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Cloud motions from IR measurements within overlap region of adjacent Nimbus II orbits compared with wind vectors from constant pressure charts
It has been demonstrated that geostationary satellite imagery provides an effective means of extracting two-dimensional cloud motion wind measurements over large areas. The addition of cloud height information is necessary, however, for the proper assignment of altitude to the wind vectors. This paper discusses the methodology and accuracy of extracting multilevel cloud motion measurements from stereo digital imagery acquired from geostationary orbit.
A world wide system of 5 geostationary satellites is being established with a primary objective: the estimation of winds from cloud motions. A series of aircraft experiments were carried out to perform an in situ verification of the satellite cloud winds, under undisturbed to moderately disturbed oceanic weather regimes.
Vortex streets formed in the stratocumulus‐capped wake of mountainous islands are the atmospheric analogues of the classic Kármán vortex street observed in laboratory flows past bluff bodies. The quantitative analysis of these mesoscale unsteady atmospheric flows has been hampered by the lack of satellite wind retrievals of sufficiently high spatial and temporal resolution. Taking advantage of the cutting‐edge Advanced Baseline Imager, we derived kilometer‐scale cloud‐motion winds at 5‐min frequency for a vortex street in the lee of Guadalupe Island imaged by Geostationary Operational Environmental Satellite‐16. Combined with Moderate Resolution Imaging Spectroradiometer data, the geostationary imagery also provided accurate stereo cloud‐top heights. The time series of geostationary winds, supplemented with snapshots of ocean surface winds from the Advanced Scatterometer, allowed us to capture the wake oscillations and measure vortex shedding dynamics. The retrievals revealed a markedly asymmetric vortex decay, with cyclonic eddies having larger peak vorticities than anticyclonic eddies at the same downstream location. Drawing on the vast knowledge accumulated about laboratory bluff body flows, we argue that the asymmetric island wake arises from the combined effects of Earth's rotation and Guadalupe's nonaxisymmetric shape resembling an inclined flat plate at low angle of attack. However, numerical simulations will need to establish whether or not the selective destabilization of the shallow atmospheric anticyclonic eddies is caused by the same mechanisms that destabilize the deep columnar anticyclones of laboratory flows, such as three‐dimensional vertical perturbations due to centrifugal or elliptical instabilities.
Current NESS winds operations provide approximately 1800 high quality wind estimates per day to about twenty domestic and foreign users. This marked improvement in NESS winds operations was the result of computer techniques development which began in 1969 to streamline and improve operational procedures. In addition, the launch of the SMS-1 satellite in 1974, the first in the second generation of geostationary spacecraft, provided an improved source of visible and infrared scanner data for the extraction of wind estimates. Currently, operational winds processing at NESS is accomplished by the automated and manual analyses of infrared data from two geostationary spacecraft. This system uses data from SMS-2 and GOES-1 to produce wind estimates valid for 00Z, 12Z and 18Z synoptic times.
The utility of VISSR Atmospheric Sounder (VAS) temperature and moisture soundings and cloud and water vapor motion winds in defining a storm and its surroundings at subsynoptic scales has been examined using a numerical analysis and prognosis system. It is shown that the VAS temperature and moisture data, which specify temperature and moisture well in cloud-free areas, are complemented by cloud and water vapor motion data generated in the cloudy areas. The cloud and water vapor 'winds' provide thermal gradient information for interpolating the soundings across cloudy regions. The loss of analysis integrity due to the reduction of VAS sounding density in the cloudy regions associated with synoptic activity is ameliorated by using cloud and water vapor motion winds. The improvement in numerical forecasts resulting from the addition of these data to the numerical analysis is recorded.
Statistical comparisons between winds measured by ACARS and winds obtained from radiosondes, geostationary satellite image cloud motions, and VAS are presented. Observations from three separate comparisons reveal over 60 percent of wind vector magnitude differences are within 9 m/s, and 70 percent of the directional differences are within 15 deg. The comparisons indicate that the ACARS system provides an independent source of wind data that complements other sources of wind data for constructing composite wind field analyses.
An unusually large amount of aircraft, rawinsonde, satellite, ship and buoy data from hurricane Frederic (1979) are composited over a 40 hr period. These are combined with Frank's (1984) analysis of Frederic's core and Powell's (1982) surface wind analysis to analyze Frederic's three dimensional low level structure between the storm center and a radius of 10 deg. latitude. The analysis is improved significantly by determining the levels at which low level cloud motion winds (CMW's) are in the best agreement with verification wind data and then adjusting the winds to uniform analysis levels. Due to the unusually good low level wind resolution afforded by this data set, it is possible to obtain kinematically derived fields of vorticity, divergence and vertical velocity. These analyses are observed to be internally consistent and should prove useful for future analysis. Analysis of Frederic's surface to 560 m angular momentum budget beyond 2 deg. radius indicates that surface drag coefficients increase slightly with increasing radius and decreasing wind speed. Estimates of storm rainfall obtained by performing a moisture budget between the surface and the top of the inflow layer show that most storm rainfall falls inside about 4 deg. radius and that substantial underestimation of storm rainfall occurs when all low level CMW's are assigned to 560 m.
