scholarly journals Radiative Effects of Cloud Horizontal Inhomogeneity and Vertical Overlap Identified from a Monthlong Cloud-Resolving Model Simulation

2005 ◽  
Vol 62 (11) ◽  
pp. 4105-4112 ◽  
Author(s):  
Xiaoqing Wu ◽  
Xin-Zhong Liang

Abstract The representation of subgrid horizontal and vertical variability of clouds in radiation schemes remains a major challenge for general circulation models (GCMs) due to the lack of cloud-scale observations and incomplete physical understanding. The development of cloud-resolving models (CRMs) in the last decade provides a unique opportunity to make progress in this area of research. This paper extends the study of Wu and Moncrieff to quantify separately the impacts of cloud horizontal inhomogeneity (optical property) and vertical overlap (geometry) on the domain-averaged shortwave and longwave radiative fluxes at the top of the atmosphere and the surface, and the radiative heating profiles. The diagnostic radiation calculations using the monthlong CRM-simulated tropical cloud optical properties and cloud fraction show that both horizontal inhomogeneity and vertical overlap of clouds are equally important for obtaining accurate radiative fluxes and heating rates. This study illustrates an objective approach to use long-term CRM simulations to separate cloud overlap and inhomogeneity effects, based on which GCM representation (such as mosaic treatment) of subgrid cloud–radiation interactions can be evaluated and improved.

2007 ◽  
Vol 135 (8) ◽  
pp. 2841-2853 ◽  
Author(s):  
Xiaoqing Wu ◽  
Xin-Zhong Liang ◽  
Sunwook Park

Abstract This study aims to combine the cloud-resolving model (CRM) simulations with the Department of Energy’s Atmospheric Radiation Measurement Program (ARM) observations to provide long-term comprehensive and physically consistent data that facilitate quantifying the effects of subgrid cloud–radiation interactions and ultimately to develop physically based parameterization of these interactions in general circulation models. The CRM is applied here to simulate the midlatitude cloud systems observed at the ARM southern Great Plains (SGP) site during the 1997 intensive observation period. As in the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE), the CRM-simulated ensemble mean quantities such as cloud liquid water, cloud fraction, precipitation, and radiative fluxes are generally in line with the surface measurements, satellite, and radar retrievals. The CRM differences from the ARM estimates, when averaged over the entire period, are less than 5 W m−2 in both longwave and shortwave radiative fluxes at the top of the atmosphere and surface. Because of the different large-scale forcing and surface heat fluxes in ARM and TOGA COARE, the CRM produces different cloud distributions over the midlatitude continent and tropical ocean. However, diagnostic analyses show that the subgrid cloud variability has similar impact on the domain-averaged radiative fluxes and heating rates in ARM as in TOGA COARE.


2008 ◽  
Vol 21 (11) ◽  
pp. 2352-2370 ◽  
Author(s):  
Jonathan K. P. Shonk ◽  
Robin J. Hogan

Abstract Radiation schemes in general circulation models currently make a number of simplifications when accounting for clouds, one of the most important being the removal of horizontal inhomogeneity. A new scheme is presented that attempts to account for the neglected inhomogeneity by using two regions of cloud in each vertical level of the model as opposed to one. One of these regions is used to represent the optically thinner cloud in the level, and the other represents the optically thicker cloud. So, along with the clear-sky region, the scheme has three regions in each model level and is referred to as “Tripleclouds.” In addition, the scheme has the capability to represent arbitrary vertical overlap between the three regions in pairs of adjacent levels. This scheme is implemented in the Edwards–Slingo radiation code and tested on 250 h of data from 12 different days. The data are derived from cloud retrievals using radar, lidar, and a microwave radiometer at Chilbolton, southern United Kingdom. When the data are grouped into periods equivalent in size to general circulation model grid boxes, the shortwave plane-parallel albedo bias is found to be 8%, while the corresponding bias is found to be less than 1% using Tripleclouds. Similar results are found for the longwave biases. Tripleclouds is then compared to a more conventional method of accounting for inhomogeneity that multiplies optical depths by a constant scaling factor, and Tripleclouds is seen to improve on this method both in terms of top-of-atmosphere radiative flux biases and internal heating rates.


2007 ◽  
Vol 7 (20) ◽  
pp. 5391-5400 ◽  
Author(s):  
K. M. Nissen ◽  
K. Matthes ◽  
U. Langematz ◽  
B. Mayer

Abstract. We introduce the improved Freie Universität Berlin (FUB) high-resolution radiation scheme FUBRad and compare it to the 4-band standard ECHAM5 SW radiation scheme of Fouquart and Bonnel (FB). Both schemes are validated against the detailed radiative transfer model libRadtran. FUBRad produces realistic heating rate variations during the solar cycle. The SW heating rate response with the FB scheme is about 20 times smaller than with FUBRad and cannot produce the observed temperature signal. A reduction of the spectral resolution to 6 bands for solar irradiance and ozone absorption cross sections leads to a degradation (reduction) of the solar SW heating rate signal by about 20%. The simulated temperature response agrees qualitatively well with observations in the summer upper stratosphere and mesosphere where irradiance variations dominate the signal. Comparison of the total short-wave heating rates under solar minimum conditions shows good agreement between FUBRad, FB and libRadtran up to the middle mesosphere (60–70 km) indicating that both parameterizations are well suited for climate integrations that do not take solar variability into account. The FUBRad scheme has been implemented as a sub-submodel of the Modular Earth Submodel System (MESSy).


