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At least 487 records · Page 27

HIRIS, the instrument and its science

The High Resolution Imaging Spectrometer (HIRIS) is a facility instrument slated for flight on the second EOS series AM platforms. HIRIS is designed to acquire 24 km wide, 30 m pixel images in 192 spectral bands simultaneously in the 0.4-2.45 micron wavelength region. With pointing mirrors it can sample any place on Earth, except the poles, every 2 days. HIRIS operates at the intermediate scale between the human and the global and therefore links studies of Earth surface processes to global monitoring carried out by lower resolution instruments. So far, over 50 science data products from HIRIS images have been identified in the fields of atmospheric gases, clouds, snow and ice, water, vegetation, and rocks and soils. The key attribute of imaging spectrometry that makes it possible to derive quantitative information from the data is the large number of contiguous, spectral bands. Therefore, spectrum-matching techniques can be applied. Such techniques are not possible with present-day, multispectral scanner data.

Goetz, Alexander F. H.↗

Satellite Data Simulator Unit: A Multisensor, Multispectral Satellite Simulator Package

Several multisensor simulator packages are being developed by different research groups across the world. Such simulator packages [e.g., COSP , CRTM, ECSIM, RTTO, ISSARS (under development), and SDSU (this article), among others] share overall aims, although some are targeted more on particular satellite programs or specific applications (for research purposes or for operational use) than others. The SDSU or Satellite Data Simulator Unit is a general-purpose simulator composed of Fortran 90 codes and applicable to spaceborne microwave radiometer, radar, and visible/infrared imagers including, but not limited to, the sensors listed in a table. That shows satellite programs particularly suitable for multisensor data analysis: some are single satellite missions carrying two or more instruments, while others are constellations of satellites flying in formation. The TRMM and A-Train are ongoing satellite missions carrying diverse sensors that observe clouds and precipitation, and will be continued or augmented within the decade to come by future multisensor missions such as the GPM and Earth-CARE. The ultimate goals of these present and proposed satellite programs are not restricted to clouds and precipitation but are to better understand their interactions with atmospheric dynamics/chemistry and feedback to climate. The SDSU's applicability is not technically limited to hydrometeor measurements either, but may be extended to air temperature and humidity observations by tuning the SDSU to sounding channels. As such, the SDSU and other multisensor simulators would potentially contribute to a broad area of climate and atmospheric sciences. The SDSU is not optimized to any particular orbital geometry of satellites. The SDSU is applicable not only to low-Earth orbiting platforms as listed in Table 1, but also to geostationary meteorological satellites. Although no geosynchronous satellite carries microwave instruments at present or in the near future, the SDSU would be useful for future geostationary satellites with a microwave radiometer and/or a radar aboard, which could become more feasible as engineering challenges are met. In this short article, the SDSU algorithm architecture and potential applications are reviewed in brief.

Masunaga, Hirohiko↗

Radar Range Sidelobe Reduction Using Adaptive Pulse Compression Technique

Pulse compression has been widely used in radars so that low-power, long RF pulses can be transmitted, rather than a highpower short pulse. Pulse compression radars offer a number of advantages over high-power short pulsed radars, such as no need of high-power RF circuitry, no need of high-voltage electronics, compact size and light weight, better range resolution, and better reliability. However, range sidelobe associated with pulse compression has prevented the use of this technique on spaceborne radars since surface returns detected by range sidelobes may mask the returns from a nearby weak cloud or precipitation particles. Research on adaptive pulse compression was carried out utilizing a field-programmable gate array (FPGA) waveform generation board and a radar transceiver simulator. The results have shown significant improvements in pulse compression sidelobe performance. Microwave and millimeter-wave radars present many technological challenges for Earth and planetary science applications. The traditional tube-based radars use high-voltage power supply/modulators and high-power RF transmitters; therefore, these radars usually have large size, heavy weight, and reliability issues for space and airborne platforms. Pulse compression technology has provided a path toward meeting many of these radar challenges. Recent advances in digital waveform generation, digital receivers, and solid-state power amplifiers have opened a new era for applying pulse compression to the development of compact and high-performance airborne and spaceborne remote sensing radars. The primary objective of this innovative effort is to develop and test a new pulse compression technique to achieve ultrarange sidelobes so that this technique can be applied to spaceborne, airborne, and ground-based remote sensing radars to meet future science requirements. By using digital waveform generation, digital receiver, and solid-state power amplifier technologies, this improved pulse compression technique could bring significant impact on future radar development. The novel feature of this innovation is the non-linear FM (NLFM) waveform design. The traditional linear FM has the limit (-20 log BT -3 dB) for achieving ultra-low-range sidelobe in pulse compression. For this study, a different combination of 20- or 40-microsecond chirp pulse width and 2- or 4-MHz chirp bandwidth was used. These are typical operational parameters for airborne or spaceborne weather radars. The NLFM waveform design was then implemented on a FPGA board to generate a real chirp signal, which was then sent to the radar transceiver simulator. The final results have shown significant improvement on sidelobe performance compared to that obtained using a traditional linear FM chirp.

