Cloud Radar Data Research Articles

Leading and Trailing Anvil Clouds of West African Squall Lines

Abstract The anvil clouds of tropical squall-line systems over West Africa have been examined using cloud radar data and divided into those that appear ahead of the leading convective line and those on the trailing side of the system. The leading anvils are generally higher in altitude than the trailing anvil, likely because the hydrometeors in the leading anvil are directly connected to the convective updraft, while the trailing anvil generally extends out of the lower-topped stratiform precipitation region. When the anvils are subdivided into thick, medium, and thin portions, the thick leading anvil is seen to have systematically higher reflectivity than the thick trailing anvil, suggesting that the leading anvil contains numerous larger ice particles owing to its direct connection to the convective region. As the leading anvil ages and thins, it retains its top. The leading anvil appears to add hydrometeors at the highest altitudes, while the trailing anvil is able to moisten a deep layer of the atmosphere.

A 3D cloud‐construction algorithm for the EarthCARE satellite mission

AbstractThis article presents and assesses an algorithm that constructs 3D distributions of cloud from passive satellite imagery and collocated 2D nadir profiles of cloud properties inferred synergistically from lidar, cloud radar and imager data. It effectively widens the active–passive retrieved cross‐section (RXS) of cloud properties, thereby enabling computation of radiative fluxes and radiances that can be compared with measured values in an attempt to perform radiative closure experiments that aim to assess the RXS. For this introductory study, A‐train data were used to verify the scene‐construction algorithm and only 1D radiative transfer calculations were performed.The construction algorithm fills off‐RXS recipient pixels by computing sums of squared differences (a cost function F) between their spectral radiances and those of potential donor pixels/columns on the RXS. Of the RXS pixels with F lower than a certain value, the one with the smallest Euclidean distance to the recipient pixel is designated as the donor, and its retrieved cloud properties and other attributes such as 1D radiative heating rates are consigned to the recipient. It is shown that both the RXS itself and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery can be reconstructed extremely well using just visible and thermal infrared channels. Suitable donors usually lie within 10 km of the recipient. RXSs and their associated radiative heating profiles are reconstructed best for extensive planar clouds and less reliably for broken convective clouds.Domain‐average 1D broadband radiative fluxes at the top of the atmosphere (TOA) for (21 km)2 domains constructed from MODIS, CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data agree well with coincidental values derived from Clouds and the Earth's Radiant Energy System (CERES) radiances: differences between modelled and measured reflected shortwave fluxes are within ±10 W m−2 for ∼35% of the several hundred domains constructed for eight orbits. Correspondingly, for outgoing longwave radiation ∼65% are within ±10 W m−2. Copyright © 2011 Royal Meteorological Society and Crown in the right of Canada

CloudSat as a Global Radar Calibrator

Abstract The calibration of the CloudSat spaceborne cloud radar has been thoroughly assessed using very accurate internal link budgets before launch, comparisons with predicted ocean surface backscatter at 94 GHz, direct comparisons with airborne cloud radars, and statistical comparisons with ground-based cloud radars at different locations of the world. It is believed that the calibration of CloudSat is accurate to within 0.5–1 dB. In the present paper it is shown that an approach similar to that used for the statistical comparisons with ground-based radars can now be adopted the other way around to calibrate other ground-based or airborne radars against CloudSat and/or to detect anomalies in long time series of ground-based radar measurements, provided that the calibration of CloudSat is followed up closely (which is the case). The power of using CloudSat as a global radar calibrator is demonstrated using the Atmospheric Radiation Measurement cloud radar data taken at Barrow, Alaska, the cloud radar data from the Cabauw site, Netherlands, and airborne Doppler cloud radar measurements taken along the CloudSat track in the Arctic by the Radar System Airborne (RASTA) cloud radar installed in the French ATR-42 aircraft for the first time. It is found that the Barrow radar data in 2008 are calibrated too high by 9.8 dB, while the Cabauw radar data in 2008 are calibrated too low by 8.0 dB. The calibration of the RASTA airborne cloud radar using direct comparisons with CloudSat agrees well with the expected gains and losses resulting from the change in configuration that required verification of the RASTA calibration.

