The CloudSat Mission
The mission's primary goal is to furnish data needed to improve how cloud and cloud-climate feedbacks are parameterized in global circulation models (GCMs).
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The mission's primary goal is to furnish data needed to improve how cloud and cloud-climate feedbacks are parameterized in global circulation models (GCMs).
Arctic low clouds strongly affect the Arctic surface energy budget. Through this impact Arctic low clouds influence important aspects of the Arctic climate system, namely surface and atmospheric temperature, sea ice extent and thickness, and atmospheric circulation. Arctic clouds are in turn influenced by these elements of the Arctic climate system, and these interactions create the potential for Arctic cloud-climate feedbacks. To further our understanding of potential Arctic cloudclimate feedbacks, the goal of this paper is to quantify the influence of atmospheric state on the surface cloud radiative effect (CRE) and its covariation with sea ice concentration (SIC). We build on previous research using instantaneous, active remote sensing satellite footprint data from the NASA A-Train. First, the results indicate significant differences in the surface CRE when stratified by atmospheric state. Second, there is a weak covariation between CRE and SIC for most atmospheric conditions. Third, the results show statistically significant differences in the average surface CRE under different SIC values in fall indicating a 3-5 W m(exp -2) larger LW CRE in 0% versus 100% SIC footprints. Because systematic changes on the order of 1 W m(exp -2) are sufficient to explain the observed long-term reductions in sea ice extent, our results indicate a potentially significant amplifying sea ice-cloud feedback, under certain meteorological conditions, that could delay the fall freeze-up and influence the variability in sea ice extent and volume. Lastly, a small change in the frequency of occurrence of atmosphere states may yield a larger Arctic cloud feedback than any cloud response to sea ice.
Since the early 1990's technology advances permit ground based lidar to operate full time and profile all significant aerosol and cloud structure of the atmosphere up to the limit of signal attenuation. These systems are known as Micro Pulse Lidars (MPL), as referenced by Spinhirne (1993), and were first in operation at DOE Atmospheric Radiation Measurement (ARM) sites. The objective of the ARM program is to improve the predictability of climate change, particularly as it relates to cloud-climate feedback. The fundamental application of the MPL systems is towards the detection of all significant hydrometeor layers, to the limit of signal attenuation. The heating and cooling of the atmosphere are effected by the distribution and characteristics of clouds and aerosol concentration. Aerosol and cloud retrievals in several important areas can only be adequately obtained with active remote sensing by lidar. For cloud cover, the height and related emissivity of thin clouds and the distribution of base height for all clouds are basic parameters for the surface radiation budget, and lidar is essetial for accurate measurements. The ARM MPL observing network represents the first long-term, global lidar study known within the community. MPL systems are now operational at four ARM sites. A six year data set has been obtained at the original Oklahoma site, and there are several years of observations at tropical and artic sites. Observational results include cloud base height distributions and aerosol profiles. These expanding data sets offer a significant new resource for cloud, aerosol and atmospheric radiation analysis. The nature of the data sets, data processing algorithms, derived parameters and application results are presented.
Supercooled droplets in cirrus uncinus cell heads between -40 and -50 C are identified from the First International Satellite Cloud Climatology Project Regional Experiment polarization lidar measurements. Although short-lived, complexes of these small liquid cells seem to have contributed importantly to the formation of the cirrus. Freezing-point depression effects in solution droplets, apparently resulting from relatively large cloud condensation nuclei of volcanic origin, can be used to explain this rare phenomenon. An unrecognized volcano-cirrus cloud climate feedback mechanism is implied by these findings.
One of the main objectives of the Clouds and the Earth's Radiant Energy System (CERES) project is the retrieval of cloud physical and microphysical properties simultaneously with observations of broadband radiative fluxes. These cloud parameter sare used for three main purposes: 1) to provide data for radiation-cloud climate feedback studies; 2) to provide scene identification data for the construction and application of angular distribution models; and 3) to be used as input to radiative transfer calculations of intra-atmospheric fluxes
Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors' numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative. A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive. These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model. together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean-Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.
