scholarly journals Radiative closure and cloud effects on the radiation budget based on satellite and ship-borne observations during the Arctic summer research cruise PS106

2022 ◽  
Author(s):  
Carola Barrientos-Velasco ◽  
Hartwig Deneke ◽  
Anja Hünerbein ◽  
Hannes J. Griesche ◽  
Patric Seifert ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Arctic Region ◽  
Early Summer ◽  
Radiation Budget ◽  
The Arctic ◽  
Climate Data ◽  
Radiative Fluxes ◽  
Mean Values ◽  
The Difference ◽  
Arctic Climate Change

Abstract. For understanding Arctic climate change, it is critical to quantify and address uncertainties in climate data records on clouds and radiative fluxes derived from long-term passive satellite observations. A unique set of observations collected during the research vessel Polarstern PS106 expedition (28 May to 16 July 2017) by the OCEANET facility is exploited here for this purpose and compared with the CERES SYN1deg Ed. 4.1 satellite remote sensing products. Mean cloud fraction (CF) of 86.7 % for CERES and 76.1 % for OCEANET were found for the entire cruise. The difference of CF between both data sets is due to different spatial resolution and momentary data gaps due to technical limitations of the set of ship-borne instruments. A comparison of radiative fluxes during clear-sky conditions enables radiative closure for CERES products by means of independent radiative transfer simulations. Several challenges were encountered to accurately represent clouds in radiative transfer under cloudy conditions, especially for ice-containing clouds and low-level stratus (LLS) clouds. During LLS conditions, the OCEANET retrievals were in particular compromised by the altitude detection limit of 155 m of the cloud radar. Radiative fluxes from CERES show a good agreement with ship observations, having a bias (standard deviation) of −6.0 (14.6) W m−2 and 23.1 (59.3) W m−2 for the downward longwave (LW) and shortwave (SW) fluxes, respectively. Based on CERES products, mean values of the radiation budget and the cloud radiative effect (CRE) were determined for the PS106 cruise track and the central Arctic region (70°–90° N). For the period of study, the results indicate a strong influence of the SW flux in the radiation budget, which is reduced by clouds leading to a net surface CRE of −8.8 W m−2 and −9.3 W m−2 along the PS106 cruise and for the entire Arctic, respectively. The similarity of local and regional CRE supports that the PS106 cloud observations can be considered to be representative of Arctic cloudiness during early summer.

scholarly journals Aggregate-area radiative flux biases

2002 ◽  
Vol 34 ◽  
pp. 101-105 ◽  
Author(s):  
Xuanji Wang ◽  
Jeffrey R. Key
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Heat Budget ◽  
Numerical Models ◽  
Radiative Flux ◽  
The Arctic ◽  
Radiative Fluxes ◽  
Cloud Properties ◽  
Model Cell ◽  
The Difference

AbstractMost climate models treat surface and atmospheric properties as being horizontally homogeneous and compute surface radiative fluxes with average gridcell properties. In this study it is found that large biases can occur if sub-gridcell variability is ignored, where bias is defined as the difference between the average of fluxes computed at high resolution within a model cell and the flux computed with the average surface and cloud properties within the cell. Data from the Advanced Very High Resolution Radiometer for the year-long Surface Heat Budget of the Arctic Ocean (SHEBA) experiment are used to determine biases in aggregate-area fluxes. A simple regression approach to correct for biases that result from horizontal variability was found to reduce the average radiative flux bias to near zero. The correction can be easily implemented in numerical models.

scholarly journals Combining atmospheric and snow radiative transfer models to assess the solar radiative effects of black carbon in the Arctic

2020 ◽  
Vol 20 (13) ◽  
pp. 8139-8156
Author(s):  
Tobias Donth ◽  
Evelyn Jäkel ◽  
André Ehrlich ◽  
Bernd Heinold ◽  
Jacob Schacht ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Arctic Ocean ◽  
Black Carbon ◽  
Heating Rate ◽  
Radiative Forcing ◽  
Mass Concentration ◽  
Early Summer ◽  
The Arctic ◽  
Snow Layer ◽  
Surface Snow

