scholarly journals The Vertical Structure of Radiative Heating Rates: A Multimodel Evaluation Using A-Train Satellite Observations

2019 ◽  
Vol 32 (5) ◽  
pp. 1573-1590 ◽  
Author(s):  
G. Cesana ◽  
D. E. Waliser ◽  
D. Henderson ◽  
T. S. L’Ecuyer ◽  
X. Jiang ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Climate Models ◽  
Lower Troposphere ◽  
Cloud Amount ◽  
Global Scale ◽  
Satellite Observations ◽  
Radiative Heating ◽  
Infrared Heating ◽  
Heating Rates ◽  
Uncertainty Estimates

Abstract We assess the vertical distribution of radiative heating rates (RHRs) in climate models using a multimodel experiment and A-Train satellite observations, for the first time. As RHRs rely on the representation of cloud amount and properties, we first compare the modeled vertical distribution of clouds directly against lidar–radar combined cloud observations (i.e., without simulators). On a near-global scale (50°S–50°N), two systematic differences arise: an excess of high-level clouds around 200 hPa in the tropics, and a general lack of mid- and low-level clouds compared to the observations. Then, using RHR profiles calculated with constraints from A-Train and reanalysis data, along with their associated maximum uncertainty estimates, we show that the excess clouds and ice water content in the upper troposphere result in excess infrared heating in the vicinity of and below the clouds as well as a lack of solar heating below the clouds. In the lower troposphere, the smaller cloud amount and the underestimation of cloud-top height is coincident with a shift of the infrared cooling to lower levels, substantially reducing the greenhouse effect, which is slightly compensated by an erroneous excess absorption of solar radiation. Clear-sky RHR differences between the observations and the models mitigate cloudy RHR biases in the low levels while they enhance them in the high levels. Finally, our results indicate that a better agreement between observed and modeled cloud profiles could substantially improve the RHR profiles. However, more work is needed to precisely quantify modeled cloud errors and their subsequent effect on RHRs.

scholarly journals A Synergistic Analysis of Cloud Cover and Vertical Distribution from A-Train and Ground-Based Sensors over the High Arctic Station Eureka from 2006 to 2010

2014 ◽  
Vol 53 (11) ◽  
pp. 2553-2570 ◽  
Author(s):  
Yann Blanchard ◽  
Jacques Pelon ◽  
Edwin W. Eloranta ◽  
Kenneth P. Moran ◽  
Julien Delanoë ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Lower Troposphere ◽  
High Arctic ◽  
Satellite Observations ◽  
The Arctic ◽  
Cloud Detection ◽  
Hit Rate ◽  
Sensitivity Loss ◽  
Independent Observations ◽  
Arctic Area

AbstractActive remote sensing instruments such as lidar and radar allow one to accurately detect the presence of clouds and give information on their vertical structure and phase. To better address cloud radiative impact over the Arctic area, a combined analysis based on lidar and radar ground-based and A-Train satellite measurements was carried out to evaluate the efficiency of cloud detection, as well as cloud type and vertical distribution, over the Eureka station (80°N, 86°W) between June 2006 and May 2010. Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat data were first compared with independent ground-based cloud measurements. Seasonal and monthly trends from independent observations were found to be similar among all datasets except when compared with the weather station observations because of the large reported fraction of ice crystals suspended in the lower troposphere in winter. Further investigations focused on satellite observations that are collocated in space and time with ground-based data. Cloud fraction occurrences from ground-based instruments correlated well with both CALIPSO operational products and combined CALIPSO–CloudSat retrievals, with a hit rate of 85%. The hit rate was only 77% for CloudSat products. The misdetections were mainly attributed to 1) undetected low-level clouds as a result of sensitivity loss and 2) missed clouds because of the distance between the satellite track and the station. The spaceborne lidar–radar synergy was found to be essential to have a complete picture of the cloud vertical profile down to 2 km. Errors are quantified and discussed.

scholarly journals Satellite Observations for CMIP5: The Genesis of Obs4MIPs

2014 ◽  
Vol 95 (9) ◽  
pp. 1329-1334 ◽  
Author(s):  
Joao Teixeira ◽  
Duane Waliser ◽  
Robert Ferraro ◽  
Peter Gleckler ◽  
Tsengdar Lee ◽  
...  
Keyword(s):  
Observational Data ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Climate Science ◽  
Satellite Observations ◽  
Model Intercomparison ◽  
Uncertainty Estimates ◽  
Science Community ◽  
Climate Model Simulations