Understanding the Importance of Microphysics and Macrophysics for Warm Rain in Marine Low Clouds. Part I: Satellite Observations

Abstract The importance of macrophysical variables [cloud thickness, liquid water path (LWP)] and microphysical variables (effective radius re, effective droplet concentration Neff) on warm drizzle intensity and frequency across the tropics and subtropics is studied. In this first part of a two-part study, Moderate Resolution Imaging Spectroradiometer (MODIS) optical and CloudSat cloud radar data are used to understand warm rain in marine clouds. Part II uses simple heuristic models. Cloud-top height and LWP substantially increase as drizzle intensity increases. Droplet radius estimated from MODIS also increases with cloud radar reflectivity (dBZ) but levels off as dBZ > 0, except where the influence of continental pollution is present, in which case a monotonic increase of re with drizzle intensity occurs. Off the Asian coast and over the Gulf of Mexico, re values are smaller (by several μm) and Neff values are larger compared to more remote marine regions. For heavy drizzle intensity, both re and Neff values off the Asian coast and over the Gulf of Mexico approach re and Neff values in more remote marine regions. Drizzle frequency, defined as profiles in which maximum dBZ > −15, increases dramatically and nearly uniformly when cloud tops grow from 1 to 2 km. Drizzle frequencies exceed 90% in all regions when LWPs exceed 250 g m−2 and Neff values are below 50 cm−3, even in regions where drizzle occurs infrequently on the whole. The fact that the relationship among drizzle frequency, LWP, and Neff is essentially the same for all regions suggests a near universality among tropical and subtropical regions.

A Method to Merge WSR-88D Data with ARM SGP Millimeter Cloud Radar Data by Studying Deep Convective Systems

Abstract A decade of collocated Atmospheric Radiation Measurement Program (ARM) 35-GHz Millimeter Cloud Radar (MMCR) and Weather Surveillance Radar-1988 Doppler (WSR-88D) data over the ARM Southern Great Plains (SGP) site have been collected during the period of 1997–2006. A total of 28 winter and 45 summer deep convective system (DCS) cases over the ARM SGP site have been selected for this study during the 10-yr period. For the winter cases, the MMCR reflectivity, on average, is only 0.2 dB lower than that of the WSR-88D, with a correlation coefficient of 0.85. This result indicates that the MMCR signals have not been attenuated for ice-phase convective clouds, and the MMCR reflectivity measurements agree well with the WSR-88D, regardless of their vastly different characteristics. For the summer nonprecipitating convective clouds, however, the MMCR reflectivity, on average, is 10.6 dB lower than the WSR-88D measurement, and the average differences between the two radar reflectivities are nearly constant with height above cloud base. Three lookup tables with Mie calculations have been generated for correcting the MMCR signal attenuation. After applying attenuation correction for the MMCR reflectivity measurements, the averaged difference between the two radars has been reduced to 9.1 dB. Within the common sensitivity range (−10 to 20 dBZ), the mean differences for the uncorrected and corrected MMCR reflectivities have been reduced to 6.2 and 5.3 dB, respectively. The corrected MMCR reflectivities were then merged with the WSR-88D data to fill in the gaps during the heavy precipitation periods. This merged dataset provides a more complete radar reflectivity profile for studying convective systems associated with heavier precipitation than the original MMCR dataset. It also provides the intensity, duration, and frequency of the convective systems as they propagate over the ARM SGP for climate modelers. Eventually, it will be possible to improve understanding of the cloud-precipitation processes, and evaluate GCM predictions using the long-term merged dataset, which could not have been done with either the MMCR or the WSR-88D dataset alone.

Cirrus cloud optical and microphysical properties determined from AIRS infrared spectra

We developed an efficient thermal infrared radiative transfer model on the basis of the delta‐four‐stream approximation to facilitate high‐spectral‐resolution remote sensing applications under cirrus cloudy conditions in the Atmospheric Infrared Sounder (AIRS) data. Numerical experiments demonstrated that sensitivity in the 800‐1130 cm−1 thermal infrared window spectral region is sufficiently distinct for the inference of cirrus optical depth and ice crystal mean effective size and shape factor. We analyzed 312 nighttime cirrus pixels in two AIRS granules over ARM TWP sites and applied the radiative transfer model to these cases to determine cirrus optical depth and ice crystal mean effective size, based on a look‐up table approach. The retrieval program has been evaluated through an error budget analysis and validation effort by comparing AIRS‐retrieved results with those determined from ground‐based millimeter‐wave cloud radar data at ARM TWP sites, for five AIRS pixels that were collocated and coincident with ground‐based measurements.

