Assessment of MISR and MODIS cloud top heights through inter-comparison with a back-scattering lidar at SIRTA

One year of back-scattering lidar cloud boundaries and optical depth were analysed for coincident inter-comparison with the latest processed versions of the NASA-TERRA MISR stereo and MODIS CO2-slicing operational cloud top heights. Optically thin clouds were found to be accurately characterised by the MISR cloud top height product as long as no other cloud was present at lower altitude. MODIS cloud top heights were generally found within the cloud extent retrieved by lidar; agreement improved as cloud optical depth increased and when CO2-slicing was the only technique used for the retrieval. The difference between Lidar and MISR cloud top heights was found to lie between −0.1 and 0.4 km for low clouds and between 0.1 and 3.1 km for high clouds. The difference between Lidar and MODIS cloud top heights was found to lie between −1.2 and 1.5 km for low clouds and between −1.4 and 2.7 km for high clouds

MISR stereoscopic image matchers: techniques and results

The Multi-angle Imaging SpectroRadiometer (MISR) instrument, launched in December 1999 on the NASA EOS Terra satellite, produces images in the red band at 275-m resolution, over a swath width of 360 km, for the nine camera angles 70.5/spl deg/, 60/spl deg/, 45.6/spl deg/, and 26.1/spl deg/ forward, nadir, and 26.1/spl deg/, 45.6/spl deg/, 60/spl deg/, and 70.5/spl deg/ aft. A set of accurate and fast algorithms was developed for automated stereo matching of cloud features to obtain cloud-top height and motion over the nominal six-year lifetime of the mission. Accuracy and speed requirements necessitated the use of a combination of area-based and feature-based stereo-matchers with only pixel-level acuity. Feature-based techniques are used for cloud motion retrieval with the off-nadir MISR camera views, and the motion is then used to provide a correction to the disparities used to measure cloud-top heights which are derived from the innermost three cameras. Intercomparison with a previously developed "superstereo" matcher shows that the results are very comparable in accuracy with much greater coverage and at ten times the speed. Intercomparison of feature-based and area-based techniques shows that the feature-based techniques are comparable in accuracy at a factor of eight times the speed. An assessment of the accuracy of the area-based matcher for cloud-free scenes demonstrates the accuracy and completeness of the stereo-matcher. This trade-off has resulted in the loss of a reliable quality metric to predict accuracy and a slightly high blunder rate. Examples are shown of the application of the MISR stereo-matchers on several difficult scenes which demonstrate the efficacy of the matching approach

Assessment of the performance of the Chilbolton 3-GHz Advanced Meteorological radar for cloud-top height retrieval

The Chilbolton 3-GHz Advanced Meteorological Radar (CAMRa), which is mounted on a fully steerable 25 metre dish, can provide three-dimensional information on the presence of hydrometeors. We investigate the potential for this radar to make useful measurements of low-altitude liquid water cloud structure. In order to assess the cloud-height assignment capabilities of the 3-GHz radar, low-level cloud-top heights were retrieved from CAMRa measurements made between May and July 2003 and compared with cloud-top heights retrieved from a vertically pointing 94-GHz radar that operates alongside CAMRa. The average difference between 94-GHz and 3-GHz radar derived cloud-top heights is shown to be -0.1±0.4 km. In order to assess the capability of 3-GHz radar scans to be used for satellite-derived cloud-top height validation, Multi-angle Imaging SpectroRadiometer (MISR) cloud-top heights were compared with both 94-GHz and 3-GHz radar retrievals. The average difference between 94-GHz radar and MISR cloud-top heights is shown to be 0.1±0.3 km while the 3-GHz radar and MISR average cloud-top height difference is shown to be –0.2±0.6 km. In assessing the value of the CAMRa measurements, the problems associated with low reflectivity values from stratiform liquid water clouds, ground clutter, and Bragg scattering resulting from turbulent mixing are all addressed. We show that in spite of the difficulties, the potential exists for CAMRa measurements to contribute significantly to liquid water cloud-top height retrievals leading to the production of twodimensional transects (i.e. maps) of cloud-top height

MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds

Global wind observations are fundamental for studying weather and climate dynamics and for operational forecasting. Most wind measurements come from atmospheric motion vectors (AMVs) by tracking the displacement of cloud or water vapor features. These AMVs generally rely on thermal infrared (IR) techniques for their height assignments, which are subject to large uncertainties in the presence of weak or reversed vertical temperature gradients near the planetary boundary layer (PBL)and tropopause folds. Stereo imaging can overcome the height assignment problem using geometric parallax for feature height determination. In this study we develop a stereo 3D-Wind algorithm to simultaneously retrieve AMV and height from geostationary (GEO) and low Earth orbit (LEO) satellite imagery and apply it to collocated Geostationary Operational Environmental Satellite (GOES)and Multi-angle Imaging SpectroRadiometer (MISR) imagery. The new algorithm improves AMV and height relative to products from GOES or MISR alone, with an estimated accuracy of <0.5 m/s in AMV and <200 m in height with 2.2 km sampling. The algorithm can be generalized to other LEO-GEO or LEO-LEO combinations for greater spatiotemporal coverage. The technique demonstrated with MISR and GOES has important implications for future high-quality AMV observations, for which a low-cost constellation of CubeSats can play a vital role