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Low-cloud feedbacks are thought to be the greatest source of uncertainty in climate projections on the centennial scale. Past research has mainly focused on the global low-cloud feedback as a whole whereas only a few studies have examined separated contributions from the two main low cloud categories: stratocumulus (Sc) and shallow cumulus (Cu). Here we aim to evaluate and constrain Sc and Cu cloud feedbacks in models using satellite observations to ultimately reduce their contribution to the spread in equilibrium climate sensitivity. We utilize the Cumulus and Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD) recently developed by Cesana et al. (2019), which discriminates Sc from Cu clouds. This algorithm – based on cloud morphological characteristics at the orbital level – outperforms previous cloud-type classifications stemming from passive-sensor measurements. We investigate the observed relationship between the Sc and Cu cloud cover in tropical subsidence oceanic regions and their link to the primary low-cloud controlling factors (sea surface temperature, estimated inversion strength). To gain further insight into the Sc-Cu cloud partitioning, we explore the Sc-Cu relationship during the four meteorological seasons (DJF, MAM, JJA, SON) as well as on monthly timescale. We find a substantial negative correlation between the Sc and Cu cloud cover on annual, seasonal and monthly timescales. We finally evaluate how well climate models of the Coupled Model Intercomparison Project phase 5 (CMIP5) and phase 6 (CMIP6) agree with the observations. These results establish a framework to advance model parameterizations of the underlying physical processes driving the stratocumulus and shallow cumulus clouds (turbulence and convection).
The top-of-atmosphere (TOA) radiative fluxes are critical components to advancing our understanding of the Earth's radiative energy balance, radiative effects of clouds and aerosols, and climate feedback. The Clouds and the Earth's Radiant Energy System (CERES) instruments provide broadband shortwave and longwave radiance measurements. These radiances are converted to fluxes by using scene-type-dependent angular distribution models (ADMs). This paper describes the next-generation ADMs that are developed for Terra and Aqua using all available CERES rotating azimuth plane radiance measurements. Coincident cloud and aerosol retrievals, and radiance measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological parameters from Goddard Earth Observing System (GEOS) data assimilation version 5.4.1 are used to define scene type. CERES radiance measurements are stratified by scene type and by other parameters that are important for determining the anisotropy of the given scene type. Anisotropic factors are then defined either for discrete intervals of relevant parameters or as a continuous functions of combined parameters, depending on the scene type. Significant differences between the ADMs described in this paper and the existing ADMs are over clear-sky scene types and polar scene types. Over clear ocean, we developed a set of shortwave (SW) ADMs that explicitly account for aerosols. Over clear land, the SW ADMs are developed for every 1 latitude1 longitude region for every calendar month using a kernel-based bidirectional reflectance model. Over clear Antarctic scenes, SW ADMs are developed by accounting the effects of sastrugi on anisotropy. Over sea ice, a sea-ice brightness index is used to classify the scene type. Under cloudy conditions over all surface types, the longwave (LW) and window (WN) ADMs are developed by combining surface and cloud-top temperature, surface and cloud emissivity, cloud fraction, and precipitable water. Compared to the existing ADMs, the new ADMs change the monthly mean instantaneous fluxes by up to 5Wm(exp -2) on a regional scale of 1 deg. latitude x 1 deg. longitude, but the flux changes are less than 0.5Wm(exp -2) on a global scale.
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.
Diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales.
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.
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.
An improved radiative-convective model (RCM) has been developed and used to examine the role of cirrus clouds in the optical thickness feedback mechanism. Low and middle clouds are approximately black bodies for infrared radiative transfer, and so any increase in their optical thickness primarily increases the cloud albedo. Thus, if a climate warming is accompanied by an increase in average atmospheric absolute humidity and hence in average cloud liquid water content, low and middle cloud optical thickness and albedo may increase. The result is a negative feedback on the climate change, tending to reduce the surface temperature increase. Recent research suggests that the optical thickness feedback can depend sensitively on aspects of cirrus which are not well observed or adequately incorporated in typical present-day climate models.
