Cloud Regimes Research Articles

Dispelling Clouds of Uncertainty

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Estimate of local features of long-term variations in cloud cover over the territory of Siberia using results of its climatic zoning according to total and low-level cloud regimes

The local features of long-term variations in cloud cover over the territory of Siberia are statistically analyzed using a 45-year (1969–2013) time series of meteorological observations at 60 stations and data of climatic zoning of this region according to total and low-level cloud regimes. It is found that, whereas poorly defined growth in the total and low-level cloud amounts was observed almost everywhere (except in Arctic regions of Siberia, where a decrease in the total cloud amount and an increase in the low-level cloud amount tended to predominate) during all seasons for the 45-year period and in 1976–2005, when there was an intense global warming, in the period of 2006–2013, when this warming was much weaker, a well-defined decrease in both total and low-level clouds was observed, especially in winter and spring seasons.

Cluster Analysis of A-Train Data: Approximating the Vertical Cloud Structure of Oceanic Cloud Regimes

AbstractModerate Resolution Imaging Spectroradiometer (MODIS) data continue to provide a wealth of two-dimensional, cloud-top information and derived environmental products. In addition, the A-Train constellation of satellites presents an opportunity to combine MODIS data with coincident vertical-profile data collected from sensors on CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Approximating the vertical structure of clouds in data-sparse regions can be accomplished through a two-step process that consists of cluster analysis of MODIS data and quantitative analysis of coincident vertical-profile data. Daytime data over the eastern North Pacific Ocean are used in this study for both the summer (June–August) and winter (December–February) seasons in separate cluster analyses. A-Train data from 2006 to 2009 are collected, and a K-means cluster analysis is applied to selected MODIS data that are coincident with single-layer clouds found in the CloudSat/CALIPSO (“GEOPROF-lidar”) data. The resultant clusters, 16 in both summer and winter, are quantified in terms of average cloud-base height, cloud-top height, and normalized cloud water content profile. A cluster and its quantified characteristics can then be assigned to a given pixel in near real-time MODIS data, regardless of its proximity to the observed vertical-profile data. When applied to a two-dimensional MODIS dataset, these assigned clusters can provide an approximate three-dimensional representation of the cloud scene.

A single‐column model intercomparison on the stratocumulus representation in present‐day and future climate

AbstractSix Single‐Column Model (SCM) versions of climate models are evaluated on the basis of their representation of the dependence of the stratocumulus‐topped boundary layer regime on the free tropospheric thermodynamic conditions. The study includes two idealized experiments corresponding to the present‐day and future climate conditions in order to estimate the low‐cloud feedback. Large‐Eddy Simulation (LES) results are used as a benchmark and GCM outputs are included to assess whether the SCM results are representative of their 3‐D counterparts. The SCMs present a variety of dependencies of the cloud regime on the free tropospheric conditions but, at the same time, several common biases. For all the SCMs the stratocumulus‐topped boundary layer is too shallow, too cool, and too moist as compared to the LES results. Moreover, they present a lack of clouds and liquid water and an excess of precipitation. The disagreement among SCMs is even more distinct for the response to a climate perturbation. Even though the overall feedback is positive for all the models, in line with the LES results, the SCMs show a rather noisy behavior, which depends irregularly on the free tropospheric conditions. Finally, the comparison with the host GCM outputs demonstrates that the considered approach is promising but needs to be further generalized for the SCMs to fully capture the behavior of their 3‐D counterparts.

Impacts of Cloud Droplet–Nucleating Aerosols on Shallow Tropical Convection

Abstract Low-level warm-phase clouds cover a substantial portion of Earth’s oceans and play an important role in the global water and energy budgets. The characteristics of these clouds are controlled by the large-scale environment, boundary layer conditions, and cloud microphysics. Variability in the concentration of aerosols can alter cloud microphysical and precipitation processes that subsequently impact the system dynamics and thermodynamics and thereby create aerosol–cloud dynamic–thermodynamic feedback effects. In this study, three distinct cloud regimes were simulated, including stratocumulus, low-level cumulus (cumulus under stratocumulus), and deeper cumulus clouds. The simulations were conducted without environmental large-scale forcing, thereby allowing all three cloud types to freely interact with the environmental state in an undamped fashion. Increases in aerosol concentration in these unforced, warm-phase, tropical cloud simulations lead to the production of fewer low-level cumuli; thinning and erosion of the widespread stratocumulus layer; and the development of deeper, inversion-penetrating cumuli. The mechanisms for these changes are explored. Despite the development of deeper, more heavily precipitating cumuli, the reduction of the widespread moderately precipitating stratocumulus clouds leads to an overall reduction in domainwide accumulated precipitation when aerosol concentrations are enhanced.

