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At least 19 records

An Evaluation of Clouds and Radiation in a Large-Scale Atmospheric Model Using a Cloud Vertical Structure Classification

We revisit the concept of the cloud vertical structure (CVS) classes we have previously employed to classify the planet's cloudiness (Oreopoulos et al., 2017). The CVS classification reflects simple combinations of simultaneous cloud occurrence in the three standard layers traditionally used to separate low, middle, and high clouds and was applied to a dataset derived from active lidar and cloud radar observations. This classification is now introduced in an atmospheric global climate model, specifically a version of NASA's GEOS-5, in order to evaluate the realism of its cloudiness and of the radiative effects associated with the various CVS classes. Such classes can be defined in GEOS-5 thanks to a sub column cloud generator paired with the model's radiative transfer algorithm, and their associated radiative effects can be evaluated against observations. We find that the model produces 50% more clear skies than observations in relative terms and produces isolated high clouds that are slightly less frequent than in observations, but optically thicker, yielding excessive planetary and surface cooling. Low clouds are also brighter than in observations, but underestimates of the frequency of occurrence (by ~20% in relative terms) help restore radiative agreement with observations. Overall the model better reproduces the longwave radiative effects of the various CVS classes because cloud vertical location is substantially constrained in the CVS framework.

Lee, Dongmin↗

Precipitating cloud vertical structure derived from passive microwave radiometry

A procedure for the retrieval of cloud vertical structure from passive microwave radiometry is demonstrated by using passive microwave radiometry observations made during the Tropical Rainfall Measuring Mission. The procedure uses a set of cloud radiative models, with each model consisting of five vertical layers, specifying a distinct cloud vertical structure in terms of the near-surface parameters. The retrieval procedure is separated into two tasks (1) retrieving a set of geophysical parameters for each cloud radiative model and (2) finding which of the cloud radiative models and its associated retrieved parameters best fit the observed geophysical conditions. It is shown that this retrieval technique can detect differences and similarities between precipitating systems.

Kummerow, Christian D.↗

Regimes of Cloud Vertical Structure From Active Observations

We introduce a new type of cloud class, which we call “active cloud regime” (ACR), owing to its provenance from active (lidar and cloud radar) spaceborne cloud observations. ACRs intend to provide a climatological description based on cloud vertical structure (CVS) of the most prevalent monthly CVS mixtures encountered at large spatial scales of ~400 km. ACRs are thus a way to create a gridded dataset of a vertically-resolved cloud mask that can facilitate joint analysis with other gridded datasets. The detailed 2D cloud mask comes from the 2B-CLDCLASS-LIDAR CloudSat dataset fusing CALIPSO (lidar) and CloudSat (cloud radar) cloud detections. We show that the global classification of cloudiness under the ACR framework provides valuable insights on how the world’s dominant cloud systems regulate the two major components of atmospheric energetics, precipitation and radiative cooling. NASA’s GEOS model allows us to demonstrate the feasibility of applying the ACR concept in Earth System Models that have the capability to produce subgrid cloudiness obeying pre-specified vertical overlap rules. Comparison of observed and simulated ACRs provides thus another means to assess the realism of modeled clouds.

cloud vertical structure↗

Vertical cloud structure of Jupiter's equatorial plumes

Multiple-scattering radiative transfer calculations were used to deduce the vertical cloud structure (VCS) of Jupiter's equatorial region. The VCS model of the equatorial plumes is obtained through an analysis of Voyager images of the 6190-A methane band and the 6000-A continuum, and ground-based 8900-A methane band images. The VCS of the equatorial plumes is found to be consistent with the hypothesis that the plumes are caused by upwelling at the ammonia condensation level produced by buoyancy due to latent heat release from the condensation of water clouds nearly three scale heights below the plumes.

Stoker, C. R.↗

Radar For Measuring Vertical Cloud Structure

Proposed radar system views clouds from above and measures their vertical structures with resolution of 500 m. Two versions of system; initial developmental version to be flown aboard aircraft and final version flown aboard spacecraft in circular orbit around Earth at altitude of 400 km.

