Evaluation of shortwave radiation fluxes in the multi-layer SPARTACUS-Urban scheme using DART

2021 ◽  
Author(s):  
Megan Stretton ◽  
William Morrison ◽  
Robin Hogan ◽  
Sue Grimmond
Keyword(s):  
Radiative Transfer ◽  
Urban Form ◽  
Climate Models ◽  
Weather Prediction ◽  
Computational Cost ◽  
Three Dimensional ◽  
Shortwave Radiation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Urban Structure

<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>

scholarly journals Mesoscale Simulations of Australian Direct Normal Irradiance, Featuring an Extreme Dust Event

2018 ◽  
Vol 57 (3) ◽  
pp. 493-515 ◽  
Author(s):  
S. K. Mukkavilli ◽  
A. A. Prasad ◽  
R. A. Taylor ◽  
A. Troccoli ◽  
M. J. Kay
Keyword(s):  
Radiative Transfer ◽  
Climate Models ◽  
Global Climate ◽  
Weather Prediction ◽  
Wrf Model ◽  
Global Climate Models ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Dust Event ◽  
Direct Normal Irradiance

AbstractDirect normal irradiance (DNI) is the main input for concentrating solar power (CSP) technologies—an important component in future energy scenarios. DNI forecast accuracy is sensitive to radiative transfer schemes (RTSs) and microphysics in numerical weather prediction (NWP) models. Additionally, NWP models have large regional aerosol uncertainties. Dust aerosols can significantly attenuate DNI in extreme cases, with marked consequences for applications such as CSP. To date, studies have not compared the skill of different physical parameterization schemes for predicting hourly DNI under varying aerosol conditions over Australia. The authors address this gap by aiming to provide the first Weather and Forecasting (WRF) Model DNI benchmarks for Australia as baselines for assessing future aerosol-assimilated models. Annual and day-ahead simulations against ground measurements at selected sites focusing on an extreme dust event are run. Model biases are assessed for five shortwave RTSs at 30- and 10-km grid resolutions, along with the Thompson aerosol-aware scheme in three different microphysics configurations: no aerosols, fixed optical properties, and monthly climatologies. From the annual simulation, the best schemes were the Rapid Radiative Transfer Model for global climate models (RRTMG), followed by the new Goddard and Dudhia schemes, despite the relative simplicity of the latter. These top three RTSs all had 1.4–70.8 W m−2 lower mean absolute error than persistence. RRTMG with monthly aerosol climatologies was the best combination. The extreme dust event had large DNI mean bias overpredictions (up to 4.6 times), compared to background aerosol results. Dust storm–aware DNI forecasts could benefit from RRTMG with high-resolution aerosol inputs.

Introducing cloud horizontal overlap at NWP scales (1-10 km) in a fast 3D radiative transfer model

2021 ◽  
Author(s):  
Mihail Manev ◽  
Bernhard Mayer ◽  
Claudia Emde ◽  
Aiko Voigt
Keyword(s):  
Radiative Transfer ◽  
Climate Models ◽  
Scale Effects ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Subgrid Scale ◽  
Computationally Efficient ◽  
Realistic Description

