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At least 253 records · Page 14

Global average concentration and trend for hydroxyl radicals deduced from ALE/GAGE trichloroethane (methyl chloroform) data for 1978-1990

An optimal estimation inversion scheme is utilized with atmospheric data and emission estimates to determined the globally averaged CH3CCl3 tropospheric lifetime and OH concentration. The data are taken from atmospheric measurements from surface stations of 1,1,1-trichloroethane and show an annual increase of 4.4 +/- 0.2 percent. Industrial emission estimates and a small oceanic loss rate are included, and the OH concentration for the same period (1978-1990) are incorporated at 1.0 +/- 0.8 percent/yr. The positive OH trend is consistent with theories regarding OH and ozone trends with respect to land use and global warming. Attention is given to the effects of the ENSO on the CH3CCl3 data and the assumption of continuing current industrial anthropogenic emissions. A novel tropical atmospheric tracer-transport mechanism is noted with respect to the CH3CCl3 data.

Prinn, R.↗

Goddard problem in presence of a dynamic pressure limit

The Goddard problem is that of maximizing the final altitude for a vertically ascending, rocket-powered vehicle under the influence of an inverse square gravitational field and atmospheric drag. The present paper deals with the effects of two additional constraints, namely, a dynamic pressure limit and specified final time. Nine different switching structures involving zero-thrust arcs, full-thrust arcs, singular-thrust arcs, and state-constrained arcs are obtained when the value of the dynamic pressure limit is varied between zero and infinity and the final time is specified between the minimum possible time within which all of the fuel can be burned and the natural final time that emerges for the problem with final time unspecified. For all points in the aforementioned domain of dynamic pressure limit and prescribed final time, the associated optimal switching structure is clearly identified. Finally, a simple intuitive feedback law is presented for the free time problem. For all values of prescribed dynamic pressure limit, this strategy yields a loss in final altitude of less than 3 percent with respect to the associated optimal solution.

Seywald, Hans↗

Geostationary Carbon Process Mapper (GCPM)

Geostationary Carbon Process Mapper (GCPM) is an earth science mission to measure key atmospheric trace gases related to climate change and human activity.Understanding of sources and sinks of CO2 is currently limited by frequency of observations and uncertainty in vertical transport. GCPM improves this situation by making simultaneous high resolution measurements of CO2, CH4, CF, and CO in near-IR, many times per day. GCPM is able to investigate processes with time scales of minutes to hours. CO2, CH4, CF, Co selected because their combination provides information needed to disentangle natural and anthropogenic sources/sinks. Quasi-continuous monitoring effectively eliminates atmospheric transport uncertainties from source/sink inversion modeling. will have one instrument (GeoFTS), hosted on a commercial communications satellite, planned for two years operation. GCPM will affordably advance the understanding of observed cycle variability improving future climate projections.

Carbon Process↗

F/NAS/ Pressure Temperature Retrieval Techniques

The purpose of this investigation is to study methods and ways for rapid inversion programs involving the correlated k-method, and to modify the existing programs so that the rapid analysis of data can be accomplished. The earth's atmosphere as well as those around the planets consist of gases which emit radiation in the infrared spectral region, providing wealth of information about chemical and physical processes in the atmosphere. The atmospheric molecular constituents absorb and radiate by vibrational and rotational transitions, and the observed spectra exhibit characteristic spectral features in the region of the electromagnetic spectrum. The observed absorption or thermal emission spectra may be obtained with space-borne high resolution infrared spectrometers the 50-1000 micrometers spectral region. A detailed analysis of the observed spectra leads to information about the atmospheric thermal structure, composition, and the physical and chemical processes. The analytic techniques involve the development of radiative transfer models for the calculation of the observed radiance and transmittances for realistic atmospheric conditions and observational geometries, and the development of inversion methods for retrieval of atmospheric parameters from the observations.