A multi-sensor approach to determining volcanic plume heights in the North Pacific

Thesis (M.S.) University of Alaska Fairbanks, 2012During a volcanic eruption, accurate height information is necessary to forecast a volcanic plume's trajectory with volcanic ash transport and dispersion (VATD) models. Recent events in the North Pacific (NOPAC) displayed significant discrepancies between different methods of plume height determination. This thesis describes two studies that attempted to resolve this discrepancy, and identify the most accurate method for plume height determination. The first study considered the 2009 eruption of Redoubt Volcano. This study found that the basic satellite temperature method, in which satellite thermal infrared temperatures are compared to temperature-altitude profiles, vastly underestimates volcanic plume height due to decreased optical depth of plumes soon after eruption. This study also found that the Multi-angle Imaging SpectroRadiometer (MISR) produced very accurate plume heights, even for optically thin plumes. The second study investigated the application of MISR data to multiple eruptions in the NOPAC: Augustine Volcano in 2006, Okmok, Cleveland, and Kasatochi volcanoes in 2008, and Redoubt and Sarychev Peak volcanoes in 2009. This study found that MISR data analysis retrieves accurate plume heights regardless of grain size, altitude, or water content. Exceptions include plumes of low optical depth over bright backgrounds. MISR is also capable of identifying ash clouds by aerosol type

Overlooked examples of cloud self-organization at the mesoscale

Stratocumulus clouds are common in the tropical and subtropical marine boundary layer, and understanding these clouds is important due to their significant impact on the earth's radiation budget. Observations show that the marine boundary layer contains complex, but poorly understood processes, which, from time to time, result in the observable self-organization of cloud structures at scales ranging from a few to a few thousand kilometers. Such shallow convective cloud features, typically observed as hexagonal cells, are known generally as mesoscale cellular convection (MCC). Actinoform clouds are rarer, but visually more striking forms of MCC, which possess a radial structure. Because mesoscale cloud features are typically too large to be observed from the ground, observations of hexagonal cells historically date only to the beginning of satellite meteorology. Examples of actinoform clouds were shown in the venerable “Picture of the Month” series in Monthly Weather Review in the early 1960s, but these clouds were generally forgotten as research focused on hexagonal cells. Recent high-resolution satellite images have, in a sense, “rediscovered” actinoform clouds, and they appear to be much more prevalent than had been previously suspected. We show a number of examples of actinoform clouds from a variety of locations worldwide. In addition, we have conducted a detailed case study of an actinoform cloud system using data from the Multiangle Imaging SpectroRadiometer (MISR) and the Geostationary Operational Environmental Satellite (GOES), including analysis of cloud heights, radiative properties, and the time-evolution of the cloud system. We also examine earlier theories regarding actinoform clouds in light of the new satellite data

Reducing the Uncertainties in Direct Aerosol Radiative Forcing

Airborne particles, which include desert and soil dust, wildfire smoke, sea salt, volcanic ash, black carbon, natural and anthropogenic sulfate, nitrate, and organic aerosol, affect Earth's climate, in part by reflecting and absorbing sunlight. This paper reviews current status, and evaluates future prospects for reducing the uncertainty aerosols contribute to the energy budget of Earth, which at present represents a leading factor limiting the quality of climate predictions. Information from satellites is critical for this work, because they provide frequent, global coverage of the diverse and variable atmospheric aerosol load. Both aerosol amount and type must be determined. Satellites are very close to measuring aerosol amount at the level-of-accuracy needed, but aerosol type, especially how bright the airborne particles are, cannot be constrained adequately by current techniques. However, satellite instruments can map out aerosol air mass type, which is a qualitative classification rather than a quantitative measurement, and targeted suborbital measurements can provide the required particle property detail. So combining satellite and suborbital measurements, and then using this combination to constrain climate models, will produce a major advance in climate prediction

Automated stereo retrieval of smoke plume injection heights and retrieval of smoke plume masks from AATSR and assessment with CALIPSO and MISR.

The longevity and dispersion of smoke and asso- ciated chemical constituents released from wildfire events are dependent on several factors, crucially including the height at which the smoke is injected into the atmosphere. The aim here is to provide improved emission data for the initialization of chemical transport models in order to better predict aerosol and trace gas dispersion following injection into the free atmosphere. A new stereo-matching algorithm, named M6, which can effec- tively resolve smoke plume injection heights (SPIH), is presented here. M6 is extensively validated against two alternative space- borne earth observation SPIH data sources and demonstrates good agreement. Further, due to the spectral and dual-view configuration of the Advanced Along-Track Scanning Radiometer imaging system, it is possible to automatically differentiate smoke from other atmospheric features effectively—a feat, which currently no other algorithm can achieve. Additionally, as the M6 algorithm shares a heritage with the other M-series matchers, it is here compared against one of its predecessors, M4, which, for the determination of SPIH, M6 is shown to substantially outperform