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The International Satellite Cloud Climatology Project (ISCCP) began collecting data in the 1980s to help understand the distribution of clouds. Since then, it has provided important information on clouds in time and space and their radiative characteristics. However, it was apparent from some long-term time series of the data that there are some latent artifacts related to the changing satellite coverage over the more than 30 years of the record. Changes in satellite coverage effectively create secular changes in the time series of view zenith angle (VZA) for a given location. There is an inconsistency in the current ISCCP cloud detection algorithm related to VZA: two satellites viewing the same location from different VZAs can produce vastly different estimates of cloud amount. Research is presented that shows that a simple change to the cloud detection algorithm can vastly increase the consistency. This is accomplished by making the cloud-no cloud threshold VZA dependent. The resulting cloud amounts are more consistent between different satellites and the distributions are shown to be more spatially homogenous. Likewise, the more consistent spatial data lead to more consistent temporal statistics. [ABSTRACT FROM AUTHOR]

This paper describes the new global long-term, International Satellite Cloud Climatology Project (ISCCP) H-Series climate data record (CDR). The H-Series data contains a suite of level 2 and level 3 products for monitoring the distribution and variation of cloud and surface properties to better understand the effects of clouds on climate, the radiation budget, and the global hydrologic cycle. This product is currently available for public use and is derived from both geostationary and polar orbiting satellite imaging radiometers with common visible and infrared (IR) channels. The H-Series data spans from July 1983 to Dec 2009 with plans for continued production to extend the record to the present with regular updates. The H-series data are the longest combined geostationary and polar orbiter satellite based CDR of cloud properties. Access to the data is provided in network Common Data Form (netCDF) and archived by NOAA's National Centers for Environmental Information (NCEI) under the satellite Climate Data Record Program (https://doi.org/10.7289/V5QZ281S). The basic characteristics, history, and evolution of the dataset are presented herein with particular emphasis on and discussion of product changes between the H-Series and the widely used predecessor D-Series product which spans from July 1983 through December 2009. Key refinements included to the ISCCP H-Series CDR are based on improved quality control measures, modified ancillary inputs, higher spatial resolution input and output products, calibration refinements, and updated documentation and metadata to bring the H-Series product into compliance with existing standards for climate data records. [ABSTRACT FROM AUTHOR]

ISCCP continues to quantify the global distribution and diurnal-to-interannual variations of cloud properties in a revised version. This paper summarizes assessments of the previous version, describes refinements of the analysis and enhanced features of the product design, discusses the few notable changes in the results, and illustrates the long-term variations of global mean cloud properties and differing high cloud changes associated with ENSO. The new product design includes a global, pixel-level product on a 0.1° grid, all other gridded products at 1.0°-equivalent equal area, separate satellite products with ancillary data for regional studies, more detailed, embedded quality information, and all gridded products in netCDF format. All the data products including all input data, expanded documentation, the processing code, and an operations guide are available online. Notable changes are 1) a lowered ice–liquid temperature threshold, 2) a treatment of the radiative effects of aerosols and surface temperature inversions, 3) refined specification of the assumed cloud microphysics, and 4) interpolation of the main daytime cloud information overnight. The changes very slightly increase the global monthly mean cloud amount with a little more high cloud and a little less middle and low cloud. Over the whole period, total cloud amount slowly decreases caused by decreases in cumulus/altocumulus; consequently, average cloud-top temperature and optical thickness have increased. The diurnal and seasonal cloud variations are very similar to earlier versions. Analysis of the whole record shows that high cloud variations, but not low clouds, exhibit different patterns in different ENSO events. Significance Statement: This paper reports on the evolution of the research goals and satellite cloud data products produced by ISCCP, a long-term international project, which is now fully operational. The growing length of record with 10-km and 3-h sampling makes possible studies of cloud variations from diurnal-to-weather scale (cloud process scale) to climate variation scale. In particular the length of record includes many examples of ENSO and is beginning to encompass the slower modes of ocean variation, allowing studies of the role of cloud feedbacks in coupling the atmosphere and ocean circulations. [ABSTRACT FROM AUTHOR]

Since the first Global Energy and Water Exchanges cloud assessment a decade ago, existing cloud property retrievals have been revised and new retrievals have been developed. The new global long-term cloud datasets show, in general, similar results to those of the previous assessment. A notable exception is the reduced cloud amount provided by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Science Team, resulting from an improved aerosol–cloud distinction. Height, opacity and thermodynamic phase determine the radiative effect of clouds. Their distributions as well as relative occurrences of cloud types distinguished by height and optical depth are discussed. The similar results of the two assessments indicate that further improvement, in particular on vertical cloud layering, can only be achieved by combining complementary information. We suggest such combination methods to estimate the amount of all clouds within the atmospheric column, including those hidden by clouds aloft. The results compare well with those from CloudSat-CALIPSO radar–lidar geometrical profiles as well as with results from the International Satellite Cloud Climatology Project (ISCCP) corrected by the cloud vertical layer model, which is used for the computation of the ISCCP-derived radiative fluxes. Furthermore, we highlight studies on cloud monitoring using the information from the histograms of the database and give guidelines for: (1) the use of satellite-retrieved cloud properties in climate studies and climate model evaluation and (2) improved retrieval strategies. [ABSTRACT FROM AUTHOR]

Climate normals are traditionally calculated every decade as the average values over a period of time, often 30 years. Such an approach assumes a stationary climate, with several alternatives recently introduced to account for monotonic climate change. However, these methods fail to account for interannual climate variability [e.g., El Niño–Southern Oscillation (ENSO)] that systematically alters the background state of the climate similar to climate change. These effects and their uncertainties are well established, but they are not reflected in any readily available climate normals datasets. A new high-resolution set of normals is derived for the contiguous United States that accounts for ENSO and uses the optimal climate normal (OCN)—a 10-yr (15 yr) running average for temperature (precipitation)—to account for climate change. Anomalies are calculated by subtracting the running means and then compositing into 5 ENSO phase and intensity categories: Strong La Niña, Weak La Niña, Neutral, Weak El Niño, and Strong El Niño. Seasonal composites are produced for each of the five phases. The ENSO normals are the sum of these composites with the OCN for a given month. The result is five sets of normals, one for each phase, which users may consult with respect to anticipated ENSO outcomes. While well-established ENSO patterns are found in most cases, a distinct east–west temperature anomaly pattern emerges for Weak El Niño events. This new product can assist stakeholders in planning for a broad array of possible ENSO impacts in a changing climate. [ABSTRACT FROM AUTHOR]