Poularikas, Alexander↗

Toward a Comprehensive Carbon Budget for North America: Potential Applications of Adjoint Methods with Diverse Datasets

A detailed mechanistic understanding of the sources and sinks of CO2 will be required to reliably predict future COS levels and climate. A commonly used technique for deriving information about CO2 exchange with surface reservoirs is to solve an "inverse problem," where CO2 observations are used with an atmospheric transport model to find the optimal distribution of sources and sinks. Synthesis inversion methods are powerful tools for addressing this question, but the results are disturbingly sensitive to the details of the calculation. Studies done using different atmospheric transport models and combinations of surface station data have produced substantially different distributions of surface fluxes. Adjoint methods are now being developed that will more effectively incorporate diverse datasets in estimates of surface fluxes of CO2. In an adjoint framework, it will be possible to combine CO2 concentration data from long-term surface monitoring stations with data from intensive field campaigns and with proposed future satellite observations. A major advantage of the adjoint approach is that meteorological and surface data, as well as data for other atmospheric constituents and pollutants can be efficiently included in addition to observations of CO2 mixing ratios. This presentation will provide an overview of potentially useful datasets for carbon cycle research in general with an emphasis on planning for the North American Carbon Project. Areas of overlap with ongoing and proposed work on air quality/air pollution issues will be highlighted.

Andrews, A.↗

An Adjoint-Based Analysis of the Sampling Footprints of Tall Tower, Aircraft and Potential Future Lidar Observations of CO2

A detailed mechanistic understanding of the sources and sinks of CO2 will be required to reliably predict future CO2 levels and climate. A commonly used technique for deriving information about CO2 exchange with surface reservoirs is to solve an 'inverse problem', where CO2 observations are used with an atmospheric transport model to find the optimal distribution of sources and sinks. Synthesis inversion methods are powerful tools for addressing this question, but the results are disturbingly sensitive to the details of the calculation. Studies done using different atmospheric transport models and combinations of surface station data have produced substantially different distributions of surface fluxes. Adjoint methods are now being developed that will more effectively incorporate diverse datasets in estimates of surface fluxes of CO2. In an adjoint framework, it will be possible to combine CO2 concentration data from longterm surface and aircraft monitoring stations with data from intensive field campaigns and with proposed future satellite observations. We have recently developed an adjoint for the GSFC 3-D Parameterized Chemistry and Transport Model (PCTM). Here, we will present results from a PCTM Adjoint study comparing the sampling footprints of tall tower, aircraft and potential future lidar observations of CO2. The vertical resolution and extent of the profiles and the observation frequency will be considered for several sites in North America.

Andrews, Arlyn↗

[Global Atmospheric Chemistry/Transport Modeling and Data-Analysis]

This grant supported a global atmospheric chemistry/transport modeling and data- analysis project devoted to: (a) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for trace gases; (b) utilization of these inverse methods which use either the Model for Atmospheric Chemistry and Transport (MATCH) which is based on analyzed observed winds or back- trajectories calculated from these same winds for determining regional and global source and sink strengths for long-lived trace gases important in ozone depletion and the greenhouse effect; (c) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple "titrating" gases; and (d) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3D models. Important ultimate goals included determination of regional source strengths of important biogenic/anthropogenic trace gases and also of halocarbons restricted by the Montreal Protocol and its follow-on agreements, and hydrohalocarbons now used as alternatives to the above restricted halocarbons.

Prinn, Ronald G.↗

1D-VAR Retrieval Using Superchannels

Since modern ultra-spectral remote sensors have thousands of channels, it is difficult to include all of them in a 1D-var retrieval system. We will describe a physical inversion algorithm, which includes all available channels for the atmospheric temperature, moisture, cloud, and surface parameter retrievals. Both the forward model and the inversion algorithm compress the channel radiances into super channels. These super channels are obtained by projecting the radiance spectra onto a set of pre-calculated eigenvectors. The forward model provides both super channel properties and jacobian in EOF space directly. For ultra-spectral sensors such as Infrared Atmospheric Sounding Interferometer (IASI) and the NPOESS Airborne Sounder Testbed Interferometer (NAST), a compression ratio of more than 80 can be achieved, leading to a significant reduction in computations involved in an inversion process. Results will be shown applying the algorithm to real IASI and NAST data.

