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At least 19 records

Compact Mid-Wave Imaging System (CMIS) for Retrieval of Cloud Motion Vectors and Cloud Geometric Heights

The Johns Hopkins University Applied Physics Laboratory (JHU/APL) is developing a compact, light-weight, and low power midwave-infrared (MWIR) imager called the Compact Midwave Imaging Sensor (CMIS), under the support of the NASA Earth Science Technology Office Instrument Incubator Program. The goal of this CMIS instrument development and demonstration project is to increase the technical readiness of CMIS, a multi-spectral sensor capable of retrieving 3D winds and cloud heights 24/7, for a space mission. The CMIS instrument employs an advanced MWIR detector that requires less cooling than traditional technologies and thus permits a compact, low-power design, which enables accommodation on small spacecraft such as CubeSats. CMIS provides the critical midwave component of a multi-spectral sensor suite that includes a high-resolution Day-Night Band and a longwave infrared (LWIR) imager to provide global cloud characterization and theater weather imagery. In this presentation, an overview of the CMIS project, including the high-level sensor design, the concept of operations, and measurement capability will be presented. System performance for a variety of different scenes generated by a cloud resolving model (CRM) will also be discussed.

midwave↗

Upgrades to the NOAA/NESDIS automated Cloud-Motion Vector system

The latest version of the automated cloud motion vector software has yielded significant improvements in the quality of the GOES cloud-drift winds produced operationally by NESDIS. Cloud motion vectors resulting from the automated system are now equal or superior in quality to those which had the benefit of manual quality control a few years ago. The single most important factor in this improvement has been the upgraded auto-editor. Improved tracer selection procedures eliminate targets in difficult regions and allow a higher target density and therefore enhanced coverage in areas of interest. The incorporation of the H2O-intercept height assignment method allows an adequate representation of the heights of semi-transparent clouds in the absence of a CO2-absorption channel. Finally, GOES-8 water-vapor motion winds resulting from the automated system are superior to any done previously by NESDIS and should now be considered as an operational product.

Nieman, Steve↗

MISR 17.6 KM Gridded Cloud Motion Vectors: Overview and Assessment

The MISR (Multi-angle Imaging SpectroRadiometer) instrument on the Terra satellite has been retrieving cloud motion vectors (CMVs) globally and almost continuously since early in 2000. In February 2012 the new MISR Level 2 Cloud product was publicly released, providing cloud motion vectors at 17.6 km resolution with improved accuracy and roughly threefold increased coverage relative to the 70.4 km resolution vectors of the current MISR Level 2 Stereo product (which remains available). MISR retrieves both horizontal cloud motion and height from the apparent displacement due to parallax and movement of cloud features across three visible channel (670nm) camera views over a span of 200 seconds. The retrieval has comparable accuracy to operational atmospheric motion vectors from other current sensors, but holds the additional advantage of global coverage and finer precision height retrieval that is insensitive to radiometric calibration. The MISR mission is expected to continue operation for many more years, possibly until 2019, and Level 2 Cloud has the possibility of being produced with a sensing-to-availability lag of 5 hours. This report compares MISR CMV with collocated motion vectors from arctic rawinsonde sites, and from the GOES and MODISTerra instruments. CMV at heights below 3 km exhibit the smallest differences, as small as 3.3 m/s for MISR and GOES. Clouds above 3 km exhibit larger differences, as large as 8.9 m/s for MISR and MODIS. Typical differences are on the order of 6 m/s.

MISR (Multi-angle Imaging SpectroRadiometer)↗

Cloud Motion Vectors from MISR using Sub-pixel Enhancements

The operational retrieval of height-resolved cloud motion vectors by the Multiangle Imaging SpectroRadiometer on the Terra satellite has been significantly improved by using sub-pixel approaches to co-registration 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 m/s, in direction of 17 deg, and in height assignment of 290 m. The use of enhanced quality control thresholds reduces these rms values to 1.5 m/s, 17 deg 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 from the Global Modeling and Assimilation Office yielded very low bias values and an rms vector difference that ranged from 5 m/s for low clouds to 10 m/s for high clouds.

Davies, Roger↗

A sample computation of kinematic properties from cloud motion vectors.