Li, Lihua↗

High Resolution Imaging Spectrometer (HIRIS): Science and Instrument

The High Resolution Imaging Spectrometer (HIRIS) is a facility instrument slated for flight on the second of the EOS-A series of platforms. HIRIS is designed to acquire 24-km wide, 30-m pixel images in 192 spectral bands simultaneously in the 0.4-2.45-micrometer wavelength region. With pointing mirrors it can sample any place on Earth, except the poles, every two days. HIRIS operates at the intermediate scale between the human and the global and therefore links studies of Earth surface processes to global monitoring carried out by lower-resolution instruments. So far, over 50 science data products from HIRIS images have been identified in the fields of atmospheric gases, clouds, snow and ice, water, vegetation, and rocks and soils. The key attribute of imaging spectrometry that makes it possible to derive quantitative information from the data is the large number of contiguous spectral bands. Therefore spectrum matching techniques can be applied. Such techniques are not possible with present-day, multispectral scanner data.

Goetz, Alexander F. H.↗

An EOF Iteration Approach for Obtaining Homogeneous Radiative Fluxes from Satellites Observations

Conventional observations of climate parameters are sparse in space and/or in time and the representativeness of such information needs to be optimized. Observations from satellites provide improved spatial coverage than point observations however they pose new challenges for obtaining homogeneous coverage. Surface radiative fluxes, the forcing functions of the hydrologic cycle and biogeophysical processes, are now becoming available from global scale satellite observations. They are derived from independent satellite platforms and sensors that differ in temporal and spatial resolution and in the size of the footprint from which information is derived. Data gaps, degraded spatial resolution near boundaries of geostationary satellites, and different viewing geometries in areas of satellite overlap, could result in biased estimates of radiative fluxes. In this study, discussed will be issues related to the sources of inhomogeneity in surface radiative fluxes as derived from satellites; development of an approach to obtain homogeneous data sets; and application of the methodology to the widely used International Satellite Cloud Climatology Project (ISCCP) data that currently serve as a source of information for deriving estimates of surface and top of the atmosphere radiative fluxes. Introduced is an Empirical Orthogonal Function (EOF) iteration scheme for homogenizing the fluxes. The scheme is evaluated in several ways including comparison of the inferred radiative fluxes against ground observations, both before and after the EOF approach is applied. On the average, the latter reduces the rms error by about 2-3 W/m2.

Zhang, Banglin↗

Preliminary results of fisheries investigation associated with Skylab-3

The author has identified the following significant results. This investigation is to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. Data from the test area in the northeastern Gulf of Mexico has made possible the identification of fisheries significant environmental parameters for white marlin. Predictive models based on catch data and surface truth information have been developed and have demonstrated potential for reducing search significantly by identifying areas which have a high probability of being productive. Three of the parameters utilized by the model, chlorophyll-a, sea surface temperature, and turbidity have been inferred from aircraft sensor data. Cloud cover and delayed receipt have inhibited the use of Skylab data. The first step toward establishing the feasibility of utilizing remotely sensed data to assess amd monitor the distribution of ocean gamefish has been taken with the successful identification of fisheries significant oceanographic parameters and the demonstration of the capability of measuring most of these parameters remotely.

