scholarly journals Application and evaluation of McICA scheme with new radiation code in BCC_AGCM2.0.1

2013 ◽  
Vol 6 (3) ◽  
pp. 4933-4982 ◽  
Author(s):  
H. Zhang ◽  
X. Jing ◽  
J. Li
Keyword(s):  
Climate Model ◽  
Atmospheric Temperature ◽  
Horizontal Distribution ◽  
Radiative Heating ◽  
Specific Humidity ◽  
Storm Tracks ◽  
Heating Rates ◽  
Radiative Forcings ◽  
Horizontal Inhomogeneity ◽  
The Tropics

Abstract. This research incorporates the Monte Carlo Independent Column Approximation (McICA) scheme with the correlated k-distribution BCC-RAD radiation model into the climate model BCC_AGCM2.0.1 and examines the impacts on modeled climate through several simulations with variations in cloud structures. Results from experiments with consistent sub-grid cloud structures show that both clear-sky radiation fluxes and cloud radiative forcings (CRFs) calculated by the new scheme are mostly improved relative to those calculated from the original one. The modeled atmospheric temperature and specific humidity are also improved due to changes in the radiative heating rates. The vertical overlap of fractional clouds and horizontal distribution of cloud condensation are important for computing CRFs. The maximum changes in seasonal CRF using the general overlap assumption (GenO) with different decorrelation depths (Lcf) are larger than 10 and 20 Wm2 for longwave (LW) CRF and shortwave (SW) CRF, respectively, mostly located in the Tropics and mid-latitude storm tracks. Larger (smaller) Lcf in the Tropics (mid-latitude storm tracks) yield better cloud fraction and CRF compared with observations. The inclusion of an observation-based horizontal inhomogeneity of cloud condensation has a distinct impact on LW CRF and SW CRF, with global means of ∼1.2 Wm−2 and ∼3.7 Wm−2 at the top of atmosphere, respectively, making these much closer to observations. These results prove the reliability of the new model configuration to be used in BCC_AGCM2.0.1 for climate simulations, and also indicate that more detailed real-world information on cloud structures should be obtained to constrain cloud settings in McICA in the future.

scholarly journals Application and evaluation of a new radiation code under McICA scheme in BCC_AGCM2.0.1

2014 ◽  
Vol 7 (3) ◽  
pp. 737-754 ◽  
Author(s):  
H. Zhang ◽  
X. Jing ◽  
J. Li
Keyword(s):  
Climate Model ◽  
Atmospheric Temperature ◽  
Radiative Heating ◽  
Specific Humidity ◽  
Climate Simulation ◽  
Heating Rates ◽  
Radiative Forcings ◽  
Radiation Fluxes ◽  
World Information ◽  
Horizontal Inhomogeneity

Abstract. This research incorporates the correlated k distribution BCC-RAD radiation model into the climate model BCC_AGCM2.0.1 and examines the change in climate simulation by implementation of the new radiation algorithm. It is shown that both clear-sky radiation fluxes and cloud radiative forcings (CRFs) are improved. The modeled atmospheric temperature and specific humidity are also improved due to changes in radiative heating rates, which most likely stem from the revised treatment of gaseous absorption. Subgrid cloud variability, including vertical overlap of fractional clouds and horizontal inhomogeneity in cloud condensate, is addressed by using the Monte Carlo Independent Column Approximation (McICA) method. In McICA, a cloud-type-dependent function for cloud fraction decorrelation length, which gives zonal mean results very close to the observations of CloudSat/CALIPSO, is developed. Compared to utilizing a globally constant decorrelation length, the maximum changes in seasonal CRFs by the new scheme can be as large as 10 and 20 W m−2 for longwave (LW) and shortwave (SW) CRFs, respectively, mostly located in the tropics. The inclusion of an observation-based horizontal inhomogeneity of cloud condensate has also a significant impact on CRFs, with global means of ~ 1.5 W m−2 and ~ 3.7 Wm−2 for LW and SW CRFs at the top of atmosphere (TOA), respectively. Generally, incorporating McICA and horizontal inhomogeneity of cloud condensate in the BCC-RAD model reduces global mean TOA and surface SW and LW flux biases in BCC_AGCM2.0.1. These results demonstrate the feasibility of the new model configuration to be used in BCC_AGCM2.0.1 for climate simulations, and also indicate that more detailed real-world information on cloud structures should be obtained to constrain cloud settings in McICA in the future.

