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Aircraft observations in a cold-air outbreak to the north of the United Kingdom are used to examine the boundary layer and cloud properties in an overcast mixed-phase stratocumulus cloud layer and across the transition to more broken open-cellular convection. The stratocumulus cloud is primarily composed of liquid drops with small concentrations of ice particles and there is a switch to more glaciated conditions in the shallow cumulus clouds downwind. The rapid change in cloud morphology is accompanied by enhanced precipitation with secondary ice processes becoming active and greater thermodynamic gradients in the subcloud layer. The measurements also show a removal of boundary layer accumulation mode aerosols via precipitation processes across the transition that are similar to those observed in the subtropics in pockets of open cells. Simulations using a convection-permitting (1.5-km grid spacing) regional version of the Met Office Unified Model were able to reproduce many of the salient features of the cloud field although the liquid water path in the stratiform region was too low. Sensitivity studies showed that ice was too active at removing supercooled liquid water from the cloud layer and that improvements could be made by limiting the overlap between the liquid water and ice phases. Precipitation appears to be the key mechanism responsible for initiating the transition from closed- to open-cellular convection by decoupling the boundary layer and depleting liquid water from the stratiform cloud.

Four distinct types of cloud objects—tropical deep convection, boundary layer cumulus, stratocumulus, and overcast stratus—were previously identified from CERES Tropical Rainfall Measuring Mission (TRMM) data. Six additional types of cloud objects—cirrus, cirrocumulus, cirrostratus, altocumulus, transitional altocumulus, and solid altocumulus—are identified from CERES Aqua satellite data in this study. The selection criteria for the 10 cloud object types are based on CERES footprint cloud fraction and cloud-top pressure, as well as cloud optical depth for the high-cloud types. The cloud object is a contiguous region of the earth with a single dominant cloud-system type. The data are analyzed according to cloud object types, sizes, regions, and associated environmental conditions. The frequency of occurrence and probability density functions (PDFs) of selected physical properties are produced for the July 2006–June 2010 period. It is found that deep convective and boundary layer types dominate the total population while the six new types other than cirrostratus do not contribute much in the tropics and subtropics. There are pronounced differences in the size spectrum between the types, with the largest ones being of deep convective type and with stratocumulus and overcast types over the ocean basins off west coasts. The summary PDFs of radiative and cloud physical properties differ greatly among the size categories. For boundary layer cloud types, the differences come primarily from the locations of cloud objects: for example, coasts versus open oceans. They can be explained by considerable variations in large-scale environmental conditions with cloud object size, which will be further qualified in future studies.

This study aims to illustrate a general procedure based on well-known information theory concepts to select the channels from advanced satellite sounders that are most advantageous to assimilate both in clear-sky and overcast conditions using an ensemble-based estimate of forecast uncertainty. To this end, the standard iterative channel selection method, which is used to select the most informative channels from advanced infrared sounders for operational assimilation, was revisited so as to allow its use with measurements that have correlated errors. The method was here applied to determine a 24-humidity-sensitive-channel set that is small in size relative to a total of 8461 channels that are available on the Infrared Atmospheric Sounding Interferometer (IASI) on board the EUMETSAT Polar System MetOp satellites. The selected channels can be used to perform all-sky data assimilation experiments, in addition to those currently used for operational data assimilation of IASI data at ECMWF. Care was taken to include in the observation uncertainty used for channel selection the contributions arising from imperfect knowledge of the concentration of contaminants (except for cloud) in a given spectral channel. Also, (cumulative) weighting functions that provide a vertically resolved picture of the (total) number of degrees of freedom for signal expressed by a given set of measurements were introduced, which allows for the definition of a novel channel selection merit function that can be used to select measurements that are most sensitive to variations of a given parameter over a given atmospheric region (e.g., in the troposphere).

Observational studies have shown that the vertical overlap of cloudy layers separated by clear sky can exceed that of the random overlap assumption, suggesting a tendency toward minimum overlap. In addition, the rate of decorrelation of vertically continuous clouds with increasing layer separation is sensitive to the horizontal scale of the cloud scenes used. The authors give a heuristic argument that these phenomena result from data truncation, where overcast or single cloud layers are removed from the analysis. This occurs more frequently as the cloud sampling scale falls progressively below the typical cloud system scale. The postulate is supported by sampling artificial cyclic and subsequently more realistic fractal cloud scenes at various length scales. The fractal clouds indicate that the degree of minimal overlap diagnosed in previous studies for discontinuous clouds could result from sampling randomly overlapped clouds at spatial scales that are 30%–80% of the cloud system scale. Removing scenes with cloud cover exceeding 50% from the analysis reduces the impact of data truncation, with discontinuous clouds not minimally overlapped and the decorrelation of continuous clouds less sensitive to the sampling scale. Using CloudSat–CALIPSO data, a decorrelation length scale of approximately 4.0 km is found. In light of these results, the previously documented dependence of overlap decorrelation length scale on latitude is not entirely a physical phenomenon but can be reinterpreted as resulting from sampling cloud systems that increase significantly in size from the tropics to midlatitudes using a fixed sampling scale.

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.

A set of 327 dropsondes from the NOAA G-IV aircraft was used to create a composite analysis of the azimuthally averaged absolute angular momentum in the outflow layer of major Hurricane Ivan (2004). Inertial instability existed over a narrow layer in the upper troposphere between the 350- and 450-km radii. Isolines of potential and equivalent potential temperature showed that the conditions for both dry and moist symmetric instability were satisfied in the same region, but over a deeper layer from 9 to 12 km. The radial flow maximized at the outer edge of the unstable region. The symmetrically unstable state existed above a region of outward decrease of temperature between the cirrus overcast of the storm and clear air outside. It is hypothesized that the temperature gradient was created as a result of longwave heating within the cirrus overcast and longwave cooling outside the cloudy region. This produced isentropes that sloped upward with radius in the same region that absolute momentum surfaces were flat or sloping downward, thus creating symmetric instability. Although this instability typically follows rather than precedes intensification, limited numerical evidence suggests that the reestablishment of a symmetrically neutral state might influence the length of the intensification period.

This study proposes an automatic smart adaptive cloud identification (SACI) system for sky imagery and solar irradiance forecast. The system is deployed using off-the-shelf fish-eye cameras that offer substantial advantages in terms of cost when compared to industry-standard sky imagers. SACI uses a smart image categorization (SIC) algorithm that combines the sky images and solar irradiance measurements to classify sky conditions into three categories: clear, overcast, and partly cloudy. A cloud detection scheme, optimized for each image category, is used to quantify cloud cover from the sky images. SACI is optimized and validated against manually annotated images. Results show that SACI achieves overall classification accuracy higher than 90% and outperforms reference cloud detection methods. Cloud cover retrieved by SACI is used as an input for an artificial neural network (ANN) model that predicts 1-min average global horizontal irradiance (GHI), 5-, 10-, and 15-min ahead of time. The performance of the ANN forecasting model is assessed in terms of common error statistics (mean bias and root-mean-square error) and in terms of forecasting skill over persistence. The model proposed in this work achieves forecasting skills above 14%, 18%, and 19% over the persistence forecast for 5-, 10-, and 15-min forecasts, respectively.