Liu, Xu↗

New observational constraints on the temperature inversions of Uranus and Neptune

The presence of a temperature inversion in the lower stratospheres of both Uranus and Neptune is confirmed by the 20-micron photometric data presented. It is found that the brightness temperature difference between 17.8 and 19.6 microns is 0.8 + or - 0.5 K for Uranus and 1.8 + or - 0.6 K for Neptune, implying that the temperature inversions of both planets are weaker than previously thought. Comparisons with model atmospheres suggested by Appleby (1980) imply that these temperature inversions may be understood as a consequence of heating through CH4 and aerosol absorption of sunlight. The stratospheric CH4 mixing ratio of Neptune must, however, be higher than that at the temperature minimum.

Tokunaga, A. T.↗

Atmospheric effects on the underground muon intensity

It has previously been reported that the barometric pressure coefficient observed for muons at Poatina (vertical absorber depth 357 hg/sq cm) appears to be appreciably higher than would be expected from atmospheric absorption alone. There is a possibility that the effect is due to an upper atmospheric temperature effect arising from an inverse correlation of surface pressure with stratospheric temperature. A new proportional telescope is discussed which has been operating at Poatina since about the beginning of 83 and which has a long term stability suitable for studying variations of atmospheric origin.

Fenton, A. G.↗

Stellar occultations by turbulent planetary atmospheres. I - A heuristic scattering model. II - The Beta Scorpii events

Effects of atmospheric turbulence on stellar-occultation inversion procedures are investigated using a heuristic scattering model that is believed to reproduce the essential features of turbulence. A quantitative estimate is made of the size of the error in deducing the mean refractivity profile of a planetary atmosphere, taking into account constant as well as exponential scattering. It is shown that ordinary turbulence has no important effect on the average intensity profile in a stellar occultation but could have an important instantaneous effect. A critical examination of possible manifestations of turbulent scattering during occultations of Beta Sco by Jupiter indicates that all observed phenomena during these events can be understood in terms of scintillations produced by turbulence.

Hubbard, W. B.↗

Atmospheric, Cloud, and Surface Parameters Retrieved from Satellite Ultra-spectral Infrared Sounder Measurements

An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multivariable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. This retrieval algorithm is applied to the MetOp satellite Infrared Atmospheric Sounding Interferometer (IASI) launched on October 19, 2006. IASI possesses an ultra-spectral resolution of 0.25 cm(exp -1) and a spectral coverage from 645 to 2760 cm(exp -1). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI measurements are obtained and presented.

Zhou, Daniel K.↗

Middle atmosphere of Venus and its clouds: Latitude and solar time variations

The structure of the middle atmosphere of Venus and its upper clouds, derived from infrared spectrometry (from 250 to 1650 cm(exp -1)) on Venera 15 are discussed. Poleward increasing of temperature, monotonous on the average, at altitudes h greater than 70 km changes to poleward decreasing at h less than 60 km. Temperature inversion at 85-95 km at low latitudes was observed as a half-day wave with two minima near 9:00 a.m. and 9:00 p.m, with a more pronounced morning feature. At high latitudes the inversion with temperature minimum near 64 km exists. There are several minima depending on solar time, but the most pronounced is one on the dayside, where the depth of inversion may reach more than 40 K (near 10:00 a.m.; we have no observations closer to noon). Another minimum is situated symmetrically on the nightside. Usually in the polar region the temperature inversion is situated deeper in the atmosphere (near 62 km). A jet at latitudes 50-55 deg N divides Venus into two drastically different latitude zones: pretty homogeneous at 56-95 km zone less than 50 deg N with diffuse clouds and daily temperature variations near cloud tops about several degrees, and zones greater than 55 deg N (where such dynamic structures as cold collar and hot dipole were observed) with dense low clouds (with the exceptions of the regions at 55-80 deg N outside the cold collar). We separate Venus into four latitudinal zones with approximate latitude boundaries, where the different IR-features were observed.

