Michael J. Foster

A Naive Bayesian Cloud-Detection Scheme Derived from CALIPSO and Applied within PATMOS-x

AbstractThe naive Bayesian methodology has been applied to the challenging problem of cloud detection with NOAA’s Advanced Very High Resolution Radiometer (AVHRR). An analysis of collocated NOAA-18/AVHRR and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)/Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations was used to automatically and globally derive the Bayesian classifiers. The resulting algorithm used six Bayesian classifiers computed separately for seven surface types. Relative to CALIPSO, the final results show a probability of correct detection of roughly 90% over water, deserts, and snow-free land; 82% over the Arctic; and below 80% over the Antarctic. This technique is applied within the NOAA Pathfinder Atmosphere’s Extended (PATMOS-x) climate dataset and the Clouds from AVHRR Extended (CLAVR-x) real-time product generation system. Comparisons of the PATMOS-x results with those from International Satellite Cloud Climatology Project (ISCCP) and Moder...

THE PATHFINDER ATMOSPHERES-EXTENDED AVHRR CLIMATE DATASET

The Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres–Extended (PATMOS-x) dataset offers over three decades of global observations from the NOAA Polar-orbiting Operational Environmental Satellite (POES) project and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) [Meteorological Operational (MetOp)] satellite series. The AVHRR has flown since 1978 and continues to provide radiometrically consistent observations with a spatial resolution of roughly 4 km and a temporal resolution of an ascending and descending node per satellite per day, achieving global coverage. The AVHRR PATMOS-x data provide calibrated AVHRR observations in addition to properties about tropospheric clouds and aerosols, Earths surface, Earths radiation budget, and relevant ancillary data. To provide three decades of data in a convenient format, PATMOS-x generates mapped and sampled results with a spatial resolution of 0.1° on a global latitude–longitude grid. This format avoid...

PATMOS-x: Results from a Diurnally Corrected 30-yr Satellite Cloud Climatology

AbstractSatellite drift is a historical issue affecting the consistency of those few satellite records capable of being used for studies on climate time scales. Here, the authors address this issue for the Pathfinder Atmospheres Extended (PATMOS-x)/Advanced Very High Resolution Radiometer (AVHRR) cloudiness record, which spans three decades and 11 disparate sensors. A two-harmonic sinusoidal function is fit to a mean diurnal cycle of cloudiness derived over the course of the entire AVHRR record. The authors validate this function against measurements from Geostationary Operational Environmental Satellite (GOES) sensors, finding good agreement, and then test the stability of the diurnal cycle over the course of the AVHRR record. It is found that the diurnal cycle is subject to some interannual variability over land but that the differences are somewhat offset when averaged over an entire day. The fit function is used to generate daily averaged time series of ice, water, and total cloudiness over the tropic...

Variability and Trends in U.S. Cloud Cover : ISCCP, PATMOS-x, and CLARA-A1 Compared to Homogeneity-Adjusted Weather Observations

AbstractVariability and trends in total cloud cover for 1982–2009 across the contiguous United States from the International Satellite Cloud Climatology Project (ISCCP), AVHRR Pathfinder Atmospheres–Extended (PATMOS-x), and EUMETSAT Satellite Application Facility on Climate Monitoring Clouds, Albedo and Radiation from AVHRR Data Edition 1 (CLARA-A1) satellite datasets are assessed using homogeneity-adjusted weather station data. The station data, considered as “ground truth” in the evaluation, are generally well correlated with the ISCCP and PATMOS-x data and with the physically related variables diurnal temperature range, precipitation, and surface solar radiation. Among the satellite products, overall, the PATMOS-x data have the highest interannual correlations with the weather station cloud data and those other physically related variables. The CLARA-A1 daytime dataset generally shows the lowest correlations, even after trends are removed. For the U.S. mean, the station dataset shows a negative but not...

Satellite Regional Cloud Climatology over the Great Lakes

Thirty-one years of imager data from polar orbiting satellites are composited to produce a satellite climate data set of cloud amount for the Great Lakes region. A trend analysis indicates a slight decreasing trend in cloud cover over the region during this time period. The trend is significant and largest (~2% per decade) over the water bodies. A strong seasonal cycle of cloud cover is observed over both land and water surfaces. Winter cloud amounts are greater over the water bodies than land due to heat and moisture flux into the atmosphere. Late spring through early autumn cloud amounts are lower over the water bodies than land due to stabilization of the boundary layer by relatively cooler lake waters. The influence of the lakes on cloud cover also extends beyond their shores, affecting cloud cover and properties far down wind. Cloud amount composited by wind direction demonstrate that the increasing cloud amounts downwind of the lakes is greatest during autumn and winter. Cold air flows over relatively warm lakes in autumn and winter generate wind parallel convective cloud bands. The cloud properties of these wind parallel cloud bands over the lakes during winter are presented.