A method is proposed to simultaneously calibrate shortwave (0.3–4 μm) global, direct, and scattering solar irradiance (GSI, DSI, and SSI, respectively) measurements. The method uses the World Radiation Reference (WRR) as a calibration standard and on-site radiation measurements as inputs. Two simple but effective techniques are used in the calibration. The first is to scale SSI and GSI detection sensitivities under overcast skies, which is based on the assumption that SSI should be equal to GSI if DSI is completely scattered and absorbed. The second is a new method to retrieve aerosol optical thickness (AOT), using the ratio of horizontal DSI (HDSI) to GSI measurements under clear and clean conditions. Thereafter, retrieved AOTs are used to drive a radiative transfer model to calculate atmospheric transmittance and then a ratio of GSI to the transmittance. Deviation of this ratio to the WRR is regarded as an indicator of GSI uncertainty, and the calibration transfer coefficient is derived as the WRR ratio. The method is applied to calibrate radiation measurements at Xianghe, China, during 2005. It is estimated from the derived transfer coefficients on 36 clear and clean days that uncertainties of DSI, GSI, and SSI measurements are within −4.0% to 2.9%, −5.9% to 2.4%, and −6.1% to 4.9%, respectively. The calibration is further validated based on comparisons of AOT at 750 nm retrieved from HDSI/GSI to Aerosol Robotic Network (AERONET) AOT products. The maximum deviation between two AOT products is 0.026. The unique advantage of this method lies in its potential applications in correcting historic radiation measurements and monitoring radiometer performance.

In this study, the representation of marine boundary layer clouds is investigated in the ECMWF model using observations from the Atmospheric Radiation Measurement (ARM) mobile facility deployment to Graciosa Island in the North Atlantic. Systematic errors in the occurrence of clouds, liquid water path, precipitation, and surface radiation are assessed in the operational model for a 19-month-long period. Boundary layer clouds were the most frequently observed cloud type but were underestimated by 10% in the model. Systematic but partially compensating surface radiation errors exist and can be linked to opposing cloud cover and liquid water path errors in broken (shallow cumulus) and overcast (stratocumulus) low-cloud regimes, consistent with previously reported results from the continental ARM Southern Great Plains (SGP) site. Occurrence of precipitation is overestimated by a factor of 1.5 at cloud base and by a factor of 2 at the surface, suggesting deficiencies in both the warm-rain formation and subcloud evaporation parameterizations. A single-column version of the ECMWF model is used to test combined changes to the parameterizations of boundary layer, autoconversion/accretion, and rain evaporation processes at Graciosa. Low-cloud occurrence, liquid water path, radiation biases, and precipitation occurrence are all significantly improved when compared to the ARM observations. Initial results from the modified parameterizations in the full model show improvement in the global top-of-the-atmosphere shortwave radiation, suggesting the reduced errors in the comparison at Graciosa are more widely applicable to boundary layer cloud around the globe.

Widespread stratocumulus clouds were observed on nine transects from seven research cruises to the southeastern tropical Pacific Ocean along 20°S, 75°–85°W in October–November of 2001–08. The nine transects sample a unique combination of synoptic and interannual variability affecting the clouds; their ensemble diagnoses longitude–vertical sections of the atmosphere, diurnal cycles of cloud properties and drizzle statistics, and the effect of stratocumulus clouds on surface radiation. Mean cloud fraction was 0.88, and 67% of 10-min overhead cloud fraction observations were overcast. Clouds cleared in the afternoon [1500 local time (LT)] to a minimum of fraction of 0.7. Precipitation radar found strong drizzle with reflectivity above 40 dBZ. Cloud-base (CB) heights rise with longitude from 1.0 km at 75°W to 1.2 km at 85°W in the mean, but the slope varies from cruise to cruise. CB–lifting condensation level (LCL) displacement, a measure of decoupling, increases westward. At night CB–LCL is 0–200 m and increases 400 m from dawn to 1600 LT, before collapsing in the evening. Despite zonal gradients in boundary layer and cloud vertical structure, surface radiation and cloud radiative forcing are relatively uniform in longitude. When present, clouds reduce solar radiation by 160 W m−2 and radiate 70 W m−2 more downward longwave radiation than clear skies. Coupled Model Intercomparison Project phase 3 (CMIP3) simulations of the climate of the twentieth century show 40 ± 20 W m−2 too little net cloud radiative cooling at the surface. Simulated clouds have correct radiative forcing when present, but models have ~50% too few clouds.

The long-term measurement records from the Atmospheric Radiation Measurement site on the Southern Great Plains show evidence of a bias in the ECMWF model’s surface irradiance. Based on previous studies, which have suggested that summertime shallow clouds may contribute to the bias, an evaluation of 146 days with observed nonprecipitating fair-weather cumulus clouds is performed. In-cloud liquid water path and effective radius are both overestimated in the model with liquid water path dominating to produce clouds that are too reflective. These are compensated by occasional cloud-free days in the model such that the fair-weather cumulus regime overall does not contribute significantly to the multiyear daytime mean surface irradiance bias of 23 W m−2. To further explore the origin of the bias, observed and modeled cloud fraction profiles over 6 years are classified and sorted based on the surface irradiance bias associated with each sample pair. Overcast low cloud conditions during the spring and fall seasons are identified as a major contributor. For samples with low cloud present in both observations and model, opposing surface irradiance biases are found for overcast and broken cloud cover conditions. A reduction of cloud liquid to a third for broken low clouds and an increase by a factor of 1.5 in overcast situations improves agreement with the observed liquid water path distribution. This approach of combining the model shortwave bias with a cloud classification helps to identify compensating errors in the model, providing guidance for a targeted improvement of cloud parameterizations.

The response of already polluted marine stratocumulus to additional particles was examined by studying the clouds where two ship tracks cross. Nearly 100 such crossings were collected and analyzed using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) multispectral imagery for the daytime passes off the western coast of the United States during the summer months of 4 years. To reduce biases in the retrieved cloud properties caused by the subpixel spatial structure of the clouds, results are presented only for ship tracks found in regions overcast by extensive layers of marine stratus. When two ship tracks cross, one of the tracks exhibits much larger changes in droplet radii when compared with the surrounding unpolluted clouds and is referred to as the dominant ship track. The clouds at the crossing typically exhibit properties that are closer to those of the dominant than to those of the subordinate ship track. To determine whether the additional particles at the crossing affect the dominant track, local gradients in the retrieved cloud properties near the crossing were determined for both ship tracks. Based on the gradients, the clouds at the junction were found to have significantly smaller droplet radii and significantly larger column droplet number concentrations than were predicted based on their values in both ship tracks on either side of the crossing. Comparing the effects of particle loading at the crossings and elsewhere along the ship tracks revealed that the effects decreased as the column droplet number concentration of the clouds being affected increased.

A large fraction of the atmospheric aerosol load reaching the free troposphere is frequently located above low clouds. Most commonly observed aerosols above clouds are carbonaceous particles generally associated with biomass burning and boreal forest fires, and mineral aerosols originating in arid and semiarid regions and transported across large distances, often above clouds. Because these aerosols absorb solar radiation, their role in the radiative transfer balance of the earth–atmosphere system is especially important. The generally negative (cooling) top-of-the-atmosphere direct effect of absorbing aerosols may turn into warming when the light-absorbing particles are located above clouds. The actual effect depends on the aerosol load and the single scattering albedo, and on the geometric cloud fraction. In spite of its potential significance, the role of aerosols above clouds is not adequately accounted for in the assessment of aerosol radiative forcing effects due to the lack of measurements. This paper discusses the basis of a simple technique that uses near-UV observations to simultaneously derive the optical depth of both the aerosol layer and the underlying cloud for overcast conditions. The two-parameter retrieval method described here makes use of the UV aerosol index and reflectance measurements at 388 nm. A detailed sensitivity analysis indicates that the measured radiances depend mainly on the aerosol absorption exponent and aerosol–cloud separation. The technique was applied to above-cloud aerosol events over the southern Atlantic Ocean, yielding realistic results as indicated by indirect evaluation methods. An error analysis indicates that for typical overcast cloudy conditions and aerosol loads, the aerosol optical depth can be retrieved with an accuracy of approximately 54% whereas the cloud optical depth can be derived within 17% of the true value.