2021 ◽  
Author(s):  
Gunter Stober ◽  
Ales Kuchar ◽  
Dimitry Pokhotelov ◽  
Huixin Liu ◽  
Han-Li Liu ◽  
...  

Abstract. Long-term and continuous observations of mesospheric/lower thermospheric winds are rare, but they are important to investigate climatological changes at these altitudes on time scales of several years, covering a solar cycle and longer. Such long time series are a natural heritage of the mesosphere/lower thermosphere climate, and they are valuable to compare climate models or long term runs of general circulation models (GCMs). Here we present a climatological comparison of wind observations from six meteor radars at two conjugate latitudes to validate the corresponding mean winds and atmospheric diurnal and semidiurnal tides from three GCMs, namely Ground-to-Topside Model of Atmosphere and Ionosphere for Aeronomy (GAIA), Whole Atmosphere Community Climate Model Extension (Specified Dynamics) (WACCM-X(SD)) and Upper Atmosphere ICOsahedral Non-hydrostatic (UA-ICON) model. Our results indicate that there are interhemispheric differences in the seasonal characteristics of the diurnal and semidiurnal tide. There also are some differences in the mean wind climatologies of the models and the observations. Our results indicate that GAIA shows a reasonable agreement with the meteor radar observations during the winter season, whereas WACCM-X(SD) shows a better agreement with the radars for the hemispheric zonal summer wind reversal, which is more consistent with the meteor radar observations. The free running UA-ICON tends to show similar winds and tides compared to WACCM-X(SD).


2018 ◽  
Vol 11 (8) ◽  
pp. 3147-3158 ◽  
Author(s):  
Hua Song ◽  
Zhibo Zhang ◽  
Po-Lun Ma ◽  
Steven Ghan ◽  
Minghuai Wang

Abstract. Satellite cloud observations have become an indispensable tool for evaluating general circulation models (GCMs). To facilitate the satellite and GCM comparisons, the CFMIP (Cloud Feedback Model Inter-comparison Project) Observation Simulator Package (COSP) has been developed and is now increasingly used in GCM evaluations. Real-world clouds and precipitation can have significant sub-grid variations, which, however, are often ignored or oversimplified in the COSP simulation. In this study, we use COSP cloud simulations from the Super-Parameterized Community Atmosphere Model (SPCAM5) and satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and CloudSat to demonstrate the importance of considering the sub-grid variability of cloud and precipitation when using the COSP to evaluate GCM simulations. We carry out two sensitivity tests: SPCAM5 COSP and SPCAM5-Homogeneous COSP. In the SPCAM5 COSP run, the sub-grid cloud and precipitation properties from the embedded cloud-resolving model (CRM) of SPCAM5 are used to drive the COSP simulation, while in the SPCAM5-Homogeneous COSP run only grid-mean cloud and precipitation properties (i.e., no sub-grid variations) are given to the COSP. We find that the warm rain signatures in the SPCAM5 COSP run agree with the MODIS and CloudSat observations quite well. In contrast, the SPCAM5-Homogeneous COSP run which ignores the sub-grid cloud variations substantially overestimates the radar reflectivity and probability of precipitation compared to the satellite observations, as well as the results from the SPCAM5 COSP run. The significant differences between the two COSP runs demonstrate that it is important to take into account the sub-grid variations of cloud and precipitation when using COSP to evaluate the GCM to avoid confusing and misleading results.


2007 ◽  
Vol 20 (11) ◽  
pp. 2602-2622 ◽  
Author(s):  
Ping Zhu ◽  
James J. Hack ◽  
Jeffrey T. Kiehl

