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Use of Skylab EREP data in a sea surface temperature experiment
The author has identified the following significant results. This report discusses an experiment to be performed on each of the three manned Skylab missions, the results of which will assess the ability of spaceborne infrared multispectral sensing to function as a means of providing improved estimates of sea surface temperature over that obtainable with a single channel radiometric instrument. The overall investigative program is outlined, the effort performed during the prelaunch phase is detailed, and pertinent results are presented.
Zenith angle effects in multichannel infrared sea surface remote sensing
Several approaches to infrared multichannel sea surface temperature retrievals propose using a universal set of constants. It is shown that the single-channel multiangle technique (i.e., GOES and NOAA) and the multichannel single-angle technique (NOAA-n) are similar concepts with a common derivation from radiative transfer theory. It is also shown that the linear correlation factor between surface temperature minus satellite temperature in one channel versus the difference in satellite temperatures in two channels is not independent of the difference in satellite sensed equivalent blackbody temperature. The 3.7-micron, 11-micron, and 12-micron channels on the NOAA-n AVHRR can be used in combination to compute atmospheric transmissivity and average atmospheric temperature, but a better combination would be substituting three 0.5-micron-wide channels centered on 11.25 micron, 11.75 micron, and 12.25 micron. A triple window multispectral scanner in the 11-12.5 micron region allows determination of diffuse surface reflectance which can bias sea surface temperatures - 0.4 K + or - 0.3 K.
Multi-frequency, multi-polarization SAR and radiometer sea ice classification
Microwave remotely sensed data were acquired simultaneously in March 1988 over Beaufort, Chukchi, and Bering Sea ice using the JPL multifrequency, polarimetric synthetic aperture radar (SAR), and multifrequency dual-polarization GSFC radiometer. The experiment was conducted as a series of coordinated underflights of the DMSP SSM/I satellite radiometer to validate ice products derived from its radiance values. Concurrent flights by an NRL P-3 aircraft enabled overlapping high-resolution, single-frequency images to be acquired over the same surfaces using a Ka-band scanning microwave radiometer. Precise coregistration to an accuracy of 100 m, +/- 25 m enables comparison of temporally and spatially coincident active and passive microwave datasets. Three-channel polarimetric SAR data are compared with dual-polarized radiometer data at several SSM/I frequencies, showing backscatter signatures to be highly correlated with radiometric temperatures. Further comparisons are used to evaluate ice concentration retrievals and to show how multiparameter datasets can be used to resolve ambiguities present in identifying certain sea ice forms with a single microwave instrument.
Accuracy of sea ice temperature derived from the advanced very high resolution radiometer
The accuracy of Arctic sea ice surface temperatures T(sub s) dericed from advanced very high resolution radiometer (AVHRR) thermal channels is evaluated in the cold seasons by comparing them with surface air temperatures T(sub air) from drifting buoys and ice stations. We use three different estimates of satellite surface temperatures, a direct estimate from AVHRR channel 4 with only correction for the snow surface emissivity but not for the atmosphere, a single-channel regression of T(sub s) with T(sub air), and Key and Haefliger's (1992) polar multichannel algorithm. We find no measurable bias in any of these estimates and few differences in their statistics. The similar performance of all three methods indicates that an atmospheric water vapor correction is not important for the dry winter atmosphere in the central Arctic, given the other sources of error that remain in both the satellite and the comparison data. A record of drifting station data shows winter air temperature to be 1.4 C warmer than the snow surface temperature. `Correcting' air temperatures to skin temperature by subtracting this amount implies that satellite T(sub s) estimates are biased warm with respect to skin temperature by about this amount. A case study with low-flying aircraft data suggests that ice crystal precipitation can cause satellite estimates of T(sub s) to be several degrees warmer than radiometric measurements taken close to the surface, presumably below the ice crystal precipitation layer. An analysis in which errors are assumed to exist in all measurements, not just the satellite measurements, gives a standard deviation in the satellite estimates of 0.9 C, about half the standard deviation of 1.7 C estimated by assigning all the variation between T(sub s) and T(sub air) to errors in T(sub s).