scholarly journals Quantifying uncertainties of climate signals related to the 11–year solar cycle. Part I: Annual mean response in heating rates,temperature and ozone

2020 ◽  
Author(s):  
Markus Kunze ◽  
Tim Kruschke ◽  
Ulrike Langematz ◽  
Miriam Sinnhuber ◽  
Thomas Reddmann ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Climate Model ◽  
Sunspot Cycle ◽  
Spectral Irradiance ◽  
Data Sets ◽  
Heating Rates ◽  
Data Set ◽  
Mixing Ratios ◽  
Solar Signal ◽  
The Tropics

Abstract. Variations of the solar spectral irradiance (SSI) with the 11-year sunspot cycle have been shown to have a significant impact on temperatures and the mixing ratios of atmospheric constituents in the stratosphere and mesosphere. Uncertainties in modelling the effects of SSI variations arise from uncertainties in the empirical models reconstructing the prescribed SSI data set as well as from uncertainties in the chemistry-climate model (CCM) formulation. In this study CCM simulations with the ECHAM MESSy Atmospheric Chemistry (EMAC) model and the Community Earth System Model 1 (CESM1) – Whole Atmosphere Chemistry Climate Model (WACCM) have been performed to quantify the uncertainties of the solar responses in chemistry and dynamics that are due to the usage of five different SSI data sets or the two CCMs. We apply a two-way analysis of variance (ANOVA) to separate the influence of the SSI data sets and the CCMs on the variability of the solar response in shortwave heating rates, temperature and ozone. The ANOVA identifies the SSI data set with the strongest influence on the variability of the solar signal in shortwave heating rates in the upper mesosphere and in the upper stratosphere/lower mesosphere. The strongest influence on the variability of the solar signal in ozone and temperature is identified in the upper stratosphere/lower mesosphere. The largest influence of the CCMs on variability of the solar responses can be identified in the upper mesosphere. The solar response in the lower stratosphere also depends on the CCM used, especially in the tropics and northern hemispheric subtropics and mid latitudes, where the model dynamics modulate the solar responses.

scholarly journals On the Approximation of Local and Linear Radiative Damping in the Middle Atmosphere

2010 ◽  
Vol 67 (6) ◽  
pp. 2070-2085 ◽  
Author(s):  
Peter Hitchcock ◽  
Theodore G. Shepherd ◽  
Shigeo Yoden
Keyword(s):  
Climate Model ◽  
Middle Atmosphere ◽  
Mechanistic Modeling ◽  
Radiative Heating ◽  
Spatiotemporal Variability ◽  
Quadratic Term ◽  
Heating Rates ◽  
Temperature State ◽  
Large Fluctuations ◽  
Damping Rate

Abstract The validity of approximating radiative heating rates in the middle atmosphere by a local linear relaxation to a reference temperature state (i.e., “Newtonian cooling”) is investigated. Using radiative heating rate and temperature output from a chemistry–climate model with realistic spatiotemporal variability and realistic chemical and radiative parameterizations, it is found that a linear regression model can capture more than 80% of the variance in longwave heating rates throughout most of the stratosphere and mesosphere, provided that the damping rate is allowed to vary with height, latitude, and season. The linear model describes departures from the climatological mean, not from radiative equilibrium. Photochemical damping rates in the upper stratosphere are similarly diagnosed. Three important exceptions, however, are found. The approximation of linearity breaks down near the edges of the polar vortices in both hemispheres. This nonlinearity can be well captured by including a quadratic term. The use of a scale-independent damping rate is not well justified in the lower tropical stratosphere because of the presence of a broad spectrum of vertical scales. The local assumption fails entirely during the breakup of the Antarctic vortex, where large fluctuations in temperature near the top of the vortex influence longwave heating rates within the quiescent region below. These results are relevant for mechanistic modeling studies of the middle atmosphere, particularly those investigating the final Antarctic warming.

scholarly journals Precipitation Budget of the Madden–Julian Oscillation

2017 ◽  
Vol 74 (6) ◽  
pp. 1799-1817 ◽  
Author(s):  
Ángel F. Adames
Keyword(s):  
Low Frequency ◽  
Horizontal Distribution ◽  
Precipitation Anomaly ◽  
Radiative Heating ◽  
Spatially Correlated ◽  
Moisture Advection ◽  
Precipitation Anomalies ◽  
Static Energy ◽  
The Tropics ◽  
Spatially Varying

