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Global model of atmospheric temperature, chemical composition and density for altitudes from 25 to 1000 km, using satellite drag determined density values
The middle atmospheric temperature structure has been studied for several decades now. It started with rocketsondes measurements, providing temperature profiles up to 60 km but with relatively poor accuracy [Schmidlin, 1981], and falling spheres allowing reaching 90 km of altitude.
This slide presentation reviews the use of shortwave channels available to the Atmospheric Infrared Sounder (AIRS) to improve the determination of surface and atmospheric temperatures. The AIRS instrument is compared with the Infrared Atmospheric Sounding Interferometer (IASI) on-board the MetOp-A satellite. The objectives of the AIRS/AMSU were to (1) provide real time observations to improve numerical weather prediction via data assimilation, (2) Provide observations to measure and explain interannual variability and trends and (3) Use of AIRS product error estimates allows for QC optimized for each application. Successive versions in the AIRS retrieval methodology have shown significant improvement.
Inverted planetary limb radiance for determining earth atmosphere temperature from orbiting satellite
A viewgraph presentation of a prototype Geostationary Synthetic Thinned Aperture Radiometer (GeoSTAR) for atmospheric temperature sounding is shown. The topics include: 1) Overview; 2) Requirements & Error allocations; 3) Design; 4) Problems, and How We Solved Them; and 5) Results
The Raman shifted return of a lidar system was utilized to make atmospheric temperature measurements. The measurements were made along a horizontal path at temperatures between -20 and +30 C and at ranges of about 100 meters. The temperature data were acquired by recording the intensity ratio of two portions of the rotational Raman spectrum which were simultaneously sampled from a preset range. Measurements were made to an accuracy of + or - 3 C with 1 minute temporal resolution.
Previously published analyses for the seasonal and longer-period cycles in middle atmosphere temperature versus pressure (or T(p)) from the Halogen Occultation Experiment (HALOE) are extended to just over 14 years and updated to properly account for the effects of autocorrelation in its time series of zonally-averaged data. The updated seasonal terms and annual averages are provided, and they can be used to generate temperature distributions that are representative of the period 1991-2005. QBO-like terms have also been resolved and are provided, and they exhibit good consistency across the range of latitudes and pressure-altitudes. Further, exploratory analyses of the residuals from each of the 221 time series have yielded significant 11-yr solar cycle (or SC-like) and linear trend terms at a number of latitudes and levels. The amplitudes of the SC-like terms for the upper mesosphere agree reasonably with calculations of the direct solar radiative effects for T(p). Those SC amplitudes increase by about a factor of 2 from the lower to the upper mesosphere and are also larger at the middle than at the low latitudes. The diagnosed cooling trends for the subtropical latitudes are in the range, -0.5 to -1.0 K/decade, which is in good agreement with the findings from models of the radiative effects on pressure surfaces due to known increases in atmospheric CO2. The diagnosed trends are somewhat larger than predicted with models for the upper mesosphere of the northern hemisphere middle latitudes.
The Raman shifted return of a lidar system has been utilized to make atmospheric temperature measurements. The measurements were made along a horizontal path at temperatures between -20 and +30 C and at ranges of about 100 meters. The temperature data were acquired by recording the intensity ratio of two portions of the rotational Raman spectrum which were simultaneously sampled from a preset range. Measurements were made to an accuracy of plus or minus 3 C with 1-minute temporal resolution.
The Raman shifted return of a lidar system has been utilized to make atmospheric temperature measurements. The measurements were made along a horizontal path at temperatures ranging from -30 C to +30 C and at ranges of about 100 meters. The temperature data were acquired by recording the intensity ratio of two portions of the rotational Raman spectrum which were simultaneously sampled from a preset range. A temperature measurement accuracy of plus or minus 4 C and a temporal resolution of one minute were realized with this system. The combined results of the theoretical analysis and the experimentation indicate that system improvements will significantly increase both accuracy and range.