Distributions of relative vorticity and balanced height have been computed from the cloud velocities associated with the cloud structure of an extratropical cyclone over the continental United States during a three-day period in March 1970. Cloud motions are assigned either to a 'mid-level,' or to a 'high level.' Derived vorticity and balanced height are compared with concurrent National Meteorological Center (NMC) analyses and also with similar kinematic quantities obtained from rawins at three constant-pressure levels. The computations of relative vorticity using mid-level cloud motion vectors show encouraging results. Patterns of computed cyclonic vorticity are related to the development, location, and movement of the surface cyclone. The analyses suggest that the 'mid-level' corresponds best to the 700-mb level. The vorticity analysis from the 'high-level' motion vectors presented difficulties.

Viezee, W.↗

Improved cloud motion wind vector and altitude assignment using VAS

A CO2 cloud tracking technique to determine simultaneous heights and velocities of cloud motion winds is presented. Using animated CO2 channel imagery from VAS (Visible Infrared Spin-Scan Radiometer Atmospheric Sounder), multi-level cloud situations are separated into high, middle and low level cloud motion wind vectors by the CO2 slicing method. The VAS CO2 channel radiometric values are used in the CO2 absorption method to assign quantitative heights to the cloud vectors; cloud top pressures are determined from the ratio of the deviations in cloud produced radiances and the corresponding clear air values for three CO2 channels in a radiative transfer equation formulation. Two case studies are presented that show CO2 cloud-motion wind vectors to be in good agreement with radiosonde wind observations and CO2 cloud heights to be within a 50 mb rms deviation of radiosonde, bispectral and stereo height determinations.

Menzel, W. P.↗

The effect of the arbitrary level assignment of satellite cloud motion wind vectors on wind analyses in the pre-thunderstorm environment

The impact of satellite-derived cloud motion vectors on SESAME rawinsonde wind fields was studied in two separate cases. The effect of wind and moisture gradients on the arbitrary assignment of the satellite data is assessed to coordinate surfaces in a severe storm environment marked by strong vertical wind shear. Objective analyses of SESAME rawinsonde winds and combined winds are produced and differences between these two analyzed fields are used to make an assessment of coordinate level choice. It is shown that the standard method of arbitrarily assigning wind vectors to a low level coordinate surface yields systematic differences between the rawinsonde and combined wind analyses. Arbitrary assignment of cloud motions to the 0.9 sigma surface produces smaller differences than assignment to the 825 mb pressure surface. Systematic differences occur near moisture discontinuities and in regions of horizontal and vertical wind shears. The differences between the combined and SESAME wind fields are made smallest by vertically interpolating cloud motions to either a pressure or sigma surface.

Peslen, C. A.↗

The effect of the arbitrary level assignment of satellite cloud motion wind vectors on wind analyses in the pre-thunderstorm environment

The impact of satellite-derived cloud motion vectors on SESAME rawinsonde wind fields was studied in two separate cases. The effect of wind and moisture gradients on the arbitrary assignment of the satellite data is assessed to coordinate surfaces in a severe storm environment marked by strong vertical wind shear. Objective analyses of SESAME rawinsonde winds and combined winds are produced and differences between these two analyzed fields are used to make an assessment of coordinate level choice. It is shown that the standard method of arbitrarily assigning wind vectors to a low level coordinate surface yields systematic differences between the rawinsonde and combined wind analyses. Arbitrary assignment of cloud motions to the 0.9 sigma surface produces smaller differences than assignment to the 825 mb pressure surface. Systematic differences occur near moisture discontinuities and in regions of horizontal and vertical wind shears. The differences between the combined and SESAME wind fields are made smallest by vertically interpolating cloud motions to either a pressure or sigma surface.

