Derived by combining data from the CloudSat radar and the CALIPSO lidar, the so‐called radar‐lidar geometrical profile product (RL‐GeoProf) allows for characterization of the vertical and spatial ...structure of hydrometeor layers. RL‐GeoProf is one of the standard data products of the CloudSat Project. In this paper we describe updates to the RL‐GeoProf algorithm. These improvements include a significant fix to the CALIPSO Vertical Feature Mask (VFM) that more accurately renders the occurrence frequencies of low‐level clouds over the global oceans. Additionally, we now account for the navigational challenges associated with coordinated measurements of the two instruments by providing additional diagnostic information in the data files. We also document how the along‐track averaging of the VFM influences the accuracy of RL‐GeoProf. We find that the 5 km averaged VFM when merged with data from the CloudSat radar provides a global description of cloud occurrence that best matches an independently derived cloud mask from Moderate Resolution Imaging Spectroradiometer (MYD35) over daytime global oceans. Expanding on the comparison with MYD35, we demonstrate that RL‐GeoProf and MYD35 closely track the monthly averaged cloud occurrence fraction during a 4 year span of measurements. A more detailed examination reveals latitudinal dependency in the comparison. Specifically, MYD35 tends to be significantly low biased relative to RL‐GeoProf over the Polar Regions when cloud layers present low visible and thermal contrast with underlying surfaces. Additional analyses examine the geometrically defined hydrometeor layer occurrence climatologies over select regions of the Earth and the seasonal variations of low‐based and low‐topped cloud cover.
Key Points
A revised radar‐lidar geometrical profile algorithm for CloudSat and CALIPSOSelected cloud occurrence statistics from RL‐GeoProf and MODIS
The properties of clouds derived using a suite of remote sensors on board the Australian research vessel (R/V) Investigator during the 5-week Clouds, Aerosols, Precipitation, Radiation, and ...Atmospheric Composition over the Southern Ocean (CAPRICORN) voyage south of Australia during March and April 2016 are examined and compared to similar measurements collected by CloudSat and CALIPSO (CC) and from data collected at Graciosa Island, Azores (GRW). In addition, we use depolarization lidar data to examine the thermodynamic phase partitioning as a function of temperature and compare those statistics to similar information reported from the CALIPSO lidar in low-Earth orbit. We find that cloud cover during CAPRICORN was 76%, dominated by clouds based in the marine boundary layer. This was lower than comparable measurements collected by CC during these months, although the CC dataset observed significantly more high clouds. In the surface-based data, approximately 2/3 (1/2) of all low-level layers observed had a reflectivity below −20 dBZ in the CAPRICORN data (GRW) with 30% (20%) of the layers observed only by the lidar. The phase partitioning in layers based in the lower 4 km of the atmosphere was similar in the two surface-based datasets, indicating a greater occurrence of the ice phase in subfreezing low clouds than what is reported from analysis of CALIPSO data.
Given the importance of constraining cloud droplet number concentrations (Nd) in low-level clouds, we explore two methods for retrieving Nd from surface-based remote sensing that emphasize the ...information content in lidar measurements. Because Nd is the zeroth moment of the droplet size distribution (DSD), and all remote sensing approaches respond to DSD moments that are at least 2 orders of magnitude greater than the zeroth moment, deriving Nd from remote sensing measurements has significant uncertainty. At minimum, such algorithms require the extrapolation of information from two other measurements that respond to different moments of the DSD. Lidar, for instance, is sensitive to the second moment (cross-sectional area) of the DSD, while other measures from microwave sensors respond to higher-order moments. We develop methods using a simple lidar forward model that demonstrates that the depth to the maximum in lidar-attenuated backscatter (Rmax) is strongly sensitive to Nd when some measure of the liquid water content vertical profile is given or assumed. Knowledge of Rmax to within 5 m can constrain Nd to within several tens of percent. However, operational lidar networks provide vertical resolutions of > 15 m, making a direct calculation of Nd from Rmax very uncertain. Therefore, we develop a Bayesian optimal estimation algorithm that brings additional information to the inversion such as lidar-derived extinction and radar reflectivity near the cloud top. This statistical approach provides reasonable characterizations of Nd and effective radius (re) to within approximately a factor of 2 and 30 %, respectively. By comparing surface-derived cloud properties with MODIS satellite and aircraft data collected during the MARCUS and CAPRICORN II campaigns, we demonstrate the utility of the methodology.
