 10 W m−2, with even larger biases (up to 25–30 W m−2) in individual models. Previous studies have identified similar climate model biases in the TOA net SW radiation at Southern Hemisphere midlatitudes and have attributed these biases to errors in the simulated cloud cover. Over the Antarctic, though, model cloud errors are of secondary importance, and biases in the simulated TOA net SW flux are instead driven mainly by biases in the clear-sky SW reflection. The latter are likely related in part to the models’ underestimation of the observed annual minimum in Antarctic sea ice extent, thus underscoring the importance of sea ice in the Antarctic energy budget. Finally, substantial differences in the climatological surface energy fluxes between existing observational datasets preclude any meaningful assessment of model skill in simulating these fluxes.

scholarly journals Atmospheric energy budget response to idealized aerosol perturbation in tropical cloud systems

2019 ◽  
Author(s):  
Guy Dagan ◽  
Philip Stier ◽  
Matthew Christensen ◽  
Guido Cioni ◽  
Daniel Klocke ◽  
...  
Keyword(s):  
Energy Budget ◽  
Sensible Heat Flux ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
Cloud Droplet ◽  
Near Surface ◽  
Cloud Systems ◽  
Atmospheric Energy ◽  
Convective Clouds ◽  
Aerosol Effects

Abstract. The atmospheric energy budget is analysed in numerical simulations of tropical cloud systems. This is done in order to better understand the physical processes behind aerosol effects on the atmospheric energy budget. The simulations include both shallow convective clouds and deep convective tropical clouds over the Atlantic Ocean. Two different sets of simulations, at different dates (10–12/8/2016 and 16–18/8/2016), are being simulated with different dominant cloud modes (shallow or deep). For each case, the cloud droplet number concentrations (CDNC) is varied as a proxy for changes in aerosol concentrations. It is shown that the total column atmospheric radiative cooling is substantially reduced with CDNC in the deep-cloud dominated case (by ~ 10.0 W/m2), while a much smaller reduction (~ 1.6 W/m2) is shown in the shallow-cloud dominated case. This trend is caused by an increase in the ice and water vapor content at the upper troposphere that leads to a reduced outgoing longwave radiation. A decrease in sensible heat flux (driven by increase in the near surface air temperature) reduces the warming by ~ 1.4 W/m2 in both cases. It is also shown that the cloud fraction response behaves in opposite ways to an increase in CDNC, showing an increase in the deep-cloud dominated case and a decrease in the shallow-cloud dominated case. This demonstrates that under different environmental conditions the response to aerosol perturbation could be different.

The Arctic lapse rate feedback: An energy budget analysis of CMIP6 models

2021 ◽  
Author(s):  
Olivia Linke ◽  
Johannes Quaas
Keyword(s):  
Arctic Ocean ◽  
Energy Budget ◽  
Surface Albedo ◽  
Heat Fluxes ◽  
Lapse Rate ◽  
The Arctic ◽  
Albedo Feedback ◽  
Temperature Lapse Rate ◽  
Atmospheric Energy ◽  
Rate Feedback

<p>The strong warming trend in the Arctic is mostly confined at the surface, and particularly evident during the cold season. The lapse rate feedback (LRF) stands out as one of the dominant causes of the Arctic amplification (besides the surface albedo feedback) given its differing response between high and lower latitudes. The LRF is the deviation from the uniform temperature change throughout the troposphere, and can thereby be quantified as the difference of tropospheric warming and surface warming. In the Arctic, it enforces a positive radiative feedback as the bottom-heavy warming is increasingly muted at higher altitudes, which has been suggested to relate to the lack of vertical mixing. In fact, climate model studies have recently identified more negative lapse rates for models with stronger inversions over large parts of the Arctic ocean, and snow-free land during winter.</p><p>Here we quantify individual components of the atmospheric energy balance to better understand the determination of the temperature lapse rate in the Arctic, which does not only interact with the surface albedo feedback, but also changes in atmospheric transport. A decomposition of the atmospheric energy budget is derived from the 6th phase of the Coupled Model Intercomparison Project (CMIP6), and concerns the radiation budgets, the transport divergence of heat and moisture, and the surface turbulent heat fluxes. Alterations of the budget components are obtained through pairs of model scenarios to simulate the impact of increasing atmospheric CO2 levels in an idealized setup.</p><p>The most notable features are the strongly opposing winter changes of the surface heat fluxes over regions of sea ice retreat and open Arctic ocean, and the interplay with the compensating energy transport divergence which can be linked to the near-surface air moist static energy in an energetic-diffusive perspective. We further aim to relate the changes of individual energetics to the temperature lapse rate in the Arctic to better understand and quantify the factors contributing to its evolution.</p>

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