Regional features of long-term changes in cloud cover in Siberian sector of Northern hemisphere for the last 45 years (1969–2013)

We discussed the results of statistical analysis of regional features of long-term changes in cloud cover on the territory of Siberia according to data of climatic zoning of this region with respect to the total and low-level cloud regimes, using 45-year (1969–2013) time series of meteorological observations at 60 stations located in the Siberian sector of the Northern hemisphere. We found that there had been a clear trend toward increase in the total and low-level cloud amounts in all seasons and over the entire year after spatial averaging of data over the entire Siberian sector, as well as separately over the territory of Western and Eastern Siberia, during the base 45-year period (1969–2013), total and low-level cloud amounts substantially decreased in all seasons (except in fall) and over the entire year on the territory of the entire Siberian sector in recent years (2006–2013), when there was a trend toward a decrease in the intensity of global warming.

Regional Assessments of Low Clouds against Large-Scale Stability in CAM5 and CAM-CLUBB Using MODIS and ERA-Interim Reanalysis Data

Abstract Daily gridded cloud data from MODIS and ERA-Interim reanalysis have been assessed to examine variations of low cloud fraction (CF) and cloud-top height and their dependence on large-scale dynamics and a measure of stability. To assess the stratocumulus (Sc) to cumulus (Cu) transition (STCT), the observations are used to evaluate two versions of the NCAR Community Atmosphere Model version 5 (CAM5), both the base model and a version that has implemented a new subgrid low cloud parameterization, Cloud Layers Unified by Binormals (CLUBB). The ratio of moist static energy (MSE) at 700–1000 hPa (MSEtotal) is a skillful predictor of median CF of screened low cloud grids. Values of MSEtotal less than 1.00 represent either conditionally or absolutely unstable layers, and probability density functions of CF suggest a preponderance of either trade Cu (median CF < 0.4) or transitional Sc clouds (0.4 < CF < 0.9). With increased stability (MSEtotal > 1.00), an abundance of overcast or nearly overcast low clouds exists. While both MODIS and ERA-Interim indicate a fairly smooth transition between the low cloud regimes, CAM5-Base simulates an abrupt shift from trade Cu to Sc, with trade Cu covering both too much area and occurring over excessively strong stabilities. In contrast, CAM-CLUBB simulates a smoother trade Cu to Sc transition (CTST) as a function of MSEtotal, albeit with too extensive coverage of overcast Sc in the primary northeastern Pacific subsidence region. While the overall CF distribution in CAM-CLUBB is more realistic, too few transitional clouds are simulated for intermediate MSEtotal compared to observations.

The consequences of a local approach in statistical models of convection on its large‐scale coherence

AbstractOrganized tropical convection is a crucial mechanism in the climate system, but its representation in climate models through parametrization schemes has numerous shortcomings. One of these shortcomings is that they are deterministic despite the statistical nature of the relationship they are representing. Several attempts at devising a stochastic parametrization scheme have been made, many of which assume a local approach, that is, one in which the convection in a grid box is determined without consideration of the previous time steps and the surrounding boxes. This study seeks to explore the effect of this assumption on the coherence of convection using cloud regimes, which represent various modes of tropical convection. First, we analyze the coherence of observed convection beyond the typical size of a model grid box and time step. Then, we evaluate the consequences of the local assumption on this coherence in simple statistical models. Cloud regimes in the real world show high degrees of coherence, manifesting in their lifetimes, areas, and inter‐regime relationships. However, in a local statistical model, they are too small, too short‐lived, and have incorrect relationships between each other. This can be improved by incorporating time memory and spatial dependence in the modeling. Our results imply that a local approach to a statistical representation of convection is not viable, and a statistical model must account for nonlocal influence in order to have large‐scale convective coherence that more closely resembles the real world.