Supercooled liquid clouds are an important component of the albedo of the Southern Ocean (SO). While ice phase occurrence in liquid‐dominant clouds (hereafter mixed phase) at temperatures warmer than ...the homogeneous freezing point is rare in the SO, the processes that create mixed‐phase clouds are not understood. Using data from the CALIPSO lidar, we reconsider the thresholds of layer‐integrated depolarization ratio and layer‐integrated attenuated backscatter that are used to diagnose the phases of fully attenuating cloud layers. We argue that liquid‐only clouds have understood physical bounds to these thresholds allowing for unique identification of layers that are not consistent with the presence of single‐phase liquid tops. Compared to the original phase algorithm the application of these physically constrained thresholds results in a ~70% increase in mixed phase during the annual cycle considered. Combining the CALIPSO data with CloudSat data, mixed‐phase clouds seem to typically cooccur with precipitation implying secondary ice forming processes.
Key Points
Mixed‐phase clouds are identified with CALIPSO data over the Southern Ocean
The occurrence frequency of ice‐containing low clouds increases in the Southern Ocean when the occurrence of mixed‐phase clouds is considered
New phase thresholds identify a strong association between ice precipitation and mixed‐phase layers in low clouds over the Southern Ocean
The CloudSat 2C‐ICE data product is derived from a synergetic ice cloud retrieval algorithm that takes as input a combination of CloudSat radar reflectivity (Ze) and Cloud‐Aerosol Lidar and Infrared ...Pathfinder Satellite Observation lidar attenuated backscatter profiles. The algorithm uses a variational method for retrieving profiles of visible extinction coefficient, ice water content, and ice particle effective radius in ice or mixed‐phase clouds. Because of the nature of the measurements and to maintain consistency in the algorithm numerics, we choose to parameterize (with appropriately large specification of uncertainty) Ze and lidar attenuated backscatter in the regions of a cirrus layer where only the lidar provides data and where only the radar provides data, respectively. To improve the Ze parameterization in the lidar‐only region, the relations among Ze, extinction, and temperature have been more thoroughly investigated using Atmospheric Radiation Measurement long‐term millimeter cloud radar and Raman lidar measurements. This Ze parameterization provides a first‐order estimation of Ze as a function extinction and temperature in the lidar‐only regions of cirrus layers. The effects of this new parameterization have been evaluated for consistency using radiation closure methods where the radiative fluxes derived from retrieved cirrus profiles compare favorably with Clouds and the Earth's Radiant Energy System measurements. Results will be made publicly available for the entire CloudSat record (since 2006) in the most recent product release known as R05.
Key Points
New Ze parameterization provides a first‐order estimation of Ze
New retrieval has been evaluated with radiative close methods
Ze parameterization will allow for more fruitful study of the thin cirrus
Using A‐Train satellite data, we investigate the distribution of clouds and their microphysical and radiative properties in Southeast Asia during the summer monsoon. We find an approximate balance in ...the top of the atmosphere (TOA) cloud radiative effect, which is largely due to commonly occurring cirrus layers that warm the atmosphere, and less frequent deep layers, which produce a strong cooling at the surface. The distribution of ice water path (IWP) in these layers, obtained from the 2C‐ICE CloudSat data product, is highly skewed with a mean value of 440 g m−2 and a median of 24 g m−2. We evaluate the fraction of the total IWP observed by CloudSat and CALIPSO individually and find that both instruments are necessary for describing the overall IWP statistics and particularly the values that are most important to cirrus radiative impact. In examining how cloud radiative effects at the TOA vary as a function of IWP, we find that cirrus with IWP less than 200 g m−2 produce a net warming in the study region. Weighting the distribution of radiative effect by the frequency of occurrence of IWP values, we determine that cirrus with IWP around 20 g m−2 contribute most to heating at the TOA. We conclude that the mean IWP is a poor diagnostic of radiative impact. We suggest that climate model intercomparisons with data should focus on the median IWP because that statistic is more descriptive of the cirrus that contribute most to the radiative impacts of tropical ice clouds.
Key Points
Mean value of ice water path is a poor diagnostic of cirrus radiative impactBoth radar and lidar are needed to describe the full ice water path distributionNet cloud radiative effect suggests balance between cirrus and deep clouds
Abstract
In late April 2006, NASA launched Cloudsat, an earth-observing satellite that uses a near-nadir-pointing millimeter-wavelength radar to probe the vertical structure of clouds and ...precipitation. The first step in using Cloudsat measurements is to distinguish clouds and other hydrometeors from radar noise. In this article the operational Cloudsat hydrometeor detection algorithm is described, difficulties due to surface clutter are discussed, and several examples from the early mission are shown. A preliminary comparison of the Cloudsat hydrometeor detection algorithm with lidar-based results from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is also provided.
