Using the Radiative Kernel Technique to Calculate Climate Feedbacks in NCAR’s Community Atmospheric Model

2008 ◽  
Vol 21 (10) ◽  
pp. 2269-2282 ◽  
Author(s):  
Karen M. Shell ◽  
Jeffrey T. Kiehl ◽  
Christine A. Shields
Keyword(s):  
Water Vapor ◽  
Radiative Forcing ◽  
Surface Albedo ◽  
Atmospheric Model ◽  
Cloud Feedback ◽  
Climate Feedback ◽  
Time Step ◽  
Global Average ◽  
Clear Sky ◽  
Vapor Temperature

Abstract Climate models differ in their responses to imposed forcings, such as increased greenhouse gas concentrations, due to different climate feedback strengths. Feedbacks in NCAR’s Community Atmospheric Model (CAM) are separated into two components: the change in climate components in response to an imposed forcing and the “radiative kernel,” the effect that climate changes have on the top-of-the-atmosphere (TOA) radiative budget. This technique’s usefulness depends on the linearity of the feedback processes. For the case of CO2 doubling, the sum of the effects of water vapor, temperature, and surface albedo changes on the TOA clear-sky flux is similar to the clear-sky flux changes directly calculated by CAM. When monthly averages are used rather than values from every time step, the global-average TOA shortwave change is underestimated by a quarter, partially as a result of intramonth correlations of surface albedo with the radiative kernel. The TOA longwave flux changes do not depend on the averaging period. The longwave zonal averages are within 10% of the model-calculated values, while the global average differs by only 2%. Cloud radiative forcing (ΔCRF) is often used as a diagnostic of cloud feedback strength. The net effect of the water vapor, temperature, and surface albedo changes on ΔCRF is −1.6 W m−2, based on the kernel technique, while the total ΔCRF from CAM is −1.3 W m−2, indicating these components contribute significantly to ΔCRF and make it more negative. Assuming linearity of the ΔCRF contributions, these results indicate that the net cloud feedback in CAM is positive.

Mechanisms of Low Cloud–Climate Feedback in Idealized Single-Column Simulations with the Community Atmospheric Model, Version 3 (CAM3)

2008 ◽  
Vol 21 (18) ◽  
pp. 4859-4878 ◽  
Author(s):  
Minghua Zhang ◽  
Christopher Bretherton
Keyword(s):  
Dynamic Effect ◽  
Atmospheric Model ◽  
Cloud Feedback ◽  
Climate Feedback ◽  
Stratus Clouds ◽  
Model Version ◽  
Boundary Layer Turbulence ◽  
Thermodynamic Effect ◽  
Single Column ◽  
Low Cloud

Abstract This study investigates the physical mechanism of low cloud feedback in the Community Atmospheric Model, version 3 (CAM3) through idealized single-column model (SCM) experiments over the subtropical eastern oceans. Negative cloud feedback is simulated from stratus and stratocumulus that is consistent with previous diagnostics of cloud feedbacks in CAM3 and its predecessor versions. The feedback occurs through the interaction of a suite of parameterized processes rather than from any single process. It is caused by the larger amount of in-cloud liquid water in stratus clouds from convective sources, and longer lifetimes of these clouds in a warmer climate through their interaction with boundary layer turbulence. Thermodynamic effects are found to dominate the negative cloud feedback in the model. The dynamic effect of weaker subsidence in a warmer climate also contributes to the negative cloud feedback, but with about one-quarter of the magnitude of the thermodynamic effect, owing to increased low-level convection in a warmer climate.

scholarly journals Surface and top-of-atmosphere radiative feedback kernels for CESM-CAM5

2018 ◽  
Vol 10 (1) ◽  
pp. 317-324 ◽  
Author(s):  
Angeline G. Pendergrass ◽  
Andrew Conley ◽  
Francis M. Vitt
Keyword(s):  
Water Vapor ◽  
Greenhouse Gases ◽  
Surface Temperature ◽  
Radiative Forcing ◽  
Surface Albedo ◽  
Large Ensemble ◽  
Radiative Fluxes ◽  
Radiative Feedback ◽  
Ensemble Simulations ◽  
Temperature Water

Abstract. Radiative kernels at the top of the atmosphere are useful for decomposing changes in atmospheric radiative fluxes due to feedbacks from atmosphere and surface temperature, water vapor, and surface albedo. Here we describe and validate radiative kernels calculated with the large-ensemble version of CAM5, CESM1.1.2, at the top of the atmosphere and the surface. Estimates of the radiative forcing from greenhouse gases and aerosols in RCP8.5 in the CESM large-ensemble simulations are also diagnosed. As an application, feedbacks are calculated for the CESM large ensemble. The kernels are freely available at https://doi.org/10.5065/D6F47MT6, and accompanying software can be downloaded from https://github.com/apendergrass/cam5-kernels.