Entering the Era of +30-Year Satellite Cloud Climatologies: A North American Case Study

AbstractThe emergence of satellite-based cloud records of climate length and quality hold tremendous potential for climate model development, climate monitoring, and studies on global water cycling and its subsequent energetics. This article examines the more than 30-yr Pathfinder Atmospheres–Extended (PATMOS-x) Advanced Very High Resolution Radiometer (AVHRR) cloudiness record over North America and assesses its suitability as a climate-quality data record. A loss of ~4.2% total cloudiness is observed between 1982 and 2012 over a North American domain centered over the contiguous United States. While ENSO can explain some of the observed change, a weather state clustering analysis identifies shifts in weather patterns that result in loss of water cloud over the Great Lakes and cirrus over southern portions of the United States. The radiative properties of the shifting weather states are characterized, and the results suggest that extended cloud satellite records may prove useful tools for increasing know...

Using the NASA EOS A-Train to Probe the Performance of the NOAA PATMOS-x Cloud Fraction CDR

An important component of the AVHRR PATMOS-x climate date record (CDR)—or any satellite cloud climatology—is the performance of its cloud detection scheme and the subsequent quality of its cloud fraction CDR. PATMOS-x employs the NOAA Enterprise Cloud Mask for this, which is based on a naive Bayesian approach. The goal of this paper is to generate analysis of the PATMOS-x cloud fraction CDR to facilitate its use in climate studies. Performance of PATMOS-x cloud detection is compared to that of the well-established MYD35 and CALIPSO products from the EOS A-Train. Results show the AVHRR PATMOS-x CDR compares well against CALIPSO with most regions showing proportional correct values of 0.90 without any spatial filtering and 0.95 when a spatial filter is applied. Values are similar for the NASA MODIS MYD35 mask. A direct comparison of PATMOS-x and MYD35 from 2003 to 2014 also shows agreement over most regions in terms of mean cloud amount, inter-annual variability, and linear trends. Regional and seasonal differences are discussed. The analysis demonstrates that PATMOS-x cloud amount uncertainty could effectively screen regions where PATMOS-x differs from MYD35.

Estimation of Liquid Cloud Properties that Conserve Total-Scene Reflectance Using Satellite Measurements

Abstract A new method of deriving statistical moments related to the distribution of liquid water path over partially cloudy scenes is tested using a satellite cloud climatology. The method improves the ability to reconstruct total-scene visible reflectance when compared with an approach that relies on valid liquid water path retrievals, and thus it maintains physical consistency with the primary satellite observations when deriving cloud climatologies. A global application of the new method finds a mean bias of −0.008 ± 0.017 when reconstructing total-scene reflectance from liquid water path distributions, as compared with a bias of 0.05 ± 0.047 when using a conventional approach. Application of the method to a multidecadal cloud climatology suggests that this may provide a means of identifying data artifacts that could affect long-term cloud property trends. The conservation of reflectance plus the ease of applicability to various satellite datasets makes this method a valuable tool for model validation...

Toward Global Harmonization of Derived Cloud Products

Formerly known as the Cloud Retrieval Evaluation Workshop (CREW; see the list of acronyms used in this paper below) group (Roebeling et al. 2013, 2015), the International Cloud Working Group (ICWG) was created and endorsed during the 42nd Meeting of CGMS. The CGMS-ICWG provides a forum for space agencies to seek coherent progress in science and applications and also to act as a bridge between space agencies and the cloud remote sensing and applications community. The ICWG plans to serve as a forum to exchange and enhance knowledge on state-of-the-art cloud parameter retrievals algorithms, to stimulate support for training in the use of cloud parameters, and to encourage space agencies and the cloud remote sensing community to share knowledge. The ICWG plans to prepare recommendations to guide the direction of future research-for example, on observing severe weather events or on process studies-and to influence relevant programs of the WMO, WCRP, GCOS, and the space agencies.

A MODIS-Derived Value-Added Climatology of Maritime Cloud Liquid Water Path That Conserves Solar Reflectance

AbstractA dataset is generated from a method to retrieve distributions of cloud liquid water path over partially cloudy scenes. The method was introduced in a 2011 paper by Foster and coauthors that described the theory and provided test cases. Here it has been applied to Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 and collection-6 cloud products, resulting in a value-added dataset that contains adjusted distributions of cloud liquid water path for more than 10 years for marine liquid cloud for both Aqua and Terra. This method adjusts horizontal distributions of cloud optical properties to be more consistent with observed visible reflectance and is especially useful in areas where cloud optical retrievals fail or are considered to be of low quality. Potential uses of this dataset include validation of climate and radiative transfer models and facilitation of studies that intercompare satellite records. Results show that the fit method is able to reduce bias between observed visible ...