Im, Eastwood↗

Vertical cloud structure models for the NTRZ EQZ, SEB and STRZ of Jupiter

Latitude-dependent models of the vertically inhomogeneous Jovian cloud structure are presented. The models assume an atmospheric composition with (CH4)/(H2) = 2.0 x .003, (He)/(H2) = 0.11 and (NH3)/(H2) = 2.0 x .0004 consistent with the Voyager IRIS measurements and employ refractive indices appropriate for ammonia ice particles and a photochemical stratospheric aerosol layer. The free parameters of the models are determined by fitting the results of multiple, scratching calculations to the near-infrared center and limb spectra of Clark and McCord and the center-to-limb 6190, 6350, 7250, 7500, 8900 and 9500 A photometric measurements of West. The resulting synthetic center-to-limb profiles are in excellent agreement with the observations. Of the regions studied the tropical zones are the most similar, with the observed differences explained by variations in the vertical extent of the cloudy layers. The Equatorial Zone is a unique region with denser NH3 clouds than either of the tropical zones. At visible and near-infrared wavelengths the belt-zone contrasts can be explained by opacity differences. The optical depth of the stratospheric aerosol layer is larger in a belt, while the tropospheric clouds are deeper and thinner.

Carlson, B. E.↗

Spatially resolved methane band photometry of Jupiter. III - Cloud vertical structures for several axisymmetric bands and the Great Red Spot

The paper presents cloud structure models for Jupiter's Great Red Spot, Equatorial and North Tropical Zones, North and South Temperate Zones, and North and South Polar Regions. The models are based on images of Jupiter in three methane bands and nearby continuum; radiative transfer calculations include multiple scattering and absorption from three aerosol layers. The model results include the transition in the upper-cloud altitude to 3 km lower altitude from the tropical zones to temperate zones and polar regions, a N/S asymmetry in cloud thickness in the tropical and temperature zones, and the presence of aerosols up to about 0.3 bar in the Great Red Spot and Equatorial Zone. It is concluded that polarization data are sensitive to aerosols in and above the upper cloud layer but insensitive to deeper cloud structure.

West, R. A.↗

The vertical cloud structure of Jupiter from 5 micron measurements

From 5-micron high-spatial-resolution images of Jupiter, flux-frequency histograms of the equatorial region show a trimodal distribution of brightness temperatures. Combined with limb-darkening measurements, a three-layer cloud model for Jupiter is developed. The highest, coldest clouds, apparently homogeneous and displaying relatively little limb darkening, cover the zones. These clouds are not present over the belts, allowing observational access to deeper regions. The belts appear heterogeneous: small, localized hot areas show enhanced limb darkening, while much of the belt is distinctly cooler and exhibits shallower limb darkening. These belt properties can be explained by a cool emitting layer superposed upon a hot, dense cloud deck.

Terrile, R. J.↗

Determining microwave brightness temperatures from precipitating horizontally finite and vertically structured clouds

Microwave radiances that may be measured from satellite-borne radiometers operating at 37 GHz have been computed as a function of rainfall rates from horizontally finite precipitating clouds that contain both ice and liquid hydrometeors. It is found that precipitating ice at the top of the cloud depresses brightness temperatures significantly. Detailed comparison between finite clouds and the equivalent sections of plane-parallel clouds are made. Footprint averaged brightness temperatures from finite clouds are found to deviate considerably from the sectioned plane-parallel approximation, especially for large rain rates. Better agreement is achieved if a plane-parallel source function is used in the finite cloud model. The effect of shape and orientation of the precipitating cells with respect to the satellite has also been considered. It is found that the largest errors introduced by plane-parallel theory besides the footprint-filling errors are encountered when precipitating cells have large fractions of their surface below the freezing level or contain large amounts of ice.