Peslen, C. A.↗

MISR Level 2 TOA/Cloud Stereo parameters (MIL2TCST_V1)

The MISR Top-of-Atmosphere (TOA)/Cloud Stereo geophysical parameters include stereoscopically-derived cloud motion vectors (winds), cloud-top heights, and an accompanying cloud mask. The Stereo product geophysical parameters include a stereoscopically-derived cloud mask and cloud height on a 1.1 km grid. It also includes cloud motion vectors on a 70.4 km grid. The three types of stereo heights are: the BestWind heights are only calculated for those regions where the associated wind vectors passed the quality tests. Therefore, they have sparse coverage but since the wind correction is included, these contain our 'best guess' as to what the true heights are. The WithoutWind heights are calculated assuming a constant wind vector of zero. They have almost complete coverage and therefore form a nice 'pretty picture' of the relative cloud heights over small areas. The RawWind heights are a diagnostic product as they are calculated using all available wind vectors (even the bad ones). It is therefore recommended that one only use the Best and Without wind products. It is important to remember that the stereo matchers pick up the layer of maximum contrast, which is not necessarily the same as the highest cloud so all the stereo heights are keyed to this level of maximum contrast. Therefore, higher and thinner cirrus layers may not be detected by any of the height fields. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km; Longitude_Resolution=1.1 km; Horizontal_Resolution_Range=1 km - < 10 km or approximately .01 degree - < .09 degree; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly].

EOSDIS↗

MISR Level 2 TOA/Cloud Stereo parameters (MIL2TCST_V2)

The MISR Top-of-Atmosphere (TOA)/Cloud Stereo geophysical parameters include stereoscopically-derived cloud motion vectors (winds), cloud-top heights, and an accompanying cloud mask. The Stereo product geophysical parameters include a stereoscopically-derived cloud mask and cloud height on a 1.1 km grid. It also includes cloud motion vectors on a 70.4 km grid. The three types of stereo heights are: the BestWind heights are only calculated for those regions where the associated wind vectors passed the quality tests. Therefore, they have sparse coverage but since the wind correction is included, these contain our 'best guess' as to what the true heights are. The WithoutWind heights are calculated assuming a constant wind vector of zero. They have almost complete coverage and therefore form a nice 'pretty picture' of the relative cloud heights over small areas. The RawWind heights are a diagnostic product as they are calculated using all available wind vectors (even the bad ones). It is therefore recommended that one only use the Best and Without wind products. It is important to remember that the stereo matchers pick up the layer of maximum contrast, which is not necessarily the same as the highest cloud so all the stereo heights are keyed to this level of maximum contrast. Therefore, higher and thinner cirrus layers may not be detected by any of the height fields. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km; Longitude_Resolution=1.1 km; Temporal_Resolution=about 15 orbits/day].

CLOUD MASK↗

Wind estimates from cloud motions - Phase 1 of an in situ aircraft verification experiment

An initial experiment has been conducted to verify geostationary-satellite-derived cloud motion wind estimates with in situ aircraft wind velocity measurements. Case histories of 1/2 to 2 h were obtained for 3-10 km diameter cumulus cloud systems on 6 days. Also, one cirrus cloud case was obtained. In most cases the clouds were discrete enough that both the cloud motion and the ambient wind could be measured with the same aircraft Inertial Navigation System (INS). Since the INS drift error is the same for both the cloud motion and wind measurements, the drift error drops out of the relative motion determinations. The magnitude of the vector difference between the cloud motion and the ambient wind at the cloud base averaged 1.2 m/sec. The wind vector at higher levels in the cloud layer differed by about 3 to 5 m/sec from the cloud motion vector.

Hasler, A. F.↗

Wind estimates from cloud motions: Phase 1 of an in situ aircraft verification experiment

An initial experiment was conducted to verify geostationary satellite derived cloud motion wind estimates with in situ aircraft wind velocity measurements. Case histories of one-half hour to two hours were obtained for 3-10km diameter cumulus cloud systems on 6 days. Also, one cirrus cloud case was obtained. In most cases the clouds were discrete enough that both the cloud motion and the ambient wind could be measured with the same aircraft Inertial Navigation System (INS). Since the INS drift error is the same for both the cloud motion and wind measurements, the drift error subtracts out of the relative motion determinations. The magnitude of the vector difference between the cloud motion and the ambient wind at the cloud base averaged 1.2 m/sec. The wind vector at higher levels in the cloud layer differed by about 3 m/sec to 5 m/sec from the cloud motion vector.