In-flight microphysical measurements in classical freezing-rain conditions were used to study the vertical and horizontal characteristics of the precipitation and associated low-ceiling, stratiform clouds, which are usually present as overcast in freezing-rain conditions. The low overcast is usually based in the surface cold layer but may extend up into the inversion, or transition layer, between the overrunning warm air and the surface cold layer. This gives the cloud an unusual temperature-inverted structure—supercooled in the lower half and warmer than freezing in the upper half. The low cloud is also subject to wind shear and turbulence that is due to the warm overrunning. The apparent effects of this are 1) increased cloud droplet concentrations in clusters up to a few hundred meters wide that occur sporadically in the cloud layer, 2) possible forcing of cloudy air upward from lower levels against the resistance of the temperature inversion and into the transition layer, and 3) highly variable air temperatures during level flight in the inversion layer.

The paper presents a robust technique for cloud clearing of satellite imagery. The proposed algorithm combines mathematical morphological techniques with a conventional cloud clearing scheme to restore clear sky values. The derived equivalent clear sky brightness temperature plays a very important role in numerical weather prediction, climate research, and monitoring. The developed methodology uses distinct approaches for reconstruction of partially clouded domains and overcast regions. It is found that the algorithm is especially suitable for pre- or postmonsoon months, where there is a high percentage of partially cloudy and small overcast cloudy regions. The algorithm is tested for the Kalpana Very High Resolution Radiometer (VHRR) thermal infrared (TIR) band data acquired over the oceanic region adjoining India throughout the month of May 2009. It is found that the algorithm is able to clear 25% of cloudy pixels with an RMSE of 1.2 K for brightness temperature.

The total downwelling shortwave (SWD) and longwave (LWD) radiation and its components are assessed for the limited-area version of the Global Environmental Multiscale Model (GEM-LAM) against Atmospheric Radiation Measurements (ARM) at two sites: the southern Great Plains (SGP) and the North Slope of Alaska (NSA) for the 1998–2005 period. The model and observed SWD and LWD are evaluated as a function of the cloud fraction (CF), that is, for overcast and clear-sky conditions separately, to isolate and analyze different interactions between radiation and 1) atmospheric aerosols and water vapor and 2) cloud liquid water. Through analysis of the mean diurnal cycle and normalized frequency distributions of surface radiation fluxes, the primary radiation error in GEM-LAM is seen to be an excess in SWD in the middle of the day. The SWD bias results from a combination of underestimated CF and clouds, when present, possessing a too-high solar transmissivity, which is particularly the case for optically thin clouds. Concurrent with the SWD bias, a near-surface warm bias develops in GEM-LAM, particularly at the SGP site in the summer. The ultimate cause of this warm bias is difficult to uniquely determine because of the range of complex interactions between the surface, atmospheric, and radiation processes that are involved. Possible feedback loops influencing this warm bias are discussed. The near-surface warm bias is the primary cause of an excess clear-sky LWD. This excess is partially balanced with respect to the all-sky LWD by an underestimated CF, which causes a negative bias in simulated all-sky emissivity. It is shown that there is a strong interaction between all the components influencing the simulated surface radiation fluxes with frequent error compensation, emphasizing the need to evaluate the individual radiation components at high time frequency.

The physical and radiative properties of tropical deep convective systems for the period from January to August 1998 are examined with the use of Clouds and the Earth’s Radiant Energy System Single-Scanner Footprint (SSF) data from the Tropical Rainfall Measuring Mission satellite. Deep convective (DC) cloud objects are contiguous regions of satellite footprints that fulfill the DC criteria (i.e., overcast footprints with cloud optical depths >10 and cloud-top heights >10 km). Extended cloud objects (ECOs) start with the original cloud object but include all other cloudy footprints within a rectangular box that completely covers the original cloud object. Most of the non-DC footprints are overcast but have optical depths and/or cloud-top heights that are too low to fit the DC criteria. The histograms of cloud physical and radiative properties are analyzed according to the size of the ECO and the SST of the underlying ocean. Larger ECOs are associated with greater magnitudes of large-scale upward motion, which supports stronger convection for larger sizes of ECOs. This leads to shifts toward higher values in the DC distributions of cloud-top height, albedo, condensate water path, and cloud optical depth. However, non-DC footprints become less reflective with increasing ECO size, as the longer-lived large convective systems have more time to develop thin cirrus anvils. The proportion of DC footprints remains fairly constant with size. The proportion of DC footprints also remains nearly constant with SST within a given size class, although the number of footprints per object increases with SST for large objects. As SSTs increase, there is a decrease in the proportion of updraft water that goes into detrainment, causing the non-DC distributions of albedo, condensate water path, and cloud optical depth to shift toward lower values. The all-cloud distributions of cloud-top temperature and outgoing longwave radiation (OLR) shift toward lower values as SST increases owing to the increase in convective instability with SST. Both the DC and non-DC distributions of cloud-top temperature do not change much with satellite precession cycle, supporting the fixed anvil temperature hypothesis of Hartmann and Larson. When a joint histogram is formed from the cloud-top pressures and cloud optical depths of the ECOs, it is very similar to the corresponding histogram of the deep convective weather state obtained by cluster analysis of International Satellite Cloud Climatology Project data.

Fu–Liou’s delta-four-stream (with a two-stream option) radiative transfer model has been implemented in the U.S. Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS)1 to calculate solar and thermal infrared fluxes in 6 shortwave and 12 longwave bands. The model performance is evaluated at high resolution for clear-sky and overcast conditions against the observations from the Southern Great Plains of the Atmospheric Radiation Measurement Program. In both cases, use of the Fu–Liou model provides significant improvement over the operational implementation of the standard Harshvardhan radiation parameterization in both shortwave and longwave fluxes. A sensitivity study of radiative flux on clouds reveals that the choices of cloud effective radius schemes for ice and liquid water are critical to the flux calculation due to the effects on cloud optical properties. The sensitivity study guides the selection of optimal cloud optical properties for use in the Fu–Liou parameterization as implemented in COAMPS. The new model is then used to produce 3-day forecasts over the continental United States for a winter and a summer month. The verifications of parallel runs using the standard and new parameterizations show that Fu–Liou dramatically reduces the model’s systematic warm bias in the upper troposphere in both winter and summer. The resultant cooling modifies the atmospheric stability and moisture transport, resulting in a significant reduction in the upper-tropospheric wet bias. Overall ice and liquid water paths are also reduced. At the surface, Fu–Liou reduces the negative temperature and sea level pressure biases by providing more accurate radiative heating rates to the land surface model. The error reductions increase with forecast length as the impact of improved radiative fluxes accumulates over time. A combination of the two- and four-stream options results in major computational efficiency gains with minimal loss in accuracy.

Relationships between physical properties are studied for three types of marine boundary layer cloud objects identified with the Clouds and the Earth’s Radiant Energy System (CERES) footprint data from the Tropical Rainfall Measuring Mission satellite between 30°S and 30°N. Each cloud object is a contiguous region of CERES footprints that have cloud-top heights below 3 km, and cloud fractions of 99%–100% (overcast type), 40%–99% (stratocumulus type), or 10%–40% (shallow cumulus type). These cloud fractions represent the fraction of ∼2 km × 2 km Visible/Infrared Scanner pixels that are cloudy within each ∼10 km × 10 km footprint. The cloud objects have effective diameters that are greater than 300 km for the overcast and stratocumulus types, and greater than 150 km for the shallow cumulus type. The Spearman rank correlation coefficient is calculated between many microphysical/optical [effective radius (re), cloud optical depth (τ), albedo, liquid water path, and shortwave cloud radiative forcing (SW CRF)] and macrophysical [outgoing longwave radiation (OLR), cloud fraction, cloud-top temperature, longwave cloud radiative forcing (LW CRF), and sea surface temperature (SST)] properties for each of the three cloud object types. When both physical properties are of the same category (microphysical/optical or macrophysical), the magnitude of the correlation tends to be higher than when they are from different categories. The magnitudes of the correlations also change with cloud object type, with the correlations for overcast and stratocumulus cloud objects tending to be higher than those for shallow cumulus cloud objects. Three pairs of physical properties are studied in detail, using a k-means cluster analysis: re and τ, OLR and SST, and LW CRF and SW CRF. The cluster analysis of re and τ reveals that for each of the cloud types, there is a cluster of cloud objects with negative slopes, a cluster with slopes near zero, and two clusters with positive slopes. The joint OLR and SST probability plots show that the OLR tends to decrease with SST in regions with boundary layer clouds for SSTs above approximately 298 K. When the cloud objects are split into “dry” and “moist” clusters based on the amount of precipitable water above 700 hPa, the associated OLRs increase with SST throughout the SST range for the dry clusters, but the OLRs are roughly constant with SST for the moist cluster. An analysis of the joint PDFs of LW CRF and SW CRF reveals that while the magnitudes of both LW and SW CRFs generally increase with cloud fraction, there is a cluster of overcast cloud objects that has low values of LW and SW CRF. These objects are generally located near the Sahara Desert, and may be contaminated with dust. Many of these overcast objects also appear in the re and τ cluster with negative slopes.