Robustness of Dynamical Feedbacks from Radiative Forcing: 2% Solar versus 2 × CO2 Experiments in an Idealized GCM

2012 ◽  
Vol 69 (7) ◽  
pp. 2256-2271 ◽  
Author(s):  
Ming Cai ◽  
Ka-Kit Tung
Keyword(s):  
Water Vapor ◽  
Radiative Forcing ◽  
Lower Troposphere ◽  
Radiative Heating ◽  
Climate Feedback ◽  
Response Analysis ◽  
High Latitudes ◽  
Water Vapor Feedback ◽  
The Tropics ◽  
Heating Profile

Abstract Despite the differences in the spatial patterns of the external forcing associated with a doubling CO2 and with a 2% solar variability, the final responses in the troposphere and at the surface in a three-dimensional general circulation model appear remarkably similar. Various feedback processes are diagnosed and compared using the climate feedback–response analysis method (CFRAM) to understand the mechanisms responsible. At the surface, solar radiative forcing is stronger in the tropics than at the high latitudes, whereas greenhouse radiative forcing is stronger at high latitudes compared with the tropics. Also solar forcing is positive everywhere in the troposphere and greenhouse radiative forcing is positive mainly in the lower troposphere. The water vapor feedback strengthens the upward-decreasing radiative heating profile in the tropics and the poleward-decreasing radiative heating profile in the lower troposphere. The “evaporative” and convective feedbacks play an important role only in the tropics where they act to reduce the warming at the surface and lower troposphere in favor of upper-troposphere warming. Both water vapor feedback and enhancement of convection in the tropics further strengthen the initial poleward-decreasing profile of energy flux convergence perturbations throughout the troposphere. As a result, the large-scale dynamical poleward energy transport, which acts on the negative temperature gradient, is enhanced in both cases, contributing to a polar amplification of warming aloft and a warming reduction in the tropics. The dynamical amplification of polar atmospheric warming also contributes additional warming to the surface below via downward thermal radiation.

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

2006 ◽  
Vol 19 (9) ◽  
pp. 1765-1783 ◽  
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.

scholarly journals Spectral and Broadband Longwave Downwelling Radiative Fluxes, Cloud Radiative Forcing, and Fractional Cloud Cover over the South Pole

2005 ◽  
Vol 18 (20) ◽  
pp. 4235-4252 ◽  
Author(s):  
Michael S. Town ◽  
Von P. Walden ◽  
Stephen G. Warren
Keyword(s):  
Water Vapor ◽  
Radiative Forcing ◽  
Cloud Cover ◽  
South Pole ◽  
The South ◽  
Near Surface ◽  
Cloud Radiative Forcing ◽  
Clear Sky ◽  
Fractional Cloud ◽  
Visual Observations

Abstract Annual cycles of downwelling broadband infrared radiative flux and spectral downwelling infrared flux were determined using data collected at the South Pole during 2001. Clear-sky conditions are identified by comparing radiance ratios of observed and simulated spectra. Clear-sky fluxes are in the range of 110–125 W m−2 during summer (December–January) and 60–80 W m−2 during winter (April–September). The variability is due to day-to-day variations in temperature, strength of the surface-based temperature inversion, atmospheric humidity, and the presence of “diamond dust” (near-surface ice crystals). The persistent presence of diamond dust under clear skies during the winter is evident in monthly averages of clear-sky radiance. About two-thirds of the clear-sky flux is due to water vapor, and one-third is due to CO2, both in summer and winter. The seasonal constancy of this approximately 2:1 ratio is investigated through radiative transfer modeling. Precipitable water vapor (PWV) amounts were calculated to investigate the H2O/CO2 flux ratio. Monthly mean PWV during 2001 varied from 1.6 mm during summer to 0.4 mm during winter. Earlier published estimates of PWV at the South Pole are similar for winter, but are 50% lower for summer. Possible reasons for low earlier estimates of summertime PWV are that they are based either on inaccurate hygristor technology or on an invalid assumption that the humidity was limited by saturation with respect to ice. The average fractional cloud cover derived from the spectral infrared data is consistent with visual observations in summer. However, the wintertime average is 0.3–0.5 greater than that obtained from visual observations. The annual mean of longwave downwelling cloud radiative forcing (LDCRF) for 2001 is about 23 W m−2 with no apparent seasonal cycle. This is about half that of the global mean LDCRF; the low value is attributed to the small optical depths and low temperatures of Antarctic clouds.