Hasler, A. F.↗

Analysis of ATS photographs using a specially designed electronic console

Measurements of cloud motion, cloud size, and growth rate were made on four days in the vicinity of rawin stations in the BOMEX network. These measurements were compared with the rawins and levels of best fit ranging from 980 to 250 mb were found. No correlation was found between cloud size and level of best fit. The magnitude of the vector difference between the cloud motion and wind at the level of best fit was as high as 15 knots for clouds with levels of best fit below the 500-mb level and 8 knots for clouds with levels of best fit above the 500-mb level. When cloud motion vectors with levels of best fit at or above the 500-mb level were compared with winds at the 300-mb level, the vector difference increased to as much as 16 knots or double the greatest minimum vector difference. A comparison between cloud motions and winds at the level of best fit showed that the clouds tended to move slightly faster than the observed winds and to move slightly to the left of the wind direction. Rate of growth appeared to influence whether clouds moved faster or slower than the wind. No relationship between cloud size and amount of deviation from the wind direction was observed.

Blackmer, R. H., Jr.↗

CubeSat Constellation Cloud Winds(C3Winds) A New Wind Observing System to Study Mesoscale Cloud Dynamics and Processes

The CubeSat Constellation Cloud Winds (C3Winds) is a NASA Earth Venture Instrument (EV-I) concept with the primary objective to better understand mesoscale dynamics and their structures in severe weather systems. With potential catastrophic damage and loss of life, strong extratropical and tropical cyclones (ETCs and TCs) have profound three-dimensional impacts on the atmospheric dynamic and thermodynamic structures, producing complex cloud precipitation patterns, strong low-level winds, extensive tropopause folds, and intense stratosphere-troposphere exchange. Employing a compact, stereo IR-visible imaging technique from two formation-flying CubeSats, C3Winds seeks to measure and map high-resolution (2 km) cloud motion vectors (CMVs) and cloud geometric height (CGH) accurately by tracking cloud features within 5-15 min. Complementary to lidar wind observations from space, the high-resolution wind fields from C3Winds will allow detailed investigations on strong low-level wind formation in an occluded ETC development, structural variations of TC inner-core rotation, and impacts of tropopause folding events on tropospheric ozone and air quality. Together with scatterometer ocean surface winds, C3Winds will provide a more comprehensive depiction of atmosphere-boundary-layer dynamics and interactive processes. Built upon mature imaging technologies and long history of stereoscopic remote sensing, C3Winds provides an innovative, cost-effective solution to global wind observations with potential of increased diurnal sampling via CubeSat constellation.

mesoscale dynamics↗

The pointing errors of geosynchronous satellites

A study of the correlation between cloud motion and wind field was initiated. Cloud heights and displacements were being obtained from a ceilometer and movie pictures, while winds were measured from pilot balloon observations on a near-simultaneous basis. Cloud motion vectors were obtained from time-lapse cloud pictures, using the WINDCO program, for 27, 28 July, 1969, in the Atlantic. The relationship between observed features of cloud clusters and the ambient wind field derived from cloud trajectories on a wide range of space and time scales is discussed.

Sikdar, D. N.↗

Automatic cloud tracking applied to GOES and Meteosat observations

An improved automatic processing method for the tracking of cloud motions as revealed by satellite imagery is presented and applications of the method to GOES observations of Hurricane Eloise and Meteosat water vapor and infrared data are presented. The method is shown to involve steps of picture smoothing, target selection and the calculation of cloud motion vectors by the matching of a group at a given time with its best likeness at a later time, or by a cross-correlation computation. Cloud motion computations can be made in as many as four separate layers simultaneously. For data of 4 and 8 km resolution in the eye of Hurricane Eloise, the automatic system is found to provide results comparable in accuracy and coverage to those obtained by NASA analysts using the Atmospheric and Oceanographic Information Processing System, with results obtained by the pattern recognition and cross correlation computations differing by only fractions of a pixel. For Meteosat water vapor data from the tropics and midlatitudes, the automatic motion computations are found to be reliable only in areas where the water vapor fields contained small-scale structure, although excellent results are obtained using Meteosat IR data in the same regions. The automatic method thus appears to be competitive in accuracy and coverage with motion determination by human analysts.

Endlich, R. M.↗