The applicability of a high resolution infrared heterodyne radiometer for atmospheric temperature profiling is considered. Upwelling radiation at the 754.321/cm and the 945.976/cm rotational-vibrational lines of CO2 are monitored by a six IF channel infrared heterodyne radiometer with spectral specificity between 0.002 and 0.012/cm. Computer simulated retrievals have been carried out which indicate a maximum temperature inaccuracy of 3.5 K for vertical profiles between ground level and 50 km and a system integration time of 8 seconds.
This presentation describes how to define IR instrument requirement based on atmospheric temperature and water variability.
Satellite-borne carbon dioxide laser system for obtaining vertical temperature profiles of atmosphere
Measurements of spectral transmittance have been performed in the nu4-fundamental band of (C-13)H4 at low temperatures of planetary atmospheric interest with spectral resolution of 0.06 per cm. Comparison of observed and computed spectral transmittance on a line-by-line basis has yielded line strengths. Best agreement between measured and computed spectra was obtained when the absolute intensity of the band was taken as 123 per (sq cm atm) at 296 K.
An extended Kalman-Bucy filter has been implemented for atmospheric temperature profile retrievals from observations made using the Scanned Microwave Spectrometer (SCAMS) instrument carried on the Nimbus 6 satellite. This filter has the advantage that it requires neither stationary statistics in the underlying processes nor linear production of the observed variables from the variables to be estimated. This extended Kalman-Bucy filter has yielded significant performance improvement relative to multiple regression retrieval methods. A multi-spot extended Kalman-Bucy filter has also been developed in which the temperature profiles at a number of scan angles in a scanning instrument are retrieved simultaneously. These multi-spot retrievals are shown to outperform the single-spot Kalman retrievals.
Passive remote sensing of the atmosphere is used to determine the atmospheric state. A radiometer measures microwave emissions from earth's atmosphere and surface. The radiance measured by the radiometer is proportional to the brightness temperature. This brightness temperature can be used to estimate atmospheric parameters such as temperature and water vapor content. These quantities are of primary importance for different applications in meteorology, oceanography, and geophysical sciences. Depending on the range in the electromagnetic spectrum being measured by the radiometer and the atmospheric quantities to be estimated, the retrieval or inverse problem of determining atmospheric parameters from brightness temperature might be linear or nonlinear. In most applications, the retrieval problem requires the inversion of a Fredholm integral equation of the first kind making this an ill-posed problem. The numerical solution of the retrieval problem requires the transformation of the continuous problem into a discrete problem. The ill-posedness of the continuous problem translates into ill-conditioning or ill-posedness of the discrete problem. Regularization methods are used to convert the ill-posed problem into a well-posed one. In this paper, we present some results of our work in applying different regularization techniques to atmospheric temperature retrievals using brightness temperatures measured with the SSM/T-1 sensor. Simulation results are presented which show the potential of these techniques to improve temperature retrievals. In particular, no statistical assumptions are needed and the algorithms were capable of correctly estimating the temperature profile corner at the tropopause independent of the initial guess.
The Raman-shifted return of a lidar system had been used to make atmospheric temperature measurements. The measurements were made along a horizontal path at temperatures ranging from -30 to 30 C and at ranges of about 100 meters. The temperature data were acquired by recording the intensity ratio of two portions of the rotational Raman spectrum, which were simultaneously sampled from a preset range. These tests verified that the theoretical predictions formulated in the design of the system were adequate. Measurements were made to an accuracy of + or - 4 C with 1-minute temporal resolution.
A dual-frequency system is used to demonstrate the measurement of atmospheric temperature, through laser energy absorption monitoring at the center of an O2 resonant absorption line near 770 nm. It is shown that the average temperature of a 1 km path can be determined within 1.0 C, with a noise level of 0.3 C. An iterative algebraic expression for this method was developed, and is shown to be applicable in the troposphere; the effects of pressure and humidity on temperature determination were made clear by the algorithm and found to be small near the earth's surface.
Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. The SiFSAP algorithm performs one retrieval for each FOV using an all-sky optimal estimation approach. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.