scholarly journals The Sensitivity of Diagnostic Radiative Properties to Cloud Microphysics among Cloud-Resolving Model Simulations

2005 ◽  
Vol 62 (4) ◽  
pp. 1241-1254 ◽  
Author(s):  
Kuan-Man Xu
Keyword(s):  
Cooling Rate ◽  
Cloud Microphysics ◽  
Radiative Properties ◽  
Radiative Cooling ◽  
Heating Rates ◽  
Radiative Fluxes ◽  
Model Simulations ◽  
Cloud Resolving Model ◽  
Spatially Varying

Abstract This study examines the sensitivity of diagnosed radiative fluxes and heating rates to different treatments of cloud microphysics among cloud-resolving models (CRMs). The domain-averaged CRM outputs are used in this calculation. The impacts of the cloud overlap and uniform hydrometeor assumptions are examined using outputs having spatially varying cloud fields from a single CRM. It is found that the cloud overlap assumption impacts the diagnosis more significantly than the uniform hydrometeor assumption for all radiative fluxes. This is also the case for the longwave radiative cooling rate except for a layer above 7 km where it is more significantly impacted by the uniform hydrometeor assumption. The radiative cooling above upper-tropospheric anvils and the warming below these clouds are overestimated by about 0.5 K day−1 using the domain-averaged outputs. These results are used to further quantify intermodel differences in radiative properties due to different treatments of cloud microphysics among 10 CRMs. The magnitudes of the intermodel differences, as measured by the deviations from the consensus of 10 CRMs, are found to be smaller than those due to the cloud overlap assumption and comparable to those due to the uniform hydrometeor assumption for most shortwave radiative fluxes and the net radiative fluxes at the top of the atmosphere (TOA) and at the surface. For all longwave radiative fluxes, they are smaller than those due to cloud overlap and uniform hydrometeor assumptions. The consensus of all diagnosed radiative fluxes except for the surface downward shortwave flux agrees with observations to a degree that is close to the uncertainties of satellite- and ground-based measurements.

scholarly journals Cloud-Resolving Model Simulations of KWAJEX: Model Sensitivities and Comparisons with Satellite and Radar Observations

2007 ◽  
Vol 64 (5) ◽  
pp. 1488-1508 ◽  
Author(s):  
Peter N. Blossey ◽  
Christopher S. Bretherton ◽  
Jasmine Cetrone ◽  
Marat Kharoutdinov
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Longwave Radiation ◽  
Radiative Fluxes ◽  
Model Simulations ◽  
Time Period ◽  
Ground Validation ◽  
Cloud Resolving Model ◽  
Sensitivity Studies ◽  
Upper Level

Abstract Three-dimensional cloud-resolving model simulations of a mesoscale region around Kwajalein Island during the Kwajalein Experiment (KWAJEX) are performed. Using observed winds along with surface and large-scale thermodynamic forcings, the model tracks the observed mean thermodynamic soundings without thermodynamic nudging during 52-day simulations spanning the whole experiment time period, 24 July–14 September 1999. Detailed comparisons of the results with cloud and precipitation observations, including radar reflectivities from the Kwajalein ground validation radar and International Satellite Cloud Climatology Project (ISCCP) cloud amounts and radiative fluxes, reveal the biases and sensitivities of the model’s simulated clouds. The amount and optical depth of high cloud are underpredicted by the model during less rainy periods, leading to excessive outgoing longwave radiation (OLR) and insufficient albedo. The simulated radar reflectivities tend to be excessive, especially in the upper troposphere, suggesting that simulated high clouds are precipitating large hydrometeors too efficiently. Occasionally, large-scale advective forcing errors also seem to contribute to upper-level cloud and relative humidity biases. An extensive suite of sensitivity studies to different microphysical and radiative parameterizations is performed, with surprisingly little impact on the results in most cases.

Combining Satellite Microwave Radiometer and Radar Observations to Estimate Atmospheric Heating Profiles

2009 ◽  
Vol 22 (23) ◽  
pp. 6356-6376 ◽  
Author(s):  
Mircea Grecu ◽  
William S. Olson ◽  
Chung-Lin Shie ◽  
Tristan S. L’Ecuyer ◽  
Wei-Kuo Tao
Keyword(s):  
Microwave Radiometer ◽  
Tropical Rainfall Measuring Mission ◽  
Radiative Heating ◽  
Training Data ◽  
Heating Rates ◽  
Model Simulations ◽  
Surface Precipitation ◽  
Cloud Resolving Model ◽  
Microwave Imager ◽  
Heating Profile