Airborne full polarization radiometry using the MSFC Advanced Microwave Precipitation Radiometer (AMPR)
The applications of vertically and horizontally polarized brightness temperatures in both atmospheric and surface remote sensing have been long recognized by many investigators, particularly those studying SMMR and SSM/I data. Here, the large contrast between the first two Stokes' parameters (T(sub V) and T(sub H)) can be used for detection of sea ice, measurement of ocean surface wind speed, and measurement of cloud and water vapor opacity. High-resolution aircraft data from instruments such as the NASA/MSFC AMPR is crucial for verifying radiative transfer models and developing retrieval algorithms. Currently, the AMPR is outfitted with single-polarization channels at 10, 18, 37 and 85 GHz. To increase its utility, it is proposed that additional orthogonal linearly polarized channels be added to the AMPR. Since the AMPR's feedhorns are already configured for dual orthogonal linearly polarized modes, this would require only a duplication of the currently existing receivers. To circumvent the resulting polarization basis skew caused by the cross-track scanning mechanism, the technique of Electronic Polarization Basis Rotation is proposed to be implemented. Implementation of EPBR requires precise measurement of the third Stokes parameter and will eliminate polarization skew by allowing the feedhorn basis skew angle to be corrected in software. In addition to upgrading AMPR to dual polarization capability (without skew), the modifications will provide an opportunity to demonstrate EPBR on an airborne platform. This is a highly desirable intermediate step prior to satellite implementation.
Land-surface temperature measurement from space - Physical principles and inverse modeling
To apply the multiple-wavelength (split-window) method used for satellite measurement of sea-surface temperature from thermal-infrared data to land-surface temperatures, the authors statistically analyze simulations using an atmospheric radiative transfer model. The range of atmospheric conditions and surface temperatures simulated is wide enough to cover variations in clear atmospheric properties and surface temperatures, both of which are larger over land than over sea. Surface elevation is also included in the simulation as the most important topographic effect. Land covers characterized by measured or modeled spectral emissivities include snow, clay, sands, and tree leaf samples. The empirical inverse model can estimate the surface temperature with a standard deviation less than 0.3 K and a maximum error less than 1 K, for viewing angles up to 40 degrees from nadir under cloud-free conditions, given satellite measurements in three infrared channels. A band in the region from 10.2 to 11.0 microns will usually give the most reliable single-band estimate of surface temperature. In addition, a band in either the 3.5-4.0-micron region or in the 11.5-12.6-micron region must be included for accurate atmospheric correction, and a band below the ozone absorption feature at 9.6 microns (e.g., 8.2-8.8 microns) will increase the accuracy of the estimate of surface temperature.
Typhoon June /1975/ viewed by a scanning microwave spectrometer
Data were collected by the scanning microwave spectrometer onboard Nimbus 6 during the June 1975 typhoon in the Philippine Sea. The spectrometer was equipped with channels centered on 22.23 GHz (a water vapor band), 31.65 GHz (a transmittance window), and 52.85, 53.85, and 55.45 GHz (an oxygen band). Temperature maps, derived from oxygen band measurements, showed that the typhoon eye had a single peak varying in amplitude with time. Water line and window measurements were used to develop a coordinate system having mutually orthogonal atmospheric variables of column water-vapor content and cloud liquid-water content. Vapor measurements showed a maximum around the intensifying typhoon with a more developed structure during typhoon development. Values were extrapolated for surface wind speed and cloud liquid water vapor content by assuming the troposphere to be saturated with respect to the water vapor in the typhoon. Comparisons with infrared cloud imagery and aircraft flight data show different time variations, attributed to poor typhoon-eye resolution in the microwave images.