Comparisons of GCM cloud cover parameterizations with cloud-resolving model explicit simulations

Three kinds of the widely-used cloudiness parameterizations are compared with data produced from the cloud-resolving model (CRM) simulations of the tropical cloud system. The investigated schemes include those based on relative humidity (RH), the semi-empirical scheme using cloud condensate as a predictor, and the statistical scheme based on probability distribution functions (PDFs). Results show that all three schemes are successful in reproducing the timing of cloud generation, except for the RH-based scheme, in which low-level clouds are artificially simulated during cloudless days. In contrast, the low-level clouds are well simulated in the semi-empirical and PDF-based statistical schemes, both of which are close to the CRM explicit simulations. In addition to the Gaussian PDF, two alternative PDFs are also explored to investigate the impact of different PDFs on cloud parameterizations. All the PDF-based parameterizations are found to be inaccurate for high cloud simulations, in either the magnitude or the structure. The primary reason is that the investigated PDFs are symmetrically assumed, yet the skewness factors in deep convective cloud regimes are highly significant, indicating the symmetrical assumption is not well satisfied in those regimes. Results imply the need to seek a skewed PDF in statistical schemes so that it can yield better performance in high cloud simulations.

Immersion freezing by natural dust based on a soccer ball model with the Community Atmospheric Model version 5: climate effects

We introduce a simplified version of the soccer ball model (SBM) developed by Niedermeier et al (2014 Geophys. Res. Lett. 41 736–741) into the Community Atmospheric Model version 5 (CAM5). It is the first time that SBM is used in an atmospheric model to parameterize the heterogeneous ice nucleation. The SBM, which was simplified for its suitable application in atmospheric models, uses the classical nucleation theory to describe the immersion/condensation freezing by dust in the mixed-phase cloud regime. Uncertain parameters (mean contact angle, standard deviation of contact angle probability distribution, and number of surface sites) in the SBM are constrained by fitting them to recent natural dust (Saharan dust) datasets. With the SBM in CAM5, we investigate the sensitivity of modeled cloud properties to the SBM parameters, and find significant seasonal and regional differences in the sensitivity among the three SBM parameters. Changes of mean contact angle and the number of surface sites lead to changes of cloud properties in Arctic in spring, which could be attributed to the transport of dust ice nuclei to this region. In winter, significant changes of cloud properties induced by these two parameters mainly occur in northern hemispheric mid-latitudes (e.g., East Asia). In comparison, no obvious changes of cloud properties caused by changes of standard deviation can be found in all the seasons. These results are valuable for understanding the heterogeneous ice nucleation behavior, and useful for guiding the future model developments.

On the relationship between responses in cloud water and precipitation to changes in aerosol

Abstract. Climate models continue to exhibit strong sensitivity to the representation of aerosol effects on cloud reflectance and cloud amount. This paper evaluates a proposed method to constrain modeled cloud liquid water path (LWP) adjustments in response to changes in aerosol concentration Na using observations of precipitation susceptibility. Recent climate modeling has suggested a linear relationship between relative LWP responses to relative changes in Na, i.e., dln LWP / dln Na, and the precipitation frequency susceptibility Spop, which is defined as the relative change in the probability of precipitation for a relative change in Na. Using large-eddy simulations (LES) of marine stratocumulus and trade wind cumulus clouds, we show that these two cloud regimes exhibit qualitatively different relationships between λ and Spop; in stratocumulus clouds, λ increases with Spop, while in trade wind cumulus, λ decreases with Spop. The LES-derived relationship for marine stratocumulus is qualitatively similar but quantitatively different than that derived from climate model simulations of oceanic clouds aggregated over much larger spatial scales. We explore possible reasons for variability in these relationships, including the selected precipitation threshold and the various definitions of precipitation susceptibility that are currently in use. Because aerosol–cloud–precipitation interactions are inherently small-scale processes, we recommend that when deriving the relationship between λ and Spop, careful attention be given to the cloud regime, the scale, and the extent of aggregation of the model output or the observed data.