Kummerow, C.↗

Colors of Jupiter's large anticyclones and the interaction of a Tropical Red Oval with the Great Red Spot in 2008

The nature and mechanisms producing the chromophore agents that provide color to the upper clouds and hazes of the atmospheres of the giant planets are largely unknown. In recent times, the changes in red coloration that have occurred in large- and medium-scale Jovian anticyclones have been particularly interesting. In late June and early July 2008, a particularly color-intense red tropical oval interacted with the Great Red Spot (GRS) leading to the destruction of the red tropical oval and cloud dispersion. We present a detailed study of the tropical vortices, usually white but sometimes red, and a characterization of their color spectral signatures and dynamics. From the spectral reflectivity in methane bands we study their vertical cloud structure compared to that of the GRS and BA. Using two spectral indices we found a near-correlation between anticyclones cloud top altitudes and red color. We present detailed observations of the interaction of the red oval with the GRS and model simulations of the phenomena that allow us to constrain the relative vertical extent of the vortices. We conclude that the vertical cloud structure, vertical extent and dynamics of Jovian anticyclones are not the causes of their coloration. We propose that the red chromophore forms when background material (a compound or particles) is entrained by the vortex, transforming into red once inside the vortex due to internal conditions, exposure to ultraviolet radiation or to the mixing of two chemical compounds that react inside the vortex, confined by a potential vorticity ring barrier.

red color↗

Cloud Structure Anomalies Over the Tropical Pacific During the 1997/98 El Nino

Satellite measurements of both cloud vertical structure and cloud-radiative forcing have been used to show that during the strong 1997/98 El Nino there was a substantial change in cloud vertical structure over the tropical Pacific Ocean. Relative to normal years, cloud altitudes were lower in the western portion of the Pacific and higher in the eastern portion. The reason for these redistributions was a collapse of the Walker circulation and enhanced large-scale upward motion over the eastern Pacific, both caused by the lack of a zonal sea surface temperature gradient during El Nino. It is proposed that these cloud structure changes, which significantly impact satellite measurements of the tropical Pacific's radiation budget, would serve as one useful means of testing cloud-climate interactions in climate models.

Cess, Robert D.↗

Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model

The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.

Molthan, Andrew L.↗

Monte Carlo Bayesian Inference on a Statistical Model of Sub-gridcolumn Moisture Variability Using High-resolution Cloud Observations : Sensitivity Tests and Results - Part II

Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.

Monte Carlo Bayesian inference↗

Global Weather States and Their Properties from Passive and Active Satellite Cloud Retrievals

In this study, the authors apply a clustering algorithm to International Satellite Cloud Climatology Project (ISCCP) cloud optical thickness-cloud top pressure histograms in order to derive weather states (WSs) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global WSs are derived, a combination of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cloud structure retrievals is used to derive the vertical distribution of the cloud field within each WS. Finally, the dynamic environment and the radiative signature of the WSs are derived and their variability is examined. The cluster analysis produces a comprehensive description of global atmospheric conditions through the derivation of 11 WSs, each representing a distinct cloud structure characterized by the horizontal distribution of cloud optical depth and cloud top pressure. Matching those distinct WSs with cloud vertical profiles derived from CloudSat and CALIPSO retrievals shows that the ISCCP WSs exhibit unique distributions of vertical layering that correspond well to the horizontal structure of cloud properties. Matching the derived WSs with vertical velocity measurements shows a normal progression in dynamic regime when moving from the most convective to the least convective WS. Time trend analysis of the WSs shows a sharp increase of the fair-weather WS in the 1990s and a flattening of that increase in the 2000s. The fact that the fair-weather WS is the one with the lowest cloud radiative cooling capability implies that this behavior has contributed excess radiative warming to the global radiative budget during the 1990s.

histograms↗

Cloud Vertical and Horizontal Structure from ICESat/GLAS and MODIS

To accurately model radiative fluxes at the surface and within the atmosphere, we need to know both vertical and horizontal structures of cloudiness. While MODIS provides accurate information on cloud horizontal structure, it has limited ability to estimate cloud vertical structure. ICESat/GLAS on the other hand, provides the vertical distribution and internal structure of clouds as deep as the laser beam can penetrate and return a signal. Having different orbits, MODIS and GLAS provide few collocated measurements; hence a statistical approach is needed to learn about 3D cloud structures from the two instruments. In the presentation, we show the results of the statistical analysis of vertical and horizontal structure of cloudiness using GLAS and MODIS cloud top(s) data acquired in October-November 2003. We revisit the (H1, C1) plot, previously used for analyzing cloud liquid water data, and illustrate cloud structure for single and multiple-layer clouds.

Marshak, Alexander↗