The objective of the Observations for Model Intercomparison Projects (Obs4MIPs) is to provide observational data to the climate science community, which is analogous (in terms of variables, temporal and spatial frequency, and periods) to output from the 5th phase of the World Climate Research Programme's (WCRP) Coupled Model Intercomparison Project (CMIP5) climate model simulations. The essential aspect of the Obs4MIPs methodology is that it strictly follows the CMIP5 protocol document when selecting the observational datasets. Obs4MIPs also provides documentation that describes aspects of the observational data (e.g., data origin, instrument overview, uncertainty estimates) that are of particular relevance to scientists involved in climate model evaluation and analysis. In this paper, we focus on the activities related to the initial set of satellite observations, which are being carried out in close coordination with CMIP5 and directly engage NASA's observational (e.g., mission and instrument) science teams. Having launched Obs4MIPs with these datasets, a broader effort is also briefly discussed, striving to engage other agencies and experts who maintain datasets, including reanalysis, which can be directly used to evaluate climate models. Different strategies for using satellite observations to evaluate climate models are also briefly summarized.

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 Direct and semi-direct radiative forcing of biomass-burning aerosols over the southeast Atlantic (SEA) and its sensitivity to absorbing properties: a regional climate modeling study

2020 ◽  
Vol 20 (21) ◽  
pp. 13191-13216
Author(s):  
Marc Mallet ◽  
Fabien Solmon ◽  
Pierre Nabat ◽  
Nellie Elguindi ◽  
Fabien Waquet ◽  
...  
Keyword(s):  
Air Temperature ◽  
Biomass Burning ◽  
Radiative Forcing ◽  
Climate Models ◽  
Regional Climate ◽  
Lower Troposphere ◽  
Regional Climate Models ◽  
Temperature Limit ◽  
Radiative Heating ◽  
Radiative Effects

Abstract. Simulations are performed for the period 2000–2015 by two different regional climate models, ALADIN and RegCM, to quantify the direct and semi-direct radiative effects of biomass-burning aerosols (BBAs) in the southeast Atlantic (SEA) region. Different simulations have been performed using strongly absorbing BBAs in accordance with recent in situ observations over the SEA. For the July–August–September (JAS) season, the single scattering albedo (SSA) and total aerosol optical depth (AOD) simulated by the ALADIN and RegCM models are consistent with the MACv2 climatology and MERRA-2 and CAMS-RA reanalyses near the biomass-burning emission sources. However, the above-cloud AOD is slightly underestimated compared to satellite (MODIS and POLDER) data during the transport over the SEA. The direct radiative effect exerted at the continental and oceanic surfaces by BBAs is significant in both models and the radiative effects at the top of the atmosphere indicate a remarkable regional contrast over SEA (in all-sky conditions), with a cooling (warming) north (south) of 10 ∘S, which is in agreement with the recent MACv2 climatology. In addition, the two models indicate that BBAs are responsible for an important shortwave radiative heating of ∼0.5–1 K per day over SEA during JAS with maxima between 2 and 4 km a.m.s.l. (above mean sea level). At these altitudes, BBAs increase air temperature by ∼0.2–0.5 K, with the highest values being co-located with low stratocumulus clouds. Vertical changes in air temperature limit the subsidence of air mass over SEA, creating a cyclonic anomaly. The opposite effect is simulated over the continent due to the increase in lower troposphere stability. The BBA semi-direct effect on the lower troposphere circulation is found to be consistent between the two models. Changes in the cloud fraction are moderate in response to the presence of smoke, and the models differ over the Gulf of Guinea. Finally, the results indicate an important sensitivity of the direct and semi-direct effects to the absorbing properties of BBAs. Over the stratocumulus (Sc) region, DRE varies from +0.94 W m−2 (scattering BBAs) to +3.93 W m−2 (most absorbing BBAs).

scholarly journals Major Characteristics of Southern Ocean Cloud Regimes and Their Effects on the Energy Budget

2011 ◽  
Vol 24 (19) ◽  
pp. 5061-5080 ◽  
Author(s):  
John M. Haynes ◽  
Christian Jakob ◽  
William B. Rossow ◽  
George Tselioudis ◽  
Josephine Brown
Keyword(s):  
Southern Ocean ◽  
Large Scale ◽  
Climate Models ◽  
Satellite Observation ◽  
Radiative Heating ◽  
Radiation Balance ◽  
Heating Rates ◽  
Cloud Systems ◽  
Low Cloud ◽  
Cloud Regimes