Cloud microphysics is critical for weather and climate prediction. In this work, we document updates and corrections to the cloud microphysical scheme used in the Community Earth System Model (CESM) and other models. These updates include a new nomenclature for the scheme, now called Parameterization of Unified Microphysics Across Scales (PUMAS), and the ability to run the scheme on graphics processing units (GPUs). The main science changes include refactoring an ice number limiter and associated changes to ice nucleation, adding vapor deposition onto snow, and introducing an implicit numerical treatment for sedimentation. We also detail the improvements in computational performance that can be achieved with GPU acceleration. We then show the impact of these scheme changes on the (a) mean state climate, (b) cloud feedback response to warming, and (c) aerosol forcing. We find that corrections are needed to the immersion freezing parameterization and that ice nucleation has important impacts on climate. We also find that the revised scheme produces less cloud liquid and ice but that this can be adjusted by changing the loss process for cloud liquid (autoconversion). Furthermore, there are few discernible effects of the PUMAS changes on cloud feedbacks but some reductions in the magnitude of aerosol–cloud interactions (ACIs). Small cloud feedback changes appear to be related to the implicit sedimentation scheme, with a number of factors affecting ACIs.
Simulations of natural variability by two general circulation models (GCMs) are examined. One GCM is a sector model, allowing relatively rapid integration without simplification of the model physics, which would potentially exclude mechanisms of variability. Two mechanisms are found in which tropical surface temperature and sea surface temperature (SST) vary on interannual and longer timescales. Both are related to changes in cloud cover that modulate SST through the surface radiative flux. Over the equatorial ocean, SST and surface temperature vary on an interannual timescale, which is determined by the magnitude of the associated cloud cover anomalies. Over the subtropical ocean, variations in low cloud cover drive SST variations. In the sector model, the variability has no preferred timescale, but instead is characterized by a 'red' spectrum with increasing power at longer periods. In the terrestrial GCM, SST variability associated with low cloud anomalies has a decadal timescale and is the dominant form of global temperature variability. Both GCMs are coupled to a mixed layer ocean model, where dynamical heat transports are prescribed, thus filtering out El Nino-Southern Oscillation (ENSO) and thermohaline circulation variability. The occurrence of variability in the absence of dynamical ocean feedbacks suggests that climatic variability on long timescales can arise from atmospheric processes alone.
Clouds interfere with the distribution of short-wave and long-wave radiations over sea ice, and thereby strongly affect the surface energy balance in polar regions. To evaluate the overall effects of clouds on climatic feedback processes in the atmosphere-ice-ocean system, the challenge is to observe sea ice surface thermal states under both clear sky and cloudy conditions. From laboratory experiments, we show that C-band radar (transparent to clouds) backscatter is very sensitive to the surface temperature of first-year sea ice. The effect of sea ice surface temperature on the magnitude of backscatter change depends on the thermal regimes of sea ice thermodynamic states. For the temperature range above the mirabilite (Na2SO4.10H20) crystallization point (-8.2 C), C-band data show sea ice backscatter changes by 8-10 dB for incident angles from 20 to 35 deg at both horizontal and vertical polarizations. For temperatures below the mirabilite point but above the crystallization point of MgCl2.8H2O (-18.0 C), relatively strong backwater changes between 4-6 dB are observed. These backscatter changes correspond to approximately 8 C change in temperature for both cases. The backscattering mechanism is related to the temperature which determines the thermodynamic distribution of brine volume in the sea ice surface layer. The backscatter is positively correlated to temperature and the process is reversible with thermodynamic variations such as diurnal insolation effects. From two different dates in May 1993 with clear and overcast conditions determined by the Advanced Very High Resolution Radiometer (AVHRR), concurrent Earth Resources Satellite 1 (ERS-1) C-band ice observed with increases in backscatter over first-year sea ice, and verified by increases in in-situ sea ice surface temperatures measured at the Collaborative-Interdisciplinary Cryosphere Experiment (C-ICE) site.
A study has been made of the effect of brokenness on the infrared and albedo feedback of clouds in climate models using a simplified treatment of broken cloudiness. It is shown that the individual feedback terms computed using the plane-parallel assumption differ markedly from the computations performed for a regular array of cuboidal clouds. If the cloudiness changes such that clear areas become cloudy but the nature of the broken cloud field remains unchanged, then both the feedbacks are magnified, the infrared more so than the albedo. However, if individual elements in the cloud field are increased horizontally in a constrained area, the feedbacks can be enhanced or diminished depending on the cloud fraction and aspect ratio of the elements. It is also shown that, in the global average, the ratio of the change in outgoing infrared flux to global albedo, as deduced from satellite measurements, will be larger than model simulations using planiform clouds.