A Simple Analytical Model for Understanding the Formation of Sea Surface Temperature Patterns under Global Warming*

Abstract How sea surface temperature (SST) changes under global warming is critical for future climate projection because SST change affects atmospheric circulation and rainfall. Robust features derived from 17 models of phase 5 of the Coupled Model Intercomparison Project (CMIP5) include a much greater warming in high latitudes than in the tropics, an El Niño–like warming over the tropical Pacific and Atlantic, and a dipole pattern in the Indian Ocean. However, the physical mechanism responsible for formation of such warming patterns remains open. A simple theoretical model is constructed to reveal the cause of the future warming patterns. The result shows that a much greater polar, rather than tropical, warming depends primarily on present-day mean SST and surface latent heat flux fields, and atmospheric longwave radiation feedback associated with cloud change further enhances this warming contrast. In the tropics, an El Niño–like warming over the Pacific and Atlantic arises from a similar process, while cloud feedback resulting from different cloud regimes between east and west ocean basins also plays a role. A dipole warming over the equatorial Indian Ocean is a response to weakened Walker circulation in the tropical Pacific.

Observations of black carbon induced semi direct effect over Northeast India

This article reports observational evidence of Black Carbon (BC) induced cloud burning effect (Semi direct effect) for the first time over a mountainous location in North east India. Simultaneous aircraft observations of Black Carbon (BC) mass concentrations and cloud microphysical parameters were carried out over Guwahati, in Northeast India during Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX) Phase-I in 2009. Elevated pollution layers of BC (concentration exceeding 1 μg m−3) were observed over the site up to 7 km on different experimental days (August 30, September 4 and 6 in 2009) in the cloud regime. The vertical heating rate and radiative forcing induced by elevated BC layers in the cloud regime were estimated using an optical model along with a radiative transfer model. The instantaneous vertical heating rate induced by BC in cloud layers is found to be as high as 2.65 K/day. The instantaneous vertical heating by BC is found to be inducing a significant reduction in the measured cloud liquid water content (LWC) over the site. Subsequently, the BC stimulated heating has been found to be reducing the cloud fraction (CFR) and thus inducing a “cloud burning effect (Semi direct effect)”, over the region. The estimated instantaneous BC induced radiative forcing in the cloud regime is found to be +12.7–+45.1 W m−2 during the experimental periods. This large warming and reduction in cloudiness can decrease the precipitation over the region. However, more simultaneous BC-cloud observations and further research are necessary to establish a stable “semi-direct effect” over the region.

Links between satellite-retrieved aerosol and precipitation

Abstract. Many theories have been proposed detailing how aerosols might impact precipitation, predicting both increases and decreases depending on the prevailing meteorological conditions and aerosol type. In convective clouds, increased aerosol concentrations have been speculated to invigorate convective activity. Previous studies have shown large increases in precipitation with increasing aerosol optical depth, concluding an aerosol effect on precipitation. Our analysis reveals that these studies may have been influenced by cloud effects on the retrieved aerosol, as well as by meteorological covariations. We use a regime-based approach to separate out different cloud regimes, allowing for the study of aerosol–cloud interactions in individual cloud regimes. We account for the influence of cloud properties on the aerosol retrieval and make use of the diurnal sampling of the TRMM satellite and the TRMM merged precipitation product to investigate the precipitation development. We find that whilst there is little effect on precipitation at the time of the aerosol retrieval, in the 6 h after the aerosol retrieval, there is an increase in precipitation from cloud in high-aerosol environments, consistent with the invigoration hypothesis. Increases in lightning flash count with increased aerosol are also observed in this period. The invigoration effect appears to be dependent on the cloud-top temperature, with clouds with tops colder than 0 °C showing increases in precipitation at times after the retrieval, as well as increases in wet scavenging. Warm clouds show little change in precipitation development with increasing aerosol, suggesting ice processes are important for the invigoration of precipitation.

Importance of natural cloud regimes to ecophysiology in the alpine species, Caltha leptosepala and Arnica parryi, Snowy Range Mountains, southeast Wyoming, USA.

