Radiative fluxes and forces in non-spherical winds

2008 ◽  
pp. 144-150 ◽  
Author(s):  
Rainer Wehrse ◽  
Guido Kanschat
Keyword(s):  
Radiative Fluxes

scholarly journals Evaluation of cloud fraction and its radiative effect simulated by IPCC AR4 global models against ARM surface observations

2012 ◽  
Vol 12 (4) ◽  
pp. 1785-1810 ◽  
Author(s):  
Y. Qian ◽  
C. N. Long ◽  
H. Wang ◽  
J. M. Comstock ◽  
S. A. McFarlane ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Probability Distribution ◽  
Vertical Structure ◽  
Cloud Amount ◽  
Cloud Fraction ◽  
Department Of Energy ◽  
The Arctic ◽  
Radiative Fluxes ◽  
The Tropics ◽  
Ipcc Ar4

Abstract. Cloud Fraction (CF) is the dominant modulator of radiative fluxes. In this study, we evaluate CF simulated in the IPCC AR4 GCMs against ARM long-term ground-based measurements, with a focus on the vertical structure, total amount of cloud and its effect on cloud shortwave transmissivity. Comparisons are performed for three climate regimes as represented by the Department of Energy Atmospheric Radiation Measurement (ARM) sites: Southern Great Plains (SGP), Manus, Papua New Guinea and North Slope of Alaska (NSA). Our intercomparisons of three independent measurements of CF or sky-cover reveal that the relative differences are usually less than 10% (5%) for multi-year monthly (annual) mean values, while daily differences are quite significant. The total sky imager (TSI) produces smaller total cloud fraction (TCF) compared to a radar/lidar dataset for highly cloudy days (CF > 0.8), but produces a larger TCF value than the radar/lidar for less cloudy conditions (CF < 0.3). The compensating errors in lower and higher CF days result in small biases of TCF between the vertically pointing radar/lidar dataset and the hemispheric TSI measurements as multi-year data is averaged. The unique radar/lidar CF measurements enable us to evaluate seasonal variation of cloud vertical structures in the GCMs. Both inter-model deviation and model bias against observation are investigated in this study. Another unique aspect of this study is that we use simultaneous measurements of CF and surface radiative fluxes to diagnose potential discrepancies among the GCMs in representing other cloud optical properties than TCF. The results show that the model-observation and inter-model deviations have similar magnitudes for the TCF and the normalized cloud effect, and these deviations are larger than those in surface downward solar radiation and cloud transmissivity. This implies that other dimensions of cloud in addition to cloud amount, such as cloud optical thickness and/or cloud height, have a similar magnitude of disparity as TCF within the GCMs, and suggests that the better agreement among GCMs in solar radiative fluxes could be a result of compensating effects from errors in cloud vertical structure, overlap assumption, cloud optical depth and/or cloud fraction. The internal variability of CF simulated in ensemble runs with the same model is minimal. Similar deviation patterns between inter-model and model-measurement comparisons suggest that the climate models tend to generate larger biases against observations for those variables with larger inter-model deviation. The GCM performance in simulating the probability distribution, transmissivity and vertical profiles of cloud are comprehensively evaluated over the three ARM sites. The GCMs perform better at SGP than at the other two sites in simulating the seasonal variation and probability distribution of TCF. However, the models remarkably underpredict the TCF at SGP and cloud transmissivity is less susceptible to the change of TCF than observed. In the tropics, most of the GCMs tend to underpredict CF and fail to capture the seasonal variation of CF at middle and low levels. The high-level CF is much larger in the GCMs than the observations and the inter-model variability of CF also reaches a maximum at high levels in the tropics, indicating discrepancies in the representation of ice cloud associated with convection in the models. While the GCMs generally capture the maximum CF in the boundary layer and vertical variability, the inter-model deviation is largest near the surface over the Arctic.

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.

Experimental and Numerical Analyses of a Pressurized Air Receiver for Solar-Driven Gas Turbines

2010 ◽  
Author(s):  
Illias Hischier ◽  
Pascal Leumann ◽  
Aldo Steinfeld
Keyword(s):  
Power Generation ◽  
Monte Carlo ◽  
Steady State ◽  
Gas Turbines ◽  
Porous Ceramic ◽  
Operating Pressure ◽  
Radiative Fluxes ◽  
Monte Carlo Techniques ◽  
Concentrated Solar Radiation ◽  
Solar Receiver

A high-temperature pressurized air-based receiver for power generation via solar-driven gas turbines is experimentally and theoretically examined. It consists of an annular reticulate porous ceramic (RPC) foam concentric with an inner cylindrical cavity-receiver exposed to concentrated solar radiation. Absorbed heat is transferred by combined conduction, radiation, and convection to the pressurized air flowing across the RPC. The governing steady-state mass, momentum and energy conservation equations are formulated and solved numerically by coupled Finite Volume and Monte Carlo techniques. Validation is accomplished with experimental results using a 1 kW solar receiver prototype subjected to average solar radiative fluxes in the range 1870–4360 kW m−2. Experimentation was carried out with air and helium as working fluids, heated from ambient temperature up to 1335 K at an absolute operating pressure of 5 bars.

scholarly journals A New Double-Moment Microphysics Parameterization for Application in Cloud and Climate Models. Part II: Single-Column Modeling of Arctic Clouds

2005 ◽  
Vol 62 (6) ◽  
pp. 1678-1693 ◽  
Author(s):  
H. Morrison ◽  
J. A. Curry ◽  
M. D. Shupe ◽  
P. Zuidema
Keyword(s):  
Climate Models ◽  
Heat Budget ◽  
Number Concentration ◽  
The Arctic ◽  
Liquid Water Path ◽  
Microphysics Scheme ◽  
Radiative Fluxes ◽  
Arctic Clouds ◽  
Single Column ◽  
Double Moment