Baseline Observations of Hemispheric Sea Ice with the Nimbus 7 Scanning Multichannel Microwave Radiometer
The Scanning Multichannel Microwave Radiometer (SMMR) on board the NASA Nimbus 7 satellite was designed to obtain data for sea surface temperatures (SSTs), near-surface wind speeds, sea ice coverage and type, rainfall rates over the oceans, cloud water content, snow water equivalent, and soil moisture. In this paper, I shall emphasize the sea ice observations and mention briefly some important SST observations. A prime factor contributing to the importance of SMMR sea ice observations lies in their successful integration into a long-term time series, presently being extended by observations from the series of Special Sensor Microwave/Imager (SSMI) on board the DOD/DMSP F8, Fl1, and F12 satellites. This currently constitutes a 19-year data set. Almost half of this was provided by the SMMR. Unfortunately, the 4-year data set produced earlier by the single-channel Electrically Scanned Microwave Radiometer (ESMR) was not successfully integrated into the SMMR/SSMI data set. This resulted primarily from the lack of an overlap period to provide intersensor adjustment, but also because of the large difference between the algorithms to produce ice concentrations and large temporal gaps in the ESMR data. The lack of overlap between the SeaSat and Nimbus 7 SMMR data sets was an important consideration for also excluding the SeatSat one, but the spatial gaps especially in the Southern Hemisphere daily SeaSat observations was another. The sea ice observations will continue into the future by means of the Advanced Microwave Scanning Radiometer (AMSR) on board the ADEOS II and EOS satellites due to be launched in mid- and late-2000, respectively. Analysis of the sea ice data has been carried out by a number of different techniques. Long-term trends have been examined by means of ordinary least squares and band-limited regression. Oscillations in the data have been examined by band-limited Fourier analysis. Here, I shall present results from a novel combination of Principal Component analysis and the recently-developed Empirical Mode Decomposition (EMD). In this method, the data are first separated into spatial and temporal parts, and then the temporal parts of the first few PCs are broken into intrinsic modes by the EMD method.
SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation
Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.
Picture this SELFI: Submillimeter Enceladus Life Fundamentals Instrument
The Submillimeter Enceladus Life Fundamentals Instrument (SELFI) is a passive remote sensing submillimeter heterodyne spectrometer being developed at NASA GSFC under NASA's Maturation of Instruments for Solar System Exploration (MatISSE) program. SELFI will advance submillimeter receiver technology by 1) investigating the chemical and isotopic compositions and corresponding densities of Enceladus' plume material, their vertical thermal structures, and the transport mechanisms within the plumes, and 2) characterizing the source regions from which the plumes emerge. The Enceladus plumes are important in the context of life and habitability of its subsurface ocean environment. SELFI remote sensing measurements will 1) measure the spatial and temporal variabilities in the plume chemical compositions, 2) provide insight in to Enceladus' subsurface ocean environment by monitoring H2O, HDO, d18O, and d17O, 3) constrain the oxidation state of the subsurface ocean using H2O2 and O3, and 4) utilize the SO2 and H2S spectral signatures to constrain the impact arising from both the sea-floor volcanoes and pre-biotic molecules. Moreover, the detection of the remaining molecular species (14 in total) is vital to improving the current state of knowledge of Enceladus' subsurface ocean habitability this also permits us to explore the chemical alteration processes arising from primordial volatiles that have been observed in comets. Lastly, SELFI's continuum observations enable the correlation between observed variations in plume activity with surface temperatures.SELFI is currently being developed under a technology maturation program that will advance the RF-to-digital electronics of a submillimeter-wave heterodyne spectrometer to simultaneously observe fourteen molecular species with resonances between 530 GHz and 600 GHz. SELFI will have fine radiometric resolution, high spectral resolution (resolving power R > 106), multiple continuum channels and a high dynamical range, necessary to map Enceladus across its 30 K to 250 K temperature range. Under the MatISSE program, SELFI will advance from TRL 4 to 6 four key technologies of the RF-to-digital subsystem, which are: 1) the RF low noise amplifier design; 2) the single-sideband (SSB) mixer and local oscillator; 3) the IF assembly down-converter that maps the fourteen species to 2 x 500 MHz bandwidth; and 4) the digital spectrometer electronics.
Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms
Following the release of the version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version (version 4; V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. The IIR Level 2 algorithm has been modified in the V4 data release to improve the accuracy of the retrievals in clouds of very small (close to 0) and very large (close to 1) effective emissivities. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear-sky brightness temperatures over oceans has been updated and tuned for the simulations using Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data to match IIR observations in clear-sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5 km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ±0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also improved retrievals in ice clouds having large emissivity by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3 and increases the number of retrievals. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 and 10.6 µm and at 12.05 and 08.65 µm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice habit models from the recent “TAMUice2016” database, namely the single-hexagonal-column model and the eight-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 and 10.6 µm and effective diameter as derived from in situ measurements at tropical and midlatitudes during the Tropical Composition, Cloud, and Climate Coupling (TC4) and Small Particles in Cirrus Science and Operations Plan (SPARTICUS) field experiments.
