Cloud motion vectors from MISR using sub-pixel enhancements

Abstract

The operational retrieval of height-resolved cloud motion vectors by the Multiangle Imaging Spectro Radiometer on the Terra satellite has been significantly improved by using sub-pixel approaches to coregistration and disparity assessment, and by imposing stronger quality control based on the agreement between independent forward and aft triplet retrievals. Analysis of the fore-aft differences indicates that CMVs pass the basic operational quality control 67% of the time, with rms differences --in speed of 2.4 d s , in direction of 17", and in height assignment of 290 m. The use of enhanced quality control thresholds reduces these rms values to 1.5 d s , 17" and 165 m, respectively, at the cost of reduced coverage to 45%. Use of the enhanced thresholds also eliminates a tendency for the rms differences to increase with height. Comparison of CMVs from an earlier operational version that had slightly weaker quality control, with 6-hour forecast winds fiom the Global Modeling and Assimilation Office yielded very low bias values and an rms vector difference that ranged from 5 d s for low clouds to 1 0 d s for high clouds. Popular SummaryUnlike most satellite instruments, Multiangle Imaging SpectroRadiometer (MISR) on the Terra satellite is a new instrument that will image Earth's climate system simultaneously at 9 different angles. One camera points toward nadir, and the others provide forward and aftward view angles, at the Earth's surface, of 26.1", 45.6", 60.0", and 70.5". As the instrument flies overhead, each region of the Earth's surface is successively imaged by all nine cameras in each of four wavelengths (blue, green, red, and near-infrared).In addition to measure the amount of sunlight that is scattered in different directions, MISR can also distinguish different types of clouds, aerosol particles, and surfaces. With the information obtained from MISR in the amount, types, and heights of clouds and the distribution of land surface cover, the heightresolved cloud motion vectors (CMVs) can be retrieved.In this paper, we focused on improving operational retrieval algorithm of height-resolved CMVs. Subpixel approaches were used for co-registration and disparity assessment, and stronger quality control was imposed based on the agreement between independent forward and aft triplet retrievals. Analysis of the fore-aft differences indicated that CMVs passed the basic operational quality control 67% of the time, with rms differences --in speed of 2.4 d s , in direction of 17", and in height assignment of 290 m.The use of enhanced quality control thresholds reduced these rms values to 1.5 d s , 14" and 165 m, respectively, at the cost of reduced coverage to 45%. Use of the enhanced thresholds also eliminated a tendency for the rms differences to increase with height. Comparison of CMVs from an earlier operational version that had slightly weaker quality control, with 6-hour forecast winds from the Global Modeling and Assimilation Office yielded very low bias values and an rms vector difference that ranged fr...

Tropical biomass burning smoke plume size, shape, reflectance, and age based on 2001–2009 MISR imagery of Borneo

“…The error associated with the MINX wind speed estimates is not well established. The estimated error of the standard MISR wind retrieval is 2.9 m s −1 (Davies et al, 2007), and the MINX algorithm is considered more accurate than the MISR retrievals (Nelson et al, 2009). In this paper, we conservatively estimate MINX wind speed error at 2.9 m s −1 for each wind retrieval, thus…”

Stereoscopic Height and Wind Retrievals for Aerosol Plumes with the MISR INteractive eXplorer (MINX)

“…Because they are automatic, the operational algorithms lack the advantage of interactivity and human-in-the-loop analysis by which features can be isolated for special study, and the operational algorithms cannot take advantage of visual cues in a scene from which wind direction can be inferred. Instead, both the along-track and across-track components of the wind speed are first derived at relatively coarse spatial resolution in order to mitigate the effects of noise [43]. These results are then applied to initial (zero-wind) retrievals of cloud-top height to produce wind-corrected heights at 1.1 km horizontal resolution.…”

“…These results are then applied to initial (zero-wind) retrievals of cloud-top height to produce wind-corrected heights at 1.1 km horizontal resolution. To extract wind direction and the along-track component of wind speed requires well-registered Df/Da (±70°) and Bf/Ba (±46°) camera imagery [43]. Including the most oblique (D) cameras is an essential element of the automatic retrieval strategy, because only these views can take advantage of earth curvature to resolve wind speed [14,15].…”

“…If a feature of interest is visible in non-nadir cameras, but not in the An camera, MINX will not be able to perform a stereo retrieval for the feature. Imagery for each camera pair must be geometrically registered to a high degree of precision to minimize errors in the retrieved heights [43]. One pixel (275 m) of co-registration error (measured relative to the An camera) translates into 560 m of error in plume height for the Af/Aa (±26°) cameras, 260 m for the Bf/Ba (±46°) cameras, and 160 m for the Cf/Ca (±60°) cameras [14,15].…”

Ten years of MISR observations from Terra: Looking back, ahead, and in between

“…The global data product, which provides cloud-tracked atmospheric wind vectors at 70.4 x 70.4 km 2 horizontal and 500 m vertical resolution, is valuable for retrospective evaluation and improvement of weather and climate models. Validation against rawinsondes and radar wind profilers indicate uncertainties smaller than obtained from geostationary platforms and superior height assignments [3], [13], [19]. Spatially and temporally matched zonally-averaged wind profiles vs. height show excellent agreement between MISR and numerical analysis models, with systematic differences showing up at midlevels in the tropics [11].…”