<p><span>Interactions between radiation and clouds are a source of significant uncertainty in both numerical weather prediction </span><span>(NWP) </span><span>and climate models. </span><span>Future models need to both incorporate more realistic description of physical processes and be computationally efficient. </span><span>With the </span><span>steadi</span><span>ly</span> <span>increasing</span><span> resolution of NWP models, </span><span>previously neglected effects like the horizontal propagation of radiation become more important. </span></p><p><span>Here we present a </span><span>hybrid</span><span> radiative transfer model that combines </span><span>a traditional twostream maximum random overlap </span><span>(twomaxrnd)</span><span> radiative solver </span><span>(</span><span>Č</span><span>rnivec and Mayer, 20</span><span>19</span><span>)</span><span> with a Neighbouring Column Approximation </span><span>(NCA)</span> <span>model </span><span>(Klinger and Mayer, 20</span><span>19</span><span>)</span><span>, which parametrizes horizontal photon transport between adjacent grid-cells. </span><span>Thereby </span><span>the hybrid</span> <span>includes</span><span> both subgrid-scale effects and grid-scale horizontal transport. </span><span>In addition</span><span> we introduced </span><span>a</span><span> horizontal </span><span>cloud </span><span>overlap scheme </span><span>to the hybrid model</span><span>. In order to </span><span>differentiate between different overlap concepts and deduce optimal overlap coefficients we used</span><span> high resolution radiative </span><span>transfer </span><span>simulations </span><span>of LES cloud fields </span><span>(horizontal resolution of 100-300 m)</span> <span>deploying </span><span>a very accurate Monte Carlo </span><span>(MYSTIC)</span><span> model </span><span>(</span><span>Mayer, 2009</span><span>)</span><span>.</span></p><p><span>Further we assess the performance of the </span><span>hybrid</span><span> model </span><span>at the NWP scale (1-10 km)</span><span> for various </span><span>realistic </span><span>cloud configurations </span><span>using</span><span> results from the benchmark MYSTIC model</span> <span>and determine the differences compared to other solvers that only consider either grid-scale or subgrid-scale effects, twomaxrnd, Tripleclouds and NCA.</span></p><p> </p>

Development of a Fast Three-Dimensional Dynamic Radiative Transfer Solver for Numerical Weather Prediction Models


2021 ◽  
Author(s):  
Richard Maier ◽  
Bernhard Mayer ◽  
Claudia Emde ◽  
Aiko Voigt
Keyword(s):  
Radiative Transfer ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Transfer Model ◽  
Heating Rates ◽  
Time Step ◽  
Numerical Weather ◽  
Numerical Weather Prediction Models

<div> <div> <div> <div> <p>The increasing resolution of numerical weather prediction models makes 3D radiative effects more and more important. These effects are usually neglected by the simple 1D independent column approximations used in most of the current models. On top of that, these 1D radiative transfer solvers are also called far less often than the model’s dynamical core.</p> <p>To address these issues, we present a new „dynamic“ approach of solving 3D radiative transfer. Building upon the existing TenStream solver (Jakub and Mayer, 2015), radiation in this 3D model is not solved completely in each radiation time step, but is rather only transported to adjacent grid boxes. For every grid box, outgoing fluxes are then calculated from the incoming fluxes from the neighboring grid cells of the previous time step. This allows to reduce the computational cost of 3D radiative transfer models to that of current 1D solvers.</p> <p>Here, we show first results obtained with this new solver with a special emphasis on heating rates. Furthermore, we demonstrate issues related to the dynamical treatment of radiation as well as possible solutions to these problems.</p> <p>In the future, the speed of this newly developed 3D dynamic TenStream solver will be further increased by reducing the number of spectral bands used in the radiative transfer calculations with the aim to get a 3D solver that can be called even more frequently than the 1D two-stream solvers used nowadays.</p> <p>Reference:<br><span>Jakub, F. and Mayer, B. (2015), A three-dimensional parallel radiative transfer model for atmospheric heating rates for use in cloud resolving models—The TenStream solver, Journal of Quantitative Spectroscopy and Radiative Transfer, Volume 163, 2015, Pages 63-71, ISSN 0022-4073, . </span></p> </div> </div> </div> </div>

scholarly journals Evaluation of MWHS-2 Using a Co-located Ground-Based Radar Network for Improved Model Assimilation

2019 ◽  
Vol 11 (20) ◽  
pp. 2338 ◽  
Author(s):  
Liu ◽  
Chu ◽  
Yin ◽  
Liu
Keyword(s):  
Radiative Transfer ◽  
Brightness Temperature ◽  
Weather Prediction ◽  
Order Relation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radar Network ◽  
Intense Precipitation ◽  
Standard Deviations ◽  
Light Precipitation