Abstract The new double-moment microphysics scheme described in Part I of this paper is implemented into a single-column model to simulate clouds and radiation observed during the period 1 April–15 May 1998 of the Surface Heat Budget of the Arctic (SHEBA) and First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment–Arctic Clouds Experiment (FIRE–ACE) field projects. Mean predicted cloud boundaries and total cloud fraction compare reasonably well with observations. Cloud phase partitioning, which is crucial in determining the surface radiative fluxes, is fairly similar to ground-based retrievals. However, the fraction of time that liquid is present in the column is somewhat underpredicted, leading to small biases in the downwelling shortwave and longwave radiative fluxes at the surface. Results using the new scheme are compared to parallel simulations using other microphysics parameterizations of varying complexity. The predicted liquid water path and cloud phase is significantly improved using the new scheme relative to a single-moment parameterization predicting only the mixing ratio of the water species. Results indicate that a realistic treatment of cloud ice number concentration (prognosing rather than diagnosing) is needed to simulate arctic clouds. Sensitivity tests are also performed by varying the aerosol size, solubility, and number concentration to explore potential cloud–aerosol–radiation interactions in arctic stratus.

scholarly journals Tropical Cirrus in Global Storm-Resolving Models. Part II: Cirrus Life Cycle and Top-of-Atmosphere Radiative Fluxes

2021 ◽  
Author(s):  
Samantha M Turbeville ◽  
Jacqueline M Nugent ◽  
Thomas P Ackerman ◽  
Christopher S. Bretherton ◽  
Peter N. Blossey
Keyword(s):  
Life Cycle ◽  
Radiative Fluxes

Can the Direct Effect of Aerosols Improve Subseasonal Predictability?

2018 ◽  
Vol 146 (10) ◽  
pp. 3481-3498 ◽  
Author(s):  
Angela Benedetti ◽  
Frédéric Vitart
Keyword(s):  
Weather Prediction ◽  
Ensemble Prediction ◽  
Radiation Balance ◽  
Carbonaceous Aerosols ◽  
Madden Julian Oscillation ◽  
Reasonable Accuracy ◽  
Ensemble Prediction System ◽  
Radiative Fluxes ◽  
Aerosol Effect ◽  
Definite Proof

Abstract The fact that aerosols are important players in Earth’s radiation balance is well accepted by the scientific community. Several studies have shown the importance of characterizing aerosols in order to constrain surface radiative fluxes and temperature in climate runs. In numerical weather prediction, however, there has not been definite proof that interactive aerosol schemes are needed to improve the forecast. Climatologies are instead used that allow for computational efficiency and reasonable accuracy. At the monthly to subseasonal range, it is still worth investigating whether aerosol variability could afford some predictability, considering that it is likely that persisting aerosol biases might manifest themselves more over time scales of weeks to months and create a nonnegligible forcing. This paper explores this hypothesis using the ECMWF’s Ensemble Prediction System for subseasonal prediction with interactive prognostic aerosols. Four experiments are conducted with the aim of comparing the monthly prediction by the default system, which uses aerosol climatologies, with the prediction using radiatively interactive aerosols. Only the direct aerosol effect is considered. Twelve years of reforecasts with 50 ensemble members are analyzed on the monthly scale. Results indicate that the interactive aerosols have the capability of improving the subseasonal prediction at the monthly scales for the spring/summer season. It is hypothesized that this is due to the aerosol variability connected to the different phases of the Madden–Julian oscillation, particularly that of dust and carbonaceous aerosols. The degree of improvement depends crucially on the aerosol initialization. More work is required to fully assess the potential of interactive aerosols to increase predictability at the subseasonal scales.

Solar radiative fluxes in the clear-sky atmosphere of Western Siberia: A comparison of simulations with field measurements

2014 ◽  
Vol 27 (2) ◽  
pp. 176-186 ◽  
Author(s):  
T. B. Zhuravleva ◽  
S. M. Sakerin ◽  
T. V. Bedareva ◽  
D. M. Kabanov ◽  
I. M. Nasrtdinov ◽  
...  
Keyword(s):  
Western Siberia ◽  
Field Measurements ◽  
Radiative Fluxes ◽  
Clear Sky

scholarly journals Turbulent fluxes above the snow surface

1998 ◽  
Vol 26 ◽  
pp. 179-183 ◽  
Author(s):  
Eric Martin ◽  
Yves Lejeune
Keyword(s):  
Surface Energy Balance ◽  
Meteorological Data ◽  
Energy Balance Equation ◽  
Turbulent Fluxes ◽  
Heat Fluxes ◽  
Indirect Measurements ◽  
Radiative Fluxes ◽  
Stable Conditions ◽  
Sonic Anemometers ◽  
Snow Model

Measurements of sensible- and latent-heat fluxes under stable conditions are rare. In order to obtain indirect measurements of turbulent fluxes, meteorological data measured at the Col de Porte laboratory (1320 m a.s.l, France) under very stable conditions (cold, clear night with low wind) are used. The radiative fluxes are measured, the conduction within the snowpack is calculated using the snow model Crocus and the turbulent fluxes are determined as a residual term of the surface-energy balance equation. These data were used to fit a new parameterization of the turbulent fluxes for the snow model. The turbulent fluxes are increased as compared to the theory. Crocus was also applied to the data from the LEADEX92 experiment and the turbulent fluxes calculated by the model were compared to the fluxes measured using sonic anemometers/thermometers on the site.

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