Abstract Column moisture and moist static energy (MSE) budgets have become common tools in the study of the processes responsible for the maintenance and evolution of the MJO. While many studies have shown that precipitation is spatially correlated with column moisture, these budgets do not directly describe the MJO-related precipitation anomalies. Other spatially varying fields may also play a role in determining the horizontal distribution of anomalous precipitation. In this study, an empirical precipitation anomaly field is derived that depends on three variables in addition to column moisture. These are the low-frequency distribution of precipitation, the low-frequency column saturation water vapor, and the sensitivity of precipitation to changes in column relative humidity. The addition of these fields improves upon moisture/MSE budgets by confining these anomalies to the climatologically rainy areas of the tropics, where MJO activity is strongest. The derived field adequately describes the MJO-related precipitation anomalies, comparing favorably with TRMM precipitation data. Furthermore, a “precipitation budget” is presented that emphasizes moist processes over the regions where precipitation is most sensitive to free-tropospheric moisture. It is found that moistening from vertical moisture advection in association with regions of shallow ascent plays a central role in the propagation of the MJO. The overall contribution from this process is comparable to the contribution from horizontal moisture advection to propagation. Consistent with previous studies, it is found that vertical advection arising from longwave radiative heating maintains the intraseasonal precipitation anomalies against drying by horizontal moisture advection.

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 Contrasting Impacts of Radiative Forcing in the Southern Ocean versus Southern Tropics on ITCZ Position and Energy Transport in One GFDL Climate Model

2018 ◽  
Vol 31 (14) ◽  
pp. 5609-5628 ◽  
Author(s):  
Baoqiang Xiang ◽  
Ming Zhao ◽  
Yi Ming ◽  
Weidong Yu ◽  
Sarah M. Kang
Keyword(s):  
Southern Ocean ◽  
Ocean Circulation ◽  
Radiative Forcing ◽  
Climate Models ◽  
Energy Transport ◽  
Climate Model ◽  
Radiative Heating ◽  
Ocean Heat Uptake ◽  
Budget Analysis ◽  
The Tropics

Abstract Most current climate models suffer from pronounced cloud and radiation biases in the Southern Ocean (SO) and in the tropics. Using one GFDL climate model, this study investigates the migration of the intertropical convergence zone (ITCZ) with prescribed top-of-the-atmosphere (TOA) shortwave radiative heating in the SO (50°–80°S) versus the southern tropics (ST; 0°–20°S). Results demonstrate that the ITCZ position response to the ST forcing is twice as strong as the SO forcing, which is primarily driven by the contrasting sea surface temperature (SST) gradient over the tropics; however, the mechanism for the formation of the SST pattern remains elusive. Energy budget analysis reveals that the conventional energetic constraint framework is inadequate in explaining the ITCZ shift in these two perturbed experiments. For both cases, the anomalous Hadley circulation does not contribute to transport the imposed energy from the Southern Hemisphere to the Northern Hemisphere, given a positive mean gross moist stability in the equatorial region. Changes in the cross-equatorial atmospheric energy are primarily transported by atmospheric transient eddies when the anomalous ITCZ shift is most pronounced during December–May. The partitioning of energy transport between the atmosphere and ocean shows latitudinal dependence: the atmosphere and ocean play an overall equivalent role in transporting the imposed energy for the extratropical SO forcing, while for the ST forcing, the imposed energy is nearly completely transported by the atmosphere. This contrast originates from the different ocean heat uptake and also the different meridional scale of the anomalous ocean circulation.