Accurate precipitation detection is one of the most important factors in satellite data assimilation, due to the large uncertainties associated with precipitation properties in radiative transfer models and numerical weather prediction (NWP) models. In this paper, a method to achieve remote sensing of precipitation and classify its intensity over land using a co-located ground-based radar network is described. This method is intended to characterize the O−B biases for the microwave humidity sounder -2 (MWHS-2) under four categories of precipitation: precipitation-free (0–5 dBZ), light precipitation (5–20 dBZ), moderate precipitation (20–35 dBZ), and intense precipitation (>35 dBZ). Additionally, O represents the observed brightness temperature (TB) of the satellite and B is the simulated TB from the model background field using the radiative transfer model. Thresholds for the brightness temperature differences between channels, as well as the order relation between the differences, exhibited a good estimation of precipitation. It is demonstrated that differences between observations and simulations were predominantly due to the cases in which radar reflectivity was above 15 dBZ. For most channels, the biases and standard deviations of O−B increased with precipitation intensity. Specifically, it is noted that for channel 11 (183.31 ± 1 GHz), the standard deviations of O−B under moderate and intense precipitation were even smaller than those under light precipitation and precipitation-free conditions. Likewise, abnormal results can also be seen for channel 4 (118.75 ± 0.3 GHz).

scholarly journals Analysis of the decrease in the tropical mean outgoing shortwave radiation at the top of atmosphere for the period 1984-2000

2005 ◽  
Vol 5 (6) ◽  
pp. 1721-1730 ◽  
Author(s):  
A. Fotiadi ◽  
N. Hatzianastassiou ◽  
C. Matsoukas ◽  
K. G. Pavlakis ◽  
E. Drakakis ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Climate Model ◽  
Shortwave Radiation ◽  
Radiative Energy ◽  
Radiative Transfer Model ◽  
Physical Parameters ◽  
Transfer Model ◽  
Monthly Basis ◽  
Decadal Scale

Abstract. A decadal-scale trend in the tropical radiative energy budget has been observed recently by satellites, which however is not reproduced by climate models. In the present study, we have computed the outgoing shortwave radiation (OSR) at the top of atmosphere (TOA) at 2.5° longitude-latitude resolution and on a mean monthly basis for the 17-year period 1984-2000, by using a deterministic solar radiative transfer model and cloud climatological data from the International Satellite Cloud Climatology Project (ISCCP) D2 database. Anomaly time series for the mean monthly pixel-level OSR fluxes, as well as for the key physical parameters, were constructed. A significant decreasing trend in OSR anomalies, starting mainly from the late 1980s, was found in tropical and subtropical regions (30° S-30° N), indicating a decadal increase in solar planetary heating equal to 1.9±0.3Wm-2/decade, reproducing well the features recorded by satellite observations, in contrast to climate model results. This increase in solar planetary heating, however, is accompanied by a similar increase in planetary cooling, due to increased outgoing longwave radiation, so that there is no change in net radiation. The model computed OSR trend is in good agreement with the corresponding linear decadal decrease of 2.5±0.4Wm-2/decade in tropical mean OSR anomalies derived from ERBE S-10N non-scanner data (edition 2). An attempt was made to identify the physical processes responsible for the decreasing trend in tropical mean OSR. A detailed correlation analysis using pixel-level anomalies of model computed OSR flux and ISCCP cloud cover over the entire tropical and subtropical region (30° S-30° N), gave a correlation coefficient of 0.79, indicating that decreasing cloud cover is the main reason for the tropical OSR trend. According to the ISCCP-D2 data derived from the combined visible/infrared (VIS/IR) analysis, the tropical cloud cover has decreased by 6.6±0.2% per decade, in relative terms. A detailed analysis of the inter-annual and long-term variability of the various parameters determining the OSR at TOA, has shown that the most important contribution to the observed OSR trend comes from a decrease in low-level cloud cover over the period 1984-2000, followed by decreases in middle and high-level cloud cover. Note, however, that there still remain some uncertainties associated with the existence and magnitude of trends in ISCCP-D2 cloud amounts. Opposite but small trends are introduced by increases in cloud scattering optical depth of low and middle clouds.

