A 10 year climatology of Arctic cloud fraction and radiative forcing at Barrow, Alaska

AbstractSatellite-based estimates of radiative forcing by aerosol–cloud interactions (RFaci) are consistently smaller than those from global models, hampering accurate projections of future climate change. Here we show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements, which tend to artificially discard the clouds with high cloud fraction. Those missed clouds exert a stronger cooling effect, and are more sensitive to aerosol perturbations. By accounting for the sampling biases, the magnitude of RFaci (from −0.38 to −0.59 W m−2) increases by 55 % globally (133 % over land and 33 % over ocean). Notably, the RFaci further increases to −1.09 W m−2 when switching total aerosol optical depth (AOD) to fine-mode AOD that is a better proxy for CCN than AOD. In contrast to previous weak satellite-based RFaci, the improved one substantially increases (especially over land), resolving a major difference with models.

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Relationship between cloud radiative forcing, cloud fraction and cloud albedo, and new surface-based approach for determining cloud albedo

Atmospheric Chemistry and Physics ◽

10.5194/acp-11-7155-2011 ◽

2011 ◽

Vol 11 (14) ◽

pp. 7155-7170 ◽

Cited By ~ 26

Author(s):

Y. Liu ◽

W. Wu ◽

M. P. Jensen ◽

T. Toto

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Cloud Fraction ◽

Shortwave Radiation ◽

Cloud Radiative Forcing ◽

Analytical Expression ◽

Cloud Albedo ◽

Annual Variations ◽

Hourly Data ◽

Radiation Parameterizations

Abstract. This paper focuses on three interconnected topics: (1) quantitative relationship between surface shortwave cloud radiative forcing, cloud fraction, and cloud albedo; (2) surface-based approach for measuring cloud albedo; (3) multiscale (diurnal, annual and inter-annual) variations and covariations of surface shortwave cloud radiative forcing, cloud fraction, and cloud albedo. An analytical expression is first derived to quantify the relationship between cloud radiative forcing, cloud fraction, and cloud albedo. The analytical expression is then used to deduce a new approach for inferring cloud albedo from concurrent surface-based measurements of downwelling surface shortwave radiation and cloud fraction. High-resolution decade-long data on cloud albedos are obtained by use of this surface-based approach over the US Department of Energy's Atmospheric Radiaton Measurement (ARM) Program at the Great Southern Plains (SGP) site. The surface-based cloud albedos are further compared against those derived from the coincident GOES satellite measurements. The three long-term (1997–2009) sets of hourly data on shortwave cloud radiative forcing, cloud fraction and cloud albedo collected over the SGP site are analyzed to explore the multiscale (diurnal, annual and inter-annual) variations and covariations. The analytical formulation is useful for diagnosing deficiencies of cloud-radiation parameterizations in climate models.

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Arctic Cloud Fraction and Radiative Fluxes in Atmospheric Reanalyses

Journal of Climate ◽

10.1175/2008jcli2213.1 ◽

2009 ◽

Vol 22 (9) ◽

pp. 2316-2334 ◽

Cited By ~ 95

Author(s):

John E. Walsh ◽

William L. Chapman ◽

Diane H. Portis

Keyword(s):