Clouds over the Southern Ocean are often poorly represented by climate models, but they make a significant contribution to the top-of-atmosphere (TOA) radiation balance, particularly in the shortwave portion of the energy spectrum. This study seeks to better quantify the organization and structure of Southern Hemisphere midlatitude clouds by combining measurements from active and passive satellite-based datasets. Geostationary and polar-orbiter satellite data from the International Satellite Cloud Climatology Project (ISCCP) are used to quantify large-scale, recurring modes of cloudiness, and active observations from CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are used to examine vertical structure, radiative heating rates, and precipitation associated with these clouds. It is found that cloud systems are organized into eight distinct regimes and that ISCCP overestimates the midlevel cloudiness of these regimes. All regimes contain a relatively high occurrence of low cloud, with 79% of all cloud layers observed having tops below 3 km, but multiple-layered clouds systems are present in approximately 34% of observed cloud profiles. The spatial distribution of regimes varies according to season, with cloud systems being geometrically thicker, on average, during the austral winter. Those regimes found to be most closely associated with midlatitude cyclones produce precipitation the most frequently, although drizzle is extremely common in low-cloud regimes. The regimes associated with cyclones have the highest in-regime shortwave cloud radiative effect at the TOA, but the low-cloud regimes, by virtue of their high frequency of occurrence over the oceans, dominate both TOA and surface shortwave effects in this region as a whole.

Impact of clouds on atmospheric heating rate profiles at Ny-Ålesund, Svalbard

2020 ◽  
Author(s):  
Kerstin Ebell ◽  
Tatiana Nomokonova ◽  
Marion Maturilli ◽  
Christoph Ritter
Keyword(s):  
Vertical Distribution ◽  
Heating Rate ◽  
Radiative Heating ◽  
The Arctic ◽  
Research Station ◽  
Frequency Of Occurrence ◽  
Radiative Effect ◽  
Heating Rates ◽  
Data Set ◽  
German Research

<p>Clouds strongly impact the available energy at the surface and at the top of the atmosphere as well as its vertical distribution within the atmosphere by modifying the shortwave (SW) and longwave (LW) fluxes and heating rates. The so-called cloud radiative effect (CRE) and the cloud radiative forcing (CRF), i.e. the difference between the all-sky and clear-sky fluxes and heating rates, respectively, strongly depend on the cloud macrophysical (e.g. frequency of occurrence, cloud vertical distribution) and microphysical (e.g. phase, water content, hydrometeor size distribution) properties.</p><p>In the Arctic, the cloud–radiative interactions are even more complex due to low temperatures, frequently occurring temperature inversions, the dryness of the atmosphere, large solar zenith angles and a high surface albedo. In particular (supercooled) liquid containing clouds, which frequently occur in the Arctic and often have very low amounts of liquid water, exhibit a strong impact on the radiative fluxes.</p><p>Recently, Ebell et al. (2020) have analysed for the first time the radiative effect of clouds for the Arctic site Ny-Ålesund exploiting more than 2 years (06/2016 -10/2018) of continuous vertical cloud measurements at the French-German research station AWIPEV. They showed that at Ny-Ålesund, the monthly net surface CRE is positive from September to April/May and negative in summer. The annual surface warming effect by clouds is 11.1 W m<sup>-2</sup>.</p><p>Based on the same data set, we will now investigate in more detail how clouds modify the LW and SW heating rates in the atmospheric profile. First results show that the net CRF is dominated by the LW CRF with warming taking place in principal below the height of the maximum frequency of occurrence of liquid around 1 km, and cooling above. The strength of this cooling and warming is closely related to the amount of liquid. We will also analyze heating rates for different cloud types similar to the study by Turner et al. (2017) who found characteristic heating rate profiles for the Arctic site Barrow. In this way, we will gain insight into the representastiveness of these heating rate profiles throughout the Arctic.</p><p><em>We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 268020496 – TRR 172,  within the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes,   and    Feedback Mechanisms (AC)³”.</em></p><p><strong>References</strong></p><p>Ebell, K., T. Nomokonova, M. Maturilli, and C. Ritter, 2020: Radiative Effect of Clouds at Ny-Ålesund, Svalbard, as Inferred from Ground-Based Remote Sensing Observations. J. Appl. Meteor. Climatol., <strong>59</strong>, 3–22, https://doi.org/10.1175/JAMC-D-19-0080.1</p><p>Turner, D.D., M.D. Shupe, and A.B. Zwink, 2018: Characteristic Atmospheric Radiative Heating Rate Profiles in Arctic Clouds as Observed at Barrow, Alaska. J. Appl. Meteor. Climatol., <strong>57</strong>, 953–968, https://doi.org/10.1175/JAMC-D-17-0252.1</p>

