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.

Measurements of global hydrometeor coverage and occurrence frequencies as observed by the cloud radar on CloudSat are summarized using data collected during Summer 2006. CloudSat was launched on 28 April 2006 and began collecting data routinely on 7 June 2006. In this article we document the distribution of cloudiness from the ITCZ to the Polar regions as observed by CloudSat during the first summer of operations. The overall global hydrometeor coverage as observed by CloudSat is found to be 0.506. The vertical distribution of zonally averaged hydrometeor occurrence shows the relationship of clouds with components of the atmospheric general circulation such as the Hadley Cell, the ubiquitous storms over the Southern Ocean, and the subtropical stratocumulus regimes.

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.

[1] It has been hypothesized that continuous ground-based remote sensing measurements from collocated active and passive remote sensors combined with regular soundings of the atmospheric thermodynamic structure can be combined to describe the effects of clouds on the clear sky radiation fluxes. We critically test that hypothesis in this paper and a companion paper (part 2). Using data collected at the Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site sponsored by the U.S. Department of Energy, we explore an analysis methodology that results in the characterization of the physical state of the atmospheric profile at time resolutions of 5 min and vertical resolutions of 90 m. The description includes thermodynamics and water vapor profile information derived by merging radiosonde soundings with ground-based data and continues through specification of the cloud layer occurrence and microphysical and radiative properties derived from retrieval algorithms and parameterizations. The description of the atmospheric physical state includes a calculation of the clear and cloudy sky solar and infrared flux profiles. Validation of the methodology is provided by comparing the calculated fluxes with top of atmosphere (TOA) and surface flux measurements and by comparing the total column optical depths to independently derived estimates. We find over a 1-year period of comparison in overcast uniform skies that the calculations are strongly correlated to measurements with biases in the flux quantities at the surface and TOA of less than 6% and median fractional errors ranging from 12% to as low as 2%. In the optical depth comparison for uniform overcast skies during the year 2000 where the optical depth varies over more than 3 orders of magnitude we find a mean positive bias of less than 1% and a 0.6 correlation coefficient. In addition to a case study where we examine the cloud radiative effects at the TOA, surface and atmosphere by a middle latitude cyclone, we examine the cloud top pressure and optical depth retrievals of ISCCP and LBTM over a period of 1 year. Using overcast periods from the year 2000, we find that the satellite algorithms tend to compare well with data overall but there is a tendency to bias cloud tops into the middle troposphere and underestimate optical depth in high optical depth events.

The lidar and radar profiling capabilities of the CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder (CALIPSO) satellites provide opportunities to improve the characterization of cloud properties. An Arctic cloud climatology based on their observations may be fundamentally different from earlier Arctic cloud climatologies based on passive satellite observations, which have limited contrast between the cloud and underlying surface. Specifically, the Radar-Lidar Geometrical Profile product (RL-GEOPROF) provides cloud vertical profiles from the combination of active lidar and radar. Based on this data product for the period July 2006 to March 2011, this paper presents a new cloud macrophysical property characteristic analysis for the Arctic, including cloud occurrence fraction (COF), vertical distributions, and probability density functions (PDF) of cloud base and top heights. Seasonal mean COF shows maximum values in autumn, minimum values in winter, and moderate values in spring and summer; this seasonality is more prominent over the Arctic Ocean on the Pacific side. The mean ratios of multi-layer cloud to total cloud over the ocean and land are between 24% and 28%. Low-level COFs are higher over ocean than over land. The ratio of low-level cloud to total cloud is also higher over ocean. Middle-level and high-level COFs are smaller over ocean than over land except in summer, and the ratios of middle-level and highlevel clouds to total cloud are also smaller over ocean. Over the central Arctic Ocean, PDFs of cloud top height and cloud bottom height show (1) two cloud top height PDF peaks, one for cloud top heights lower than 1200 m and another between 7 and 9 km; and (2) high frequency for cloud base below 1000 m with the majority of cloud base heights lower than 2000 m.