Surface Energy ◽

Energy Budget ◽

Radiative Forcing ◽

Cloud Fraction ◽

Surface Energy Budget ◽

Japan Meteorological Agency ◽

Central Research ◽

Radiative Fluxes ◽

Arctic Clouds ◽

Cloud Radiative Forcing

Abstract Arctic radiative fluxes, cloud fraction, and cloud radiative forcing are evaluated from four currently available reanalysis models using data from the North Slope of Alaska (NSA) Barrow site of the Atmospheric Radiation Measurement Program (ARM). A primary objective of the ARM–NSA program is to provide a high-resolution dataset of direct measurements of Arctic clouds and radiation so that global climate models can better parameterize high-latitude cloud radiative processes. The four reanalysis models used in this study are the 1) NCEP–NCAR global reanalysis, 2) 40-yr ECMWF Re-Analysis (ERA-40), 3) NCEP–NCAR North American Regional Reanalysis (NARR), and 4) Japan Meteorological Agency and Central Research Institute of Electric Power Industry 25-yr Reanalysis (JRA25). The reanalysis models simulate the radiative fluxes well if/when the cloud fraction is simulated correctly. However, the systematic errors of climatological reanalysis cloud fractions are substantial. Cloud fraction and radiation biases show considerable scatter, both in the annual mean and over a seasonal cycle, when compared to those observed at the ARM–NSA. Large seasonal cloud fraction biases have significant impacts on the surface energy budget. Detailed comparisons of ARM and reanalysis products reveal that the persistent low-level cloud fraction in summer is particularly difficult for the reanalysis models to capture creating biases in the shortwave radiation flux that can exceed 160 W m−2. ERA-40 is the best performer in both shortwave and longwave flux seasonal representations at Barrow, largely because its simulation of the cloud coverage is the most realistic of the four reanalyses. Only two reanalyses (ERA-40 and NARR) capture the observed transition from positive to negative surface net cloud radiative forcing during a 2–3-month period in summer, while the remaining reanalyses indicate a net warming impact of Arctic clouds on the surface energy budget throughout the entire year. The authors present a variable cloud radiative forcing metric to diagnose the erroneous impact of reanalysis cloud fraction on the surface energy balance. The misrepresentations of cloud radiative forcing in some of the reanalyses are attributable to errors in both simulated cloud amounts and the models’ radiative response to partly cloudy conditions.

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Quantifying the Dependence of Satellite Cloud Retrievals on Instrument Uncertainty

Journal of Climate ◽

10.1175/jcli-d-16-0429.1 ◽

2017 ◽

Vol 30 (17) ◽

pp. 6959-6976 ◽

Cited By ~ 6

Author(s):

Yolanda L. Shea ◽

Bruce A. Wielicki ◽

Sunny Sun-Mack ◽

Patrick Minnis

Keyword(s):

Climate Change ◽

Optical Thickness ◽

Indirect Effect ◽

Effective Temperature ◽

Radiative Forcing ◽

Cloud Fraction ◽

Effective Radius ◽

Aerosol Indirect Effect ◽

Sources Of Uncertainty ◽

Water Cloud

Cloud response to Earth’s changing climate is one of the largest sources of uncertainty among global climate model (GCM) projections. Two of the largest sources of uncertainty are the spread in equilibrium climate sensitivity (ECS) and uncertainty in radiative forcing due to uncertainty in the aerosol indirect effect. Satellite instruments with sufficient accuracy and on-orbit stability to detect climate change–scale trends in cloud properties will improve confidence in the understanding of the relationship between observed climate change and cloud property trends, thus providing information to better constrain ECS and radiative forcing. This study applies a climate change uncertainty framework to quantify the impact of measurement uncertainty on trend detection times for cloud fraction, effective temperature, optical thickness, and water cloud effective radius. Although GCMs generally agree that the total cloud feedback is positive, disagreement remains on its magnitude. With the climate uncertainty framework, it is demonstrated how stringent measurement uncertainty requirements for reflected solar and infrared satellite measurements enable improved constraint of SW and LW cloud feedbacks and the ECS by significantly reducing trend uncertainties for cloud fraction, optical thickness, and effective temperature. The authors also demonstrate improved constraint on uncertainty in the aerosol indirect effect by reducing water cloud effective radius trend uncertainty.

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Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels

Journal of Climate ◽

10.1175/jcli-d-11-00248.1 ◽

2012 ◽

Vol 25 (11) ◽

pp. 3715-3735 ◽

Cited By ~ 120

Author(s):

Mark D. Zelinka ◽

Stephen A. Klein ◽

Dennis L. Hartmann

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Grid Point ◽

Cloud Fraction ◽

Cloud Feedback ◽

Global Climate Models ◽

Radiative Transfer Model ◽

Transfer Model ◽

Cloud Feedbacks ◽

Low Clouds

This study proposes a novel technique for computing cloud feedbacks using histograms of cloud fraction as a joint function of cloud-top pressure (CTP) and optical depth (τ). These histograms were generated by the International Satellite Cloud Climatology Project (ISCCP) simulator that was incorporated into doubled-CO2 simulations from 11 global climate models in the Cloud Feedback Model Intercomparison Project. The authors use a radiative transfer model to compute top of atmosphere flux sensitivities to cloud fraction perturbations in each bin of the histogram for each month and latitude. Multiplying these cloud radiative kernels with histograms of modeled cloud fraction changes at each grid point per unit of global warming produces an estimate of cloud feedback. Spatial structures and globally integrated cloud feedbacks computed in this manner agree remarkably well with the adjusted change in cloud radiative forcing. The global and annual mean model-simulated cloud feedback is dominated by contributions from medium thickness (3.6 < τ ≤ 23) cloud changes, but thick (τ > 23) cloud changes cause the rapid transition of cloud feedback values from positive in midlatitudes to negative poleward of 50°S and 70°N. High (CTP ≤ 440 hPa) cloud changes are the dominant contributor to longwave (LW) cloud feedback, but because their LW and shortwave (SW) impacts are in opposition, they contribute less to the net cloud feedback than do the positive contributions from low (CTP > 680 hPa) cloud changes. Midlevel (440 < CTP ≤ 680 hPa) cloud changes cause positive SW cloud feedbacks that are 80% as large as those due to low clouds. Finally, high cloud changes induce wider ranges of LW and SW cloud feedbacks across models than do low clouds.