The spatial variation of melt energy can influence snow cover depletion rates and in turn be influenced by the spatial variability of shortwave irradiance to snow. The spatial variability of shortwave irradiance during melt under uniform and discontinuous evergreen canopies at a U.S. Rocky Mountains site was measured, analyzed, and then compared to observations from mountain and boreal forests in Canada. All observations used arrays of pyranometers randomly spaced under evergreen canopies of varying structure and latitude. The spatial variability of irradiance for both overcast and clear conditions declined dramatically, as the sample averaging interval increased from minutes to 1 day. At daily averaging intervals, there was little influence of cloudiness on the variability of subcanopy irradiance; instead, it was dominated by stand structure. The spatial variability of irradiance on daily intervals was higher for the discontinuous canopies, but it did not scale reliably with canopy sky view. The spatial variation in irradiance resulted in a coefficient of variation of melt energy of 0.23 for the set of U.S. and Canadian stands. This variability in melt energy smoothed the snow-covered area depletion curve in a distributed melt simulation, thereby lengthening the duration of melt by 20%. This is consistent with observed natural snow cover depletion curves and shows that variations in melt energy and snow accumulation can influence snow-covered area depletion under forest canopies.

To aid in understanding the role that marine boundary layer (MBL) clouds play in climate and assist in improving their representations in general circulation models (GCMs), their long-term microphysical and macroscale characteristics are quantified using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the National Aeronautics and Space Administration’s (NASA’s) Terra satellite. Six years of MODIS pixel-level cloud products are used from oceanic study regions off the west coasts of California, Peru, the Canary Islands, Angola, and Australia where these cloud types are common. Characterizations are given for their organization (macroscale structure), the associated microphysical properties, and the seasonal dependencies of their variations for scales consistent with the size of a GCM grid box (300 km × 300 km). MBL mesoscale structure is quantified using effective cloud diameter CD, which is introduced here as a simplified measure of bulk cloud organization; it is straightforward to compute and provides descriptive information beyond that offered by cloud fraction. The interrelationships of these characteristics are explored while considering the influences of the MBL state, such as the occurrence of drizzle. Several commonalities emerge for the five study regions. MBL clouds contain the best natural examples of plane-parallel clouds, but overcast clouds occur in only about 25% of the scenes, which emphasizes the importance of representing broken MBL cloud fields in climate models (that are subgrid scale). During the peak months of cloud occurrence, mesoscale organization (larger CD) increases such that the fractions of scenes characterized as “overcast” and “clumped” increase at the expense of the “scattered” scenes. Cloud liquid water path and visible optical depth usually trend strongly with CD, with the largest values occurring for scenes that are drizzling. However, considerable interregional differences exist in these trends, suggesting that different regression functionalities exist for each region. For peak versus off-peak months, the fraction of drizzling scenes (as a function of CD) are similar for California and Angola, which suggests that a single probability distribution function might be used for their drizzle occurrence in climate models. The patterns are strikingly opposite for Peru and Australia; thus, the contrasts among regions may offer a test bed for model simulations of MBL drizzle occurrence.

Three boundary layer cloud object types—overcast, stratocumulus, and cumulus—that occurred over the Pacific Ocean during January–August 1998 are identified from the Clouds and the Earth’s Radiant Energy System (CERES) single scanner footprint data. Characteristics of each cloud object type matched with atmospheric states are examined for large regions in the tropics and subtropics and for different size categories. Stratocumulus cloud objects dominate the entire boundary layer cloud population in all regions and size categories. Overcast cloud objects, which have the largest average size, are more prevalent in the subtropics and near the coastal regions, while cumulus cloud objects are prevalent over the open oceans and the equatorial regions, particularly within the small-size categories. Cloud objects with equivalent diameters less than 75 km are excluded in the analysis. The differences between the tropical and subtropical statistical distributions of cloud properties are small for liquid water path (LWP), cloud optical depth, and top-of-the-atmosphere (TOA) albedo, but large for cloud-top temperature and outgoing longwave radiation (OLR), for each of the three cloud object types. The larger cloud objects have higher LWPs, cloud optical depths, TOA albedos, and OLRs, but lower SSTs and cloud-top heights for the stratocumulus and overcast types. Lower-tropospheric stability seems to be the primary factor for the differences in the distributions of cloud physical properties between the regions or between the size categories. Atmospheric dynamics also play a role in determining the differences in the distributions of cloud physical properties between the size categories, but not a significant role for those between the types or between the regions. The latter may be due to uncertainties in the matched vertical velocity data. When the three cloud object types are combined in small regions, lower-tropospheric stability determines the transition of boundary layer cloud types along a Pacific transect. The proportion of each type is the most important factor for diagnosing the combined cloud properties along this transect, such as LWP, cloud optical depth, and TOA albedo. Atmospheric dynamics also play complicated roles in determining the combined cloud properties along this transect.

Cloud droplet effective radius (DER) and liquid water path (LWP) are two key parameters for the quantitative assessment of cloud effects on the exchange of energy and water. Chang and Li presented an algorithm using multichannel measurements made at 3.7, 2.1, and 1.6 μm to retrieve a cloud DER vertical profile for improved cloud LWP estimation. This study applies the multichannel algorithm to the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data on the Aqua satellite, which also carries the Advanced Microwave Scanning Radiometer (AMSR-E) for measuring cloud LWP and precipitation. By analyzing one day of coincident MODIS and AMSR-E observations over the tropical oceans between 40°S and 40°N for overcast warm clouds (>273 K) having optical depths between 3.6 and 23, the effects of DER vertical variation on the MODIS-derived LWP are reported. It is shown that the LWP tends to be overestimated if the DER increases with height within the cloud and underestimated if the DER decreases with height within the cloud. Despite the uncertainties in both MODIS and AMSR-E retrievals, the result shows that accounting for the DER vertical variation reduces the mean biases and root-mean-square errors between the MODIS- and AMSR-E–derived LWPs. Besides, the manner in which the DER changes with height has the potential for differentiating precipitative and nonprecipitative warm clouds. For precipitating clouds, the DER at the cloud top is substantially smaller than the DER at the cloud base. For nonprecipitating clouds, however, the DER differences between the cloud top and the cloud base are much less.

