Michael J. Pavolonis

Daytime Global Cloud Typing from AVHRR and VIIRS: Algorithm Description, Validation, and Comparisons

Abstract Three multispectral algorithms for determining the cloud type of previously identified cloudy pixels during the daytime, using satellite imager data, are presented. Two algorithms were developed for use with 0.65-, 1.6-/3.75-, 10.8-, and 12.0-μm data from the Advanced Very High Resolution Radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) operational polar-orbiting satellites. The AVHRR algorithms are identical except for the near-infrared data that are used. One algorithm uses AVHRR channel 3a (1.6 μm) reflectances, and the other uses AVHRR channel 3b (3.75 μm) reflectance estimates. Both of these algorithms are necessary because the AVHRRs on NOAA-15 through NOAA-17 have the capability to transmit either channel 3a or 3b data during the day, whereas all of the other AVHRRs on NOAA-7 through NOAA-14 can only transmit channel 3b data. The two AVHRR cloud-typing schemes are used operationally in NOAA’s extended Clouds from AVHRR (CLAVR)-x processing system. The ...

Development of a new over‐water Advanced Very High Resolution Radiometer dust detection algorithm

A new over–water dust detection algorithm is developed and applied to the 5–channel Advanced Very High Resolution Radiometer (AVHRR) imager onboard the National Oceanic and Atmospheric Administration series of polar orbiting satellites. The algorithm has been developed to improve the distinction between dust and meteorological clouds for very optically thick dust storms that would have previously been flagged as cloud under the Clouds from AVHRR Extended cloud mask algorithm. The algorithm has been assessed by making daily comparisons with data from the Aerosol Robotic Network and by making a climatological comparison with METEOSAT and Total Ozone Mapping Spectrometer data over a portion of the North Atlantic. The new algorithm improves the separation of clouds and airborne dust. Application of the new product to the 5–channel AVHRR historic data sets can provide information on the global dust signal, especially on an interannual time scale.

Automated cloud detection and classification of data collected by the Visible Infrared Imager Radiometer Suite (VIIRS)

The Visible Infrared Imager Radiometer Suite (VIIRS) is a high‐resolution Earth imager of the United States National Polar‐orbiting Operational Environmental Satellite System (NPOESS). VIIRS has its heritage in three sensors currently collecting imagery of the Earth—the Advanced Very High Resolution Radiometer, the Moderate Resolution Imaging Spectroradiometer, and the Operational Linescan Sensor. The first launch of the VIIRS sensor is on NASAs NPOESS Preparatory Project (NPP). Data collected by VIIRS will provide products to a variety of users, supporting applications from real‐time to long‐term climate change timescales. VIIRS has been uniquely designed to satisfy this full range of requirements. Cloud masks derived from the automated analyses of VIIRS data are critical data products for the NPOESS program. In this paper, the VIIRS cloud mask (VCM) performance requirements are highlighted, along with the algorithm developed to satisfy these requirements. The expected performance of the VCM algorithm is established using global synthetic cloud simulations and manual cloud analyses of VIIRS proxy imagery. These results show the VCM analyses will satisfy the performance expectations of products created from it, including land and ocean surface products, cloud microphysical products, and automated cloud forecast products. Finally, minor deficiencies that remain in the VCM algorithm logic are identified along with a mitigation plan to resolve each prior to NPP launch or shortly thereafter.

Antarctic Cloud Radiative Forcing at the Surface Estimated from the AVHRR Polar Pathfinder and ISCCP D1 Datasets, 1985–93

Abstract Surface cloud radiative forcing from the newly extended Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP-x) dataset and surface cloud radiative forcing calculated using cloud and surface properties from the International Satellite Cloud Climatology Project (ISCCP) D-series product were used in this 9-yr (1985–93) study. On the monthly timescale, clouds were found to have a warming effect on the surface of the Antarctic continent every month of the year in both datasets. Over the ocean poleward of 58.75°S, clouds were found to have a warming effect on the surface from March through October in the ISCCP-derived dataset and from April through September in the APP-x dataset. Net surface fluxes from both datasets were validated against net surface fluxes calculated from measurements of upwelling and downwelling shortwave and longwave radiation at the Neumayer and Amundsen–Scott South Pole Stations in the Antarctic. The net all-wave surface flux from the ISCCP-derived dataset was ...

A new AVHRR cloud climatology

The NOAA/NESDIS Office of Research and Applications (ORA) has embarked on a pilot data stewardship project aimed at improving the data record from the Advanced Very High Resolution Radiometer (AVHRR). One part of this larger project includes the generation of a new cloud climatology from the Extended AVHRR Pathfinder Atmospheres (PATMOS-x) data set. Included within the PATMOS-x data-stream is a full suite of cloud products including various cloud amounts. This paper compares the PATMOS-x cloud amount time series for all July data (1982-2004) to the cloud amount time series from the International Satellite Cloud Climatology Project (ISCCP) and University of Wisconsin High Resolution Infrared Sounder (UW/HIRS) data sets. The results indicate that the large intersatellite discontinuities in the total amount seen in the original PATMOS are reduced in PATMOS-x. The total cloud for July time series from PATMOS-x, UW/HIRS and PATMOS show little trend over the period studied but that ISCCP time series does indicate a continuous downward trend When comparing the time series of high cloud amount, it was that PATMOS-x shows no significant trend in high cloud from 20S to 20N.