Nuclear Safety Analysis for Cassini Accidental Earth Reentries

1999 ◽  
Author(s):  
Richard L. Baker ◽  
Duane A. Nelson
Keyword(s):  
Nuclear Fuel ◽  
Radiative Heating ◽  
Sensitivity Analyses ◽  
Analysis Model ◽  
Heating Rates ◽  
Gravity Assist ◽  
Earth Gravity ◽  
The Earth ◽  
Uncertainty Estimates ◽  
Major Factors

Abstract An engineering analysis model for predicting the response and potential breakup of Cassini spacecraft nuclear fuel modules during accidental Earth reentries is described. Physical aspects considered include aerodynamics, aerothermodynamics, thermostructural loads and ablation response. The extreme velocity, 19 km/sec, of an inadvertent reentry during the Earth gravity-assist flyby requires the development of a new model to predict the dominant radiative heating rates. Uncertainty estimates are established for each of the major factors in the model. Sensitivity analyses are also carried out to determine the effect of off-nominal environments on the predicted outcome. This allows output from the calculations to be expressed as a probability density function for atmospheric fuel release. It is concluded that 18 to 36 percent of the nuclear fuel contained in the spacecraft will be released as respirable material if reentry occurs.

scholarly journals Direct and semi-direct radiative forcing of biomass burning aerosols over the Southeast Atlantic (SEA) and its sensitivity to absorbing properties: a regional climate modeling study

2020 ◽  
Author(s):  
Marc Mallet ◽  
Fabien Solmon ◽  
Pierre Nabat ◽  
Nellie Elguindi ◽  
Fabien Waquet ◽  
...  
Keyword(s):  
Air Temperature ◽  
Biomass Burning ◽  
Radiative Forcing ◽  
Climate Models ◽  
Regional Climate ◽  
Lower Troposphere ◽  
Regional Climate Models ◽  
Temperature Limit ◽  
Radiative Heating ◽  
Radiative Effects

Abstract. Simulations are performed for the period 2000–2015 by two different regional climate models, ALADIN–Climat and RegCM, to quantify the direct and semi-direct radiative effects of biomass burning aerosols (BBA) in the Southeast Atlantic (SEA) region. The approach of using two different independent RCMs reinforces the robustness of the results. Different simulations have been performed using strongly absorbing BBA in accordance with recent in situ observations over the SEA. For the July–August–September (JAS) season, the single scattering albedo (SSA) and total aerosol optical depth (AOD) simulated by the ALADIN–Climat and RegCM models are consistent with the MACv2 climatology and MERRA-2 and CAMS-RA reanalyses near the biomass burning emission sources. However, the above-cloud AOD is slightly underestimated compared to satellite (MODIS and POLDER) data during the transport over the SEA. The direct radiative effect exerted at the continental and oceanic surfaces by BBA is significant in both models and the radiative effects at the top of the atmosphere indicate a remarkable regional contrast over SEA (in all-sky conditions), with a cooling (warming) north (south) of 10° S, which is in agreement with the recent MACv2 climatology. In addition, the two models indicate that BBA are responsible for an important shortwave radiative heating of ~ 0.5–1 K per day over SEA during JAS with maxima between 2 and 4 km above mean sea-level. At these altitudes, BBA increase air temperature by ~ 0.2–0.5 K, with the highest values being co-located with low stratocumulus clouds. Vertical changes in air temperature limit the subsidence over SEA creating a cyclonic anomaly. The opposite effect is simulated over the continent due to the increase in lower troposphere stability. The BBA semi-direct effect on the lower troposphere circulation is found to be consistent between the two models. Changes in the cloud fraction are moderate in response to the presence of smoke and the models differ over the Gulf of Guinea. Finally, the results indicate an important sensitivity of the direct and semi-direct effects to the absorbing properties of BBA.

scholarly journals Equatorial transport as diagnosed from nitrous oxide variability

2009 ◽  
Vol 9 (1) ◽  
pp. 4899-4930 ◽  
Author(s):  
P. Ricaud ◽  
J.-P. Pommereau ◽  
J.-L. Attié ◽  
E. Le Flochmoën ◽  
L. El Amraoui ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Annual Cycle ◽  
Scale Up ◽  
Three Dimensional ◽  
Global Scale ◽  
Radiative Heating ◽  
Heating Rates ◽  
Transport Models ◽  
Weather Forecasts ◽  
Medium Range