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A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility. Part II: Cloud Fraction and Surface Radiative Forcing

Journal of Climate ◽

10.1175/jcli3710.1 ◽

2006 ◽

Vol 19 (9) ◽

pp. 1765-1783 ◽

Cited By ~ 81

Author(s):

Xiquan Dong ◽

Baike Xi ◽

Patrick Minnis

Keyword(s):

Water Vapor ◽

Radiative Forcing ◽

Cloud Cover ◽

Surface Albedo ◽

Cloud Fraction ◽

Total Cloud Cover ◽

Cloud Radiative Forcing ◽

Low Clouds ◽

High Clouds ◽

Central Facility

Abstract Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (SCF) are analyzed to determine the monthly and hourly variations of cloud fraction and radiative forcing between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layered low (0–3 km), middle (3–6 km), and high clouds (>6 km) using ARM SCF ground-based paired lidar–radar measurements. Shortwave (SW) and longwave (LW) fluxes are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties of ∼10 W m−2. The annual averages of total and single-layered low-, middle-, and high-cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Both total- and low-cloud amounts peak during January and February and reach a minimum during July and August; high clouds occur more frequently than other types of clouds with a peak in summer. The average annual downwelling surface SW fluxes for total and low clouds (151 and 138 W m−2, respectively) are less than those under middle and high clouds (188 and 201 W m−2, respectively), but the downwelling LW fluxes (349 and 356 W m−2) underneath total and low clouds are greater than those from middle and high clouds (337 and 333 W m−2). Low clouds produce the largest LW warming (55 W m−2) and SW cooling (−91 W m−2) effects with maximum and minimum absolute values in spring and summer, respectively. High clouds have the smallest LW warming (17 W m−2) and SW cooling (−37 W m−2) effects at the surface. All-sky SW cloud radiative forcing (CRF) decreases and LW CRF increases with increasing cloud fraction with mean slopes of −0.984 and 0.616 W m−2 %−1, respectively. Over the entire diurnal cycle, clouds deplete the amount of surface insolation more than they add to the downwelling LW flux. The calculated CRFs do not appear to be significantly affected by uncertainties in data sampling and clear-sky screening. Traditionally, cloud radiative forcing includes not only the radiative impact of the hydrometeors, but also the changes in the environment. Taken together over the ARM SCF, changes in humidity and surface albedo between clear and cloudy conditions offset ∼20% of the NET radiative forcing caused by the cloud hydrometeors alone. Variations in water vapor, on average, account for 10% and 83% of the SW and LW CRFs, respectively, in total cloud cover conditions. The error analysis further reveals that the cloud hydrometeors dominate the SW CRF, while water vapor changes are most important for LW flux changes in cloudy skies. Similar studies over other locales are encouraged where water and surface albedo changes from clear to cloudy conditions may be much different than observed over the ARM SCF.

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Statistical Analyses of Satellite Cloud Object Data from CERES. Part V: Relationships between Physical Properties of Marine Boundary Layer Clouds

Journal of Climate ◽

10.1175/2008jcli2307.1 ◽

2008 ◽

Vol 21 (24) ◽

pp. 6668-6688 ◽

Cited By ~ 19

Author(s):

Zachary A. Eitzen ◽

Kuan-Man Xu ◽

Takmeng Wong

Keyword(s):