A Study of the Antarctic Surface Energy Budget Using a Polar Regional Atmospheric Model Forced with Satellite-Derived Cloud Properties

Abstract Cloud properties from the newly extended Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP-x) dataset were incorporated into the atmospheric component of the Arctic Regional Climate System Model (ARCSyM) in order to improve the simulation of the Antarctic surface energy balance. A method for using the APP-x cloud properties in 48-h model simulations is presented. In the experiments, the model cloud fields were altered via the water vapor mixing ratio using cloud properties from the APP-x dataset. Significant improvements in monthly mean downwelling longwave radiation at the surface were observed relative to surface measurements. In the austral summer, the use of the APP-x dataset resulted in improvements as large as 30 W m−2 at the South Pole when compared to model results without APP-x clouds. However, only a very small improvement was seen in the turbulent heat fluxes and the surface temperature. It was also found that the satellite data can be used to shorten the model “sp...

Preliminary global cloud comparisons from the AVHRR, MODIS, and GLAS: cloud amount and cloud overlap

Near-global total cloud frequencies and multilayered cloud frequencies derived from AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), and GLAS (Geoscience Laser Altimeter System) were analyzed and compared. The GLAS retrievals can be used to quantify the amount of cloud that may go undetected from satellite imagers such AVHRR and MODIS and to help validate satellite cloud overlap detection algorithms. Model sensitivity studies indicate that clouds with a total column optical depth of 0.5 or less may often go undetected by AVHRR and MODIS. The GLAS data show that such cloudy observations comprised 18.3% (14.5%) of all cloudy GLAS footprints during the most convectively active (least convectively active) portion of the day. Where the most (least) convectively active time period is defined as local solar noon plus (minus) 12 hours. It was also shown that the zonal mean total cloud frequency from GLAS and AVHRR and GLAS and MODIS are well correlated but often differ in magnitude because of thin clouds or small-scale cloud systems that are missed by the AVHRR and MODIS cloud detection algorithms. With the exception of the polar regions, the AVHRR and GLAS and the MODIS (via the Visible/Infrared Imager/Radiometer Suite algorithm) and GLAS multilayered cloud frequencies are in good agreement.

Antarctic cloud radiative forcing at the surface estimated from the ISCCP D2 and AVHRR Polar Pathfinder data sets, 1985-1993

Surface cloud radiative forcing was calculated using cloud and surface properties from the International Satellite Cloud Climatology Project (ISCCP) D-series product as input into a radiative transfer model. In addition, the newly extended AVHRR Polar Pathfinder (APP) data set, which includes surface cloud radiative forcing, was used in this 9-year (1985-1993) study. Spatial and temporal trends in the surface net cloud forcing for the Antarctic were examined in both the ISCCP-derived and APP data sets. Monthly means of the ISCCP-derived net cloud radiative forcing at the surface were found to be greater than zero all year-round poleward of 80/spl deg/S. The APP net cloud forcing was found to exceed 10 W/m/sup 2/ south of 80/spl deg/S every month of the year. The differences in the net cloud forcing between the two data sets largely occurs because of differing cloud amounts. Both the ISCCP and APP net surface fluxes were compared to fluxes measured at Neumayer Station. Errors in the monthly mean net all-wave surface flux of up to 50 W/m/sup 2/ were found for the ISCCP-derived product. The APP product errors were found not to exceed 13 W/m/sup 2/ at the monthly time scale.

Advancements in identifying cirrus and multilayered cloud systems from operational satellite imagers at night

Radiances and brightness temperatures from three near-infrared/infrared channels that are available on most current and past satellite imagers were used to develop automated algorithms for identifying multilayered cloud systems (cloud overlap) and cirrus clouds at night. The cloud overlap algorithm uses information from the 3.75 micron, 11 micron, and 12 micron regions of the spectrum and the cirrus algorithm uses 3.75 micron and 11 micron channel data. The cloud overlap algorithm was developed assuming that a scene with cloud overlap consists of a semitransparent ice cloud that overlaps a lower cloud composed of liquid water droplets. Cirrus clouds are taken to be high ice clouds with a visible optical depth of 5.0 or less. The algorithms are applied to single satellite pixels that are already assumed to be cloudy based on cloud mask information. The utility of each algorithm was demonstrated on two different Moderate Resolution Imaging Spectroradiometer (MODIS) scenes and the cloud overlap algorithm was validated against millimeter radar-derived cloud boundaries. Overall the results show that both algorithms have the potential to be very useful for nighttime cloud studies.

Arctic climate characteristics and recent trends revealed by the AVHRR Polar Pathfinder data set

The newly available Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) data set was used to retrieve cloud amount, cloud optical depth, cloud particle phase and size, cloud temperature, surface temperature, surface broadband albedo, radiation fluxes and cloud forcing in the Arctic for the period 1982-1999. The spatial and temporal distributions of those retrieved Arctic climate parameters together with an analysis of their seasonal and interannual variability, especially surface and cloud properties are presented here. The present study indicates that the Arctic has been warming in spring, summer and autumn, the decadal rates are 1.1°C degree, 0.68°C degree and 0.70°C degree, respectively. While in winter the Arctic has been cooling at the decadal rate of -0.34°C degree. The Arctic surface broadband albedo also signals the warming trend of the Arctic at the decadal rate of -3.0% at the confidence level of 98.8% in autumn, indicating a longer melt period and later freeze-up. Results also show that the Arctic has become cloudier in spring and summer, but less cloudy in winter.