The Monte Carlo Independent Column Approximation (McICA) method for computing domain-average radiative fluxes allows a flexible treatment of unresolved cloud structure, and it is unbiased with respect to the full ICA, but its flux estimates contain conditional random noise. Here, tests of McICA in the ECHAM5 atmospheric GCM are reported. ECHAM5 provides an interesting test bed for McICA because it carries prognostic variables for the subgrid-scale probability distribution of total water content, which allows us to determine subgrid-scale cloud variability directly from the resolved-scale model variables. Three experiments with differing levels of radiative noise, each consisting of ten 6-yr runs, are performed to estimate the impact of McICA noise on simulated climate. In an experiment that attempted to deliberately maximize McICA noise, a systematic reduction in low cloud fraction occurred. For a more reasonable implementation of McICA, the impact of noise is very small, although statistically discernible. In terms of the impacts of noise, McICA appears to be a viable approach for use in ECHAM5. However, to improve the simulation of cloud radiative effects, realistic representation of both unresolved and resolved cloud structures is needed, which remains a challenging problem. Comparison of ECHAM5 data with a global cloud system–resolving model dataset and with International Satellite Cloud Climatology Project data suggested two problems related to unresolved cloud structures. First, ECHAM5 appears to underestimate subgrid-scale cloud variability. This problem seems partly related to the use of the beta distribution scheme for total water content in ECHAM5: in its current form, the scheme is unable to generate highly inhomogeneous clouds (relative standard deviation of condensate amount >1). Second, it appears that in ECHAM5, overcast cloud layers occur too frequently and partially cloudy layers too rarely. This problem is not unique to the beta distribution scheme; in fact, it is more pronounced when using an alternative, relative humidity–based cloud fraction scheme.

Studies using International Satellite Cloud Climatology Project (ISCCP) data have reported decreases in cloud optical depth with increasing temperature, thereby suggesting a positive feedback in cloud optical depth as climate warms. The negative cloud optical depth and temperature relationships are questioned because ISCCP employs threshold assumptions to identify cloudy pixels that have included partly cloudy pixels. This study applies the spatial coherence technique to one month of Advanced Very High Resolution Radiometer (AVHRR) data over the Pacific Ocean to differentiate overcast pixels from the partly cloudy pixels and to reexamine the cloud optical depth–temperature relationships. For low-level marine stratus clouds studied here, retrievals from partly cloudy pixels showed 30%–50% smaller optical depths, 1°–4°C higher cloud temperatures, and slightly larger droplet effective radii, when they were compared to retrievals from the overcast pixels. Despite these biases, retrievals for the overcast and partly cloudy pixels show similar negative cloud optical depth–temperature relationships and their magnitudes agree with the ISCCP results for the midlatitude and subtropical regions. There were slightly negative droplet effective radius–temperature relationships, and considerable positive cloud liquid water content–temperature relationships indicated by aircraft measurements. However, cloud thickness decreases appear to be the main reason why cloud optical depth decreases with increasing temperature. Overall, cloud thickness thinning may explain why similar negative cloud optical depth–temperature relationships are found in both overcast and partly cloudy pixels. In addition, comparing the cloud-top temperature to the air temperature at 740 hPa indicates that cloud-top height generally rises with warming. This suggests that the cloud thinning is mainly due to the ascending of cloud base. The results presented in this study are confined to the midlatitude and subtropical Pacific and may not be applicable to the Tropics or other regions.

Time series of daily broadband surface albedo for 1998 and 1999 have been analyzed from six locations in the network of 22 Atmospheric Radiation Measurement Program Solar–Infrared Radiation Stations distributed from central Kansas to central Oklahoma. Two of the stations are in Kansas, and four are in Oklahoma; together they reasonably encompass the variation in geography in the southern Great Plains. Daily precipitation totals locally measured or obtained from nearby Oklahoma Mesonet stations and time series of biweekly maximum normalized difference vegetation index obtained from NOAA’s Advanced Very High Resolution Radiometer were used to determine linkages between surface albedo and amount of precipitation and degree of green vegetation. As part of this determination, daily albedo was categorized according to sky condition, that is, clear, partly cloudy, or overcast, with appropriate boundaries for each category. The more notable results are the following: 1) 2-yr mean annual albedos varied by more than 20% among the six sites, the lowest albedo being 0.18 and the highest albedo being 0.22; 2) the numerical difference was about 4 times the maximum interannual mean difference among the six stations, indicating the importance of geographic location; 3) for sites with a large amount of bare soil, a systematic decrease in albedo in response to rainfall events and a systematic increase in albedo as the soil dried were observed; 4) at the one site with total vegetation cover, that is, no bare soil, albedo response to precipitation events was suppressed; 5) no relation was found between mean annual albedo and annual precipitation; 6) whether days were classified as clear or partly cloudy had little influence on daily albedo, but overcast days typically reduced albedo, sometimes substantially; and 7) the main contributor to low albedos on overcast days with rain was the wet surface; the contribution by the overcast sky was secondary.

Cloud overlapping has been a major issue in climate studies owing to a lack of reliable information available over both oceans and land. This study presents the first near-global retrieval and analysis of single-layer and overlapped cloud vertical structures and their optical properties retrieved by applying a new method to the Moderate Resolution Imaging Spectroradiometer (MODIS) data. Taking full advantage of the MODIS multiple channels, the method can differentiate cirrus overlapping lower water clouds from single-layer clouds. Based on newly retrieved cloud products using daytime Terra/MODIS 5-km overcast measurements sampled in January, April, July, and October 2001, global statistics of the frequency of occurrence, cloud-top pressure/temperature (Pc/Tc), visible optical depth (τVIS), and infrared emissivity (ɛ) are presented and discussed. Of all overcast scenes identified over land (ocean), the MODIS data show 61% (52%) high clouds (Pc < 500 hPa), 39% (48%) lower clouds (Pc > 500 hPa), and an extremely low occurrence (

A record of single-layer and overcast low cloud (stratus) properties has been generated using approximately 4000 h of data collected from January 1997 to December 2002 at the Atmospheric Radiation Measurement (ARM) Southern Great Plains Central Facility (SCF). The cloud properties include liquid-phase and liquid-dominant mixed-phase low cloud macrophysical, microphysical, and radiative properties including cloud-base and -top heights and temperatures, and cloud physical thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding; cloud liquid water path (LWP) and content (LWC), and cloud-droplet effective radius (re) and number concentration (N) derived from the macrophysical properties and radiometer data; and cloud optical depth (τ), effective solar transmission (γ), and cloud/top-of-atmosphere albedos (Rcldy/RTOA) derived from Eppley precision spectral pyranometer measurements. The cloud properties were analyzed in terms of their seasonal, monthly, and hourly variations. In general, more stratus clouds occur during winter and spring than in summer. Cloud-layer altitudes and physical thicknesses were higher and greater in summer than in winter with averaged physical thicknesses of 0.85 and 0.73 km for day and night, respectively. The seasonal variations of LWP, LWC, N, τ, Rcldy, and RTOA basically follow the same pattern with maxima and minima during winter and summer, respectively. There is no significant variation in mean re, however, despite a summertime peak in aerosol loading. Although a considerable degree of variability exists, the 6-yr average values of LWP, LWC, re, N, τ, γ, Rcldy, and RTOA are 151 gm−2 (138), 0.245 gm−3 (0.268), 8.7 μm (8.5), 213 cm−3 (238), 26.8 (24.8), 0.331, 0.672, and 0.563 for daytime (nighttime). A new conceptual model of midlatitude continental low clouds at the ARM SGP site has been developed from this study. The low stratus cloud amount monotonically increases from midnight to early morning (0930 LT), and remains large until around local noon, then declines until 1930 LT when it levels off for the remainder of the night. In the morning, the stratus cloud layer is low, warm, and thick with less LWC, while in the afternoon it is high, cold, and thin with more LWC. Future parts of this series will consider other cloud types and cloud radiative forcing at the ARM SCF.

