Band‐by‐Band Contributions to the Longwave Cloud Radiative Feedbacks

Cloud radiative feedback is central to our projection of future climate change. It can be estimated using the cloud radiative kernel (CRK) method or adjustment method. This study, for the first time, examines the contributions of each spectral band to the longwave (LW) cloud radiative feedbacks (CRFs). Simulations of three warming scenarios are analyzed, including +2 K sea surface temperature, 2 × CO2, and 4 × CO2 experiments. While the LW broadband CRFs derived from the CRK and adjustment methods agree with each other, they disagree on the relative contributions from the far‐infrared and window bands. The CRK method provides a consistent band‐by‐band decomposition of LW CRF for different warming scenarios. The simulated and observed short‐term broadband CRFs for the 2003–2013 period are similar to the long‐term counterparts, but their band‐by‐band decompositions are different, which can be further related to the cloud fraction changes in respective simulations and observation.Plain Language SummaryWe studied how the cloud change in response to surface temperature change leads to the changes of radiation at the top of the atmosphere (referred to as cloud radiative feedback) over different frequency ranges in the longwave (referred to as spectral bands). While different methods can provide a similar estimate of broadband cloud radiative feedbacks, the decomposition to different longwave spectral bands can be different from one method to another. The cloud radiative kernel method can provide a more consistent band‐by‐band decomposition of the longwave cloud radiative feedback for different warming scenarios. The decomposition for cloud radiative feedback derived from the warming experiments is considerably different from that derived from decadal‐scale observations and simulations. Such differences in spectral band decomposition can be related to the specific cloud fraction changes for different types of clouds defined with respect to cloud top pressure and cloud opacity.Key PointsThe band‐by‐band decomposition of cloud radiative feedback is studied for the first timeTwo different methods can give similar longwave broadband radiative feedbacks, but their band‐by‐band decompositions are differentSeemingly agreeable broadband cloud radiative feedbacks can have different spectral decompositions, which can be related to cloud changesPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150592/1/grl59162_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150592/2/grl59162.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150592/3/grl59162-sup-0001-2019GL083466-SI.pd

Fast and slow shifts of the zonal-mean intertropical convergence zone in response to an idealized anthropogenic aerosol

Previous modeling work showed that aerosol can affect the position of the tropical rain belt, i.e., the intertropical convergence zone (ITCZ). Yet it remains unclear which aspects of the aerosol impact are robust across models, and which are not. Here we present simulations with seven comprehensive atmosphere models that study the fast and slow impacts of an idealized anthropogenic aerosol on the zonal-mean ITCZ position. The fast impact, which results from aerosol atmospheric heating and land cooling before sea-surface temperature (SST) has time to respond, causes a northward ITCZ shift. Yet the fast impact is compensated locally by decreased evaporation over the ocean, and a clear northward shift is only found for an unrealistically large aerosol forcing. The local compensation implies that while models differ in atmospheric aerosol heating, this does not contribute to model differences in the ITCZ shift. The slow impact includes the aerosol impact on the ocean surface energy balance and is mediated by SST changes. The slow impact is an order of magnitude more effective than the fast impact and causes a clear southward ITCZ shift for realistic aerosol forcing. Models agree well on the slow ITCZ shift when perturbed with the same SST pattern. However, an energetic analysis suggests that the slow ITCZ shifts would be substantially more model-dependent in interactive-SST setups due to model differences in clear-sky radiative transfer and clouds. We also discuss implications for the representation of aerosol in climate models and attributions of recent observed ITCZ shifts to aerosol

POLDER observations of cloud bidirectional reflectances compared to a plane-parallel model using the International Satellite Cloud Climatology Project cloud phase functions

International audienceThis study investigates the validity of the plane-parallel cloud model and in addition the suitability of water droplet and ice polycrystal phase functions for stratocumulus and cirrus clouds, respectively. To do that, we take advantage of the multidirectional viewing capability of the Polarization and Directionality of the Earth's Reflectances (POLDER) instrument which allows us to characterize the anisotropy of the reflected radiation field. We focus on the analysis of airborne-POLDER data acquired over stratocumulus and cirrus clouds during two selected flights (on April 17 and April 18, 1994) of the European Cloud and Radiation Experiment (EUCREX'94) campaign. The bidirectional reflectances measured in the 0.86 μm channel are compared to plane-parallel cloud simulations computed with the microphysical models used by the International Satellite Cloud Climatology Project (ISCCP). Although clouds are not homogeneous plane-parallel layers, the extended cloud layers under study appear to act, on average, as a homogeneous plane-parallel layer. The standard water droplet model (with an effective radius of 10 μm) used in the ISCCP analysis seems to be suitable for stratocumulus clouds. The relative root-mean-square difference between the observed bidirectional reflectances and the model is only 2%. For cirrus clouds, the water droplet cloud model is definitely inadequate since the rms difference rises to 9%; when the ice polycrystal model chosen for the reanalysis of ISCCP data is used instead, the rms difference is reduced to 3%

Domain choice in an experimental nested modeling prediction system for South America

The purposes of this paper are to evaluate the new version of the regional model, RegCM3, over South America for two test seasons, and to select a domain for use in an experimental nested prediction system, which incorporates RegCM3 and the European Community-Hamburg (ECHAM) general circulation model (GCM). To evaluate RegCM3, control experiments were completed with RegCM3 driven by both the NCEP/NCAR Reanalysis (NNRP) and ECHAM, using a small control domain (D-CTRL) and integration periods of January–March 1983 (El Niño) and January–March 1985 (La Niña). The new version of the regional model captures the primary circulation and rainfall differences between the two years over tropical and subtropical South America. Both the NNRP-driven and ECHAM-driven RegCM3 improve the simulation of the Atlantic intertropical convergence zone (ITCZ) compared to the GCM. However, there are some simulation errors. Irrespective of the driving fields, weak northeasterlies associated with reduced precipitation are observed over the Amazon. The simulation of the South Atlantic convergence zone is poor due to errors in the boundary condition forcing which appear to be amplified by the regional model. To select a domain for use in an experimental prediction system, sensitivity tests were performed for three domains, each of which includes important regional features and processes of the climate system. The domain sensitivity experiments were designed to determine how domain size and the location of the GCM boundary forcing affect the regional circulation, moisture transport, and rainfall in two years with different large scale conditions. First, the control domain was extended southward to include the exit region of the Andes low level jet (D-LLJ), then eastward to include the South Atlantic subtropical high (D-ATL), and finally westward to include the subsidence region of the South Pacific subtropical high and to permit the regional model more freedom to respond to the increased resolution of the Andes Mountains (D-PAC). In order to quantify differences between the domain experiments, measures of bias, root mean square error, and the spatial correlation pattern were calculated between the model results and the observed data for the seasonal average fields. The results show the GCM driving fields have remarkable control over the RegCM3 simulations. Although no single domain clearly outperforms the others in both seasons, the control domain, D-CTRL, compares most favorably with observations. Over the ITCZ region, the simulations were improved by including a large portion of the South Atlantic subtropical high (D-ATL). The methodology presented here provides a quantitative basis for evaluating domain choice in future studies