Andrew K. Heidinger

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

Clouds cover about 70% of Earths surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that compose weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climate data records must be compiled from different satellite datasets and can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors and retrieval methods. The Global Energy and Water Cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel (GEWEX Data and Assessment Panel since 2011), provides the first coordinated intercomparison of publicly available, standard global cloud products (gridded monthly statistics) retrieved from measurements of multispectral imagers (some with multiangle view and polarization capabilities), IR soun...

The Role of Aerosols in the Evolution of Tropical North Atlantic Ocean Temperature Anomalies

Dust in the Wind The temperature of North Atlantic surface waters has a major effect on climate in a variety of ways, not least because its heat content helps to control hurricane formation and strength. The North Atlantic surface has warmed considerably in recent decades, a trend generally associated with global or regional air temperature increases, or with changes in ocean circulation. Evan et al. (p. 778, published online 26 March) use nearly 30 years of satellite data to examine another source of ocean temperature variability, the radiative effects of atmospheric aerosols. Low frequency changes in local tropical North Atlantic surface temperatures seem mostly to be caused by variability in mineral and stratospheric aerosol abundances. Thus, to provide more accurate projections of these temperatures, general circulation models will need to account for long-term changes in dust loadings. Changes in tropical North Atlantic sea surface temperatures are caused by variability in atmospheric aerosol abundances. Observations and models show that northern tropical Atlantic surface temperatures are sensitive to regional changes in stratospheric volcanic and tropospheric mineral aerosols. However, it is unknown whether the temporal variability of these aerosols is a key factor in the evolution of ocean temperature anomalies. We used a simple physical model, incorporating 26 years of satellite data, to estimate the temperature response of the ocean mixed layer to changes in aerosol loadings. Our results suggest that the mixed layer’s response to regional variability in aerosols accounts for 69% of the recent upward trend, and 67% of the detrended and 5-year low pass–filtered variance, in northern tropical Atlantic Ocean temperatures.

A Daytime Complement to the Reverse Absorption Technique for Improved Automated Detection of Volcanic Ash

Abstract An automated volcanic cloud detection algorithm that utilizes four spectral channels (0.65, 3.75, 11, and 12 μm) that are common among several satellite-based instruments is presented. The new algorithm is physically based and globally applicable and can provide quick information on the horizontal location of volcanic clouds that can be used to improve real-time ash hazard assessments. It can also provide needed input into volcanic cloud optical depth and particle size retrieval algorithms, the products of which can help improve ash dispersion forecasts. The results of this new four-channel algorithm for several scenes were compared to a threshold-based reverse absorption algorithm, where the reverse absorption algorithm is used to identify measurements with a negative 11–12-μm brightness temperature difference. The results indicate that the new four-channel algorithm is not only more sensitive to the presence of volcanic clouds but also generally less prone to false alarms than the standard reve...

Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band

Daytime measurements of reflected sunlight in the visible spectrum have been a staple of Earth-viewing radiometers since the advent of the environmental satellite platform. At night, these same optical-spectrum sensors have traditionally been limited to thermal infrared emission, which contains relatively poor information content for many important weather and climate parameters. These deficiencies have limited our ability to characterize the full diurnal behavior and processes of parameters relevant to improved monitoring, understanding and modeling of weather and climate processes. Visible-spectrum light information does exist during the nighttime hours, originating from a wide variety of sources, but its detection requires specialized technology. Such measurements have existed, in a limited way, on USA Department of Defense satellites, but the Suomi National Polar-orbiting Partnership (NPP) satellite, which carries a new Day/Night Band (DNB) radiometer, offers the first quantitative measurements of nocturnal visible and near-infrared light. Here, we demonstrate the expanded potential for nocturnal low-light visible applications enabled by the DNB. Via a combination of terrestrial and extraterrestrial light sources, such observations are always available—expanding many current existing applications while enabling entirely new capabilities. These novel low-light measurements open doors to a wealth of new interdisciplinary research topics while lighting a pathway toward the optimized design of follow-on satellite based low light visible sensors.

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...