The respective errors caused by the gamma-weighted two-stream approximation and the effective thickness approximation for computing the domain-averaged broadband shortwave irradiance are evaluated using cloud optical thicknesses derived from 1 h of radiance measurements by the Moderate Resolution Imaging Spectrometer (MODIS) over footprints of Clouds and the Earth’s Radiant Energy System (CERES) instruments. Domains are CERES footprints of which dimension varies approximately from 20 to 70 km, depending on the viewing zenith angle of the instruments. The average error in the top-of-atmosphere irradiance at a 30° solar zenith angle caused by the gamma-weighted two-stream approximation is 6.1 W m−2 (0.005 albedo bias) with a one-layer overcast cloud where a positive value indicates an overestimate by the approximation compared with the irradiance computed using the independent column approximation. Approximately one-half of the error is due to deviations of optical thickness distributions from a gamma distribution and the other half of the error is due to other approximations in the model. The error increases to 14.7 W m−2 (0.012 albedo bias) when the computational layer dividing the cloud layer is increased to four. The increase is because of difficulties in treating the correlation of cloud properties in the vertical direction. Because the optical thickness under partly cloudy conditions, which contribute two-thirds of cloudy footprints, is smaller, the error is smaller than under overcast conditions; the average error for partly cloudy condition is −2.4 W m−2 (−0.002 albedo bias) at a 30° solar zenith angle. The corresponding average error caused by the effective thickness approximation is 0.5 W m−2 for overcast conditions and −21.5 W m−2 (−0.018 albedo bias) for partly cloudy conditions. Although the error caused by the effective thickness approximation depends strongly on the optical thickness, its average error under overcast conditions is smaller than the error caused by the gamma-weighted two-stream approximation because the errors at small and large optical thicknesses cancel each other. Based on these error analyses, the daily average error caused by the gamma-weighted two-stream and effective thickness approximations is less than 2 W m−2.

Algorithms for cloud detection (cloud mask) and classification (cloud type) at high and midlatitudes using data from the Advanced Very High Resolution Radiometer (AVHRR) on board the current NOAA satellites and future polar Meteorological and Operational Weather Satellites (METOP) of the European Organisation for the Exploitation of Meteorological Satellites have been extensively validated over northern Europe and the adjacent seas. The algorithms have been described in detail in Part I and are based on a multispectral grouped threshold approach, making use of cloud-free radiative transfer model simulations. The thresholds applied in the algorithms have been validated and tuned using a database interactively built up over more than 1 yr of data from NOAA-12, -14, and -15 by experienced nephanalysts. The database contains almost 4000 rectangular (in the image data)-sized targets (typically with sides around 10 pixels), with satellite data collocated in time and space with atmospheric data from a short-range NWP forecast model, land cover characterization, elevation data, and a label identifying the given cloud or surface type as interpreted by the nephanalyst. For independent and objective validation, a large dataset of nearly 3 yr of collocated surface synoptic observation (Synop) reports, AVHRR data, and NWP model output over northern and central Europe have been collected. Furthermore, weather radar data were used to check the consistency of the cloud type. The cloud mask performs best over daytime sea and worst at twilight and night over land. As compared with Synop, the cloud cover is overestimated during night (except for completely overcast situations) and is underestimated at twilight. The algorithms have been compared with the more empirically based Swedish Meteorological and Hydrological Institute (SMHI) Cloud Analysis Model Using Digital AVHRR Data (SCANDIA), operationally run at SMHI since 1989, and results show that performance has improved significantly.

Retrievals of cloud properties from satellite imagery often invoke the assumption that the fields of view are overcast when cloud-contaminated, even though a significant fraction are only partially cloud-covered. The overcast assumption leads to biases in the retrieved cloud properties: cloud amounts and droplet effective radii are typically overestimated, while visible optical depths, cloud altitudes, cloud liquid water amounts, and column droplet number concentrations are typically underestimated. In order to estimate these biases, a retrieval scheme was developed to obtain the properties of clouds for partially covered imager fields of view. The partly cloudy pixel retrieval scheme is applicable to single-layered cloud systems and invokes the assumption that clouds that only partially cover a field of view are at the same altitude as nearby clouds from the same layer that completely cover imager pixels. The properties of the retrieval are illustrated through its application to 2-km Visible and Infrared Scanner (VIRS) data from the Tropical Rainfall Measuring Mission (TRMM) for a marine stratocumulus scene. The scene was chosen because the cloud properties are typical of such systems based on an analysis of VIRS data for February and March 1998. Comparisons of properties for clouds in partly cloudy pixels and those for clouds in nearby overcast pixels reveal that the optical depths and droplet effective radii are generally smaller for the clouds in the partly cloudy pixels. In addition, for pixel-scale cloud fractions between 0.2 and 0.8, optical depth, droplet effective radius, and column droplet number concentration decrease slowly with decreasing cloud cover fraction. The changes are only about 20%–30%, while cloud cover fraction changes by 80%. For comparison, changes in optical depth and column number concentration retrieved using a threshold method decrease by 80%–90%. As long as the cloud cover in partly cloudy pixels is greater than about 0.1, uncertainties in the estimates of the cloud altitudes and of the radiances for the cloud-free portions of the fields of view give rise to uncertainties in the retrieved cloud properties that are comparable to the uncertainties in the properties retrieved for overcast pixels.

In this paper, an empirical equation is presented that can be used to estimate shortwave cloud optical thickness from measurements and analysis of shortwave broadband irradiances. When applied to a time series of broadband observations, this method can predict cloud optical thickness distributions that are very similar to those obtained using the algorithm of Min and Harrison (henceforth the Min algorithm). For a given site, medians of the Min algorithm–derived and empirically derived distributions differ by less than 10%. This level of agreement holds over a wide geographical range of sites. The equation is designed for fully overcast skies, surface albedos less than 0.3, and a cosine of the solar zenith angle greater than 0.15.

In recent years, global warming concerns have focused attention on cloud radiative forcing and its accurate encapsulation in radiative transfer measurement and modeling programs. At present, this process is constrained by the dynamic movement and inhomogeneity of cloud structure. This study attempts to quantify the UV sky radiance distribution induced by a partial and overcast stratiform cloud field while addressing some of the inherent spatial and temporal errors resulting from cloud. For this purpose, high-quality azimuthally averaged 2-min measurements of erythemal UV-B sky radiance distribution were undertaken by a variable sky-view platform at Hobart, Australia (42.90°S, 147.33°E). Measurements were subsequently compared with Monte Carlo radiative transfer simulations using both a multifractal and plane-parallel homogenous (PPH) cloud field. Data were also compared with several empirical parameterizations. Results at solar zenith angles of 30° and 50° show that for overcast conditions, the multifractal model is superior to the PPH model. For broken cloud conditions, the radiance measurements are biased toward higher instances of direct-beam interruption by cloud. This tends to smooth the near-sun sky radiance field whereas the multifractal model under the same conditions continues to exhibit the circumsolar effect, indicating that its performance may be still valid for radiation modeling. An empirical parameterization of the same multifractal model produced similar sky radiance profiles, warranting its use in radiative transfer models.

Previously, the acquisition of sky-view factor data for climate studies has been time consuming and dependent on postprocessing. However, advances in technology now mean that techniques using fish-eye imagery can be algorithmically processed in real time to provide an instant calculation of the sky-view factor. Although data collection is often limited due to the need to survey under homogenous overcast skies, vast datasets can now be rapidly assembled for the training of proxy “all weather” techniques. An artificial neural network is used to estimate the sky-view factor using raw global positioning system (GPS) data and is shown to explain over 69% of the variation of the sky-view factor in urban areas.

Several changes in U.S. observational practice [in particular, the introduction of the Automated Surface Observing System (ASOS) in the early 1990s] have led to a challenging heterogeneity of time series of most ground-based cloud observations. In this article, an attempt is made to preserve/restore the time series of average low cloud cover (LCC) over the country up to the year 2001 using cloud sky condition and cloud-base height information collected in the national archive data and to describe its spatial and temporal variability. The switch from human observations to ASOS can be bridged through the use of frequency of overcast/broken cloudiness. During the past 52 yr, the nationwide LCC appears to exhibit a significant increase but all of this increase occurred prior to the early 1980s and thereafter tends to decrease. This finding is consistent with similar changes in the frequency of days with precipitation. When the cloud-type information was still available (i.e., during the pre-ASOS peri...