The south-central Rocky Mountains, USA, are characterised by a dry, continental mesoclimate with typical convective cloud formation during the afternoon. Little is known about the specific influence of such predictable cloud patterns on the microclimate and ecophysiology of associated species. During the summer of 2012, days with afternoon clouds were most common (50% of all days) compared with completely clear (24%) or cloudy days (6.5%). In two representative alpine species, Caltha leptosepala DC. and Arnica parryi A. Gray, fully overcast days reduced mean daily photosynthesis (A) by nearly 50% relative to fully clear days. Mean afternoon A was significantly lower on fully cloudy days relative to days with afternoon clouds only or no clouds in both species. Notably, A did not differ during afternoon cloud days relative to clear afternoons. Afternoon clouds significantly reduced transpiration (E) in C. leptosepala relative to clear days, and both species showed mean reductions in plant water stress (i.e. higher Ψ), though this difference was not significant. Water use efficiency (WUE) (A/E) decreased from morning to afternoon, especially on cloudy days, and the presence of clouds had a positive effect on the light reactions of photosynthesis based on fluorescence measurements (Fv'/Fm'), in both species. Cloudy days were characterised by higher Fv/Fm than afternoon clouds and clear days during both the morning and the afternoon (especially for A. parryi) and recovery to near pre-dawn values for cloudy and afternoon cloud day types, but not clear days. Overall, similar ecophysiological advantages of this typical afternoon cloud pattern was apparent in both species, although their spatial microsite differences related to winter snow accumulation may also play an important role.

Modeling instantaneous heavy gas releases with FDS5

Releases of heavy flammable gases are responsible of many major civil and industrial incidents with very large property loss and number of victims. Fire Dynamics Simulator 5 (FDS5) is a fire modeling CFD code developed by NIST that is widely known in the fire engineering community.The code is specifically suited to deal with multicomponent buoyancy driven natural flow, where the low Mach number assumption holds and the pressure is only slightly different from the background atmospheric value. This study presents the comparison between experimental results relevant to heavy gas or vapors instantaneous releases and FDS5 predictions. Comparison with experimental results shows that concentrations and cloud arrival times in the heavy gas cloud regime, when concentrations of the heavy component in the plume are high, can be predicted by the code. The present work is focused on gravitationally driven heavy gas dispersion in calm environments.

LES of a Spatially Developing Atmospheric Boundary Layer: Application of a Fringe Method for the Stratocumulus to Shallow Cumulus Cloud Transition

AbstractAn arrangement of a large-eddy simulation (LES) is described that facilitates a spatially developing thermally stratified atmospheric boundary layer (ABL). When the inflow and outflow boundary conditions are specified, the LES of stably stratified ABL turns out to be challenging because spurious reflections of waves at the boundary accumulate inside the domain. To tackle this problem, a fringe method with an auxiliary LES running concurrently is applied to enforce upstream/downstream boundary conditions. An artificial forcing term is applied within a fringe region located at the beginning of the main LES domain in order to ensure statistically stationary inflow boundary conditions. The auxiliary LES, which is horizontally homogeneous in a doubly periodic domain, is used to determine the inflow condition of the main LES domain. The present scheme is used to provide an Eulerian perspective of the stratocumulus to shallow cumulus cloud (Sc–Cu) transition, one of the key cloud regimes over the subtropical ocean. In this study, the transition is triggered by increasing the sea surface temperature (SST) and the LES runs until a statistically steady evolution of the Sc–Cu transition is achieved. The flow statistics are compared with those from a recycling-type method and it is found that the fringe method is more suitable for the current applications.

Potential of airborne lidar measurements for cirrus cloud studies

Abstract. Aerosol and water vapour measurements were performed with the lidar system WALES of Deutsches Zentrum für Luft- und Raumfahrt (DLR) in October and November 2010 during the first mission with the new German research aircraft G55-HALO. Curtains composed of lidar profiles beneath the aircraft show the vertical and horizontal distribution and variability of water vapour mixing ratio and backscatter ratio above Germany. Two missions on 3 and 4 November 2010 were selected to derive the water vapour mixing ratio inside cirrus clouds from the lidar instrument. A good agreement was found with in situ observations performed on a second research aircraft flying below HALO. ECMWF analysis temperature data are used to derive relative humidity fields with respect to ice (RHi) inside and outside of cirrus clouds from the lidar water vapour observations. The RHi variability is dominated by small-scale fluctuations in the water vapour fields while the temperature variation has a minor impact. The most frequent in-cloud RHi value from lidar observations is 98%. The RHi variance is smaller inside the cirrus than outside of the cloud. 2-D histograms of relative humidity and backscatter ratio show significant differences for in-cloud and out-of-cloud situations for two different cirrus cloud regimes. Combined with accurate temperature measurements, the lidar observations have a great potential for detailed statistical cirrus cloud and related humidity studies.