scholarly journals Process-based analysis of relative contributions to the multi-model warming projection over East Asia

2021 ◽  
Author(s):  
Hanjie Fan ◽  
Xiaoming Hu ◽  
Song Yang ◽  
Yong-Sang Choi ◽  
Yoon-Kyoung Lee
Keyword(s):  
Water Vapor ◽  
East Asia ◽  
Model Uncertainty ◽  
Surface Albedo ◽  
Southern China ◽  
Climate Feedback ◽  
Response Analysis ◽  
Climate Projections ◽  
The Tibetan Plateau ◽  
Radiative Processes

AbstractClimate models predict that East Asia (EA) will be substantially warmer than the present despite large inter-model uncertainty. This study investigated the major sources of the climate projections and the inter-model uncertainty. Particularly, we decomposed the differences in surface temperatures between the historical and RCP8.5 runs from 26 CMIP5 into partial surface temperature changes due to individual radiative and non-radiative processes through the climate feedback-response analysis method. Results show that anthropogenic greenhouse forcing and subsequent water vapor feedback processes are primarily responsible for the surface warming over EA. Relatively more rapid warming over the snow/ice-covered area and southern China is due to feedback processes associated with surface albedo and cloud, respectively. The regional warming is, however, compensated by the surface non-radiative (sensible and latent heat) cooling. The inter-model projection uncertainty is substantially large over high latitudes and the Tibetan Plateau mainly due to surface albedo feedback. Again, this large uncertainty is partly suppressed by surface non-radiative cooling. Water vapor and cloud feedbacks are the secondary important sources of the projection uncertainty. Moreover, the contributions of greenhouse forcing and atmospheric dynamics to the projection uncertainty are found to be minor.

scholarly journals A Comparison of Climate Feedback Strength between CO2 Doubling and LGM Experiments

2009 ◽  
Vol 22 (12) ◽  
pp. 3374-3395 ◽  
Author(s):  
Masakazu Yoshimori ◽  
Tokuta Yokohata ◽  
Ayako Abe-Ouchi
Keyword(s):  
Water Vapor ◽  
Climate Sensitivity ◽  
Radiative Forcing ◽  
General Circulation ◽  
Lapse Rate ◽  
Climate Feedback ◽  
Water Vapor Feedback ◽  
Feedback Strength ◽  
Significant Difference ◽  
The Difference

Abstract Studies of the climate in the past potentially provide a constraint on the uncertainty of climate sensitivity, but previous studies warn against a simple scaling to the future. Climate sensitivity is determined by a number of feedback processes, and they may vary according to climate states and forcings. In this study, the similarities and differences in feedbacks for CO2 doubling, a Last Glacial Maximum (LGM), and LGM greenhouse gas (GHG) forcing experiments are investigated using an atmospheric general circulation model coupled to a slab ocean model. After computing the radiative forcing, the individual feedback strengths of water vapor, lapse-rate, albedo, and cloud feedbacks are evaluated explicitly. For this particular model, the difference in the climate sensitivity between the experiments is attributed to the shortwave cloud feedback, in which there is a tendency for it to become weaker or even negative in cooling experiments. No significant difference is found in the water vapor feedback between warming and cooling experiments by GHGs. The weaker positive water vapor feedback in the LGM experiment resulting from a relatively weaker tropical forcing is compensated for by the stronger positive lapse-rate feedback resulting from a relatively stronger extratropical forcing. A hypothesis is proposed that explains the asymmetric cloud response between the warming and cooling experiments associated with a displacement of the region of mixed-phase clouds. The difference in the total feedback strength between the experiments is, however, relatively small compared to the current intermodel spread, and does not necessarily preclude the use of LGM climate as a future constraint.

scholarly journals Impact of different definitions of clear-sky flux on the determination of longwave cloud radiative forcing: NICAM simulation results

2010 ◽  
Vol 10 (9) ◽  
pp. 22093-22107
Author(s):  
B. J. Sohn ◽  
T. Nakajima ◽  
M. Satoh ◽  
H.-S. Jang
Keyword(s):  
Radiative Forcing ◽  
Atmospheric Model ◽  
Satellite Measurements ◽  
Cloud Radiative Forcing ◽  
Cloud Forcing ◽  
Clear Sky ◽  
Atmospheric State ◽  
The Impact ◽  
Mean State

