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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

MISR Level 1B1 Radiance Data (MI1B1_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [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; Temporal_Resolution_Range=about 15 orbits/day].

AM-1↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

MISR radiometric camera-by-camera Cloud Mask (MIRCCM_V4)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The RCCM is derived from the radiance values, and is calculated independently for each camera. Therefore, the amount of apparent cloudiness will vary with view angle, with the oblique view angles generally being more cloudy than the near-nadir ones. Since the RCCM is calculated primarily from the radiance values, it does not work well over snow and ice and will usually confuse clear snow/ice with cloud. It works the best over clear-sky ocean, but other surface types are also of quite good quality. The RCCM product also contains a glint mask for each camera, and this mask is set to true whenever the scattering angles indicate that glint could be possible. This glint mask is not masked out over land; users must do this step themselves. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

SUN GLINT↗
NASA NTRS2014

Constraints on Smoke Injection Height, Source Strength, and Transports from MISR and MODIS

The AeroCom BB (Biomass Burning) Experiment AOD (Aerosol Optical Depth) motivation: We have a substantial set of satellite wildfire plume AOD snapshots and injection heights to help calibrate model/inventory performance; We are 1) adding more fire source-strength cases 2) using MISR to improve the AOD constrains and 3) adding 2008 global injection heights; We selected GFED3-daily due to good overall source strength performance, but any inventory can be tested; Joint effort to test multiple, global models, to draw robust BB injection height and emission strength conclusions. We provide satellite-based injection height and smoke plume AOD climatologies.

smoke injection height↗
NASA NTRS2012

Top-down Estimate of Dust Emissions Through Integration of MODIS and MISR Aerosol Retrievals With the Geos-chem Adjoint Model

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOSChem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

MODIS aerosol retrievals↗
NASA NTRS2011

MISR Interactive Explorer (MINX) : Production Digitizing to Retrieve Smoke Plume Heights and Validating Heights Against Lidar Data

The height at which smoke from a wildfire is injected into the atmosphere is an important parameter for climatology, because it determines how far the smoke can be transported. Using the MINX program to analyze MISR (Multi-angle Imaging Spectro-Radiometer) data, I digitized wildfire smoke plumes to add to an existing database of these heights for use by scientists studying smoke transport and plume dynamics. In addition to using MINX to do production digitizing of heights, I assisted in gathering lidar data for an ongoing validation of MINX and helped evaluate those data.

smoke plume↗
NASA NTRS1997

Instrument Verification Tests on the Multi-Angle Imaging SpectroRadiometer (MISR)

The Multi-angle Imaging SpectroRadiometer (MISR) cameras completed detailed calibrationa done characterization testing a year ago, as reported in earlier literature. Since that time the cameras have been assembled onto a common flight optical bench, along with photodiode detector standards and diffuse calibration targets.

MISR↗
NASA NTRS1996

Lloyd's Mirror for MTF Testing of MISR CCD

Direct measurement of CCD MTF using a unique Lloyd's mirror fringe projector is described. MTF measurements on the MISR linear CCD arrays have been performed as a function of spatial frequency, wavelength, number of charge transfers, radiation dosage, and device architecture. Test results are reported here.

MTF↗
NASA NTRS2003

Longwave Radiative Forcing of Saharan Dust Aerosols Estimated from MODIS, MISR and CERES Observations on Terra

Using observations from the Multi-angle Imaging Spectroradiometer (MISR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Clouds and the Earth's Radiant Energy System (CERES) instruments onboard the Terra satellite; we present a new technique for studying longwave (LW) radiative forcing of dust aerosols over the Saharan desert for cloud-free conditions. The monthly-mean LW forcing for September 2000 is 7 W/sq m and the LW forcing efficiency' (LW(sub eff)) is 15 W/sq m. Using radiative transfer calculations, we also show that the vertical distribution of aerosols and water vapor are critical to the understanding of dust aerosol forcing. Using well calibrated, spatially and temporally collocated data sets, we have combined the strengths of three sensors from the same satellite to quantify the LW radiative forcing, and show that dust aerosols have a "warming" effect over the Saharan desert that will counteract the shortwave "cooling effect" of aerosols.

Zhang, Jiang-Long↗