Comparisons are made between winds obtained from EOLE balloons and winds determined from cloud motions as observed from the Applications Technology Satellites, ATS-1 and ATS-3. The results show that the mean winds determined from EOLE balloons are greater in speed than mean winds derived from cloud motion observations. Inspection of the total set of comparisons lead one to conclude that the cloud motion winds in the 20-50 S latitude band apply to a level lower than 200 mb. The mean differences become smaller toward the equator and the results further suggest that the cloud motion winds apply to altitudes higher than 200 mb equatorward of 20 S.
A robust and computationally efficient object tracking algorithm is developed by incorporating various tracking techniques. Physical properties of the objects, such as brightness temperature or reflectivity, are not considered. Therefore, the algorithm is adaptable for tracking convection-like features in simulated data and remotely sensed two-dimensional images. In this algorithm, a first guess of the motion, estimated using the Fourier phase shift, is used to predict the candidates for matching. A disparity score is computed for each target–candidate pair. The disparity also incorporates overlapping criteria in the case of large objects. Then the Hungarian method is applied to identify the best pairs by minimizing the global disparity. The high-disparity pairs are unmatched, and their target and candidate are declared expired and newly initiated objects, respectively. They are tested for merger and split on the basis of their size and overlap with the other objects. The sensitivity of track duration is shown for different disparity and size thresholds. The report highlights the algorithm’s ability to study convective life cycles using radar and simulated data over Darwin, Australia. The algorithm skillfully tracks individual convective cells (a few pixels in size) and large convective systems. The duration of tracks and cell size are found to be lognormally distributed over Darwin. The evolution of size and precipitation types of isolated convective cells is presented in the Lagrangian perspective. This algorithm is part of a vision for a modular platform [viz., TINT is not TITAN (TINT) and Tracking and Object-Based Analysis of Clouds (tobac)] that will evolve into a sustainable choice to analyze atmospheric features.
Data from the geostationary Visible Infrared Spin-Scan Radiometer (VISSR) Atmospheric Sounder (VAS) for assigning simultaneous heights and velocities of cloud motion winds were processed. The following two techniques are discussed: The technique which delivers qualitative height assignments from imagery; and which uses the radiometric information contained in the VAS data to calculate quantitative heights.
The CD-ROM concerning the June 2001 Monthly Report of the Meteorological Satellite Center (MSC) contains the observation data derived from the Geostationary Meteorological Satellite (GMS) of Japan and the Polar Orbital Meteorological Satellites operated by NOAA. The CD-ROM contains the following observation data: Full Disk Earth's Cloud Image; Cloud Image of Japan and its vicinity; Cloud Amount; Sea Surface Temperature; Cloud Motion Wind; Water Vapor Motion Wind; Equivalent Blackbody Temperature; OLR (Out-going Longwave Radiation), Solar Radiation; Snow and Ice Index; Orbit Data; Attitude Data; VISSR Image Data Catalog (Cartridge Magnetic Tape (CMT), Micro Film); TOVS (TIROS Operational Vertical Sounder) Vertical Profile of Temperature and Precipitable Water; and TOVS Total Ozone Amount.
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].
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].
A 5-year aircraft experiment to verify the quality of satellite cloud winds over oceans using in situ aircraft Inertial Navigation System wind measurements is presented. Cloud motions measured by satellite and aircraft wind measurements that were coincident in time and space, and the results from the experiment are for undisturbed to moderately disturbed oceanic weather regimes. The results show that satellite measured cumulus cloud motions are good estimators of the cloud-base wind for trade wind and subtropical high regions. The average magnitude of the vector differences between the cloud motion and the cloud-base wind was determined; for cumulus clouds near frontal regions, the cloud motions agreed best with the mean cloud layer wind. For a very limited sample, cirrus cloud motions most closely followed the mean wind in the cloud layer.
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.
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.
A five year aircraft experiment to verify the quality of satellite cloud winds over oceans using in situ aircraft inertial navigation system wind measurements is presented. The final results show that satellite measured cumulus cloud motions are very good estimators of the cloud base wind for trade wind and subtropical high regions. The average magnitude of the vector differences between the cloud motion and the cloud base wind is given. For cumulus clouds near frontal regions, the cloud motion agreed best with the mean cloud layer wind. For a very limited sample, cirrus cloud motions also most closely followed the mean wind in the cloud layer.