Boundary Layer ◽

Cluster Analysis ◽

Physical Properties ◽

Radiative Forcing ◽

Marine Boundary Layer ◽

Radiant Energy ◽

Cloud Fraction ◽

Cloud Radiative Forcing ◽

Boundary Layer Clouds ◽

Shallow Cumulus

Abstract Relationships between physical properties are studied for three types of marine boundary layer cloud objects identified with the Clouds and the Earth’s Radiant Energy System (CERES) footprint data from the Tropical Rainfall Measuring Mission satellite between 30°S and 30°N. Each cloud object is a contiguous region of CERES footprints that have cloud-top heights below 3 km, and cloud fractions of 99%–100% (overcast type), 40%–99% (stratocumulus type), or 10%–40% (shallow cumulus type). These cloud fractions represent the fraction of ∼2 km × 2 km Visible/Infrared Scanner pixels that are cloudy within each ∼10 km × 10 km footprint. The cloud objects have effective diameters that are greater than 300 km for the overcast and stratocumulus types, and greater than 150 km for the shallow cumulus type. The Spearman rank correlation coefficient is calculated between many microphysical/optical [effective radius (re), cloud optical depth (τ), albedo, liquid water path, and shortwave cloud radiative forcing (SW CRF)] and macrophysical [outgoing longwave radiation (OLR), cloud fraction, cloud-top temperature, longwave cloud radiative forcing (LW CRF), and sea surface temperature (SST)] properties for each of the three cloud object types. When both physical properties are of the same category (microphysical/optical or macrophysical), the magnitude of the correlation tends to be higher than when they are from different categories. The magnitudes of the correlations also change with cloud object type, with the correlations for overcast and stratocumulus cloud objects tending to be higher than those for shallow cumulus cloud objects. Three pairs of physical properties are studied in detail, using a k-means cluster analysis: re and τ, OLR and SST, and LW CRF and SW CRF. The cluster analysis of re and τ reveals that for each of the cloud types, there is a cluster of cloud objects with negative slopes, a cluster with slopes near zero, and two clusters with positive slopes. The joint OLR and SST probability plots show that the OLR tends to decrease with SST in regions with boundary layer clouds for SSTs above approximately 298 K. When the cloud objects are split into “dry” and “moist” clusters based on the amount of precipitable water above 700 hPa, the associated OLRs increase with SST throughout the SST range for the dry clusters, but the OLRs are roughly constant with SST for the moist cluster. An analysis of the joint PDFs of LW CRF and SW CRF reveals that while the magnitudes of both LW and SW CRFs generally increase with cloud fraction, there is a cluster of overcast cloud objects that has low values of LW and SW CRF. These objects are generally located near the Sahara Desert, and may be contaminated with dust. Many of these overcast objects also appear in the re and τ cluster with negative slopes.

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Model intercomparison of indirect aerosol effects

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-6-1579-2006 ◽

2006 ◽

Vol 6 (1) ◽

pp. 1579-1617 ◽

Cited By ~ 6

Author(s):

J. E. Penner ◽

J. Quaas ◽

T. Storelvmo ◽

T. Takemura ◽

O. Boucher ◽

...

Keyword(s):

Liquid Water ◽

Indirect Effect ◽

Radiative Forcing ◽

Cloud Fraction ◽

Liquid Water Path ◽

Aerosol Indirect Effect ◽

Water Path ◽

Series Of Experiments ◽

Aerosol Effects ◽

Indirect Forcing

Abstract. Modeled differences in predicted effects are increasingly used to help quantify the uncertainty of these effects. Here, we examine modeled differences in the aerosol indirect effect in a series of experiments that help to quantify how and why model-predicted aerosol indirect forcing varies between models. The experiments start with an experiment in which aerosol concentrations, the parameterization of droplet concentrations and the autoconversion scheme are all specified and end with an experiment that examines the predicted aerosol indirect forcing when only aerosol sources are specified. Although there are large differences in the predicted liquid water path among the models, the predicted aerosol indirect effect for the first experiment is rather similar. Changes to the autoconversion scheme can lead to large changes in the liquid water path of the models and to the response of the liquid water path to changes in aerosols. Nevertheless, these changes do not necessarily lead to large changes in the radiative forcing. The parameterization of cloud fraction within models is not sensitive to the aerosol concentration, and, therefore, the response of the modeled cloud fraction within the present models appears to be smaller than that which would be associated with model ''noise''. The prediction of aerosol concentrations, given a fixed set of sources, leads to some of the largest differences in the predicted aerosol indirect radiative forcing among the models. Thus, this aspect of modeling requires significant improvement in order to improve the prediction of aerosol indirect effects.