Abstract. The mechanisms of transport on annual, semi-annual and quasi-biennial time scales in the equatorial (10° S–10° N) stratosphere are investigated using the nitrous oxide (N2O) measurements of the space-borne ODIN Sub-Millimetre Radiometer instrument from November 2001 to June 2005, and the simulations of the three-dimensional Chemistry Transport Models MOCAGE and SLIMCAT. Both models are forced with analyses from the European Centre for Medium-range Weather Forecasts, but the vertical transport is derived either from the forcing analyses by solving the continuity equation (MOCAGE), or from diabatic heating rates using a radiation scheme (SLIMCAT). The N2O variations in the mid-to-upper stratosphere at levels above 32 hPa are shown to be generally captured by the models though significant differences appear with the observations as well as between the models, attributed to the difficulty of capturing correctly the slow vertical velocities of the Brewer-Dobson circulation. In the lower stratosphere (LS), below 32 hPa, the variations are shown to be principally seasonal with peak amplitude at 400 K (~19 km), and are totally missed by the models. The decrease in diabatic radiative heating in the LS during the Northern Hemisphere summer is found to be out of phase by one month and far too small to explain the observed N2O seasonal cycle. The proposed explanation for this annual variation is a combination of i) the annual cycle of tropopause height of 1 km amplitude, ii) the convective overshooting above 400 K peaking in May and absent in the models, and iii) an annual cycle of 15 ppbv amplitude of the N2O concentration at the tropopause, but for which no confirmation exists in the upper troposphere in the absence of global-scale measurements. The present study indicates i) a significant contribution of deep convective overshooting on the chemical composition of the LS at global scale up to 500 K, ii) a preferred region for that over the African continent, and iii) a maximum impact in May when the overshoot intensity is the largest and horizontal winds are the slowest.

scholarly journals The Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD)

2019 ◽  
Author(s):  
Grégory Cesana ◽  
Anthony D. Del Genio ◽  
Hélène Chepfer
Keyword(s):  
Climate Models ◽  
Global Scale ◽  
Original Method ◽  
Cloud Feedback ◽  
Satellite Observations ◽  
Geometrical Shape ◽  
Spatial Distributions ◽  
Shallow Convection ◽  
Cloud Feedbacks ◽  
Cloud Height

Abstract. Low clouds continue to contribute greatly to the uncertainty in cloud feedback estimates. Depending on whether a region is dominated by cumulus (Cu) or stratocumulus (Sc) clouds, the interannual low-cloud feedback is somewhat different in both space-borne and large eddy simulation studies. Therefore, simulating the correct amount and variation of the Cu and Sc cloud distributions could be crucial to predict future cloud feedbacks. Here we document spatial distributions and profiles of Sc and Cu clouds derived from Cloud-Aerosols Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat measurements. For this purpose, we create a new dataset called the Cumulus And Stratocumulus CloudSat-CAlipso Dataset (CASCCAD). To separate the Cu from Sc, we design an original method based on the cloud height, horizontal extent and vertical variability, which is applied to both CALIPSO and combined CloudSat-CALIPSO observations. First, the choice of parameters used in the discrimination algorithm is investigated and validated in selected Cu, Sc and and Sc-Cu transition case studies. Then, the global statistics are compared against those from existing passive and active-sensor satellite observations. Our results indicate that the cloud optical thickness –as used in passive-sensor observations– is not a sufficient parameter to discriminate Cu from Sc clouds, in agreement with previous literature. On the contrary, classifying Cu and Sc clouds based on their geometrical shape leads to spatial distributions consistent with prior knowledge of these clouds, from ground-based, shipbased and field campaigns. Furthermore, we show that our method improves existing Sc-Cu classification by using additional information on cloud height and vertical cloud fraction variation. Finally, the CASCCAD datasets provide a basis to evaluate shallow convection (Cu) and boundary layer (Sc) clouds on a global scale in climate models and potentially improve our understanding of low-level cloud feedbacks. The CASCCAD dataset (Cesana, 2019, DOI:https://doi.org/10.5281/zenodo.2667637) is available on the Goddard Institute for Space Studies (GISS) website at https://data.giss.nasa.gov/clouds/casccad/ and on zenodo website at https://zenodo.org/record/2667637 .

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