scholarly journals RTTOV-gb – Adapting the fast radiative transfer model RTTOV for the assimilation of ground-based microwave radiometer observations

2016 ◽  
Author(s):  
Francesco De Angelis ◽  
Domenico Cimini ◽  
James Hocking ◽  
Pauline Martinet ◽  
Stefan Kneifel
Keyword(s):  
Radiative Transfer ◽  
Liquid Water ◽  
Weather Prediction ◽  
Microwave Radiometer ◽  
Software Tool ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
60 Ghz ◽  
Variational Assimilation ◽  
Temperature And Humidity

Abstract. Ground-based microwave radiometers (MWR) offer a new capability to provide continuous observations of the atmospheric thermodynamic state in the planetary boundary layer. Thus, they are potential candidates to supplement radiosonde network and satellite data to improve numerical weather prediction (NWP) models through a variational assimilation of their data. However in order to assimilate MWR observations a fast radiative transfer model is required and such a model is not currently available. This is necessary for going from the model state vector space to the observation space at every observation point. The fast radiative transfer model RTTOV is well accepted in the NWP community, though it was developed to simulate satellite observations only. In this work, the RTTOV code has been modified to allow for simulations of ground-based upward looking microwave sensors. In addition, the Tangent Linear, Adjoint, and K-modules of RTTOV have been adapted to provide Jacobians (i.e. the sensitivity of observations to the atmospheric thermodynamical state) for ground-based geometry. These modules are necessary for the fast minimization of the cost function in a variational assimilation scheme. The proposed ground-based version of RTTOV, called RTTOV-gb, has been validated against accurate and less time-efficient line-by-line radiative transfer models. In the frequency range commonly used for temperature and humidity profiling (22–60 GHz), root-mean-square brightness temperature differences are smaller than typical MWR uncertainties (~ 0.5 K) at all channels used in this analysis. Brightness temperatures (TB) computed with RTTOV-gb from radiosonde profiles have been compared with nearly simultaneous and colocated ground-based MWR observations. Differences between simulated and measured TB are below 0.5 K for all channels except for the water vapor band, where most of the uncertainty comes from instrumental errors. The Jacobians calculated with the K-module of RTTOV-gb have been compared with those calculated with the brute force technique and those from the line-by-line model ARTS. Jacobians are found to be almost identical, except for liquid water content Jacobians for which a 10 % difference between ARTS and RTTOV-gb at transparent channels around 450 hPa is attributed to differences in liquid water absorption models. Finally, RTTOV-gb has been applied as the forward model operator within a 1-Dimensional Variational (1D-Var) software tool in an Observing-System Simulation Experiment (OSSE). For both temperature and humidity profiles, the 1D-Var with RTTOV-gb improves the retrievals with respect to NWP model in the first few kilometers from the ground.

scholarly journals FLiES-SIF ver. 1.0: Three-dimensional radiative transfer model for estimating solar induced fluorescence

2020 ◽  
Author(s):  
Yuma Sakai ◽  
Hideki Kobayashi ◽  
Tomomichi Kato
Keyword(s):  
Sensitivity Analysis ◽  
Chlorophyll Fluorescence ◽  
Radiative Transfer ◽  
Three Dimensional ◽  
Radiative Transfer Model ◽  
Model Description ◽  
Transfer Model ◽  
Plant Canopy ◽  
Parallel Layer ◽  
Leaf Level

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.

scholarly journals Seeking edge-on galaxies with substantial extraplanar dust using a radiative transfer model: determination of the model parameter uncertainties for EON_10.477_41.954 (FGC 79)

2019 ◽  
Vol 489 (4) ◽  
pp. 4690-4704 ◽  
Author(s):  
Jong-Ho Shinn
Keyword(s):  
Radiative Transfer ◽  
Confidence Intervals ◽  
Three Dimensional ◽  
Radiative Transfer Model ◽  
Model Parameters ◽  
Transfer Model ◽  
Target Classification ◽  
Parameter Uncertainties ◽  
Model Parameter ◽  
Galaxy Model

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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