Abstract In this study, it is shown that the NCAR and GFDL GCMs exhibit a marked difference in climate sensitivity of clouds and radiative fluxes in response to doubled CO2 and ±2-K SST perturbations. The GFDL model predicted a substantial decrease in cloud amount and an increase in cloud condensate in the warmer climate, but produced a much weaker change in net cloud radiative forcing (CRF) than the NCAR model. Using a multiple linear regression (MLR) method, the full-sky radiative flux change at the top of the atmosphere was successfully decomposed into individual components associated with the clear sky and different types of clouds. The authors specifically examined the cloud feedbacks due to the cloud amount and cloud condensate changes involving low, mid-, and high clouds between 60°S and 60°N. It was found that the NCAR and GFDL models predicted the same sign of individual longwave and shortwave feedbacks resulting from the change in cloud amount and cloud condensate for all three types of clouds (low, mid, and high) despite the different cloud and radiation schemes used in the models. However, since the individual longwave and shortwave feedbacks resulting from the change in cloud amount and cloud condensate generally have the opposite signs, the net cloud feedback is a subtle residual of all. Strong cancellations between individual cloud feedbacks may result in a weak net cloud feedback. This result is consistent with the findings of the previous studies, which used different approaches to diagnose cloud feedbacks. This study indicates that the proposed MLR approach provides an easy way to efficiently expose the similarity and discrepancy of individual cloud feedback processes between GCMs, which are hidden in the total cloud feedback measured by CRF. Most importantly, this method has the potential to be applied to satellite measurements. Thus, it may serve as a reliable and efficient method to investigate cloud feedback mechanisms on short-term scales by comparing simulations with available observations, which may provide a useful way to identify the cause for the wide spread of cloud feedbacks in GCMs.


2014 ◽  
Vol 27 (22) ◽  
pp. 8323-8341 ◽  
Author(s):  
Rachel R. McCrary ◽  
David A. Randall ◽  
Cristiana Stan

Abstract The relationship between African easterly waves and convection is examined in two coupled general circulation models: the Community Climate System Model (CCSM) and the “superparameterized” CCSM (SP-CCSM). In the CCSM, the easterly waves are much weaker than observed. In the SP-CCSM, a two-dimensional cloud-resolving model replaces the conventional cloud parameterizations of CCSM. Results show that this allows for the simulation of easterly waves with realistic horizontal and vertical structures, although the model exaggerates the intensity of easterly wave activity over West Africa. The simulated waves of SP-CCSM are generated in East Africa and propagate westward at similar (although slightly slower) phase speeds to observations. The vertical structure of the waves resembles the first baroclinic mode. The coupling of the waves with convection is realistic. Evidence is provided herein that the diabatic heating associated with deep convection provides energy to the waves simulated in SP-CCSM. In contrast, horizontal and vertical structures of the weak waves in CCSM are unrealistic, and the simulated convection is decoupled from the circulation.


2018 ◽  
Author(s):  
Dietmar Dommenget ◽  
Kerry Nice ◽  
Tobias Bayr ◽  
Dieter Kasang ◽  
Christian Stassen ◽  
...  

Abstract. This study introduces the Monash Simple Climate Model (MSCM) experiment database. The model simulations are based on the Globally Resolved Energy Balance (GREB) model. They provide a basis to study three different aspects of climate model simulations: (1) understanding the processes that control the mean climate, (2) the response of the climate to a doubling of the CO2 concentration, and (3) scenarios of external CO2 concentration and solar radiation forcings. A series of sensitivity experiments in which elements of the climate system are turned off in various combinations are used to address (1) and (2). This database currently provides more than 1,300 experiments and has an online web interface for fast analysis of the experiments and for open access to the data. We briefly outline the design of all experiments, give a discussion of some results, and put the findings into the context of previously published results from similar experiments. We briefly discuss the quality and limitations of the MSCM experiments and also give an outlook on possible further developments. The GREB model simulation of the mean climate processes is quite realistic, but does have uncertainties in the order of 20–30 %. The GREB model without flux corrections has a root mean square error in mean state of about 10 °C, which is larger than those of general circulation models (2 °C). However, the MSCM experiments show good agreement to previously published studies. Although GREB is a very simple model, it delivers good first-order estimates, is very fast, highly accessible, and can be used to quickly try many different sensitivity experiments or scenarios.


2009 ◽  
Vol 27 (7) ◽  
pp. 2755-2770 ◽  
Author(s):  
Z. Li ◽  
X. Zhao ◽  
R. Kahn ◽  
M. Mishchenko ◽  
L. Remer ◽  
...  

Abstract. As a result of increasing attention paid to aerosols in climate studies, numerous global satellite aerosol products have been generated. Aerosol parameters and underlining physical processes are now incorporated in many general circulation models (GCMs) in order to account for their direct and indirect effects on the earth's climate, through their interactions with the energy and water cycles. There exists, however, an outstanding problem that these satellite products have substantial discrepancies, that must be lowered substantially for narrowing the range of the estimates of aerosol's climate effects. In this paper, numerous key uncertain factors in the retrieval of aerosol optical depth (AOD) are articulated for some widely used and relatively long satellite aerosol products including the AVHRR, TOMS, MODIS, MISR, and SeaWiFS. We systematically review the algorithms developed for these sensors in terms of four key elements that influence the quality of passive satellite aerosol retrieval: calibration, cloud screening, classification of aerosol types, and surface effects. To gain further insights into these uncertain factors, the NOAA AVHRR data are employed to conduct various tests, which help estimate the ranges of uncertainties incurred by each of the factors. At the end, recommendations are made to cope with these issues and to produce a consistent and unified aerosol database of high quality for both environment monitoring and climate studies.


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