scholarly journals Doubling–Adding Method for Delta-Four-Stream Spherical Harmonic Expansion Approximation in Radiative Transfer Parameterization

2013 ◽  
Vol 70 (10) ◽  
pp. 3084-3101 ◽  
Author(s):  
Feng Zhang ◽  
Jiangnan Li
Keyword(s):  
Radiative Transfer ◽  
Invariance Principle ◽  
Computational Efficiency ◽  
Spherical Harmonic ◽  
Radiative Forcing ◽  
Climate Models ◽  
Spherical Harmonic Expansion ◽  
Discrete Ordinates ◽  
Heating Rates ◽  
Relative Errors

Abstract Though the single-layer solutions have been found for the δ-four-stream spherical harmonic expansion method (SHM) in radiative transfer, there is lack of a corresponding doubling–adding method (4SDA), which enables the calculation of radiative transfer through a vertically inhomogeneous atmosphere with multilayers. The doubling–adding method is based on Chandrasekhar's invariance principle, which was originally developed for discrete ordinates approximation. It is shown that the invariance principle can also be applied to SHM and δ-four-stream spherical harmonic expansion doubling–adding method (δ-4SDA) is proposed in this paper. The δ-4SDA method has been systematically compared to the δ-Eddington doubling–adding method (δ-2SDA), the δ-two-stream discrete ordinates doubling–adding method (δ-2DDA), and δ-four-stream discrete ordinates doubling–adding method (δ-4DDA). By applying δ-4SDA to a realistic atmospheric profile with gaseous transmission considered, it is found that the accuracy of δ-4SDA is superior to δ-2SDA or δ-2DDA, especially for the cloudy/aerosol conditions. It is shown that the relative errors of δ-4SDA are generally less than 1% in both heating rate and flux, while the relative errors of both δ-2SDA and δ-2DDA can be over 6%. Though δ-4DDA is slightly more accurate than δ-4SDA in heating rates, both of them are accurate enough to obtain the cloud-top solar heating. Here δ-4SDA is superior to δ-4DDA in computational efficiency. It is found that the error of aerosol radiative forcing can be up to 3 W m−2 by using δ-2SDA at the top of the atmosphere (TOA); such error is substantially reduced by applying δ-4SDA. In view of the overall accuracy and computational efficiency, δ-4SDA is suitable for application in climate models.

Aerosol influences on radiative heating rates in the Asian tropopause aerosol layer

2021 ◽  
Author(s):  
Jie Gao ◽  
Jonathon Wright
Keyword(s):  
Radiative Transfer ◽  
Radiative Forcing ◽  
Asian Monsoon ◽  
Volcanic Eruptions ◽  
Radiative Heating ◽  
Spatiotemporal Variability ◽  
Radiation Budget ◽  
Aerosol Layer ◽  
Heating Rates ◽  
Aerosol Analysis

<p>The Asian Tropopause Aerosol Layer (ATAL) has emerged over recent decades to play an increasingly prominent role in the upper troposphere and lower stratosphere above the Asian monsoon region. Although the effects of the ATAL on the surface and top-of-atmosphere radiation budget have been examined by several studies, the processes and effects by which the ATAL alters radiative transfer within the tropopause layer have been much less discussed. We have used a conditional composite approach to investigate aerosol mixing ratios and their impacts on radiative heating rates in the Asian monsoon tropopause layer in MERRA-2. We have then subsampled in time based on known volcanic eruptions and the evolution of emission and data assimilation inputs to the MERRA-2 aerosol analysis to isolate the ATAL contribution and compare it to radiative heating signatures in the monsoon anticyclone region after volcanic eruptions. The results indicate that the ATAL impact on radiative heating rates in this region is on the order of 0.1 K/day, similar to that associated with ozone variability in MERRA-2 but weaker than cloud radiative effects at these altitudes. We have validated these results and tested their sensitivity to variations in the vertical structure and composition of ATAL aerosols using offline radiative transfer simulations. The idealized simulations produce similar but slightly stronger responses of radiative heating rates to the ATAL and are in good agreement with previous estimates of the top-of-atmosphere radiative forcing. Although the ATAL perturbations inferred from MERRA-2 are only about 10% of mean heating rates at these levels, their spatial distribution suggests potential implications for both isentropic and diabatic transport within the monsoon anticyclone, which should be examined in future work. Our results are limited by uncertainties in the composition and spatiotemporal variability of the ATAL, and reflect only the conditions in this layer as represented by MERRA-2. Targeted observations and model simulations are needed to adequately constrain the uncertainties, particularly with respect to the relative proportions and contributions of nitrate aerosols, which are not included in the MERRA-2 aerosol analysis.</p>

Analytical Delta-Four-Stream Doubling–Adding Method for Radiative Transfer Parameterizations

