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Light reflected from Spectralon, the material chosen for on-board radiometric calibration of the Multi-angle Imaging SpectroRadiometer (MISR) is quantified in terms of the fraction of the reflected intensity that has the same polarization as the incident light.
The directional hemispheric reflecatance is measured for Spectralon, the material chosen for on-board radiometric calibration of the Multiangle Imaging SpectroRadiometer (MISR), at laser wavelengths of 442, 632.8 and 859.9nm.
The Multi-Angle Imaging SpectroRadiometer (MISR) instrument is being developed at JPL for the EOS AM1 spacecraft, scheduled for launch in June 1998. The development status and strategy for observing atmospheric aerosols are described.
The Multi-Angle Imaging SpectroRadiometer (MISR) is being developed at JPL for the AM1 spacecraft in the Earth Observing System (EOS) series. This paper reports on the progress of instrument fabrication and testing, and it discusses the strategy to use the instrument for studying tropospheric aerosols.
This Algorithm Basis (ATB) document describes the algorithms used to retrieve the aerosol parameters of the MISR Level 2 Aerosol/Surface Product.
Multiangle, multispectral remote sensing observations, such as those anticipated from the Earth Observing System (EOS) Multiangle Imaging SpectroRadiometer (MISR), can significantly improve our ability to constrain aerosol properties from space.
We present an analysis of simulations of the global aerosol system in the NASA GEOS-5 transport, radiation, and chemistry model. The model includes representations of all major tropospheric aerosol species, including dust, sea salt, black carbon, particulate organic matter, and sulfates. The aerosols are run online for the period 2000 through 2005 in a simulation driven by assimilated meteorology from the NASA Goddard Data Assimilation System. Aerosol surface mass concentrations are compared with existing long-term surface measurement networks. Aerosol optical thickness is compared with ground-based AERONET sun photometry and space-based retrievals from MODIS, MISR, and OMI. Particular emphasis is placed here on consistent sampling of model and satellite aerosol optical thickness to account for diurnal variations in aerosol optical properties. Additionally, we illustrate the use of this system for providing chemical weather forecasts in support of various NASA and community field missions.
The Surface Radiation Budget (SRB) data sets contain global 3-hourly, daily and monthly averages of surface longwave and shortwave radiative properties, cloud amount, and meteorological properties computed using models. The main input data for these models include cloud information, top-of-atmosphere radiances and profiles of atmospheric water vapor and temperature. Some of the input data include Earth Radiation Budget Energy (ERBE) top-of-atmosphere clear-sky albedo and International Satellite Cloud Climatology Project (ISCCP) radiances and cloud amount. SRB parameters derived for the renewable energy community are also available from the Surface meteorology and Solar Energy (SSE) data set. Other SRB data are available from Clouds and the Earth's Radiant Energy System (CERES) and Multi-angle Imaging SpectroRadiometer (MISR). [Mission Objectives] The objective of the SRB Project is to produce and archive a global data set of shortwave (SW) and longwave (LW) surface and top of the atmosphere parameters. The data generated in the SRB project may be used in conjunction with other data sets to facilitate the development of renewable energy resources and increase understanding of radiative properties within the meteorological community. [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].
Atmospheric aerosols interact with sun light by scattering and absorbing radiation. By changing irradiance of the Earth surface, modifying cloud fractional cover and microphysical properties and a number of other mechanisms, they affect the energy balance, hydrological cycle, and planetary climate [IPCC, 2007]. In many world regions there is a growing impact of aerosols on air quality and human health. The Earth Observing System [NASA, 1999] initiated high quality global Earth observations and operational aerosol retrievals over land. With the wide swath (2300 km) of MODIS instrument, the MODIS Dark Target algorithm [Kaufman et al., 1997; Remer et al., 2005; Levy et al., 2007] currently complemented with the Deep Blue method [Hsu et al., 2004] provides daily global view of planetary atmospheric aerosol. The MISR algorithm [Martonchik et al., 1998; Diner et al., 2005] makes high quality aerosol retrievals in 300 km swaths covering the globe in 8 days. With MODIS aerosol program being very successful, there are still several unresolved issues in the retrieval algorithms. The current processing is pixel-based and relies on a single-orbit data. Such an approach produces a single measurement for every pixel characterized by two main unknowns, aerosol optical thickness (AOT) and surface reflectance (SR). This lack of information constitutes a fundamental problem of the remote sensing which cannot be resolved without a priori information. For example, MODIS Dark Target algorithm makes spectral assumptions about surface reflectance, whereas the Deep Blue method uses ancillary global database of surface reflectance composed from minimal monthly measurements with Rayleigh correction. Both algorithms use Lambertian surface model. The surface-related assumptions in the aerosol retrievals may affect subsequent atmospheric correction in unintended way. For example, the Dark Target algorithm uses an empirical relationship to predict SR in the Blue (B3) and Red (B1) bands from the 2.1 m channel (B7) for the purpose of aerosol retrieval. Obviously, the subsequent atmospheric correction will produce the same SR in the red and blue bands as predicted, i.e. an empirical function of 2.1. In other words, the spectral, spatial and temporal variability of surface reflectance in the Blue and Red bands appears borrowed from band B7. This may have certain implications for the vegetation and global carbon analysis because the chlorophyll-sensing bands B1, B3 are effectively substituted in terms of variability by band B7, which is sensitive to the plant liquid water. This chapter describes a new recently developed generic aerosol-surface retrieval algorithm for MODIS. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm simultaneously retrieves AOT and surface bi-directional reflection factor (BRF) using the time series of MODIS measurements.