A new algorithm for the extraction of cloud parameters using multipeak analysis of cloud radar data First application and preliminary results

Spectral and polarimetric signatures of echoes, obtained with a vertically pointing millimeter wave radar are examined with regard of their potential to retrieve range resolved microphysical characteristics of clouds, including the detection of mixed phases. A novel target classification algorithm based on this information was applied to deep frontal clouds. Examples of spectral/polarimetric profiles are shown to illustrate the retrieval technique, and first findings on microphysical structures and dynamics of such cloud systems are presented.

Cirrus cloud microphysical properties and air motion statistics using cloud radar Doppler moments: Water content, particle size, and sedimentation relationships

Improved knowledge of ice cloud properties and the processes that maintain them is needed for modeling applications. A cirrus cloud property retrieval algorithm is applied to a 7‐year Cloud Radar data set collected at the Atmospheric Radiation Measurement Program ground sites. With this dataset, the ice cloud vertical structure is studied in terms of Temperature (T). Then the interrelationships between the ice particle size, ice water content (IWC), and mass‐weighted sedimentation rate are investigated. The mass‐weighted sedimentation rate is usually parameterized as a function T only or IWC only. Here, the mass weighted sedimentation rate is parameterized as a joint function of ice water content and T for both midlatitude and tropical ice clouds. We further examine the validity of several commonly used GCM parameterizations of ice sedimentation rate in comparison to the cirrus cloud results derived from measurements.

An evaluation of operational GOES‐derived single‐layer cloud top heights with ARSCL data over the ARM Southern Great Plains Site

Cloud top heights retrieved from Geostationary Operational Environmental Satellite (GOES) data are evaluated using comparisons to 5 years of surface‐based cloud radar and lidar data taken at the Atmospheric Radiation Measurement (ARM) program's site near Lamont, Oklahoma. Separate daytime and nighttime algorithms developed at NASA Langley Research Center (LaRC) applied to GOES imager data and an operational CO2‐slicing technique applied to GOES sounder data are tested. Comparisons between the daytime, nighttime and CO2‐slicing cloud top heights and the surface retrievals yield mean differences of −0.84 ± 1.48 km, −0.56 ± 1.31 km, and −1.30 ± 2.30 km, respectively, for all clouds. The errors generally increase with increasing cloud altitude and decreasing optical thickness. These results, which highlight some of the challenges associated with passive satellite cloud height retrievals, are being used to guide development of a blended LaRC/CO2‐slicing cloud top height product with accuracies suitable for assimilation into weather forecast models.

Vertical structure of tropical oceanic convective clouds and its relation to precipitation

Cloudsat cloud radar data are used to investigate the vertical structure of cloud systems of the ITCZ across the West and East Pacific and its contribution to precipitation. Cloud radar data are collocated with precipitation rates from the Advanced Microwave Scanning Radiometer (AMSR) to examine differences in cloud top PDFs for different rain rate regimes. Heavily precipitating clouds have high tops that are nearly two km deeper than moderately raining or non‐raining high clouds. Rain rate increases with cloud height, especially for clouds higher than 12 km, with nearly a tenfold rain rate increase from 12 km to the tropical tropopause. Clouds with tops below 9.5 km contribute 38% to total rainfall in the West Pacific and 47% in the East Pacific, but they contribute 60% and 74% to total rain area, respectively.

Cloud Vertical Structure Observed from Space and Ship over the Bay of Bengal and the Eastern Tropical Pacific