2013 ◽  
Vol 70 (3) ◽  
pp. 794-808 ◽  
Author(s):  
Feng Zhang ◽  
Zhongping Shen ◽  
Jiangnan Li ◽  
Xiuji Zhou ◽  
Leiming Ma
Keyword(s):  
Optical Properties ◽  
Radiative Transfer ◽  
Transfer Process ◽  
Solar Spectrum ◽  
Single Layer ◽  
Discrete Ordinates ◽  
Discrete Ordinates Method ◽  
Atmospheric Profile ◽  
Relative Errors ◽  
Transmission And Absorption

Abstract Although single-layer solutions have been obtained for the δ-four-stream discrete ordinates method (DOM) in radiative transfer, a four-stream doubling–adding method (4DA) is lacking, which enables us to calculate the radiative transfer through a vertically inhomogeneous atmosphere with multiple layers. In this work, based on the Chandrasekhar invariance principle, an analytical method of δ-4DA is proposed. When applying δ-4DA to an idealized medium with specified optical properties, the reflection, transmission, and absorption are the same if the medium is treated as either a single layer or dividing it into multiple layers. This indicates that δ-4DA is able to solve the multilayer connection properly in a radiative transfer process. In addition, the δ-4DA method has been systematically compared with the δ-two-stream doubling–adding method (δ-2DA) in the solar spectrum. For a realistic atmospheric profile with gaseous transmission considered, it is found that the accuracy of δ-4DA is superior to that of δ-2DA in most of cases, especially for the cloudy sky. The relative errors of δ-4DA are generally less than 1% in both the heating rate and flux, while the relative errors of δ-2DA can be as high as 6%.

Adding method of delta-four-stream spherical harmonic expansion approximation for infrared radiative transfer parameterization

2016 ◽  
Vol 78 ◽  
pp. 254-262 ◽  
Author(s):  
Kun Wu ◽  
Feng Zhang ◽  
Jinzhong Min ◽  
Qiu-Run Yu ◽  
Xin-Yue Wang ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Spherical Harmonic ◽  
Spherical Harmonic Expansion

The δ-six-stream spherical harmonic expansion adding method for solar radiative transfer

2020 ◽  
Vol 243 ◽  
pp. 106818 ◽  
Author(s):  
Dan Xue ◽  
Feng Zhang ◽  
Yi-Ning Shi ◽  
Hironobu Iwabuchi ◽  
Jiangnan Li ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Spherical Harmonic ◽  
Spherical Harmonic Expansion

scholarly journals RadNet 1.0: Exploring deep learning architectures for longwave radiative transfer

2020 ◽  
Author(s):  
Ying Liu ◽  
Rodrigo Caballero ◽  
Joy Merwin Monteiro
Keyword(s):  
Neural Network ◽  
Radiative Transfer ◽  
Climate Models ◽  
Climate Model ◽  
Mean Squared Error ◽  
Network Models ◽  
Radiative Heating ◽  
Human Populations ◽  
Heating Rates ◽  
Neural Network Models

Abstract. Simulating global and regional climate at high resolution is essential to study the effects of climate change and capture extreme events affecting human populations. To achieve this goal, the scalability of climate models and the efficiency of individual model components are both important. Radiative transfer is among the most computationally expensive components in a typical climate model. Here we attempt to model this component using a neural network. We aim to study the feasibility of replacing an explicit, physics-based computation of longwave radiative transfer by a neural network emulator, and assessing the resultant performance gains. We compare multiple neural-network architectures, including a convolutional neural network and our results suggest that the performance loss from the use of convolutional networks is not offset by gains in accuracy. We train the networks with and without noise added to the input profiles and find that adding noise improves the ability of the networks to generalise beyond the training set. Prediction of radiative heating rates using our neural network models achieve up to 370x speedup on a GTX 1080 GPU setup and 11x speedup on a Xeon CPU setup compared to the a state of the art radiative transfer library running on the same Xeon CPU. Furthermore, our neural network models yield less than 0.1 Kelvin per day mean squared error across all pressure levels. Upon introducing this component into a single column model, we find that the time evolution of the temperature and humidity profiles are physically reasonable, though the model is conservative in its prediction of heating rates in regions where the optical depth changes quickly. Differences exist in the equilibrium climate simulated when using the neural networks, which are attributed to small systematic errors that accumulate over time. Thus, we find that the accuracy of the neural network in the "offline" mode does not reflect its performance when coupled with other components.

scholarly journals Comparison of three vertically resolved ozone data sets: climatology, trends and radiative forcings

2013 ◽  
Vol 13 (11) ◽  
pp. 5533-5550 ◽  
Author(s):  
B. Hassler ◽  
P. J. Young ◽  
R. W. Portmann ◽  
G. E. Bodeker ◽  
J. S. Daniel ◽  
...  
Keyword(s):  
Ozone Depletion ◽  
Radiative Forcing ◽  
Climate Models ◽  
Linear Trend ◽  
Piecewise Linear ◽  
Stratospheric Ozone ◽  
Data Sets ◽  
Heating Rates ◽  
Data Set ◽  
Ozone Concentrations

