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At least 199 records · Page 11

Improvement of Radiative Fluxes for the CERES FluxByCldTyp Data Product Based on Machine Learning Technique

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere and surface flux data for climate studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models. The FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate their broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Preliminary results show significant LW improvement.

Sun, Moguo↗

Nonlocal, Pattern-Aware Response and Feedback Framework for Regional Climate Response

We devise a pattern-aware feedback framework for representing the forced climate response using a suite of Green’s function experiments with solar radiation perturbations. By considering the column energy balance, a comprehensive linear response function (CLRF) for important climate variables and feedback quantities such as moist static energy, sea surface temperature, albedo, cloud optical depth, and lapse rate is learned from Green’s function data. The learned CLRF delineates the effects of the energy diffusion in both the ocean and atmosphere and the pattern-aware feedbacks from the aforementioned radiatively active processes. The CLRF can then be decomposed into forcing–response mode pairs, which are in turn used to construct a reduced-order model describing the dominant dynamics of climate responses. These mode pairs capture nonlocal effects and teleconnections in the climate and thus make the reduced-order model apt for capturing regional features of climate response. A key observation is that the CLRF captures the polar-amplified response as the most excitable mode of the climate system, and this mode is explainable in the data-learned pattern-aware feedback framework. The reduced-order model can be used for predicting the response for a given forcing and for reconstructing the forcing from a given response; we demonstrate these capabilities for multiple independent forcing scenarios.

Feedback↗

Observational Constraint on Cloud Feedbacks Suggests Moderate Climate Sensitivity

Global climate models (GCMs) predict warming in response to increasing greenhouse gases, partly due to decreased tropical low-level cloud cover and reflectance. We use satellite observations that discriminate stratocumulus (Sc) from shallow cumulus (Cu) clouds to separately evaluate their sensitivity to warming and constrain the tropical contribution to low-cloud feedback. We find an observationally inferred low-level feedback two times smaller than a previous estimate. Cu are insensitive to warming whereas GCMs exhibit a large positive cloud feedback in Cu regions. In contrast, Sc show sensitivity to warming and the tropical inversion layer strength, controlled by the tropical Pacific SST gradient. Models fail to reproduce the historical SST gradient trends and therefore changes in inversion strength, generating an overestimate of the positive Sc cloud feedback. Continued weak east-Pacific warming would therefore produce a weaker low-cloud feedback and imply a more moderate climate sensitivity (3.47  0.33 K) than many models predict.

Cloud feedback↗

Feedback Processes and Climate Response

The response of the climate system to an external perturbation--e.g., a change in solar irradiance or a change in atmospheric opacity due to an increase in CO2--depends rather strongly on feedback processes in the system, which either amplify or dampen the effects of the initial perturbation. A simple representation of the climate system is used to compare several important feedbacks, based upon general circulation model (GCM) simulations by various investigators. The models are in general agreement with respect to water vapor feedback, but in wide disagreement with respect to cloud feedback. Because of the arguments raised by Lindzen (1990)--that the processes which determine water vapor mixing ratio in the upper atmosphere are quite different from those which operate in the planetary boundary layer, and that upper tropospheric water vapor might actually decrease even when the boundary layer is getting warmer and more moist--researchers undertook a study to determine the sensitivity of climate to changes in water vapor at various levels in the troposphere. The result is that climate is just as sensitive to percentage changes in upper tropospheric water vapor, where the mixing ratio is very small, as it is to percentage changes in the boundary layer, which contains the bulk of total column water vapor.