Abstract. The magnitude of solar radiative effects (cooling or warming) of black carbon (BC) particles embedded in the Arctic atmosphere and surface snow layer was explored on the basis of case studies. For this purpose, combined atmospheric and snow radiative transfer simulations were performed for cloudless and cloudy conditions on the basis of BC mass concentrations measured in pristine early summer and more polluted early spring conditions. The area of interest is the remote sea-ice-covered Arctic Ocean in the vicinity of Spitsbergen, northern Greenland, and northern Alaska typically not affected by local pollution. To account for the radiative interactions between the black-carbon-containing snow surface layer and the atmosphere, an atmospheric and snow radiative transfer model were coupled iteratively. For pristine summer conditions (no atmospheric BC, minimum solar zenith angles of 55∘) and a representative BC particle mass concentration of 5 ng g−1 in the surface snow layer, a positive daily mean solar radiative forcing of +0.2 W m−2 was calculated for the surface radiative budget. A higher load of atmospheric BC representing early springtime conditions results in a slightly negative mean radiative forcing at the surface of about −0.05 W m−2, even when the low BC mass concentration measured in the pristine early summer conditions was embedded in the surface snow layer. The total net surface radiative forcing combining the effects of BC embedded in the atmosphere and in the snow layer strongly depends on the snow optical properties (snow specific surface area and snow density). For the conditions over the Arctic Ocean analyzed in the simulations, it was found that the atmospheric heating rate by water vapor or clouds is 1 to 2 orders of magnitude larger than that by atmospheric BC. Similarly, the daily mean total heating rate (6 K d−1) within a snowpack due to absorption by the ice was more than 1 order of magnitude larger than that of atmospheric BC (0.2 K d−1). Also, it was shown that the cooling by atmospheric BC of the near-surface air and the warming effect by BC embedded in snow are reduced in the presence of clouds.

scholarly journals Analysis of snow bidirectional reflectance from ARCTAS spring-2008 campaign

2009 ◽  
Vol 9 (5) ◽  
pp. 21993-22040 ◽  
Author(s):  
A. Lyapustin ◽  
C. K. Gatebe ◽  
R. Kahn ◽  
R. Brandt ◽  
J. Redemann ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Phase Function ◽  
Full Range ◽  
Arctic Region ◽  
The Arctic ◽  
Bidirectional Reflectance ◽  
International Polar Year ◽  
Sensing Applications ◽  
Synthetic Phase ◽  
Best Fit

Abstract. The spring 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) experiment was one of the major intensive field campaigns of the International Polar Year, aimed at detailed characterization of atmospheric physical and chemical processes in the Arctic region. Part of this campaign was a unique snow bidirectional reflectance experiment on the NASA P-3B aircraft conducted on 7 and 15 April by the Cloud Absorption Radiometer (CAR) jointly with airborne Ames Airborne Tracking Sunphotometer (AATS) and ground-based Aerosol Robotic Network (AERONET) sunphotometers. The CAR data were atmospherically corrected to derive snow bidirectional reflectance at high 1° angular resolution in view zenith and azimuthal angles along with surface albedo. The derived albedo was generally in good agreement with ground albedo measurements collected on 15 April. The CAR snow bidirectional reflectance factor (BRF) was used to study the accuracy of analytical Ross-Thick Li-Sparse (RTLS), Modified Rahman-Pinty-Verstraete (MRPV) and Asymptotic Analytical Radiative Transfer (AART) BRF models. Except for the glint region (azimuthal angles φ<40°), the best fit MRPV and RTLS models fit snow BRF to within ±0.05. The plane-parallel radiative transfer (PPRT) solution was also analyzed with the models of spheres, spheroids, randomly oriented fractal crystals, and with a synthetic phase function. The latter merged the model of spheroids for the forward scattering angles with the fractal model in the backscattering direction. The PPRT solution with synthetic phase function provided the best fit to measured BRF in the full range of angles. Regardless of the snow grain shape, the PPRT model significantly over-/underestimated snow BRF in the glint/backscattering regions, respectively, which agrees with other studies. To improve agreement with the experiment, we introduced a model of macroscopic snow surface roughness by averaging the PPRT solution over the slope distribution function and by adding a simple model of shadows. With macroscopic roughness described by two parameters, the AART model achieved an accuracy of about ±0.05 with a possible bias of ±0.03 in the spectral range 0.4–2.2 μm. This high accuracy holds at view zenith angles below 55–60° covering the practically important range for remote sensing applications, and includes both glint and backscattering directions.