Savastano, K. J.↗

Science Writer's Guide to Landsat 7

The Earth Observing System (EOS), the centerpiece of NASA's Earth science program, is a suite of spacecraft and interdisciplinary science investigations dedicated to advancing our understanding of global change. The flagship EOS satellite, Terra (formerly EOS AM-1), scheduled for launch in July 1999, will provide key measurements of the physical and radiative properties of clouds; air-land and air-sea exchanges of energy, carbon, and water; trace gases; and volcanoes. Flying in formation with Terra, Landsat 7 will make global high spatial resolution measurements of land surface and surrounding coastal regions. Other upcoming EOS missions and instruments include QuikSCAT, to collect sea surface wind data; the Stratospheric Gas and Aerosol Experiment (SAGE III), to create global profiles of key atmospheric gases; and the Active Cavity Radiometer Irradiance Monitors (ACRIM) to measure the energy output of the Sun. The second of the major, multi-instrument EOS platforms, PM-1, is scheduled for launch in 2000. Interdisciplinary research projects sponsored by EOS use specific Earth science data sets for a broader investigation into the function of Earth systems. Current EOS research spans a wide range of sciences, including atmospheric chemistry, hydrology, land use, and marine ecosystems. The EOS program has been managed since 1990 by the Goddard Space Flight Center in Greenbelt, Md., for NASA's Office of Earth Science in Washington, D. C. Additional information on the program can be found on the EOS Project Science Office Web site (http://eospso.gsfc.nasa.gov).

Source record↗

Assessment of Clear Sky Radiative Forcing in the Caribbean Region Using an Aerosol Dispersion Model and Ground Radiometry During Puerto Rico Dust Experiment

This study investigates the surface and top of the atmosphere solar radiative forcing by long-range transport of Saharan dust. The calculations of radiative forcing are based on measurements collected in the Puerto Rico Dust Experiment (PRIDE) carried out during July, 2000. The purpose of the experiment was the characterization of the Saharan dust plume, which frequently reaches the Caribbean region during the summer. The experiment involved the use of three approaches to study the plume: space and ground based remote sensing, airborne and ground based in-situ measurements and aerosol dispersion modeling. The diversity of measuring platforms provides an excellent opportunity for determination of the direct effect of dust on the clear sky radiative forcing. Specifically, comparisons of heating rates, surface and TOA fluxes derived from the Navy global aerosol dispersion model NAAPS (NRL Aerosol Analysis and Prediction System) and actual measurements of fluxes from ground and space based platforms are shown. In addition, the direct effect of dust on the clear sky radiative forcing is modeled. The extent and time of evolution of the radiative properties of the plume are computed with the aerosol concentrations modeled by NAAPS. Standard aerosol parameterizations, as well as in-situ composition and size distributions measured during PRIDE, are utilized to compute the aerosol optical depth, single scattering albedo and asymmetry factor. Radiative transfer computations are done with an in-house modified spectral radiative transfer code (Fu-Liou). The code includes gas absorption and cloud particles (ice and liquid phase) and it allows the input of meteorological data. The code was modified to include modules for the aerosols contribution to the calculated fluxes. This comparison study helps to narrow the current uncertainty in the dust direct radiative forcing, as recently reported in the 2001 IPCC assessment.

Gasso, Santiago↗

Evolving HPC and Application Design Toward a Coupled Data Assimilation System at NASA Suitable for Emerging Exascale Platforms

The prediction capabilities of global models have continuously evolved from the traditional medium-range global weather prediction application to span scales in support of hourly prediction of convective scale storms to seasonal Earth system prediction. This evolution has increased the demands on the system infrastructure design and workflow to achieve the required performance on modern high-performance computing (HPC) platforms. The planned evolution of the Goddard Earth Observing System (GEOS) modeling and assimilation system will stress the capabilities of conventional HPC overwhelming the available compute cycles at the NASA Center for Climate Simulation (NCCS) at the NASA Goddard Space Flight Center in the coming 5-10 years. This has led to the re-design of key elements of the assimilation and modeling systems to achieve significant gains in performance on anticipated Exacale platforms. The transition of the assimilation system to the Joint Effort for Data assimilation Integration (JEDI) framework has positioned GEOS to exploit new efficient algorithms for data assimilation (DA) in a fully-coupled Earth system context. The suitability of the GEOS model to leverage a domain specific language (DSL) approach and artificial intelligence (AI) is being explored to accelerate computational performance and data exchange efficiency of the coupled Earth system model. The storage and processing of large data volumes produced by these advance systems is being redesigned with a data-centric cloud-based approach. We will highlight the recent efforts in these areas and emphasize the demand for further development and re-design to achieve the science objectives in support of NASA's Earth system modeling and assimilation missions.