Inter-comparison of the longwave infrared channels of MODIS and AVHRR/NOAA-16 using simultaneous nadir observations at orbit intersections

Near nadir observations in the 11μm and 12 μm bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the TERRA spacecraft and the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA-16 spacecraft are collected at their orbit intersections, where both MODIS and AVHRR view the Earth and its atmosphere at the same location within 30 seconds in the Arctic region. Sample data with 1 km resolution from spatially uniform areas are taken for direct inter-comparison of the scene radiance and brightness temperatures at around 270 K. Then a pixel-by-pixel match between the MODIS and AVHRR observations is performed to evaluate their correlation at different scene temperatures. The results show that MODIS and AVHRR observations agree well (difference less than 0.3 K) for both the 11μm and 12 μm bands, although their band correlation exhibits a slightly non-linear trend for scene temperatures greater than 285 K. The performance of MODIS is considered a good predictor of the performance of the National Polar-orbiting Operational Environmental Satellite System (NPOESS)/Visible Infrared Imager/Radiometer Suite (VIIRS), the future replacement of AVHRR. The direct comparison of MODIS and AVHRR observations is therefore considered a risk reduction study for VIIRS.

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.

Bulk Scattering Properties for the Remote Sensing of Ice Clouds. Part III: High-Resolution Spectral Models from 100 to 3250 cm−1

Abstract This study reports on the development of bulk single-scattering models for ice clouds that are appropriate for use in hyperspectral radiative transfer cloud modeling over the spectral range from 100 to 3250 cm−1. The models are developed in a manner similar to that recently reported for the Moderate-Resolution Imaging Spectroradiometer (MODIS); therefore these models result in a consistent set of scattering properties from visible to far-infrared wavelengths. The models incorporate a new database of individual ice-particle scattering properties that includes droxtals, 3D bullet rosettes, hexagonal solid and hollow columns, aggregates, and plates. The database provides single-scattering properties for each habit in 45 size bins ranging from 2 to 9500 μm, and for 49 wavenumbers between 100 and 3250 cm−1, which is further interpolated to 3151 discrete wavenumbers on the basis of a third-order spline interpolation method. Bulk models are developed by integrating various properties over both particle ...

Spectral signature of ice clouds in the far-infrared region: Single-scattering calculations and radiative sensitivity study

(extinction efficiency, absorption efficiency, and the asymmetry factor of the scattering phase function) are calculated for small particles using circular cylinders and for large crystals using hexagonal columns. The scattering properties are computed for particle sizes over a size range from 1 to 10,000 mm in maximum dimension from a combination of the T-matrix method, the Lorenz-Mie theory, and an improved geometric optics method. Bulk scattering properties are derived subsequently for 30 particle size distributions, with effective particle sizes ranging from 15 to 150 mm, obtained from various field campaigns for midlatitude and tropical cirrus clouds. Furthermore, a parameterization of the bulk scattering properties is developed. The radiative properties of ice clouds and the clear-sky optical thickness computed from the line-by-line method are input to a radiative transfer model to simulate the upwelling spectral radiance in the far-IR spectral region at the research aircraft height (20 km). On the basis of the simulations, we investigate the sensitivity of far-IR spectra to ice cloud optical thickness and effective particle size. The brightness temperature difference (BTD) between 250 and 559.5 cm � 1 is shown to be sensitive to optical thickness for optically thin clouds (visible optical thickness t 8), the BTD between 250 and 410.2 cm � 1 is shown to be sensitive to the effective particle size up to a limit of 100 mm. INDEX TERMS: 3359 Meteorology and Atmospheric Dynamics: Radiative processes; 3360 Meteorology and Atmospheric Dynamics: Remote sensing; 0649 Electromagnetics: Optics; KEYWORDS: far-infrared, cirrus cloud, ice crystal

Nowcasting Convective Storm Initiation Using Satellite-Based Box-Averaged Cloud-Top Cooling and Cloud-Type Trends

Abstract Short-term (0–1 h) convective storm nowcasting remains a problem for operational weather forecasting, and convective storms pose a significant monetary sink for the aviation industry. Numerical weather prediction models, traditional meteorological observations, and radar are all useful for short-term convective forecasting, but all have shortcomings. Geostationary imagers, while having their own shortcomings, are valuable assets for addressing the convective initiation nowcast problem. The University of Wisconsin Convective Initiation (UWCI) nowcasting algorithm is introduced for use as an objective, satellite-based decision support tool. The UWCI algorithm computes Geostationary Operational Environmental Satellite (GOES) Imager infrared window channel box-averaged cloud-top cooling rates and creates convective initiation nowcasts based on a combination of cloud-top cooling rates and satellite-derived cloud-top type–phase trends. The UWCI approach offers advantages over existing techniques, such ...