Monitoring and Assessing Arctic Climate Change

2020 ◽  
Author(s):  
Lars-Otto Reiersen ◽  
Robert W. Corell
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Global Climate ◽  
Arctic Region ◽  
The Arctic ◽  
Sea Ice Extent ◽  
The North ◽  
Meteorological Observations ◽  
Arctic Climate Change ◽  
Global Systems

This overview of climate observation, monitoring, and research for the Arctic region outlines the key elements essential to an enhanced understanding of the unprecedented climate change in the region and its global influences. The first recorded observation of sea ice extent around Svalbard date back to the whaling activities around 1600. Over the following 300 years there are periodic and inadequate observations of climate and sea ice from explorers seeking a northern sea route for sailing to Asia or reaching the North Pole. Around 1900 there were few fixed meteorological stations in the circumpolar North. During the Second World War and the following Cold War, the observation network increased significantly due to military interest. Since the 1970s the use of satellites has improved the climate and meteorological observations of Arctic areas, and advancements in marine observations (beneath the sea surface and within oceanic sediments) have contributed to a much improved network of climate and meteorological variables. Climate change in the Arctic and its possible effects within the Arctic and on global climate such as extreme weather and sea level rise were first reported in the ACIA 2005 report. Since then there has been a lot of climate-related assessments based on data from the Arctic and ongoing processes within the Arctic that are linked to global systems.

scholarly journals Decomposing Shortwave Top-of-Atmosphere and Surface Radiative Flux Variations in Terms of Surface and Atmospheric Contributions

2019 ◽  
Vol 32 (16) ◽  
pp. 5003-5019 ◽  
Author(s):  
Norman G. Loeb ◽  
Hailan Wang ◽  
Fred G. Rose ◽  
Seiji Kato ◽  
William L. Smith ◽  
...  
Keyword(s):  
Regional Distribution ◽  
Radiant Energy ◽  
Surface Flux ◽  
Energy System ◽  
The Arctic ◽  
Radiative Fluxes ◽  
The Difference ◽  
Atmospheric Variations ◽  
Modern Era ◽  
Global Mean

AbstractA diagnostic tool for determining surface and atmospheric contributions to interannual variations in top-of-atmosphere (TOA) reflected shortwave (SW) and net downward SW surface radiative fluxes is introduced. The method requires only upward and downward radiative fluxes at the TOA and surface as input and therefore can readily be applied to both satellite-derived and model-generated radiative fluxes. Observations from the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 4.0 product show that 81% of the monthly variability in global mean reflected SW TOA flux anomalies is associated with atmospheric variations (mainly clouds), 6% is from surface variations, and 13% is from atmosphere–surface covariability. Over the Arctic Ocean, most of the variability in both reflected SW TOA flux and net downward SW surface flux anomalies is explained by variations in sea ice and cloud fraction alone (r2 = 0.94). Compared to CERES, variability in two reanalyses—the ECMWF interim reanalysis (ERA-Interim) and NASA’s Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)—show large differences in the regional distribution of variance for both the atmospheric and surface contributions to anomalies in net downward SW surface flux. For MERRA-2 the atmospheric contribution is 17% too large compared to CERES while ERA-Interim underestimates the variance by 15%. The difference is mainly due to how cloud variations are represented in the reanalyses. The overall surface contribution in both ERA-Interim and MERRA-2 is smaller than CERES EBAF by 15% for ERA-Interim and 58% for MERRA-2, highlighting limitations of the reanalyses in representing surface albedo variations and their influence on SW radiative fluxes.

scholarly journals Uncertainty in Satellite-Derived Surface Irradiances and Challenges in Producing Surface Radiation Budget Climate Data Record

2020 ◽  
Vol 12 (12) ◽  
pp. 1950
Author(s):  
Seiji Kato ◽  
David A. Rutan ◽  
Fred G. Rose ◽  
Thomas E. Caldwell ◽  
Seung-Hee Ham ◽  
...  
Keyword(s):  
Sensible Heat Flux ◽  
Radiant Energy ◽  
Energy System ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Climate Data ◽  
Surface Irradiance ◽  
Uncertainty Estimates ◽  
The Difference ◽  
Global Mean