Spacecraft flight operations often require activities that involve different kinds of maneuvers for orbital adjustments (pitch, yaw, and roll). Different maneuvers, when properly planned and scheduled, can also be applied to support and/or to perform on-board sensor calibration and characterization. This paper uses MODIS (Moderate Resolution Imaging Spectroradiometer) as an example to illustrate applications of spacecraft maneuvers for Earth-observing sensors on-orbit calibration and characterization. MODIS is one of the key instruments for NASA's Earth Observing System (EOS) currently operated on-board the EOS Terra and Aqua spacecraft launched in December 1999 and May 2002, respectively. Since their launch, both Terra and Aqua spacecraft have made a number of maneuvers, specially the yaw and roll maneuvers, to support the MODIS on-orbit calibration and characterization. For both Terra and Aqua MODIS, near-monthly spacecraft roll maneuvers are executed for lunar observations. These maneuvers are carefully scheduled so that the lunar phase angles are nearly identical for each sensor's lunar observations. The lunar observations are used to track MODIS reflective solar bands (RSB) calibration stability and to inter-compare Terra and Aqua MODIS RSB calibration consistency. To date, two sets of yaw maneuvers (each consists of two series of 8 consecutive yaws) by the Terra spacecraft and one set by the Aqua spacecraft have been performed to validate MODIS solar diffuser (SD) bi-directional reflectance factor (BRF) and to derive SD screen transmission. Terra spacecraft pitch maneuvers, first made on March 26, 2003 and the second on April 14, 2003 (with the Moon in the spacecraft nadir view), have been applied to characterize MODIS thermal emissive bands (TEB) response versus scan angle (RVS). This is particularly important since the pre-launch TEB RSV measurements made by the sensor vendor were not successful. Terra MODIS TEB RVS obtained from pitch maneuvers have been used in the current LIB calibration algorithm. Lunq observations from pitch maneuvers also provided information to cross-calibrate MODIS with other sensors (MISR and ASTER) on the same platform. We will provide a summary of MODIS maneuver activities and their applications for MODIS calibration and characterization. The results and lessons learned discussed in this paper from MODIS maneuver activities will provide useful insights into future spacecraft and sensor operation.
An improved algorithm is developed based on support vector regression (SVR) to estimate horizonal water vapor transport integrated through the depth of the atmosphere ((Theta)) over the global ocean from observations of surface wind-stress vector by QuikSCAT, cloud drift wind vector derived from the Multi-angle Imaging SpectroRadiometer (MISR) and geostationary satellites, and precipitable water from the Special Sensor Microwave/Imager (SSM/I). The statistical relation is established between the input parameters (the surface wind stress, the 850 mb wind, the precipitable water, time and location) and the target data ((Theta) calculated from rawinsondes and reanalysis of numerical weather prediction model). The results are validated with independent daily rawinsonde observations, monthly mean reanalysis data, and through regional water balance. This study clearly demonstrates the improvement of (Theta) derived from satellite data using SVR over previous data sets based on linear regression and neural network. The SVR methodology reduces both mean bias and standard deviation comparedwith rawinsonde observations. It agrees better with observations from synoptic to seasonal time scales, and compare more favorably with the reanalysis data on seasonal variations. Only the SVR result can achieve the water balance over South America. The rationale of the advantage by SVR method and the impact of adding the upper level wind will also be discussed.
A proposed method of design and fabrication of vacuum-packaged microelectromechanical systems (MEMS) and of individual microelectromechanical devices involves the use of multiple internal seal rings (MISRs) in conjunction with vias (through holes plated with metal for electrical contacts). The proposed method is compatible with mass production in a wafer-level fabrication process, in which the dozens of MEMS or individual microelectromechanical devices on a typical wafer are simultaneously vacuum packaged by bonding a capping wafer before the devices are singulated (cut apart by use of a dicing saw). In addition to being compatible with mass production, the proposed method would eliminate the need for some complex and expensive production steps and would yield more reliable vacuum seals. Conventionally, each MEMS or individual microelectromechanical device is fabricated as one of many identical units on a device wafer. Vacuum packaging is accomplished by bonding the device wafer to a capping wafer with metal seal rings (one ring surrounding each unit) that have been formed on the capping wafer. The electrical leads of each unit are laid out on what would otherwise be a flat surface of the device wafer, against which the seal ring is to be pressed for sealing. The resulting pattern of metal lines and their insulating oxide coverings presents a very rough and uneven surface, upon which it is difficult to pattern the sealing metal. Consequently, the seal is prone to leakage unless additional costly and complex planarization steps are performed before patterning the seal ring and bonding the wafers.