The cloud vertical structure at two remote tropical oceanic convective locations is characterized using both ship-based (35 GHz) and space-based (94 GHz) cloud radar data. The field experiment data depicted the full diurnal cycle and detail of the vertical structures, while the CloudSat sampling was more extensive, but did not coincide with the field experiments. One location is the monsoonal Bay of Bengal, sampled as part of the Joint Air-Sea Monsoon Interaction Experiment (JASMINE), and the other location is the eastern Pacific intertropical convergence zone, sampled during the Eastern Pacific Investigation of Climate (EPIC) experiment. Both ship- and space-based radar datasets find more high cloudiness (9-14 km altitude with an 11-12 km maximum) over the Bay of Bengal than over the eastern tropical Pacific, postulated to reflect the advection of cirrus by upper-level easterly winds. Low-level cloudiness, with some extending into what may be cumulus congestus, is more characteristic of the eastern tropical Pacific than the Bay of Bengal. CloudSat cloud fractions over the eastern Pacific were only ˜ one-third those over the Bay of Bengal, in contrast to comparable cloud fractions within the field experiment datasets. A thin melting-level cloud population was also more apparent in the JASMINE data than in the EPIC field experiment data, but the larger CloudSat dataset showed the opposite. These differences discourage regional generalities based on a few weeks of point sampling. Pre-monsoon-onset conditions included a slight afternoon low cloud amount maximum combined with typically one warm rain event per night. High thin cirrus was common (cloud fraction of ˜35% with cloud optical depths of 2 or less and ice water paths typically < 40 g m-2). After monsoon onset, the ship-based cloud radar documented examples of coherent relationships among cloud structure, precipitation, and the larger-scale wind field. CloudSat did not detect much precipitating low cloud during its pre-monsoon time period, but did sample the upper-level clouds at approximately the maximum and minimum of their diurnal range. An intriguing finding is that CloudSat perceived a greater daytime occurrence of the highest clouds with reflectivitives < 10 dBZ at both locations, a finding replicated with a year’s data covering the full, ocean-only, tropical belt. We speculate the daytime high cloud may reflect remains of outflow from previous convection. The comparison also highlights differences in the Rayleigh versus Mie responses of the two radars.

3-D polarised simulations of space-borne passive mm/sub-mm midlatitude cirrus observations: a case study

Abstract. Global observations of ice clouds are needed to improve our understanding of their impact on earth's radiation balance and the water-cycle. Passive mm/sub-mm has some advantages compared to other space-borne cloud-ice remote sensing techniques. The physics of scattering makes forward radiative transfer modelling for such instruments challenging. This paper demonstrates the ability of a recently developed RT code, ARTS-MC, to accurately simulate observations of this type for a variety of viewing geometries corresponding to operational (AMSU-B, EOS-MLS) and proposed (CIWSIR) instruments. ARTS-MC employs an adjoint Monte-Carlo method, makes proper account of polarisation, and uses 3-D spherical geometry. The actual field of view characteristics for each instrument are also accounted for. A 3-D midlatitude cirrus scenario is used, which is derived from Chilbolton cloud radar data and a stochastic method for generating 3-D ice water content fields. These demonstration simulations clearly demonstrate the beamfilling effect, significant polarisation effects for non-spherical particles, and also a beamfilling effect with regard to polarisation.

Finescale Vertical Structure and Evolution of a Preconvective Dryline on 19 June 2002

Abstract High-resolution airborne cloud radar data and other International H2O Project datasets are used to describe the vertical structure of an unusual prefrontal dryline. This dryline, observed in northwestern Kansas on 19 June 2002, first progressed eastward and tilted toward the west, and later became more stationary and reversed its tilt, toward the moist side. The convective boundary layer (CBL) depth difference also reversed: only in the later phase did the dry-side CBL become deeper than on the moist side. Echo and single/dual-Doppler velocity data in a vertical transect across the dryline suggest a solenoidal circulation dynamically consistent with the observed horizontal buoyancy gradient. Both this gradient and the solenoidal circulation reversed in the later phase. Simultaneously, confluence toward the dryline increased, resulting in an increasing moisture gradient as well as a deepening CBL in the dryline convergence zone. It is speculated that the baroclinically generated horizontal vorticity contributed to this CBL deepening, as the sign of this vorticity was opposite to that of the low-level wind shear on the opposite side of the dryline in both phases. Deep-convective initiation appears to have resulted from this local CBL deepening, leading to a total elimination of convective inhibition near the dryline.