Abstract In this study, satellite passive microwave sensor observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are utilized to make estimates of latent + eddy sensible heating rates (Q1 − QR) where Q1 is the apparent heat source and QR is the radiative heating rate in regions of precipitation. The TMI heating algorithm (herein called TRAIN) is calibrated or “trained” using relatively accurate estimates of heating based on spaceborne Precipitation Radar (PR) observations collocated with the TMI observations over a one-month period. The heating estimation technique is based on a previously described Bayesian methodology, but with improvements in supporting cloud-resolving model simulations, an adjustment of precipitation echo tops to compensate for model biases, and a separate scaling of convective and stratiform heating components that leads to an approximate balance between estimated vertically integrated condensation and surface precipitation. Estimates of Q1 − QR from TMI compare favorably with the PR training estimates and show only modest sensitivity to the cloud-resolving model simulations of heating used to construct the training data. Moreover, the net condensation in the corresponding annual mean satellite latent heating profile is within a few percent of the annual mean surface precipitation rate over the tropical and subtropical oceans where the algorithm is applied. Comparisons of Q1 produced by combining TMI Q1 − QR with independently derived estimates of QR show reasonable agreement with rawinsonde-based analyses of Q1 from two field campaigns, although the satellite estimates exhibit heating profile structures with sharper and more intense heating peaks than the rawinsonde estimates.

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
Keyword(s):  
General Circulation ◽  
Model Simulation ◽  
General Circulation Models ◽  
Radiative Heating ◽  
Heating Rates ◽  
Radiative Fluxes ◽  
Cloud Resolving Model ◽  
Horizontal Inhomogeneity ◽  
Heating Profiles

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.

scholarly journals On the Sensitivity of Atmospheric Ensembles to Cloud Microphysics in Long-Term Cloud-Resolving Model Simulations

2008 ◽  
Vol 86A ◽  
pp. 45-65 ◽  
Author(s):  
Xiping ZENG ◽  
Wei-Kuo TAO ◽  
Stephen LANG ◽  
Arthur Y. HOU ◽  
Minghua ZHANG ◽  
...  
Keyword(s):  
Cloud Microphysics ◽  
Model Simulations ◽  
Cloud Resolving Model

scholarly journals Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles

2018 ◽  
Vol 115 (11) ◽  
pp. 2687-2692 ◽  
Author(s):  
Jesús Vergara-Temprado ◽  
Annette K. Miltenberger ◽  
Kalli Furtado ◽  
Daniel P. Grosvenor ◽  
Ben J. Shipway ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Climate Models ◽  
Climate Model ◽  
Cloud Droplet ◽  
Radiative Properties ◽  
Model Simulations ◽  
Cloud Resolving Model ◽  
Climate Model Simulations ◽  
Mixed Phase Clouds ◽  
Strong Control

Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions.

scholarly journals Cloud-Resolving Model Simulations over the ARM SGP

2007 ◽  
Vol 135 (8) ◽  
pp. 2841-2853 ◽  
Author(s):  
Xiaoqing Wu ◽  
Xin-Zhong Liang ◽  
Sunwook Park
Keyword(s):  
Great Plains ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Heat Fluxes ◽  
Heating Rates ◽  
Tropical Ocean ◽  
Radiative Fluxes ◽  
Toga Coare ◽  
Cloud Resolving Model

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.

scholarly journals Assessing the Role of Particles in Radiative Heat Transfer during Oxy-Combustion of Coal and Biomass Blends

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Gautham Krishnamoorthy ◽  
Caitlyn Wolf
Keyword(s):  
Heat Transfer ◽  
Radiative Heat Transfer ◽  
Radiative Heat ◽  
Radiative Properties ◽  
Test Facility ◽  
Biomass Combustion ◽  
Radiative Fluxes ◽  
Scattering Phase ◽  
Scattering Phase Function ◽  
Fuel Fragmentation

This study assesses the required fidelities in modeling particle radiative properties and particle size distributions (PSDs) of combusting particles in Computational Fluid Dynamics (CFD) investigations of radiative heat transfer during oxy-combustion of coal and biomass blends. Simulations of air and oxy-combustion of coal/biomass blends in a 0.5 MW combustion test facility were carried out and compared against recent measurements of incident radiative fluxes. The prediction variations to the combusting particle radiative properties, particle swelling during devolatilization, scattering phase function, biomass devolatilization models, and the resolution (diameter intervals) employed in the fuel PSD were assessed. While the wall incident radiative flux predictions compared reasonably well with the experimental measurements, accounting for the variations in the fuel, char and ash radiative properties were deemed to be important as they strongly influenced the incident radiative fluxes and the temperature predictions in these strongly radiating flames. In addition, particle swelling and the diameter intervals also influenced the incident radiative fluxes primarily by impacting the particle extinction coefficients. This study highlights the necessity for careful selection of particle radiative property, and diameter interval parameters and the need for fuel fragmentation models to adequately predict the fly ash PSD in CFD simulations of coal/biomass combustion.

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