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Model intercomparison of indirect aerosol effects

Atmospheric Chemistry and Physics ◽

10.5194/acp-6-3391-2006 ◽

2006 ◽

Vol 6 (11) ◽

pp. 3391-3405 ◽

Cited By ~ 174

Author(s):

J. E. Penner ◽

J. Quaas ◽

T. Storelvmo ◽

T. Takemura ◽

O. Boucher ◽

...

Keyword(s):

Liquid Water ◽

Indirect Effect ◽

Radiative Forcing ◽

Liquid Water Content ◽

Cloud Fraction ◽

Shortwave Radiation ◽

Liquid Water Path ◽

Water Path ◽

Cloud Forcing ◽

Indirect Forcing

Abstract. Modeled differences in predicted effects are increasingly used to help quantify the uncertainty of these effects. Here, we examine modeled differences in the aerosol indirect effect in a series of experiments that help to quantify how and why model-predicted aerosol indirect forcing varies between models. The experiments start with an experiment in which aerosol concentrations, the parameterization of droplet concentrations and the autoconversion scheme are all specified and end with an experiment that examines the predicted aerosol indirect forcing when only aerosol sources are specified. Although there are large differences in the predicted liquid water path among the models, the predicted aerosol first indirect effect for the first experiment is rather similar, about −0.6 Wm−2 to −0.7 Wm−2. Changes to the autoconversion scheme can lead to large changes in the liquid water path of the models and to the response of the liquid water path to changes in aerosols. Adding an autoconversion scheme that depends on the droplet concentration caused a larger (negative) change in net outgoing shortwave radiation compared to the 1st indirect effect, and the increase varied from only 22% to more than a factor of three. The change in net shortwave forcing in the models due to varying the autoconversion scheme depends on the liquid water content of the clouds as well as their predicted droplet concentrations, and both increases and decreases in the net shortwave forcing can occur when autoconversion schemes are changed. The parameterization of cloud fraction within models is not sensitive to the aerosol concentration, and, therefore, the response of the modeled cloud fraction within the present models appears to be smaller than that which would be associated with model "noise". The prediction of aerosol concentrations, given a fixed set of sources, leads to some of the largest differences in the predicted aerosol indirect radiative forcing among the models, with values of cloud forcing ranging from −0.3 Wm−2 to −1.4 Wm−2. Thus, this aspect of modeling requires significant improvement in order to improve the prediction of aerosol indirect effects.

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Suppression of Cold Weather Events over High-Latitude Continents in Warm Climates

Journal of Climate ◽

10.1175/jcli-d-18-0129.1 ◽

2018 ◽

Vol 31 (23) ◽

pp. 9625-9640 ◽

Cited By ~ 1

Author(s):

Zeyuan Hu ◽

Timothy W. Cronin ◽

Eli Tziperman

Keyword(s):

High Latitude ◽

Radiative Forcing ◽

Cloud Fraction ◽

Sea Surface ◽

Lapse Rate ◽

Climate Change Scenarios ◽

Cloud Radiative Forcing ◽

Low Cloud ◽

Extreme Cold ◽

Continental Interior

Recent studies, using Lagrangian single-column atmospheric models, have proposed that in warmer climates more low clouds would form as maritime air masses advect into Northern Hemisphere high-latitude continental interiors during winter (DJF). This increase in low cloud amount and optical thickness could reduce surface radiative cooling and suppress Arctic air formation events, partly explaining both the warm winter high-latitude continental interior climate and frost-intolerant species found there during the Eocene and the positive lapse-rate feedback in future Arctic climate change scenarios. Here the authors examine the robustness of this low-cloud mechanism in a three-dimensional atmospheric model that includes large-scale dynamics. Different warming scenarios are simulated under prescribed CO2 and sea surface temperature, and the sensitivity of winter temperatures and clouds over high-latitude continental interior to mid- and high-latitude sea surface temperatures is examined. Model results show that winter 2-m temperatures on extreme cold days increase about 50% faster than the winter mean temperatures and the prescribed SST. Low cloud fraction and surface longwave cloud radiative forcing also increase in both the winter mean state and on extreme cold days, consistent with previous Lagrangian air-mass studies, but with cloud fraction increasing for different reasons than proposed by previous work. At high latitudes, the cloud longwave warming effect dominates the shortwave cooling effect, and the net cloud radiative forcing at the surface tends to warm high-latitude land but cool midlatitude land. This could contribute to the reduced meridional temperature gradient in warmer climates and help explain the greater warming of winter cold extremes relative to winter mean temperatures.

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