Characterizing Observed Midtopped Cloud Regimes Associated with Southern Ocean Shortwave Radiation Biases

Abstract Clouds strongly affect the absorption and reflection of shortwave and longwave radiation in the atmosphere. A key bias in climate models is related to excess absorbed shortwave radiation in the high-latitude Southern Ocean. Model evaluation studies attribute these biases in part to midtopped clouds, and observations confirm significant midtopped clouds in the zone of interest. However, it is not yet clear what cloud properties can be attributed to the deficit in modeled clouds. Present approaches using observed cloud regimes do not sufficiently differentiate between potentially distinct types of midtopped clouds and their meteorological contexts. This study presents a refined set of midtopped cloud subregimes for the high-latitude Southern Ocean, which are distinct in their dynamical and thermodynamic background states. Active satellite observations from CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) are used to study the macrophysical structure and microphysical properties of the new cloud regimes. The subgrid-scale variability of cloud structure and microphysics is quantified within the cloud regimes by identifying representative physical cloud profiles at high resolution from the radar–lidar (DARDAR) cloud classification mask. The midtopped cloud subregimes distinguish between stratiform clouds under a high inversion and moderate subsidence; an optically thin cold-air advection cloud regime occurring under weak subsidence and including altostratus over low clouds; optically thick clouds with frequent deep structures under weak ascent and warm midlevel anomalies; and a midlevel convective cloud regime associated with strong ascent and warm advection. The new midtopped cloud regimes for the high-latitude Southern Ocean will provide a refined tool for model evaluation and the attribution of shortwave radiation biases to distinct cloud processes and properties.

Application of active spaceborne remote sensing for understanding biases between passive cloud water path retrievals

AbstractBias between the Advanced Microwave Scanning Radiometer–EOS (AMSR‐E) version 2 and the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 5.1 cloud liquid water path (Wc) products are explored with the aid of coincident active observations from the CloudSat radar and the CALIPSO lidar. In terms of detection, the active observations provide precise separation of cloudy from clear sky and precipitating from nonprecipitating clouds. In addition, they offer a unique quantification of precipitation water path (Wp) in warm clouds. They also provide an independent quantification of Wc that is based on an accurate surface reference technique, which is an independent arbiter between the two passive approaches. The results herein establish the potential for CloudSat and CALIPSO to provide an independent assessment of bias between the conventional passive remote sensing methods from reflected solar and emitted microwave radiation. After applying a common data filter to the observations to account for sampling biases, AMSR‐E is biased high relative to MODIS in the global mean by 26.4 gm−2. The RMS difference in the regional patterns is 32.4 gm−2, which highlights a large geographical dependence in the bias which is related to the tropical transitions from stratocumulus to cumulus cloud regimes. The contributions of four potential sources for this bias are investigated by exploiting the active observations: (1) bias in MODIS related to solar zenith angle dependence accounts for −2.3 gm−2, (2) bias in MODIS due to undersampling of cloud edges accounts for 4.2 gm−2, (3) a wind speed and water vapor‐dependent “clear‐sky biase” in the AMSR‐E retrieval accounts for 6.3 gm−2, and (4) evidence suggests that much of the remaining 18 gm−2 bias is related to the assumed partitioning of the observed emission signal between cloud and precipitation water in the AMSR‐E retrieval. This is most evident through the correlations between the regional mean patterns of Wp and the Wc bias within the latitudes of 30°N and 30°S, suggesting that the assumption of a regionally invariant cloud/precipitation partitioning in the AMSR‐E algorithm is the likely causal factor.