Zasova, L. V.↗

A Principal-Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Shortwave and Longwave Satellite Sensors and Its Applications

The radiative transfer model (RTM) or forward model is an essential component in satellite remote sensing. For modern hyperspectral remote sensors, fast and accurate RTMs are needed due to a large number of spectral dimensions and high spatial resolutions. We will describe a Principal Component-based radiative transfer model (PCRTM) which can simulate the top-of-atmosphere (TOA) radiance or reflectance spectra 250 nm to 2000 micrometers quickly and accurately. The PCRTM has been demonstrated to be extremely accurate, compared to the line-by-line RTM benchmarks, and the former is several orders more computationally efficient than the latter. We will demonstrate how the PCRTM and the associated inversion algorithms are used to infer atmospheric temperature, moisture, and trace gas profiles, as well as cloud and surface properties from hyperspectral IR sounders such as Atomspheric Infrared Souder (AIRS) and Cross-track Infrared Sounder (CrIS). High-quality climate records for a 20-year duration have been derived from these IR hyperspectral data. Finally, we will show some examples of using PCRTM to retrieve cloud properties from Earth Surface Mineral Dust Source Investigation (EMIT) and its applicability of PCRTM to future missions such as the CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF) CPF and the Surface Biology and Geology (SBG).

Xu Liu↗

High Vertically Resolved Atmospheric and Surface/Cloud Parameters Retrieved with Infrared Atmospheric Sounding Interferometer (IASI)

The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25/cm and a spectral coverage from 645 to 2760/cm. Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the cloud-free and/or clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals are achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals will be further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated indicating a high vertical structure of atmosphere is retrieved.

Zhou, Daniel K.↗

Current Sounding Capability From Satellite Meteorological Observation With Ultraspectral Infrared Instruments

Ultraspectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. The intent of the measurement of tropospheric thermodynamic state and trace abundances is the initialization of climate models and the monitoring of air quality. The NPOESS Airborne Sounder Testbed-Interferometer (NAST-I), designed to support the development of future satellite temperature and moisture sounders, aboard high altitude aircraft has been collecting data throughout many field campaigns. An advanced retrieval algorithm developed with NAST-I is now applied to satellite data collected with the Atmospheric InfraRed Sounder (AIRS) on the Aqua satellite launched on 4 May 2002 and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite launched on October 19, 2006. These instruments possess an ultra-spectral resolution, for example, both IASI and NAST-I have ~0.25 cm-1 and a spectral coverage from 645 to 2760 cm-1. The retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error less than 1 km). Retrievals of atmospheric soundings, surface properties, and cloud microphysical properties with the AIRS and IASI observations are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed? Interferometer (NAST I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the AIRS and IASI are investigated. These advanced satellite ultraspectral infrared instruments are now playing an important role in satellite meteorological observation for numerical weather prediction.

Zhou, Daniel K.↗

Improving vertical detail in simulated temperature and humidity data using machine learning

Atmospheric models used for weather forecasting and climate predictions discretise the atmosphere onto a vertical grid. There are however atmospheric phenomena that occur on scales smaller than the thickness of those model layers. The formation of low-level clouds due to temperature inversions is an example. This leads to atmospheric models underestimating, or even missing, these clouds and their radiative effects. Using radiosonde observations as training data, a machine learning model is used to improve the vertical detail of modelled profiles of temperature and specific humidity. In addition, a physics-informed machine learning model is developed and compared to the traditional approach; showing improvements in the cloud fraction profiles calculated from its predictions. The vertically enhanced profiles also improve the representation of layers of convective inhibition and anomalous refractivity gradients. This work facilitates targeted improvements to the representation of certain atmospheric processes without the burden of increased memory and computational cost from increasing vertical resolution throughout the whole model.

54 ENVIRONMENTAL SCIENCES↗

Inversion of SAGE II measurements

Stratospheric aerosol data acquired by the seven channels of the SAGE II passive radiometer system are first converted to atmospheric slant path transmission (SPT) values before deriving inversion values. The sun-pointing configuration permits bypassing calibration equipment required by other instruments and also furnishes high resolution vertical profile data. The retrieval techniques for quantifying the amounts of aerosol, water vapor, NO2 and O3, the species to which the SAGE II sensors are tuned, are summarized, along with methods for estimating the uncertainty in the calculations.

Chu, W. P.↗