Putman, Bill↗

Contributions of Nimbus 7 TOMS Data to Volcanic Study and Hazard Mitigation

Nimbus TOMS data have led to advancements among many volcano-related scientific disciplines, from the initial ability to quantify SO2 clouds leading to derivations of eruptive S budgets and fluxes, to tracking of individual clouds, assessing global volcanism and atmospheric impacts. Some of the major aspects of TOMS-related research, listed below, will be reviewed and updated: (1) Measurement of volcanic SO2 clouds: Nimbus TOMS observed over 100 individual SO2 clouds during its mission lifetime; large explosive eruptions are now routinely and reliably measured by satellite. (2) Eruption processes: quantification of SO2 emissions have allowed assessments of eruption sulfur budgets, the evaluation of "excess" sulfur, and inferences of H2S emissions. (3) Detection of ash: TOMS data are now used to detect volcanic particulates in the atmosphere, providing complementary analyses to infrared methods of detection. Paired TOMS and AVHRR studies have provided invaluable information on volcanic cloud compositions and processes. (4) Cloud tracking and hazard mitigation: volcanic clouds can be considered gigantic tracers in the atmosphere, and studies of the fates of these clouds have led to new knowledge of their physical and chemical dispersion in the atmosphere for predictive models. (5) Global trends: the long term data set has provided researchers an unparalleled record of explosive volcanism, and forms a key component in assessing annual to decadal trends in global S emissions. (6) Atmospheric impacts: TOMS data have been linked to independent records of atmospheric change, in order to compare cause and effect processes following a massive injection of SO2 into the atmosphere. (7) Future TOMS instruments and applications: Nimbus TOMS has given way to new satellite platforms, with several wavelength and resolution modifications. New efforts to launch a geostationary TOMS could provide unprecedented observations of volcanic activity.

Krueger, Arlin J.↗

Embedded Real-Time Linux for Instrument Control and Data Logging

When I moved to the west. coast to take a job at NASA's Ames Research Center in Mountain View, CA, I was impressed with the variety of equipment and software which scientists at the center use to conduct their research. was happy to find that I was just as likely to see a machine running Lenox as one running Windows in the offices and laboratories of NASA Ames (although many people seem to use Moos around here). I was especially happy to find that the particular group with whom I was going to work, the Atmospheric Physics Branch at Ames, relied almost entirely on Lenox machines for their day-to-day work. So it was no surprise that when it was time to construct a new control system for one of their most important pieces of hardware, a switch from an unpredictable DOS-based platform to an Embedded Linux-based one was a decision easily made. The system I am working on is called the Solar Spectral Flux Radiometer (SSFR), a PC-104 based system custom-built by Dr. Warren Gore at Ames. Dr. Gore, Dr. Peter Pilewskie, Dr. Maura Robberies and Larry Pezzolo use the SSFR in their research. The team working on the controller project consists of Dr. Gore, John Pommier, and myself. The SSFR is used by the ,cities Atmospheric Radiation Group to measure solar spectral irradiance at moderate resolution to determine the radiative effect of clouds, aerosols, and gases on climate, and also to infer the physical properties of aerosols and clouds. Two identical SSFR's have been built and successfully deployed in three field missions: 1) the Department of Energy Atmospheric Radiation Measurement (ARM) Enhanced Shortwave Experiment (ARESE) II in February/March, 2000; 2) the Puerto Rico Dust Experiment (PRIDE) in July, 2000; and 3) the South African Regional Science Initiative (SAFARI) in August/September, 2000. Additionally, the SSFR was used to acquire water vapor spectra using the Ames Diameter base-path multiple-reflection absorption cell in a laboratory experiment.