Globally, clouds are known to warm the climate system in the thermal infrared because they typically emit thermal radiation to space at effective temperatures lower than the combined cloud‐free ...atmosphere and surface. However, here we show that ∼40% of low‐level clouds over sea ice tend to cool the Arctic system at TOA and contribute to a radiative cooling of the Arctic winter climate by −2.3 Wm−2, or a ∼16% reduction over the infrared warming effect of all clouds during winter. Based on satellite observations, low‐level clouds residing in surface‐based temperature inversions emit more longwave radiation to space than would occur in cloudless skies. While these clouds are known to significantly warm the surface, they cool the Arctic climate system overall. Our results imply that accurately representing the cloud radiative effects unique to the Arctic could help to constrain the regional energy budget.
Plain Language Summary
The Arctic has become emblematic of climate change, with rapid warming that is at least twice as fast as the rest of the planet. However, major uncertainties in our confidence to understand and predict Arctic climate persist, particularly regarding the radiative effects of clouds. Here we use satellite data to quantify the radiative effects of Arctic low‐level clouds, and find approximately 40% of low‐level clouds over sea ice tend to radiatively cool the Arctic climate system (Earth's surface and the atmosphere) in winter, rather than warm the climate system as is typical for most clouds in the thermal infrared regime. This cooling effect is governed by the widespread surface temperature inversions (layers in which temperature increases with altitude), which cap these low‐level clouds and allow more longwave radiation to escape from the Earth to space compared to clear skies. This finding reveals a fundamental, but overlooked, characteristic of cloud radiative effects in the wintertime Arctic and establishes a new perspective for understanding Arctic climate change.
Key Points
A full range of radiative effects for Arctic wintertime low clouds over sea ice is investigated
About 40% of low clouds over sea ice tends to cool the Arctic at the top of the atmosphere in the polar night
These low clouds with a cooling effect at the top of the atmosphere reside within frequent surface‐based temperature inversions
The distribution of clouds and their radiative effects in the Community Atmosphere Model, version 5 (CAM5), are compared to A-Train satellite data in Southeast Asia during the summer monsoon. Cloud ...radiative kernels are created based on populations of observed and modeled clouds separately in order to compare the sensitivity of the TOA radiation to changes in cloud fraction. There is generally good agreement between the observation- and model-derived cloud radiative kernels for most cloud types, meaning that the clouds in the model are heating and cooling like clouds in nature. Cloud radiative effects are assessed by multiplying the cloud radiative kernel by the cloud fraction histogram. For ice clouds in particular, there is good agreement between the model and observations, with optically thin cirrus producing a moderate warming effect and cirrostratus producing a slight cooling effect, on average. Consistent with observations, the model also shows that the median value of the ice water path (IWP) distribution, rather than the mean, is a more representative measure of the ice clouds that are responsible for heating. In addition, in both observations and the model, it is cirrus clouds with an IWP of 20 g m−2 that have the largest warming effect in this region, given their radiative heating and frequency of occurrence.
The occurrence statistics of hydrometeor layers covering the Earth's surface is described using the first year of millimeter radar data collected by Cloudsat merged with lidar data collected by ...CALIPSO (July 2006 to June 2007). These satellites are flown in a tight orbital configuration so that they probe nearly the same volumes of the atmosphere within 10–15 s of each other. This configuration combined with the capacity for millimeter radar to penetrate optically thick hydrometeor layers and the ability of the lidar to detect optically thin clouds has allowed us to characterize the vertical and horizontal structure of hydrometeor layers with unprecedented precision. We find that the global hydrometeor coverage averages 76% and demonstrates a fairly smooth annual cycle with a range of 3% peaking in October 2006 and reaching a minimum in March 2007. The geographic distribution of hydrometeor layers defined in terms of layer base, layer top, and layer thickness is described. The predominance of geometrically thin boundary layer clouds is illustrated as is the spatial distribution of upper tropospheric ice clouds in the tropics. The cooccurrence of multiple layers is shown to be a strong function of latitude and geography with cooccurring middle‐level (3 km < layer base < 6 km) and high‐level (base > 6 km) layers being predominant over the continents. Cloud layer overlap is also examined, and a bias due to an assumption of maximum fractional overlap in coarse resolution models is quantified and shown to be on the order of −5 to −7% globally maximizing over the high‐latitude continents of the Northern Hemisphere.
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