Horizontal Convective Rolls in Cold Air over Water: Buoyancy Characteristics of Coherent Plumes Detected by an Airborne Radar

Abstract Aircraft and airborne cloud radar data are used to describe the vertical structure of the convective boundary layer (CBL) during cold-air outbreaks over Lake Michigan in January 2004. Two days with mesoscale cloud street structure and a day with cellular organization are contrasted. The radar reflectivity and vertical velocity structure of the CBL, as well as the radar-inferred topography of the CBL inversion, are collected along flight legs normal to the cloud streets. High-resolution horizontal and vertical transects of the dual-Doppler airflow field capture horizontal convective roll circulations on one day. Coherent structures within the CBL are analyzed as echo plumes, updraft plumes, and CBL domes. Only updraft plumes have the characteristics of buoyant thermals. Updrafts are narrower, weaker, and less buoyant on the no-roll day, but the differences in characteristics between two cloud street days are larger than those between the no-roll day and the two cloud street days. The lack of a clear buoyancy signal in echo plumes and under CBL domes is attributed to a temporal phase shift between maximum buoyancy, maximum ice particle size, and maximum overshooting in thermals, and the transience of convective updrafts.

Cirrus Clouds and the Large-Scale Atmospheric State: Relationships Revealed by Six Years of Ground-Based Data

AbstractThe properties of cirrus clouds observed at the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) in Oklahoma are documented from a nearly continuous 6-yr record of 35-GHz cloud radar data. Cirrus frequency over the ACRF is 23% and 28% of the time in the warm (May–September) and cold seasons (November–March), respectively, with maxima and minima during the period studied of 30% and 16% in the warm season and 34% and 24% in the cold seasons. Cirrus, as defined here, reveal a seasonal oscillation in their macroscale properties that can be traced to the seasonal deepening of the troposphere in the Southern Plains region. While the average bulk microphysical properties do not change significantly from season to season, the variability of certain parameters demonstrates seasonal change. It is shown that the properties of cirrus clouds vary perceptively with the large-scale vertical motion. Using NCEP–NCAR reanalysis data to define the large-scale meteorological state when cirrus are observed at the ACRF, the authors find that cirrus tend to exist within a maximum in upper-tropospheric humidity and downstream of the peak upper-tropospheric vertical motion. Cirrus that exist in large-scale ascent upstream of the synoptic-scale middle-tropospheric ridge axis are shown to have higher water contents than cirrus that exist in large-scale subsidence downstream of the ridge axis, although the overall nature of the statistical distributions of water contents do not change greatly, suggesting that it may be difficult to parameterize the properties of cirrus based solely on large-scale vertical motion. The layer-mean particle size, on the other hand, shows no such sensitivity to the large-scale vertical motion.

Association of Tropical Cirrus in the 10–15-km Layer with Deep Convective Sources: An Observational Study Combining Millimeter Radar Data and Satellite-Derived Trajectories

Abstract In this paper, millimeter cloud radar (MMCR) and Geosynchronous Meteorological Satellite (GMS) data are combined to study the properties of tropical cirrus that are common in the 10–15-km layer of the tropical troposphere in the western Pacific. Millimeter cloud radar observations collected by the Atmospheric Radiation Measurement program on the islands of Manus and Nauru in the western and central equatorial Pacific during a 12-month period spanning 1999 and 2000 show differences in cirrus properties: over Manus, where clouds above 7 km are observed 48% of the time, the cirrus are thicker and warmer on average and the radar reflectivity and Doppler velocity are larger; over Nauru clouds above 7 km are observed 23% of time. To explain the differences in cloud properties, the relationship between tropical cirrus and deep convection is examined by combining the radar observations with GMS satellite-derived back trajectories. Using a data record of 1 yr, it is found that 47% of the cirrus observed over Manus can be traced to a deep convective source within the past 12 h while just 16% of the cirrus observed over Nauru appear to have a convective source within the previous 12 h. Of the cirrus that can be traced to deep convection, the evolution of the radar-observed cloud properties is examined as a function of apparent cloud age. The radar Doppler moments and ice water path of the observed cirrus at both sites generally decrease as the cirrus age increase. At Manus, it is found that cirrus during boreal winter typically advect over the site from the southeast from convection associated with the winter monsoon, while during boreal summer, the trajectories are mainly from the northeast. The properties of these two populations of cirrus are found to be different, with the winter cirrus having higher concentrations of smaller particles. Examining statistics of the regional convection using Tropical Rainfall Measuring Mission (TRMM), it is found that the properties of the winter monsoon convection in the cirrus source region are consistent with more intense convection compared to the convection in the summer source region.