Clanton, Sam↗

An Update on Oceanic Precipitation Rate and its Zonal Distribution in Light of Advanced Observations from Space

This study contributes to the estimation of the global mean and zonal distribution of oceanic precipitation rate using complementary information from advanced precipitation measuring sensors and provides an independent reference to assess current precipitation products. Precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and CloudSat cloud profiling radar (CPR) were merged, as the two complementary sensors yield an unprecedented range of sensitivity to quantify rainfall from drizzle through the most intense rates. At higher latitudes, where TRMM PR does not exist, precipitation estimates from Aqua's Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) complemented CloudSat CPR to capture intense precipitation rates. The high sensitivity of CPR allows estimation of snow rate, an important type of precipitation at high latitudes, not directly observed in current merged precipitation products. Using the merged precipitation estimate from the CloudSat, TRMM, and Aqua platforms (this estimate is abbreviated to MCTA), the authors' estimate for 3-yr (2007-09) nearglobal (80degS-80degN) oceanic mean precipitation rate is approx. 2.94mm/day. This new estimate of mean global ocean precipitation is about 9% higher than that of the corresponding Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) value (2.68mm/day) and about 4% higher than that of the Global Precipitation Climatology Project (GPCP; 2.82mm/day). Furthermore, MCTA suggests distinct differences in the zonal distribution of precipitation rate from that depicted in GPCPand CMAP, especially in the Southern Hemisphere.

profiling radar↗

CLARREO Approach for Reference Intercalibration of Reflected Solar Sensors: On-Orbit Data Matching and Sampling

The implementation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission was recommended by the National Research Council in 2007 to provide an on-orbit intercalibration standard with accuracy of 0.3% (k = 2) for relevant Earth observing sensors. The goal of reference intercalibration, as established in the Decadal Survey, is to enable rigorous high-accuracy observations of critical climate change parameters, including reflected broadband radiation [Clouds and Earth's Radiant Energy System (CERES)], cloud properties [Visible Infrared Imaging Radiometer Suite (VIIRS)], and changes in surface albedo, including snow and ice albedo feedback. In this paper, we describe the CLARREO approach for performing intercalibration on orbit in the reflected solar (RS) wavelength domain. It is based on providing highly accurate spectral reflectance and reflected radiance measurements from the CLARREO Reflected Solar Spectrometer (RSS) to establish an on-orbit reference for existing sensors, namely, CERES and VIIRS on Joint Polar Satellite System satellites, Advanced Very High Resolution Radiometer and follow-on imagers on MetOp, Landsat imagers, and imagers on geostationary platforms. One of two fundamental CLARREO mission goals is to provide sufficient sampling of high-accuracy observations that are matched in time, space, and viewing angles with measurements made by existing instruments, to a degree that overcomes the random error sources from imperfect data matching and instrument noise. The data matching is achieved through CLARREO RSS pointing operations on orbit that align its line of sight with the intercalibrated sensor. These operations must be planned in advance; therefore, intercalibration events must be predicted by orbital modeling. If two competing opportunities are identified, one target sensor must be given priority over the other. The intercalibration method is to monitor changes in targeted sensor response function parameters: effective offset, gain, nonlinearity, optics spectral response, and sensitivity to polarization. In this paper, we use existing satellite data and orbital simulationmethods to determinemission requirements for CLARREO, its instrument pointing ability, methodology, and needed intercalibration sampling and data matching for accurate intercalibration of RS radiation sensors on orbit.

radiometry↗

Highlights from a Decade of OMI-TOMS Total Ozone Observations on EOS Aura

Total ozone measurements from OMI have been instrumental in meeting Aura science objectives. In the last decade, OMI has extended the length of the TOMS total ozone record to over 35 years to monitor stratospheric ozone recovery. OMI-TOMS total ozone measurements have also been combined synergistically with measurements from other Aura instruments and MLS in particular, which provides vertically resolved information that complements the total O3 mapping capability of OMI. With this combined approach, the EOS Aura platform has produced more accurate and detailed measurements of tropospheric ozone. This has led in turn to greater understanding of the sources and transport of tropospheric ozone as well as its radiative forcing effect. The combined use of OMI and MLS data was also vital to the analysis of the severe Arctic ozone depletion event of 2011. The quality of OMI-TOMS total O3 data used in these studies is the result of several factors: a mature and well-validated algorithm, the striking stability of the OMI instrument, and OMI's hyperspectral capabilities used to derive cloud pressures. The latter has changed how we think about the effects of clouds on total ozone retrievals. We will discuss the evolution of the operational V8.5 algorithm and provide an overview and motivation for V9. After reviewing results and developments of the past decade, we finally highlight how ozone observations from EOS Aura are playing an important role in new ozone mapping missions.