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 Separating the role of direct radiative heating and photolysis in modulating the atmospheric response to the 11-year solar cycle forcing

2018 ◽  
Author(s):  
Ewa M. Bednarz ◽  
Amanda C. Maycock ◽  
Peter Braesicke ◽  
Paul J. Telford ◽  
N. Luke Abraham ◽  
...  
Keyword(s):  
Solar Cycle ◽  
Climate Model ◽  
Heating Temperature ◽  
Radiative Heating ◽  
Dynamical Response ◽  
Atmospheric Response ◽  
Active Season ◽  
Photolysis Rates ◽  
Induced Changes ◽  
The Tropics

Abstract. The atmospheric response to the 11-year solar cycle forcing is separated into the contributions from changes in direct radiative heating and photolysis rates using specially designed sensitivity simulations with the UM-UKCA chemistry-climate model. We find that contributions from changes in direct heating and photolysis rates are important for determining the shortwave heating, temperature and ozone responses to the solar cycle forcing. The combined effects of the processes are found to be largely additive in the tropics but non-additive in the high latitudes, in particular in the Southern Hemisphere (SH) during the dynamically active season. We find marked differences in the changes in magnitude and vertical structure of shortwave heating rates gradients across the SH in austral winter, thereby highlighting a potential sensitivity of the polar dynamical response to the altitude of the anomalous radiative tendencies. In addition, our results indicate that, in contrast to the original mechanism proposed in the literature, the solar-induced changes in the horizontal shortwave heating rate gradients not only in autumn/early winter, but throughout the dynamically active season are important for modulating the dynamical response. In spring, these gradients are strongly influenced by the shortwave heating anomalies at higher southern latitudes, which are closely linked to the concurrent changes in ozone. Our results suggest that solar-induced changes in ozone, both in the tropics/mid-latitudes and the polar regions, are important for modulating the SH dynamical response to the 11-year solar cycle. In addition, the markedly non-additive character of the SH polar vortex response simulated in austral spring highlights the need for consistent model implementation of the solar cycle forcing in both the radiative heating and photolysis schemes.

Effect of Volcanic Eruptions on the Vertical Temperature Profile in Radiosonde Data and Climate Models

2009 ◽  
Vol 22 (11) ◽  
pp. 2925-2939 ◽  
Author(s):  
Melissa Free ◽  
John Lanzante
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Volcanic Eruptions ◽  
Atmospheric Temperature ◽  
Radiosonde Data ◽  
Stratospheric Warming ◽  
Vertical Temperature Profile ◽  
Mount Pinatubo ◽  
Hadley Centre ◽  
The Tropics

Abstract Both observed and modeled upper-air temperature profiles show the tropospheric cooling and tropical stratospheric warming effects from the three major volcanic eruptions since 1960. Detailed comparisons of vertical profiles of Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC) and Hadley Centre Atmospheric Temperatures, version 2 (HadAT2), radiosonde temperatures with output from six coupled GCMs show good overall agreement on the responses to the 1991 Mount Pinatubo and 1982 El Chichón eruptions in the troposphere and stratosphere, with a tendency of the models to underestimate the upper-tropospheric cooling and overestimate the stratospheric warming relative to observations. The cooling effect at the surface in the tropics is amplified with altitude in the troposphere in both observations and models, but this amplification is greater for the observations than for the models. Models and observations show a large disagreement around 100 mb for Mount Pinatubo in the tropics, where observations show essentially no change, while models show significant warming of ∼0.7 to ∼2.6 K. This difference occurs even in models that accurately simulate stratospheric warming at 50 mb. Overall, the Parallel Climate Model is an outlier in that it simulates more volcanic-induced stratospheric warming than both the other models and the observations in most cases. From 1979 to 1999 in the tropics, RATPAC shows a trend of less than 0.1 K decade−1 at and above 300 mb before volcanic effects are removed, while the mean of the models used here has a trend of more than 0.3 K decade−1, giving a difference of ∼0.2 K decade−1. At 300 mb, from 0.02 to 0.10 K decade−1 of this difference may be due to the influence of volcanic eruptions, with the smaller estimate appearing more likely than the larger. No more than ∼0.03 K of the ∼0.1-K difference in trends between the surface and troposphere at 700 mb or below in the radiosonde data appears to be due to volcanic effects.

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

2020 ◽  
Vol 13 (9) ◽  
pp. 4399-4412 ◽  
Author(s):  
Ying Liu ◽  
Rodrigo Caballero ◽  
Joy Merwin Monteiro
Keyword(s):  
Neural Network ◽  
Radiative Transfer ◽  
Climate Model ◽  
Mean Squared Error ◽  
Network Models ◽  
Radiative Heating ◽  
Human Populations ◽  
Heating Rates ◽  
Neural Network Models ◽  
The Neural Network

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 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 conventional 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 370× speedup on a GTX 1080 GPU setup and 11× 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 K d−1 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 is 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 network, 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.

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