Arking, Albert↗

The Role of Deep Convection and Large-scale Circulation in Driving Model Spread in Low Cloud Feedback and Equilibrium Climate Sensitivity

This project aims to advance the understanding of the processes that drive the large uncertainties in climate change projections, use observations to constrain model physics and reduce the inter-model spread in equilibrium climate sensitivity (ECS). There are three major goals: 1) Characterize the representation of the physical pathways that link deep convection, large-scale circulation and low cloud feedback in CMIP6 model simulations and determine the relative contribution of each pathway to the CMIP6 model spread in low cloud feedback and ECS; 2) Use process-oriented diagnostics and multiple observations to evaluate CMIP6 model performance in capturing the observed cloud-circulation relation and deep convection characteristics including convective transition statistics and the bulk properties of mesoscale convective systems (MCSs). Error decomposition in CMIP6 models will be performed. 3) Conduct E3SM short-range hindcasts following the DOE Cloud-Associated Parameterizations Testbed (CAPT) protocol to pinpoint specific model parameters/processes that are crucial to the representation of deep convection, circulation, clouds and the pathways that connect them. We will modify convective parameters in E3SM and analyze the perturbed physics experiments (PPEs) to isolate model parameters that are critical to the uncertainty of ECS.

54 ENVIRONMENTAL SCIENCES↗

On the dynamic forcing of short-term climate fluctuations by feedback mechanisms

Various internal feedback mechanisms in the ocean atmosphere system were studied. A variability pattern of sea surface temperature with a quasibiennial oscillation (QBO) was detected off the coast of Senegal, in the Gulf of Guinea and even in the Gulf Stream as it leaves the North American continental shelf. Possible physical connections between some of these QBO's were pointed out by a hypothetical feedback model. Interaction of a QBO with the annual cycle may lead to beating frequencies resembling climatic trends of a duration of several years.

Reiter, E. R.↗

Aerosol-Cloud Interactions and the Intersection of Climate Forcing and Feedback

The goal of this project has been to understand at the process level how the interaction of aerosols and cloud microphysics may alter the cloud response to climate change from the scale of turbulence to the global scale. Atmospheric aerosols (suspended particulates) have a unique role to play in the climate system. Anthropogenic aerosols may be an air pollution hazard and degrade human health. Their presence also results in the direct scattering or absorption of sunlight, with small net impacts on climate. But aerosols are also a key part of cloud formation, as the locations on which cloud droplets and ice crystals form. Understanding these Aerosol Cloud Interactions (ACI) is a critical uncertainty for climate models, including the Energy Exascale Earth System Model (E3SM), and affects how well models like E3SM can simulate the past and future. This work aims to understand cloud microphysics as well as the interaction of aerosol forcing and cloud feedback through improving our understanding of aerosol-cloud interactions (ACI) by looking at their uncertainty in critical environments at the process level. It will also contribute to the development of E3SM. Specific goals include: first, high level analysis of Perturbed Parameter Ensemble (PPE) simulations already available from the Community Earth System Model (CESM) and E3SM. Second, detailed analysis of recent changes to temperature and the role of aerosols.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Aerosol Direct Effects on the South Asian Climate: Assessment of Radiative Feedback Processes Using Model Simulations and Satellite/Surface Measurements

Current assessment of aerosol radiative effect is hindered by our incomplete knowledge of aerosol optical properties, especially absorption, and our current inability to quantify physical and microphysical processes. In this research, we investigate direct aerosol radiative effect over heavy aerosol loading areas (e.g., Indo-Gangetic Plains, South/East Asia) and its feedbacks on the South Asian climate during the pre-monsoon season (March-June) using the Purdue Regional Climate Model (PRCM) with prescribed aerosol data derived by the NASA Goddard Earth Observing System Model (GEOS-5). Our modeling domain covers South and East Asia (60-140E and 0-50N) with spatial resolutions of 45 km in horizontal and 28 layers in vertical. The model is integrated from 15 February to 30 June 2008 continuously without nudging (i.e., only forced by initial/boundary conditions). Two numerical experiments are conducted with and without the aerosol-radiation effects. Both simulations are successful in reproducing the synoptic patterns on seasonal-to-interannual time scales and capturing a pre-monsoon feature of the northward rainfall propagation over Indian region in early June which shown in Tropical Rainfall Measuring Mission (TRMM) observation. Preliminary result suggests aerosol-radiation interactions mainly alter surface-atmosphere energetics and further result in an adjustment of the vertical temperature distribution in lower atmosphere (below 700 hPa). The modifications of temperature and associated rainfall and circulation feedbacks on the regional climate will be discussed in the presentation.