The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 4.1 data product provides global surface irradiances. Uncertainties in the global and regional monthly and annual mean all-sky net shortwave, longwave, and shortwave plus longwave (total) irradiances are estimated using ground-based observations. Error covariance is derived from surface irradiance sensitivity to surface, atmospheric, cloud and aerosol property perturbations. Uncertainties in global annual mean net shortwave, longwave, and total irradiances at the surface are, respectively, 5.7 Wm−2, 6.7 Wm−2, and 9.7 Wm−2. In addition, the uncertainty in surface downward irradiance monthly anomalies and their trends are estimated based on the difference derived from EBAF surface irradiances and observations. The uncertainty in the decadal trend suggests that when differences of decadal global mean downward shortwave and longwave irradiances are, respectively, greater than 0.45 Wm−2 and 0.52 Wm−2, the difference is larger than 1σ uncertainties. However, surface irradiance observation sites are located predominately over tropical oceans and the northern hemisphere mid-latitude. As a consequence, the effect of a discontinuity introduced by using multiple geostationary satellites in deriving cloud properties is likely to be excluded from these trend and decadal change uncertainty estimates. Nevertheless, the monthly anomaly timeseries of radiative cooling in the atmosphere (multiplied by −1) agrees reasonably well with the anomaly time series of diabatic heating derived from global mean precipitation and sensible heat flux with a correlation coefficient of 0.46.

Process-Based Decomposition of the Decadal Climate Difference between 2002–13 and 1984–95

2017 ◽  
Vol 30 (12) ◽  
pp. 4373-4393 ◽  
Author(s):  
Xiaoming Hu ◽  
Yana Li ◽  
Song Yang ◽  
Yi Deng ◽  
Ming Cai
Keyword(s):  
Radiative Transfer ◽  
Heat Storage ◽  
Decomposition Analysis ◽  
Arctic Region ◽  
The Arctic ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Calculations ◽  
Surface Warming ◽  
Decadal Climate

This study examines at the process level the climate difference between 2002–13 and 1984–95 in ERA-Interim. A linearized radiative transfer model is used to calculate the temperature change such that its thermal radiative cooling would balance the energy flux perturbation associated with the change of an individual process, without regard to what causes the change of the process in the first place. The global mean error of the offline radiative transfer model calculations is 0.09 K, which corresponds to the upper limit of the uncertainties from a single term in the decomposition analysis. The process-based decomposition indicates that the direct effect of the increase of CO2 (0.15 K) is the largest contributor to the global warming between the two periods (about 0.27 K). The second and third largest contributors are the cloud feedback (0.14 K) and the combined effect of the oceanic heat storage and evaporation terms (0.11 K), respectively. The largest warming associated with the oceanic heat storage term is found in the tropical Pacific and Indian Oceans, with relatively weaker warming over the tropical Atlantic Ocean. The increase in atmospheric moisture adds another 0.1 K to the global surface warming, but the enhancement in tropical convections acts to reduce the surface warming by 0.17 K. The ice-albedo and atmospheric dynamical feedbacks are the two leading factors responsible for the Arctic polar warming amplification (PWA). The increase of atmospheric water vapor over the Arctic region also contributes substantially to the Arctic PWA pattern.

scholarly journals Ocean Surface Albedo and Its Impact on Radiation Balance in Climate Models

2006 ◽  
Vol 19 (24) ◽  
pp. 6314-6333 ◽  
Author(s):  
J. Li ◽  
J. Scinocca ◽  
M. Lazare ◽  
N. McFarlane ◽  
K. von Salzen ◽  
...  
Keyword(s):  
Wind Speed ◽  
Radiative Transfer ◽  
Surface Albedo ◽  
Ocean Surface ◽  
Radiation Budget ◽  
Climate Modelling ◽  
Negative Bias ◽  
Clear Sky ◽  
The Difference ◽  
The Impact

Abstract An analysis of several ocean surface albedo (OSA) schemes is undertaken through offline comparisons and through application in the Canadian Centre for Climate Modelling and Analysis (CCCma) fourth-generation atmospheric general circulation model (AGCM4). In general, each scheme requires different input quantities to determine the OSA. Common to all schemes is a dependence on the solar zenith angle (SZA). A direct comparison of the SZA dependence of the schemes reveals significant differences in the predicted albedos. Other input quantities include wind speed and aerosol/cloud optical depth, which are also analyzed. An offline one-dimensional radiative transfer model is used to quantitatively study the impact of ocean surface albedo on the radiative transfer process. It is found that, as a function of SZA and wind speed, the difference in reflected solar flux at the top of the atmosphere is in general agreement between OSA schemes that depend on these quantities, with a difference &lt;10 W m−2. However, for simpler schemes that depend only on SZA the difference in this flux can approach 10–20 W m−2. The impact of the different OSA schemes is assessed through multiyear simulations of present-day climate in AGCM4. Five-year means of the reflected clear-sky flux at the top of the atmosphere reveal local differences of up to several watts per meters squared between any of the schemes. Globally, all schemes display a similar negative bias relative to the Earth Radiation Budget Experiment (ERBE) observations. This negative bias is largely reduced by comparison with the recently released Clouds and the Earth’s Radiant Energy System (CERES) data. It is shown that the local upward clear-sky flux at the surface is more sensitive to the OSA formulation than the clear-sky upward flux at the top of atmosphere. It is found that the global energy balance of the model at the top of the atmosphere and at the surface is surprisingly insensitive to which OSA scheme is employed.