Ozone↗

Atmospheric Research 2018 Technical Highlights

Atmospheric research in the Earth Sciences Division (610) consists of research and technology development programs dedicated to advancing knowledge and understanding of the atmosphere and its interaction with the climate of Earth. The Division’s goals are to improve understanding of the dynamics and physical properties of precipitation, clouds, and aerosols; atmospheric chemistry, including the role of natural and anthropogenic trace species on the ozone balance in the stratosphere and the troposphere; and radiative properties of Earth’s atmosphere and the influence of solar variability on the Earth’s climate. Major research activities are carried out in the Mesoscale Atmospheric Processes Laboratory, the Climate and Radiation Laboratory, the Atmospheric Chemistry and Dynamics Laboratory, and the Wallops Field Support Office. The overall scope of the research covers an end-to-end process, starting with the identification of scientific problems, leading to observation requirements for remote sensing platforms, technology and retrieval algorithm development; followed by flight projects and satellite missions; and eventually, resulting in data processing, analyses of measurements, and dissemination from flight projects and missions.

Highlights↗

Inter-Calibration and Concatenation of Climate Quality Infrared Cloudy Radiances from Multiple Instruments

A change in climate is not likely captured from any single instrument, since no single instrument can span decades of time. Therefore, to detect signals of global climate change, observations from many instruments on different platforms have to be concatenated. This requires careful and detailed consideration of instrumental differences such as footprint size, diurnal cycle of observations, and relative biases in the spectral brightness temperatures. Furthermore, a common basic assumption is that the data quality is independent of the observed scene and therefore can be determined using clear scene data. However, as will be demonstrated, this is not necessarily a valid assumption as the globe is mostly cloudy. In this study we highlight challenges in inter-calibration and concatenation of infrared radiances from multiple instruments by focusing on the analysis of deep convective or anvil clouds. TRMM/VIRS is potentially useful instrument to make correction for observational differences in the local time and foot print sizes, and thus could be applied retroactively to vintage instruments such as AIRS, IASI, IRIS, AVHRR, and HIRS. As the first step, in this study, we investigate and discuss to what extent AIRS and VIRS agree in capturing deep cloudy radiances at the same local time. The analysis also includes comparisons with one year observations from CrIS. It was found that the instruments show calibration differences of about 1K under deep cloudy scenes that can vary as a function of land type and local time of observation. The sensitivity of footprint size, view angle, and spectral band-pass differences cannot fully explain the observed differences. The observed discrepancies can be considered as a measure of the magnitude of issues which will arise in the comparison of legacy data with current data.

cloudy radiance↗

Retrieval of Aerosol Properties from Multi-Spectral Extinction Measurements

The direct-beam spectral extinction of solar radiation contains information on atmospheric composition in a form that is essentially free from the data analysis complexities that often arise from multiple scattering. Ground based Multi-Filter Shadowband Radiometer (MFRSR) measurements provide such information for the vertical atmospheric column path, while solar occultation measurements from a satellite platform provide horizontal slices through the atmosphere. We describe application of a Multi-Spectral Atmospheric Column Extinction (MACE) analysis technique used to analyze MFRSR data also to occultation measurements made by SAGE II. For analysis, we select the 1985 Nevado del Ruiz volcanic eruption period to retrieve atmospheric profiles of ozone and NO2, and changes in the stratospheric aerosol size and optical depth. The time evolution of volcanic aerosol serves as a passive tracer to study stratospheric dynamics, and changes in particle size put constraints on the sulfur chemistry modeling of volcanic aerosols. Paper presented at The '99 Kyoto Aerosol-Cloud Workshop, held Dec 1-3, 1999, Kyoto, Japan

Lacis, Andrew A.↗

Design of a Far-Infrared Spectrometer for Atmospheric Thermal Emission Measurements

Global measurements of far infrared emission from the upper troposphere are required to test models of cloud radiative forcing, water vapor continuum emission, and cooling rates. Spectra with adequate resolution can also be used for retrieving atmospheric temperature and humidity profiles, and yet there are few spectrally resolved measurements of outgoing longwave flux at wavelengths longer than 16 m. It has been difficult to make measurements in the far infrared due to the need for liquid-helium cooled detectors and large optics to achieve adequate sensitivity and bandwidth. We review design considerations for infrared Fourier transform spectrometers, including the dependence of system performance on basic system parameters, and discuss the prospects for achieving useful sensitivity from a satellite platform with a lightweight spectrometer using uncooled detectors.

Johnson, David G.↗