Wang, Sheng-Hsiang↗

Incorporation of surface albedo-temperature feedback in a one-dimensional radiative-connective climate model

The feedback between ice snow albedo and temperature is included in a one dimensional radiative convective climate model. The effect of this feedback on sensitivity to changes in solar constant is studied for the current values of the solar constant and cloud characteristics. The ice snow albedo feedback amplifies global climate sensitivity by 33% and 50%, respectively, for assumptions of constant cloud altitude and constant cloud temperature.

Wang, W. C.↗

Effect of cloud-radiation feedback on the climate of a general circulation model

Experiments are described which show significant changes in the simulated large-scale dynamical circulation of a global model. Fixed clouds acting as zonally asymmetric radiative heat sources increase the generation of eddy available potential energy (EAPE) and the energy's conversion to eddy kinetic energy. Generation of EAPE by net radiative heating increases by 50% (0.11 W/sq m) for the fixed cloud experiment. The increase caused by the stationary component is much larger (approximately 100%), but it is partially compensated by a decrease caused by the transient component. A substantial increase is found in the variances of the planetary-scale stationary waves and the medium-scale waves of 2.7 day period. Although the sea surface temperatures are prescribed identically in both integrations, the changes in evaporation and precipitation are found to be much larger over the oceans than over the land.

Shukla, J.↗

An energy balance climate model with cloud feedbacks

The present two-level global climate model, which is based on the atmosphere-surface energy balance, includes physically based parameterizations for the exchange of heat and moisture across latitude belts and between the surface and the atmosphere, precipitation and cloud formation, and solar and IR radiation. The model field predictions obtained encompass surface and atmospheric temperature, precipitation, relative humidity, and cloudiness. In the model integrations presented, it is noted that cloudiness is generally constant with changing temperature at low latitudes. High altitude cloudiness increases with temperature, although the cloud feedback effect on the radiation field remains small because of compensating effects on thermal and solar radiation. The net global feedback by the cloud field is negative, but small.

Roads, J. O.↗

Investigation of biogeophysical feedback on the African climate using a two-dimensional model

A numerical scheme is specifically designed to develop a time-dependent climate model to ensure the conservation of mass, momentum, energy, and water vapor, in order to study the biogeophysical feedback for the climate of Africa. A vegetation layer is incorporated in the present two-dimensional climate model. Using the coupled climate-vegetation model, two tests were performed involving the removal and expansion of the Sahara Desert. Results show that variations in the surface conditions produce a significant feedback to the climate system. It is noted that the simulation responses to the temperature and zonal wind in the case of an expanded desert agree with the climatological data for African dry years. Perturbed simulations have also been performed by changing the albedo only, without allowing the variation in the vegetation layer. It is shown that the variation in latent heat release is significant and is related to changes in the vegetation cover. As a result, precipitation and cloud cover are reduced.

Xue, Yongkang↗

Cloud optical thickness feedbacks in the CO2 climate problem

A radiative-convective equilibrium model is developed and applied to study cloud optical thickness feedbacks in the CO2 climate problem. The basic hypothesis is that in the warmer and moister CO2-rich atmosphere, cloud liquid water content will generally be larger too. For clouds other than thin cirrus the result is to increase the albedo more than to increase the greenhouse effect. Thus, the sign of the feedback is negative: cloud optical properties act as a thermostat and alter in such a way as to reduce the surface and tropospheric warming caused by the addition of CO2. This negative feedback can be substantial. When observational estimates of the temperature dependence of cloud liquid water content are employed in the model, the surface temperature change caused by doubling CO2 is reduced by about one half. This result is obtained for global and annual average conditions, no change in cloud amount or altitude, and constant relative humidity. These idealizations, together with other simplifications typical of one-dimensional radiative-convective climate models, render the result tentative. Further study of cloud optical property feedbacks is warranted, however, because the climate is apparently so sensitive to them.