scholarly journals Quantifying Emerging Local Anthropogenic Emissions in the Arctic Region: The ACCESS Aircraft Campaign Experiment

2015 ◽  
Vol 96 (3) ◽  
pp. 441-460 ◽  
Author(s):  
A. Roiger ◽  
J.-L. Thomas ◽  
H. Schlager ◽  
K. S. Law ◽  
J. Kim ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Anthropogenic Activities ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Arctic Climate ◽  
The Arctic ◽  
Local Pollution ◽  
Arctic Climate Change ◽  
The Impact ◽  
Pollution Plumes

Abstract Arctic sea ice has decreased dramatically in the past few decades and the Arctic is increasingly open to transit shipping and natural resource extraction. However, large knowledge gaps exist regarding composition and impacts of emissions associated with these activities. Arctic hydrocarbon extraction is currently under development owing to the large oil and gas reserves in the region. Transit shipping through the Arctic as an alternative to the traditional shipping routes is currently underway. These activities are expected to increase emissions of air pollutants and climate forcers (e.g., aerosols, ozone) in the Arctic troposphere significantly in the future. The authors present the first measurements of these activities off the coast of Norway taken in summer 2012 as part of the European Arctic Climate Change, Economy, and Society (ACCESS) project. The objectives include quantifying the impact that anthropogenic activities will have on regional air pollution and understanding the connections to Arctic climate. Trace gas and aerosol concentrations in pollution plumes were measured, including emissions from different ship types and several offshore extraction facilities. Emissions originating from industrial activities (smelting) on the Kola Peninsula were also sampled. In addition, pollution plumes originating from Siberian biomass burning were probed in order to put the emerging local pollution within a broader context. In the near future these measurements will be combined with model simulations to quantify the influence of local anthropogenic activities on Arctic composition. Here the authors present the scientific objectives of the ACCESS aircraft experiment and the the meteorological conditions during the campaign, and they highlight first scientific results from the experiment.

scholarly journals The ability of a GCM-forced hydrological model to reproduce global discharge variability

2010 ◽  
Vol 7 (1) ◽  
pp. 687-724 ◽  
Author(s):  
F. C. Sperna Weiland ◽  
L. P. H. van Beek ◽  
J. C. J. Kwadijk ◽  
M. F. P. Bierkens
Keyword(s):  
General Circulation ◽  
Hydrological Model ◽  
General Circulation Models ◽  
The Arctic ◽  
Climate Data ◽  
Mean Values ◽  
Ensemble Mean ◽  
Runoff Variability ◽  
Abstract Data ◽  
Impacts Of Climate Change

Abstract. Data from General Circulation Models (GCMs) are often used in studies investigating hydrological impacts of climate change. However GCM data are known to have large biases, especially for precipitation. In this study the usefulness of GCM data for hydrological studies was tested by applying bias-corrected daily climate data of the 20CM3 control experiment from an ensemble of twelve GCMs as input to the global hydrological model PCR-GLOBWB. Results are compared with discharges calculated from a model run based on a reference meteorological dataset constructed from the CRU TS2.1 data and ERA-40 reanalysis time-series. Bias-correction was limited to monthly mean values as our focus was on the reproduction of runoff variability. The bias-corrected GCM based runs resemble the reference run reasonably well, especially for rivers with strong seasonal patterns. However, GCM derived discharge quantities are overall too low. Furthermore, from the arctic regimes it can be seen that a few deviating GCMs can bias the ensemble mean. Moreover, the GCMs do not well represent intra- and inter-year variability as exemplified by a limited persistence. This makes them less suitable for the projection of future runoff extremes.

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