Abstract. Climate models that do not simulate changes in stratospheric ozone concentrations require the prescription of ozone fields to accurately calculate UV fluxes and stratospheric heating rates. In this study, three different global ozone time series that are available for this purpose are compared: the data set of Randel and Wu (2007) (RW07), Cionni et al. (2011) (SPARC), and Bodeker et al. (2013) (BDBP). All three data sets represent multiple-linear regression fits to vertically resolved ozone observations, resulting in a spatially and temporally continuous stratospheric ozone field covering at least the period from 1979 to 2005. The main differences among the data sets result from regression models, which use different observations and include different basis functions. The data sets are compared against ozonesonde and satellite observations to assess how the data sets represent concentrations, trends and interannual variability. In the Southern Hemisphere polar region, RW07 and SPARC underestimate the ozone depletion in spring ozonesonde measurements. A piecewise linear trend regression is performed to estimate the 1979–1996 ozone decrease globally, covering a period of extreme depletion in most regions. BDBP overestimates Arctic and tropical ozone depletion over this period relative to the available measurements, whereas the depletion is underestimated in RW07 and SPARC. While the three data sets yield ozone concentrations that are within a range of different observations, there is a large spread in their respective ozone trends. One consequence of this is differences of almost a factor of four in the calculated stratospheric ozone radiative forcing between the data sets (RW07: −0.038 Wm−2, SPARC: −0.033 Wm−2, BDBP: −0.119 Wm−2), important in assessing the contribution of stratospheric ozone depletion to the total anthropogenic radiative forcing.

scholarly journals Comparison of three vertically resolved ozone data bases: climatology, trends and radiative forcings

2012 ◽  
Vol 12 (10) ◽  
pp. 26561-26605 ◽  
Author(s):  
B. Hassler ◽  
P. J. Young ◽  
R. W. Portmann ◽  
G. E. Bodeker ◽  
J. S. Daniel ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Linear Trend ◽  
Piecewise Linear ◽  
Stratospheric Ozone ◽  
Data Sets ◽  
Heating Rates ◽  
Data Set ◽  
Radiative Forcings ◽  
Ozone Trends

Abstract. Climate models that do not simulate changes in stratospheric ozone concentrations require ozone input fields to accurately calculate UV fluxes and stratospheric heating rates. In this study, three different global ozone time series that are available for this purpose are compared: the data set of Randel and Wu (2007) (RW07), Cionni et al. (2011) (SPARC), and Bodeker et al. (2012) (BDBP). The latter is a very recent data set, based on the comprehensive ozone measurement database described by Hassler et al. (2008). All three data sets represent multiple-linear regression fits to vertically resolved ozone observations, resulting in a patially and temporally continuous stratospheric ozone field covering at least the period from 1979 to 2005. The main difference between the data sets result from using different observations and including different basis functions for the regression model fits. These three regression-based data sets are compared against observations from ozonesondes and satellites to compare how the data sets represent concentrations, trends, and interannual variability. In the Southern Hemisphere polar region, RW07 and SPARC underestimate the ozone depletion in spring as seen in ozonesonde measurements. A piecewise linear trend regression is performed to estimate the 1979–1996 ozone decrease globally, covering a period of extreme depletion in most regions. BDBP seems to overestimate Arctic and tropical ozone loss over this period somewhat relative to the available measurements, whereas these appear to be underestimated in RW07 and SPARC. In most regions, the three data sets yield ozone values that are within the range of the different observations that serve as input to the regressions. However, the differences among the three suggest that there are large uncertainties in ozone trends. These result in differences of almost a factor of four in radiative forcing, which is important for the resulting climate changes.

scholarly journals Standard climate models radiation codes underestimate black carbon radiative forcing

2015 ◽  
Vol 15 (5) ◽  
pp. 2883-2888 ◽  
Author(s):  
G. Myhre ◽  
B. H. Samset
Keyword(s):  
Radiative Transfer ◽  
Black Carbon ◽  
Radiative Forcing ◽  
Surface Albedo ◽  
Climate Models ◽  
High Surface ◽  
Weak Absorption ◽  
Enhanced Absorption ◽  
Sky Conditions ◽  
Global Mean

Abstract. Radiative forcing (RF) of black carbon (BC) in the atmosphere is estimated using radiative transfer codes of various complexities. Here we show that the two-stream radiative transfer codes used most in climate models give too strong forward scattering, leading to enhanced absorption at the surface and too weak absorption by BC in the atmosphere. Such calculations are found to underestimate the positive RF of BC by 10% for global mean, all sky conditions, relative to the more sophisticated multi-stream models. The underestimation occurs primarily for low surface albedo, even though BC is more efficient for absorption of solar radiation over high surface albedo.

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