The Retrieval of Ice-Cloud Properties from Cloud Radar and Lidar Synergy

Abstract Clouds are an important component of the earth’s climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L’Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE’98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.

Cluster analysis of cloud regimes and characteristic dynamics of midlatitude synoptic systems in observations and a model

Global climate models typically do not correctly simulate cloudiness associated with midlatitude synoptic systems because coarse grid spacing prevents them from resolving dynamics occurring at smaller scales and there exist no adequate parameterizations for the effects of these subgrid‐scale dynamics. Comparison of modeled and observed cloud properties averaged over similar regimes (e.g., compositing) aids the diagnosis of simulation errors and identification of meteorological forcing responsible for producing particular cloud conditions. This study uses a k‐means clustering algorithm to objectively classify satellite cloud scenes into distinct regimes based on grid box mean cloud fraction, cloud reflectivity, and cloud top pressure. The spatial domain is the densely instrumented southern Great Plains site of the Atmospheric Radiation Measurement Program, and the time period is the cool season months (November–March) of 1999–2001. As a complement to the satellite retrievals of cloud properties, lidar and cloud radar data are analyzed to examine the vertical structure of the cloud layers. Meteorological data from the constraint variational analysis is averaged for each cluster to provide insight on the large‐scale dynamics and advective tendencies coincident with specific cloud types. Meteorological conditions associated with high and low subgrid spatial variability are also investigated for each cluster. Cloud outputs from a single‐column model version of the GFDL AM2 atmospheric model forced with meteorological boundary conditions derived from observations and a numerical weather prediction model were compared to observations for each cluster in order to determine the accuracy with which the model reproduces attributes of specific cloud regimes.

Daytime Cloud Overlap Detection from AVHRR and VIIRS

Abstract Two algorithms for detecting multilayered cloud systems with satellite data are presented. The first algorithm utilizes data in the 0.65-, 11-, and 12-μm regions of the spectrum that are available on the Advanced Very High Resolution Radiometer (AVHRR). The second algorithm incorporates two different techniques to detect cloud overlap: the same technique used in the first algorithm and an additional series of spectral tests that now include data from the 1.38- and 1.65-μm near-infrared regions that are available on the Moderate Resolution Imaging Spectroradiometer (MODIS) and will be available on the Visible/Infrared Imager/Radiometer Suite (VIIRS). VIIRS is the imager that will replace the AVHRR on the next generation of polar-orbiting satellites. Both algorithms were derived assuming that a scene with cloud overlap consists of a semitransparent ice cloud that overlaps a cloud composed of liquid water droplets. Each algorithm was tested on three different MODIS scenes. In all three cases, the second (VIIRS) algorithm was able to detect more cloud overlap than the first (AVHRR) algorithm. Radiative transfer calculations indicate that the VIIRS algorithm will be more effective than the AVHRR algorithm when the visible optical depth of the ice cloud is greater than 3. Both algorithms will work best when the visible optical depth of the water cloud is greater than 5. Model sensitivity studies were also performed to assess the sensitivity of each algorithm to various parameters. It was found that the AVHRR algorithm is most sensitive to cloud particle size and the VIIRS near-infrared test is most sensitive to cloud vertical location. When validating each algorithm using cloud radar data, the VIIRS algorithm was shown to be more effective at detecting cloud overlap than the AVHRR algorithm; however, the VIIRS algorithm was slightly more prone to false cloud overlap detection.

An Assessment of the Parameterization of Subgrid-Scale Cloud Effects on Radiative Transfer. Part I: Vertical Overlap

Abstract Different approaches for parameterizing the effects of vertical variability of cloudiness on radiative transfer are assessed using a database constructed from observations derived from lidar and millimeter cloud radar data collected from three different locations. Five different methods for dealing with the vertical overlap of clouds were incorporated into a single radiation model that was applied to the lidar/radar data averaged in time. The calculated fluxes and heating rates derived with this model are compared to broadband fluxes and heating rates calculated with the independent column approximation using the time-resolved cloud data. These comparisons provide a way of evaluating the effects of different overlap assumptions on the calculation of domain-mean fluxes. It was demonstrated how two of the most commonly used overlap schemes, the random and maximum-random methods, suffer a severe problem in that the total cloud amount defined by these methods depends on the vertical resolution of the...