The Accuracy of Determining Three-Dimensional Radiative Transfer Effects in Cumulus Clouds Using Ground-Based Profiling Instruments

2005 ◽  
Vol 62 (7) ◽  
pp. 2284-2293 ◽  
Author(s):  
Robert Pincus ◽  
Cécile Hannay ◽  
K. Franklin Evans

Abstract Three-dimensional radiative transfer calculations are accurate, though computationally expensive, if the spatial distribution of cloud properties is known. The difference between these calculations and those using the much less expensive independent column approximation is called the 3D radiative transfer effect. Assessing the magnitude of this effect in the real atmosphere requires that many realistic cloud fields be obtained, and profiling instruments such as ground-based radars may provide the best long-term observations of cloud structure. Cloud morphology can be inferred from a time series of vertical profiles obtained from profilers by converting time to horizontal distance with an advection velocity, although this restricts variability to two dimensions. This paper assesses the accuracy of estimates of the 3D effect in shallow cumulus clouds when cloud structure is inferred in this way. Large-eddy simulations provide full three-dimensional, time-evolving cloud fields, which are sampled every 10 s to provide a “radar’s eye view” of the same cloud fields. The 3D effect for shortwave surface fluxes is computed for both sets of fields using a broadband Monte Carlo radiative transfer model, and intermediate calculations are made to identify reasons why estimates of the 3D effect differ in these fields. The magnitude of the 3D effect is systematically underestimated in the two-dimensional cloud fields because there are fewer cloud edges that cause the effect, while the random error in hourly estimates is driven by the limited sample observed by the profiling instrument.

2007 ◽  
Vol 64 (10) ◽  
pp. 3499-3520 ◽  
Author(s):  
Laura M. Hinkelman ◽  
K. Franklin Evans ◽  
Eugene E. Clothiaux ◽  
Thomas P. Ackerman ◽  
Paul W. Stackhouse

Abstract Cumulus clouds can become tilted or elongated in the presence of wind shear. Nevertheless, most studies of the interaction of cumulus clouds and radiation have assumed these clouds to be isotropic. This paper describes an investigation of the effect of fair-weather cumulus cloud field anisotropy on domain-averaged solar fluxes and atmospheric heating rate profiles. A stochastic field generation algorithm was used to produce 20 three-dimensional liquid water content fields based on the statistical properties of cloud scenes from a large eddy simulation. Progressively greater degrees of x–z plane tilting and horizontal stretching were imposed on each of these scenes, so that an ensemble of scenes was produced for each level of distortion. The resulting scenes were used as input to a three-dimensional Monte Carlo radiative transfer model. Domain-averaged transmission, reflection, and absorption of broadband solar radiation were computed for each scene along with the average heating rate profile. Both tilt and horizontal stretching were found to significantly affect calculated fluxes, with the amount and sign of flux differences depending strongly on sun position relative to cloud distortion geometry. The mechanisms by which anisotropy interacts with solar fluxes were investigated by comparisons to independent pixel approximation and tilted independent pixel approximation computations for the same scenes. Cumulus anisotropy was found to most strongly impact solar radiative transfer by changing the effective cloud fraction (i.e., the cloud fraction with respect to the solar beam direction).


2021 ◽  
Author(s):  
Megan Stretton ◽  
William Morrison ◽  
Robin Hogan ◽  
Sue Grimmond

<p>The heterogenous structure of cities impacts radiative exchanges (e.g. albedo and heat storage). Numerical weather prediction (NWP) models often characterise the urban structure with an infinite street canyon – but this does not capture the three-dimensional urban form. SPARTACUS-Urban (SU) - a fast, multi-layer radiative transfer model designed for NWP - is evaluated using the explicit Discrete Anisotropic Radiative Transfer (DART) model for shortwave fluxes across several model domains – from a regular array of cubes to real cities .</p><p>SU agrees with DART (errors < 5.5% for all variables) when the SU assumptions of building distribution are fulfilled (e.g. randomly distribution). For real-world areas with pitched roofs, SU underestimates the albedo (< 10%) and shortwave transmission to the surface (< 15%), and overestimates wall-plus-roof absorption (9-27%), with errors increasing with solar zenith angle. SU should be beneficial to weather and climate models, as it allows more realistic urban form (cf. most schemes) without large increases in computational cost.</p>


2020 ◽  
Author(s):  
Yuma Sakai ◽  
Hideki Kobayashi ◽  
Tomomichi Kato

Abstract. Global terrestrial ecosystems control the atmospheric CO2 concentration through gross primary production (GPP) and ecosystem respiration processes. Chlorophyll fluorescence is one of the energy release pathways of excess incident lights in the photosynthetic process. Over the last ten years, extensive studies have been revealed that canopy scale sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf level photosynthesis to global GPP, can be observed from satellites. SIF is used to infer photosynthetic capacity of plant canopy, however, it is not clear how the leaf-level SIF emission contributes to the top of canopy directional SIF. Plant canopy radiative transfer models are the useful tools to understand the causality of directional canopy SIF. One dimensional (1-D) plane parallel layer models (e.g. the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model) have been widely used and are useful to understand the general mechanisms behind the temporal and seasonal variations in SIF. However, due to the lack of complexity of the actual canopy structures, three dimensional models (3-D) have a potential to delineate the realistic directional canopy SIFs. Forest Light Environmental Simulator for SIF (FLiES-SIF) version 1.0 is the 3-D Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind the SIF emission from complex forest canopies. In this model description paper, we focused on the model formulation and simulation schemes, and showed some sensitivity analysis against several major variables such as view angle and leaf area index (LAI). The simulation results show that SIF increases with LAI then saturated at LAI > 2–4 depending on the spectral wavelength. The sensitivity analysis also shows that simulated SIF radiation may decrease with LAI at higher LAI domain (LAI > 5). These phenomena are seen in certain sun and view angle conditions. This type of non-linear and non-monotonic SIF behavior to LAI is also related to spatial forest structure patterns. FLiES-SIF version 1.0 can be used to quantify the canopy SIF in various view angles including the contribution of multiple scattering which is the important component in the near infrared domain. The potential use of the model is to standardize the satellite SIF by correcting the bi-directional effect. This step will contribute to the improvement of the GPP estimation accuracy through SIF.


2019 ◽  
Vol 489 (4) ◽  
pp. 4690-4704 ◽  
Author(s):  
Jong-Ho Shinn

ABSTRACT We have revisited the target EON_10.477_41.954 in order to determine more accurately the uncertainties in the model parameters that are important for target classification (i.e. galaxies with or without substantial extraplanar dust). We performed a Markov chain Monte Carlo (MCMC) analysis for the 15 parameters of the three-dimensional radiative-transfer galaxy model we used previously for target classification. To investigate the convergence of the MCMC sampling – which is usually neglected in the literature but should not be – we monitored the integrated autocorrelation time (τint), and we achieved effective sample sizes >5650 for all the model parameters. The confidence intervals are unstable at the beginning of the iterations where the values of τint are increasing, but they become stable in later iterations where those values are almost constant. The final confidence intervals are ∼5–100 times larger than the nominal uncertainties used in our previous study (the standard deviation of three best-fitting results). Thus, those nominal uncertainties are not good proxies for the model-parameter uncertainties. Although the position of EON_10.477_41.954 in the target-classification plot (the scale height to diameter ratio of dust versus that of light source) decreases by about 20–30 per cent when compared to our previous study, its membership in the ‘high-group’ – i.e. among galaxies with substantial extraplanar dust – nevertheless remains unchanged.


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