This paper examines the impact of orographically induced mesoscale heterogeneities on the macroscopic behavior of planetary boundary layer (PBL) stratiform clouds, and implements and tests a physically based parameterization of this effect in the University of California, Los Angeles (UCLA), atmospheric general circulation model (AGCM). The orographic variance and associated thermal circulations induce inhomogeneities in the cloud field that can significantly alter the PBL evolution; an effect that has been largely ignored in existing climate models. The impact of this effect on AGCM simulations is examined and the mechanisms at work are studied by analyzing a series of Cloud System Resolving Model (CSRM) simulations. Both the CSRM and AGCM results show that, in the absence of the orographic effect, the continental PBL tends to be in one of two regimes: the solid regime characterized by a cold and overcast PBL and the broken regime characterized by a low time-mean cloud incidence and a large-ampl...

Testing general circulation model parameterizations against observations is traditionally done by comparing simulated and observed, time-averaged quantities, such as monthly mean cloud cover, evaluated on a stationary grid. This approach ignores the dynamical aspects of clouds, such as their life cycle characteristics, spatial coverage, temporal duration, and internal variability. In this study, a complementary Lagrangian approach to the validation of modeled tropical cloudiness is explored. An automated cloud detection and tracking algorithm is used to observe and track overcast decks of cloud in a consecutive set of hourly Meteosat-5 images and the National Center for Atmospheric Research Community Climate Model version 3 (NCAR CCM3). The algorithm is applied to the deep convective cloud systems of the tropical Indian Ocean region during a 49-day period of the 1999 winter monsoon season. Observations of precipitation are taken from the Tropical Rainfall Measuring Mission (TRMM) satellite in add...

To relate the error associated with 1D radiative calculations to the geometrical scales of cloud organization and/or in-cloud optical inhomogeneities, a new idealized methodology, based on a Fourier statistical technique, has been developed. Three-dimensional cloud fields with variability over a selected range of horizontal spatial scales and consistent vertical structure can be obtained and controlled by a small number of parameters, which relate directly to the dynamical and thermodynamical meteorology of the situation to be examined. This initial study deals with marine stratocumulus. Two experiments are conducted: an overcast situation and a broken cloud case with maximum cloud cover of 80%. For each experiment, five cloud fields are generated with the dominant organizational scale changing from 1.4 to 22 km, while all other quantities—such as cloud cover, cloud liquid water, and total water variance—remain constant. For each scene, three radiative calculations are performed for solar zenith angles of 08 and 608: a plane parallel (PP) calculation, similar to that commonly implemented in general circulation models; an independent pixel approximation (IPA); and a full 3D calculation. The ‘‘PP bias’’ (IPA-PP) is used to assess cloud optical homogeneity approximation, while the ‘‘IPA bias’’ (3D-IPA) measures the impact of horizontal photon transport. For the overcast scenes, the neglect of horizontal photon transport was found to be unimportant, and the IPA calculation gives accurate results. For the broken cloud case, this was only true for clouds with dominant horizontal spatial scales exceeding 10 km. With a scale of 2 km or less, the IPA bias in reflectivity, transmissivity, and absorption could exceed 5%. This indicates that even for shallow cloud systems, cloud geometry can play an important role. The sign of the bias depends critically on the solar angle, with IPA over- (under) estimating reflectivity for high (low) sun angles. The PP bias in reflectivity was also found to be around 5% for both cases, comparable to the IPA bias, and smaller than previous estimates for this cloud type. Additional sensitivity tests prove this to be due to the vertical cloud structure. Vertically resolving the subcloud adiabatic liquid profile leads to a more opaque cloud upper boundary, reducing photon penetration into the cloud layer, and thus also PP biases. Additionally, for the broken cloud case it was found that changes in cloud fraction with height are translated by cloud overlap rules into effective horizontal variability in the liquid water path, further reducing biases. Taking a vertically uniform slab with identical integrated properties led to much larger PP biases comparable to previous estimates. Thus, models with sufficient vertical resolution are likely to suffer from smaller PP biases than previously estimated.

The primary purpose of this study is to assess the performance of 1D solar radiative transfer codes that are used currently both for research and in weather and climate models. Emphasis is on interpretation and handling of unresolved clouds. Answers are sought to the following questions: (i) How well do 1D solar codes interpret and handle columns of information pertaining to partly cloudy atmospheres? (ii) Regardless of the adequacy of their assumptions about unresolved clouds, do 1D solar codes perform as intended? One clear-sky and two plane-parallel, homogeneous (PPH) overcast cloud cases serve to elucidate 1D model differences due to varying treatments of gaseous transmittances, cloud optical properties, and basic radiative transfer. The remaining four cases involve 3D distributions of cloud water and water vapor as simulated by cloud-resolving models. Results for 25 1D codes, which included two line-by-line (LBL) models (clear and overcast only) and four 3D Monte Carlo (MC) photon transport ...

Data from 24 airport weather stations along the north–south axis (35°–45°N) of the Appalachian Mountains are used to show a significant rising trend in cloud-ceiling height over the past three decades. The mean change in cloud-ceiling height was 4.14 ± 1.03 m yr−1 [mean ± 1 SE (standard error), p ≤ 0.001] across all stations. The trend was negative (−2.22 ± 0.67 m yr−1) for the six stations south of 37.5°N, but positive (6.26 ± 0.89 m yr−1) for the 18 stations north of this latitude. Mean ceiling height for broken cloud cover was higher and rising faster than mean ceiling height for overcast cloud cover. There were strong seasonal patterns that varied between the northernmost and southernmost stations; differences were most pronounced during the spring and summer months. Some of the potential ecological effects on high-elevation forests, where the transition from deciduous to coniferous forest is thought to be controlled by the height of the cloud base, are discussed.

Subsynoptic, warm core low pressure areas are frequently observed along the west coast of subtropical South America during austral winter. These so-called coastal lows (CLs) tend to develop as an upper-air, midlatitude ridge is approaching the subtropical Andes and, therefore, while pressure is increasing aloft and farther to the south. These CLs have a profound impact in the coastal weather associated with a rapid transition from clear skies and stronger than average equatorward low-level flow to overcast conditions and relaxed equatorward (or even poleward) flow. Weather conditions inland mostly reflect the associated changes in the strength and height of the base of the subsidence inversion. In this work, a mesoscale simulation of a typical CL episode is performed using a numerical weather prediction model [the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5)] Comparison with observations reveals that the model simulation properly captures the large-scale pattern as we...

Spatial and temporal variations of surface albedo on the North Slope of Alaska were investigated using both ground-based tower measurements and satellite remote sensing data. Ground-based measurements of incident and reflected solar radiation at several stations along the Dalton Highway over the period 1985–98 are used to determine in situ surface albedo. Advanced Very High Resolution Radiometer (AVHRR)-derived surface albedo were obtained from AVHRR Polar Pathfinder products, available from the National Snow and Ice Data Center, using a modified cloud mask. AVHRR-derived surface albedo agrees closely with in situ measurements. Results from this study indicate that surface albedo varies from greater than 0.9 for a snow-covered land surface under overcast conditions to less than 0.1 for a wet tundra land surface. Five distinct temporal periods are discerned, based on seasonal variations of surface albedo: winter stationary, spring snowmelt, postsnowmelt, summer stationary, and autumn freeze-up per...

A record of single-layer and overcast low-level Arctic stratus cloud properties has been generated using data collected from May to September 2000 at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) (71.3°N, 156.6°W) site near Barrow, Alaska. The record includes liquid-phase and liquid dominant mixed-phase Arctic stratus macrophysical, microphysical, and radiative properties, as well as surface radiation budget and cloud radiative forcing. The macrophysical properties consist of cloud fractions, cloud-base/top heights and temperatures, and cloud thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding. The microphysical properties include cloud liquid water path and content, and cloud-droplet effective radius and number concentration obtained from microwave radiometer brightness temperature measurements, and the new cloud parameterization. The radiative properties contain cloud optical depth, effective solar transmission, and surface/cloud/top-of-...