Distributed Real-time Plume Monitoring for Deep Sea Mineral Extraction
In the emerging industry of deep-sea mining for minerals and deposits (e.g. polymetallic nodules for nickel, cobalt, copper, and manganese), more data is required to understand the effects of sediment plume generation and predict the distribution of disturbed sediment. There are two main sources of plume generation, the first being at the active mining site where the “collector” directly removes the top layer of the sea floor. The other is the “midwater plume” consisting of unwanted sediment that was collected during extraction that is pumped back into the aphotic zone. The vast majority of plume generation is caused by the collector, causing detrimental and long-lasting impacts on seafloor ecosystems due to the lack of wave activity or strong currents at the sea floor. Therefore, it is crucial to invest in the infrastructure to support the study and constant monitoring over a large area of the sea floor where plume generation is present. Due to the limited number of usable channels and power requirements, current subsea wireless communications technologies are not well suited to instrumenting the large areas of the sea floor needed to monitor plume migration. The scope of this effort is to transition experimental demonstrations of high-bandwidth, full-duplex scalable underwater laser communications to the seafloor in an open ocean environment. Specifically tackling challenges associated with the dynamic nature of the subsea world, including but not limited to, deployment logistics, sustainability, and range. The goal is to enable the internet of underwater things for deep sea industries by broadening the capabilities of subsea communications. By using high-precision laser transmitters, many of the challenges current subsea optical systems face can be circumvented, such as power consumption, interference, and bandwidth limitations. This approach lends itself to wireless interlinking multi-node networks, in series or parallel, facilitating the implementation of a wide array of sensor types. This interlinking allows all the data gathered from the network to be processed through a single hardline uplink to the surface, lowering the complexity required for near real-time data processing. Additionally, the laser control systems produce metadata that can be used to help characterize the water column between the nodes. Combining data from various sensors such as turbidity, temperature, current velocity with metadata such as beam attenuation and deflection can produce a high-resolution model of sea floor conditions around an active mining zone. The resulting near real-time model can be used to optimize location and flow rate of the mining operation to minimize and quantify the environmental impact.
The NASA Airborne Earth Science Microwave Imaging Radiometer (AESMIR): A New Sensor for Earth Remote Sensing
The Airborne Earth Science Microwave Imaging Radiometer (AESMIR) is a versatile new airborne imaging radiometer recently developed by NASA. The AESMIR design is unique in that it performs dual-polarized imaging at all standard passive microwave frequency bands (6-89 GHz) using only one sensor headscanner package, providing an efficient solution for Earth remote sensing applications (snow, soil moisture/land parameters, precipitation, ocean winds, sea surface temperature, water vapor, sea ice, etc.). The microwave radiometers themselves will incorporate state-of-the-art receivers, with particular attention given to instrument calibration for the best possible accuracy and sensitivity. The single-package design of AESMIR makes it compatible with high-altitude aircraft platforms such as the NASA ER-2s. The arbitrary 2-axis gimbal can perform conical and cross-track scanning, as well as fixed-beam staring. This compatibility with high-altitude platforms coupled with the flexible scanning configuration, opens up previously unavailable science opportunities for convection/precip/cloud science and co-flying with complementary instruments, as well as providing wider swath coverage for all science applications. By designing AESMIR to be compatible with these high-altitude platforms, we are also compatible with the NASA P-3, the NASA DC-8, C-130s and ground-based deployments. Thus AESMIR can provide low-, mid-, and high- altitude microwave imaging. Parallel filter banks allow AESMIR to simultaneously simulate the exact passbands of multiple satellite radiometers: SSM/I, TMI, AMSR, Windsat, SSMI/S, and the upcoming GPM/GMI and NPOESS/CMIS instruments --a unique capability among aircraft radiometers. An L-band option is also under development, again using the same scanner. With this option, simultaneous imaging from 1.4 to 89 GHz will be feasible. And, all receivers except the sounding channels will be configured for 4-Stokes polarimetric operation using high-speed digital correlators in the near future. The capabilities and unique design features of this new sensor will be described, and example imagery will be presented.