Abstract. Using one month of the cloud-resolving Nonhydrostatic Icosahedral Atmospheric Model (NICAM) simulations, we examined the impact of different definitions of clear-sky flux on the determination of longwave cloud radiative forcing (CRF). Because the satellite-like cloud-free composite preferentially samples drier conditions relative to the all-sky mean state, the conventional clear-sky flux calculation using the all-sky mean state in the model may represent a more humid atmospheric state in comparison to the cloud-free state. The drier bias is evident for the cloud-free composite in the NICAM simulations, causing an overestimation of the longwave CRF by about 10% compared to the NICAM simulated longwave CRF. Overall, water vapor contributions of up to 10% of the total longwave CRF should be added to make the NICAM-generated cloud forcing comparable to the satellite measurements.

scholarly journals Impact of different definitions of clear-sky flux on the determination of longwave cloud radiative forcing: NICAM simulation results

2010 ◽  
Vol 10 (23) ◽  
pp. 11641-11646 ◽  
Author(s):  
B. J. Sohn ◽  
T. Nakajima ◽  
M. Satoh ◽  
H.-S. Jang
Keyword(s):  
Radiative Forcing ◽  
Atmospheric Model ◽  
Satellite Measurements ◽  
Cloud Radiative Forcing ◽  
Cloud Forcing ◽  
Clear Sky ◽  
Atmospheric State ◽  
The Impact ◽  
Mean State

Abstract. Using one month of the cloud-resolving Nonhydrostatic Icosahedral Atmospheric Model (NICAM) simulations, we examined the impact of different definitions of clear-sky flux on the determination of longwave cloud radiative forcing (CRF). Because the satellite-like cloud-free composite preferentially samples drier conditions relative to the all-sky mean state, the conventional clear-sky flux calculation using the all-sky mean state in the model may represent a more humid atmospheric state in comparison to the cloud-free state. The drier bias is evident for the cloud-free composite in the NICAM simulations, causing an overestimation of the longwave CRF by about 10% compared to the NICAM simulated longwave CRF. Overall, water vapor contributions of up to 10% of the total longwave CRF should be taken account for making model-generated cloud forcing comparable to the satellite measurements.

scholarly journals Dry Bias in Satellite-Derived Clear-Sky Water Vapor and Its Contribution to Longwave Cloud Radiative Forcing

2006 ◽  
Vol 19 (21) ◽  
pp. 5570-5580 ◽  
Author(s):  
Byung-Ju Sohn ◽  
Johannes Schmetz ◽  
Rolf Stuhlmann ◽  
Joo-Young Lee
Keyword(s):  
Water Vapor ◽  
Radiative Forcing ◽  
Active Regions ◽  
Tropical Regions ◽  
Cloud Radiative Forcing ◽  
Cloud Data ◽  
Clear Sky ◽  
Cloud Development ◽  
Sampling Problem ◽  
Sky Conditions

Abstract In this paper, the amount of satellite-derived longwave cloud radiative forcing (CRF) that is due to an increase in upper-tropospheric water vapor associated with the evolution from clear-sky to the observed all-sky conditions is assessed. This is important because the satellite-derived clear-sky outgoing radiative fluxes needed for the CRF determination are from cloud-free areas away from the cloudy regions in order to avoid cloud contamination of the clear-sky fluxes. However, avoidance of cloud contamination implies a sampling problem as the clear-sky fluxes represent an area drier than the hypothetical clear-sky humidity in cloudy regions. While this issue has been recognized in earlier works this study makes an attempt to quantitatively estimate the bias in the clear-sky longwave CRF. Water vapor amounts in the 200–500-mb layer corresponding to all-sky condition are derived from microwave measurements with the Special Sensor Microwave Temperature-2 Profiler and are used in combination with cloud data for determining the clear-sky water vapor distribution of that layer. The obtained water vapor information is then used to constrain the humidity profiles for calculating clear-sky longwave fluxes at the top of the atmosphere. It is shown that the clear-sky moisture bias in the upper troposphere can be up to 40%–50% drier over convectively active regions. Results indicate that up to 12 W m−2 corresponding to about 15% of the satellite-derived longwave CRF in tropical regions can be attributed to the water vapor changes associated with cloud development.

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