Somerville, R. C. J.↗

Cloud optical thickness feedbacks in the CO2 climate problem

A radiative-convective equilibrium model is developed and applied to study cloud optical thickness feedbacks in the CO2 climate problem. The basic hypothesis is that in the warmer and moister CO2-rich atmosphere, cloud liquid water content will generally be larger than at present, so that cloud optical thickness will be larger too. For clouds other than thin cirrus, the result is to increase the albedo more than to increase the greenhouse effect. Thus the sign of the feedback is negative: cloud optical properties alter in such a way as to reduce the surface and tropospheric warming caused by the addition of CO2. This negative feedback can be substantial. When observational estimates of the temperature dependence of cloud liquid water content are employed in the model, the surface temperature change due to doubling CO2 is reduced by about one half.

Somerville, R. C. J.↗

Effect of ice-albedo feedback on global sensitivity in a one-dimensional radiative-convective climate model

The feedback between the ice albedo and temperature is included in a one-dimensional radiative-convective climate model. The effect of this feedback on global sensitivity to changes in solar constant is studied for the current climate conditions. This ice-albedo feedback amplifies global sensitivity by 26 and 39%, respectively, for assumptions of fixed cloud altitude and fixed cloud temperature. The global sensitivity is not affected significantly if the latitudinal variations of mean solar zenith angle and cloud cover are included in the global model. The differences in global sensitivity between one-dimensional radiative-convective models and energy balance models are examined. It is shown that the models are in close agreement when the same feedback mechanisms are included. The one-dimensional radiative-convective model with ice-albedo feedback included is used to compute the equilibrium ice line as a function of solar constant.

Wang, W.-C.↗

Climate-driven Chemistry and Aerosol Feedbacks in CMIP6 Earth System Models

Feedbacks play a fundamental role in determining the magnitude of the response of the climate system to external forcing, such as from anthropogenic emissions. The latest generation of Earth system models includes aerosol and chemistry components that interact with each other and with the biosphere. These interactions introduce a complex web of feedbacks that is important to understand and quantify. This paper addresses multiple pathways for aerosol and chemical feedbacks in Earth system models. These focus on changes in natural emissions (dust, sea salt, dimethyl sulfide, biogenic volatile organic compounds (BVOCs) and lightning) and changes in reaction rates for methane and ozone chemistry. The feedback terms are then given by the sensitivity of a pathway to climate change multiplied by the radiative effect of the change. We find that the overall climate feedback through chemistry and aerosols is negative in the sixth Coupled Model Intercomparison Project (CMIP6) Earth system models due to increased negative forcing from aerosols in a climate with warmer surface temperatures following a quadrupling of CO2 concentrations. This is principally due to increased emissions of sea salt and BVOCs which are sensitive to climate change and cause strong negative radiative forcings. Increased chemical loss of ozone and methane also contributes to a negative feedback. However, overall methane lifetime is expected to increase in a warmer climate due to increased BVOCs. Increased emissions of methane from wetlands would also offset some of the negative feedbacks. The CMIP6 experimental design did not allow the methane lifetime or methane emission changes to affect climate, so we found a robust negative contribution from interactive aerosols and chemistry to climate sensitivity in CMIP6 Earth system models.

Aerosol feedbacks↗

Simple and Multiple Endmember Mixture Analysis in the Boreal Forest

A key scientific objective of the original Boreal Ecosystem-Atmospheric Study (BOREAS) field campaign (1993-1996) was to obtain the baseline data required for modeling and predicting fluxes of energy, mass, and trace gases in the boreal forest biome. These data sets are necessary to determine the sensitivity of the boreal forest biome to potential climatic changes and potential biophysical feedbacks on climate. A considerable volume of remotely sensed and supporting field data were acquired by numerous researchers to meet this objective. By design, remote sensing and modeling were considered critical components for scaling efforts, extending point measurements from flux towers and field sites over larger spatial and longer temporal scales. A major focus of the BOREAS Follow-on program was concerned with integrating the diverse remotely sensed and ground-based data sets to address specific questions such as carbon dynamics at local to regional scales.

Roberts, Dar A.↗