The microwave radiometer‐derived cloud liquid water path (LWP) and a profile of radar reflectivity are used to derive a profile of cloud liquid water content (LWC). Two methods (M1 and M2) have been developed for inferring the profile of cloud-droplet effective radius (re) in liquid phase or liquid dominant mixed phase stratocumulus clouds. The M1-inferred re profile is proportional to a previously derived layer-mean re and to the ratio of the radar reflectivity to the integrated radar reflectivity. This algorithm is independent of the radar calibration and is applicable to overcast low-level stratus clouds that occur during the day because it is dependent on solar transmission observations. In order to extend the retrieval algorithm to a wider range of conditions, a second method is described that uses an empirical relationship between effective radius and radar reflectivity based on theory and the results of M1. Sensitivity studies show that the surface-retrieved re is more sensitive to the variation of radar reflectivity when the radar reflectivity is large, and the uncertainties of retrieved re related to the assumed vertically constant cloud-droplet number concentration and shape of the size distribution are about 9% and 2%, respectively. For validation, a total of 10 h of aircraft data and 36 h of surface data were collected over the Atmospheric Radiation Measurement (ARM) program’s Southern Great Plains (SGP) site during the March 2000 cloud intensive observational period (IOP). More detailed comparisons in two cases quantify the agreement between the aircraft data and the surface retrievals. When the temporal averages of the two datasets increase from 1 min to 30 min, the means and standard deviations of differences between the two datasets decrease from 22.5% 6 84% to 1.3% 6 42.6% and their corresponding correlation coefficients increase from 0.47 to 0.8 for LWC; and decrease from 24.8% 6 36.4% to 23.3% 6 22.5% with increased coefficients from 0.64 to 0.94 for re (both M1 and M2). The agreement between the aircraft and surface data in the 30-min averages suggests that the two platforms are capable of characterizing the cloud microphysics over this temporal scale. On average, the surface retrievals are unbiased relative to the aircraft in situ measurements. However, when only the 1-min averaged aircraft data within 3 km of the surface site were selected, the means and standard deviations of differences between the two datasets are larger (23.4% 6 113% for LWC and 28.3% 6 60.7% for re) and their correlation coefficients are smaller (0.32 for LWC and 0.3 for re) than those from all 1-min samples. This result suggests that restricting the comparison to the samples better matched in space and time between the surface and aircraft data does not result in a better comparison.

A new single-column model for the cloudy boundary layer, described in a companion paper, is tested for a variety of regimes. To represent the subgrid-scale variability, the model uses a joint probability density function (PDF) of vertical velocity, temperature, and moisture content. Results from four different cases are presented and contrasted with large eddy simulations (LES). The cases include a clear convective layer based on the Wangara experiment, a trade wind cumulus layer from the Barbados Oceanographic and Meteorological Experiment (BOMEX), a case of cumulus clouds over land, and a nocturnal marine stratocumulus boundary layer. Results from the Wangara experiment show that the model is capable of realistically predicting the diurnal growth of a dry convective layer. Compared to the LES, the layer produced is slightly less well mixed and entrainment is somewhat slower. The cloud cover in the cloudy cases varied widely, ranging from a few percent cloud cover to nearly overcast. In each of the cloudy cases, the parameterization predicted cloud fractions that agree reasonably well with the LES. Typically, cloud fraction values tended to be somewhat smaller in the parameterization, and cloud bases and tops were slightly underestimated. Liquid water content was generally within 40% of the LES-predicted values for a range of values spanning almost two orders of magnitude. This was accomplished without the use of any case-specific adjustments.

A 1D infrared radiative transfer model that handles clouds with subgrid-scale horizontal variability is developed and tested. It assumes that fluctuations in cloud absorptance optical depth k across layers (and collections of layers) can be described by gamma distributions. Unlike homogeneous clouds, flux incident at a level inside a horizontally inhomogeneous cloud requires explicit computation of transmittance to all other levels in the cloud. Consequently, in addition to estimates of variability for each layer, variability between any two levels must be specified too. Scattering by hydrometeors and a general treatment of cloud overlap are included in this model. Solutions for isothermal and nonisothermal Planck source functions are presented. For the synthetic cloudy atmospheres used here, the new model produces errors for outgoing longwave radiation (OLR) and cloud cooling rates that are typically more than an order of magnitude smaller than those associated with the conventional homogeneous cloud model (as used in all GCMs at present). It is shown that up- and downwelling fluxes and cloud cooling rates can depend much on subgrid-scale variability. For high overcast clouds with realistic variability, OLR can be up to 20 W m 22 more than that predicted by a conventional homogeneous model using the same mean k. At the same time, cooling rate errors at cloud top and cloud base due to the homogeneous assumption can be up to 625%; the sign depending primarily on mean k and magnitude of variability. For lower, thicker clouds, the homogeneous assumption leads primarily to errors in cloud-top cooling. The new code usually remedies these errors greatly. This model, and its solar counterpart, are used currently in the Canadian Centre for Climate Modelling and Analysis GCM.

Cloud remote sensing techniques are conventionally based on the independent pixel approximation (IPA). Here, three-dimensional (3D) radiative effects on IPA-based retrieved optical thickness from a visible-wavelength moderate-resolution (about 1 km) sensor are investigated. A Monte Carlo 3D radiative transfer model and a lognormal spectral cloud model are used to simulate monochromatic radiance reflected from overcast boundary layer cloud. A characterization of statistical properties of the optical thickness by the mean (M) and variance (S2) of the logarithm of the optical thickness is proposed, where S represents a degree of cloud inhomogeneity. Biases in retrieved values of the two parameters with the IPA are defined as ΔM and ΔS2 and attributed to neglect of net horizontal radiative transport in the IPA. Sensitivities of ΔM and ΔS2 are tested with respect to geometrical roughness, M, S, mean geometrical thickness, spectral exponent of optical thickness fluctuation, ground surface reflectance, ...

The cloud and radiation fields produced by the operational ECMWF forecasts are assessed using observations from the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site over the April–May 1999 period. Over the first 36 h of the forecasts, most of the model fields, taken over a 24-h time window (either 0–24, 6–30, or 12–36 h) are generally in good agreement with each other. Comparisons of model fields taken from any such 24-h time window with observations are therefore representative of the quality of the ECMWF model physical parameterizations. The surface radiation fluxes are assessed separately for clear-sky, overcast, and whole-sky situations. For clear-sky fluxes, differences between model and observations are linked to differences in humidity and temperature profiles, the characterization of aerosols, and potential problems in the radiation schemes. For clear-sky conditions, the downward longwave radiation is usually within the accuracy of the measurements. For ove...

An algorithm is developed for the gamma-weighted discrete ordinate two-stream approximation that computes profiles of domain-averaged shortwave irradiances for horizontally inhomogeneous cloudy atmospheres. The algorithm assumes that frequency distributions of cloud optical depth at unresolved scales can be represented by a gamma distribution though it neglects net horizontal transport of radiation. This algorithm is an alternative to the one used in earlier studies that adopted the adding method. At present, only overcast cloudy layers are permitted.

The usual procedure for retrieving the optical thickness of liquid water clouds from satellite-measured radiances is based on the assumption of plane-parallel layers composed of liquid water droplets. This study investigates the validity of this assumption from Advanced Earth Orbiting Satellite–Polarization and Directionality of the Earth's Reflectances (ADEOS–POLDER) observations. To do that, the authors take advantage of the multidirectional viewing capability of the POLDER instrument, which functioned nominally aboard ADEOS from November 1996 to June 1997. The usual plane-parallel cloud model composed of water droplets with an effective radius of 10 μm provides a reasonable approximation of the angular dependence in scattering at visible wavelengths from overcast liquid water clouds for moderate solar zenith angles. However, significant differences between model and observations appear in the rainbow direction and for the smallest observable values of scattering angle (Θ < 90°). A better overa...