The aerosol data products from the NASA Earth Observing System's MISR and MODIS instruments provide significant advances in regional and global aerosol optical depth (AOD) mapping, aerosol type measurement, and source plume characterization from space. Although these products have been and are being used for many applications, ranging from regional air quality assessment, to aerosol air mass type identification and evolution, to aerosol injection height and aerosol transport model validation, uncertainties still limit the quantitative constraints these satellite data place on global-scale direct aerosol radiative forcing. Some further refinement of the current aerosol products is possible, but a major advance in this area seems to require a different paradigm, involving the integration of satellite and suborbital data with models. This presentation will briefly summarize where we stand, and what incremental advances we can expect, with the current aerosol products, and will then elaborate on some initial steps aimed at the necessary integration of data from multiple sources and models.
This slide presentation reviews the Cloud Hydrology and Albedo Synthesis Mission (CHASM). The interaction of clouds with radiation and the hydrological cycle represents a huge uncertainty in our understanding of climate science and the modeling of climate system feedbacks. Despite the recognized need for a unified treatment of cloud processes, the present global average values of remotely sensed cloud liquid water and theoretically accepted values used for cloud physics and precipitation modeling differ by an order of magnitude. This is due in part to sampling and saturation effects, as well as to threedimensional cloud structure effects. In recent work with the Multiangle Imaging SpectroRadiometer (MISR) on Terra, we have gained new insights as to how the remote sensing approach could be significantly improved using a new instrument that combines passive optical (visible and near infrared) and microwave measurements, both as pushbroom scanners with multiple viewing angles, to the degree that measurements of liquid water path over deep convective clouds over land also become possible. This instrument would also have the ability of measuring height-resolved cloud-tracked winds using a hyper stereo retrieval technique. Deployment into a precessing low earth orbit would be optimal for measuring diurnal cloud activity. We have explored an instrument design concept for this that looks promising if we can establish partnerships that provide launch and bus capabilities.
Dust generated from Asian permanent desert and desertification areas can be efficiently transported around the globe, making significant radiative impact through their absorbing and scattering solar radiation and through their deposition on snow and ice to modify the surface albedo. Asian dust is also a major concern of surface air quality not only in the source and immediate downwind regions but also areas thousands of miles away across the Pacific. We present here a global model, GOCART, analysis of data from satellite remote sensing instrument (MODIS, MISR, CALIPSO, OMI) and other observations on Asian dust sources, transport, and deposition, and use the model to assess the Asian dust impact on global climate and air quality.
We have computed the Aerosol Index (AI) at 354 nm, useful for observing the presence of absorbing aerosols in the atmosphere, from aerosol simulations conducted with the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) module running online the GEOS-5 Atmospheric GCM. The model simulates five aerosol types: dust, sea salt, black carbon, organic carbon and sulfate aerosol and can be run in replay or data assimilation modes. In the assimilation mode, information's provided by the space-based MODIS and MISR sensors constrains the model aerosol state. Aerosol optical properties are then derived from the simulated mass concentration and the Al is determined at the OMI footprint using the radiative transfer code VLIDORT. In parallel, model derived Absorption Aerosol Optical Depth (AAOD) is compared with OMI retrievals. We have focused our study during ARCTAS (June - July 2008), a period with a good sampling of dust and biomass burning events. Our ultimate goal is to use OMI measurements as independent validation for our MODIS/MISR assimilation. Towards this goal we document the limitation of OMI aerosol absorption measurements on a global scale, in particular sensitivity to aerosol vertical profile and cloud contamination effects, deriving the appropriate averaging kernels. More specifically, model simulated (full) column integrated AAOD is compared with model derived Al, this way identifying those regions and conditions under which OMI cannot detect absorbing aerosols. Making use of ATrain cloud measurements from MODIS, C1oudSat and CALIPSO we also investigate the global impact on clouds on OMI derived Al, and the extent to which GEOS-5 clouds can offer a first order representation of these effects.
During the NASA TC-4 field campaign in July 2007, several Saharan dust events were observed over the Caribbean basin. A-Train observations suggest that these Saharan dust events are confined the Caribbean and rarely transported across Central America to the Pacific Ocean. We investigate the nature of this barrier to dust transport using the NASA GEOS-5 atmospheric general circulation model. Our simulations with GEOS-5 are driven by the Modern Era Retrospective-Analysis for Research and Applications (MERRA) meteorological analyses, and include online simulation of aerosol distributions using a version of the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) model. Simulated dust distributions are evaluated using A-Train observations from MODIS and CALIOP, as well as MISR and ground-based AERONET sun photometers, and show good agreement with the observations in terms of the timing and magnitude of dust events. A component analysis of the dust transport and removal pathways is used to evaluate the relative roles of these processes in establishing the observed dust transport barrier. From this analysis, we show that while both atmospheric dynamics and wet removal contribute towards the Caribbean dust barrier, northward dust transport is the more dominant term. Additional simulations are performed to ascertain the sensitivity of our results to uncertain loss processes (i.e., wet removal) in our model.
Among the known atmospheric constituents, aerosols represent the greatest uncertainty in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood ', there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource,., an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainty analysis of aerosol products from multiple satellite sensors.