Determination of Atmospheric and Surface Parameters From Simulated AIRS/AMSU Sounding Data: Retrieval and Cloud Clearing Methodology
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The Infrared Atmospheric Sounding Interferometer (IASI) is a hyperspectral sensor with 8461 spectral channels and a nominal spectral resolution of 0.25 cm(sup -1). It is computationally intensive to perform radiative transfer calculations and inversions using all these channels. We will present a Principal Component-based Radiative Transfer Model (PCRTM) and a retrieval algorithm which perform all the necessary calculations in EOF domain. Since the EOFs are orthogonal to each other, only about 100 principal components are needed to represent the information content of the 8461 channels. The PCRTM provides the EOF coefficients and associated derivatives with respect to atmospheric and surface parameters needed by the inversion algorithm. The inversion algorithm is based on a non-linear Levenberg-Marquardt method with climatology covariance and a priori information as constraints. The retrieved parameters include atmospheric temperature, moisture and ozone profiles, cloud parameters, surface skin temperature, and surface emissivities. To make the retrieval system even more compact and stable. The atmospheric vertical profiles are compressed into the EOF space as well. The surface emissivities are also compressed into EOF space.
Atmosphere and ocean surface parameters are being derived from weather satellite data acquired by the High Resolution Infrared Sounder and the Microwave Sounding Unit. In this paper, the global distribution and accuracy of the derived parameters are described, and the satellite-derived skin surface temperature is compared with available shelter temperature. Seasonal and interannual changes are examined to study the response time of large-scale atmospheric changes to changes in surface conditions.
Based on guidelines from the Federal Aviation Administration, research supported by the NASA Advanced Composites Project is investigating methods to improve process control for surface preparation and pre-bond surface characterization on aerospace composite structures. The overall goal is to identify high fidelity, rapid, and reproducible surface treatments and surface characterization methods to reduce the uncertainty associated with the bonding process. The desired outcome is a more reliable bonded airframe structure, and to reduce time to achieve certification. In this work, a design of experiments (DoE) approach was conducted to determine optimum laser ablation conditions using a pulsed laser source with a nominal pulse width of 10 picoseconds. The laser power, frequency, scan speed, and number of passes (1 or 2) were varied within the laser system operating boundaries. Aerospace structural carbon fiber reinforced composites (Torayca® 3900-2/T800H) were laser treated, then characterized for contamination, and finally bonded for mechanical testing. Pre-bond characterization included water contact angle (WCA) using a handheld device, ablation depth measurement using scanning electron microscopy (SEM), and silicone contamination measurement using laser induced breakdown spectroscopy (LIBS). In order to accommodate the large number of specimens in the DoE, a rapid-screening, double cantilever beam (DCB) test specimen configuration was devised based on modifications to ASTM D5528. Specimens were tested to assess the failure modes observed under the various laser surface treatment parameters. The models obtained from this DoE indicated that results were most sensitive to variation in the average laser power. Excellent bond performance was observed with nearly 100% cohesive failure for a wide range of laser parameters. Below about 200 mW, adhesive failure was observed because contamination was left on the surface. For laser powers greater than about 600 mW, large amounts of fiber were exposed, and the failure mode was predominately fiber tear.
Examples are given of the accuracy of the results obtained from the HIRS 2/MSU (High Resolution Infrared Sounder and Microwave Sounding Unit) analysis of ocean, atmosphere, and land parameters. Sea surface temperatures are compared with available ship and buoy radiosonde data, and land surface temperatures are compared with shelter temperatures. The seasonal change in land and ocean skin surface temperature is reviewed. The distribution of clouds is examined and their opacities in the visible and infrared parts of the spectrum are compared.
Parameter and state estimation techniques for an elliptic system arising in a developmental model for the antenna surface in the Maypole Hoop/Column antenna are discussed. A computational algorithm based on spline approximations for the state and elastic parameters is given and numerical results obtained using this algorithm are summarized.
Surface roughness parameters, namely the roughness length and displacement height, are an integral input used to model surface fluxes. However, most models assume these parameters to be a fixed property of plant functional type and disregard the governing structural heterogeneity and dynamics. In this study, we use large-eddy simulations to explore, in silico, the effects of canopy-structure characteristics on surface roughness parameters. We performed a virtual experiment to test the sensitivity of resolved surface roughness to four axes of canopy structure: (1) leaf area index, (2) the vertical profile of leaf density, (3) canopy height, and (4) canopy gap fraction. We found roughness parameters to be highly variable, but uncovered positive relationships between displacement height and maximum canopy height, aerodynamic canopy height and maximum canopy height and leaf area index, and eddy-penetration depth and gap fraction. We also found negative relationships between aerodynamic canopy height and gap fraction, as well as between eddy-penetration depth and maximum canopy height and leaf area index. We generalized our model results into a virtual "biometric" parameterization that relates roughness length and displacement height to canopy height, leaf area index, and gap fraction. Using a decade of wind and canopy-structure observations in a site in Michigan, we tested the effectiveness of our model-driven biometric parameterization approach in predicting the friction velocity over heterogeneous and disturbed canopies. We compared the accuracy of these predictions with the friction-velocity predictions obtained from the common simple approximation related to canopy height, the values calculated with large-eddy simulations of the explicit canopy structure as measured by airborne and ground-based lidar, two other parameterization approaches that utilize varying canopy-structure inputs, and the annual and decadal means of the surface roughness parameters at the site from meteorological observations. We found that the classical representation of constant roughness parameters (in space and time) as a fraction of canopy height performed relatively well. Nonetheless, of the approaches we tested, most of the empirical approaches that incorporate seasonal and interannual variation of roughness length and displacement height as a function of the dynamics of canopy structure produced more precise and less biased estimates for friction velocity than models with temporally invariable parameters.
Global warming signals are expected to be amplified in the Arctic primarily because of ice-albedo feedback associated with the high reflectivity of ice and snow that blankets much of the region. The Arctic had been a poorly explored territory basically because of its general inaccessibility on account of extremely harsh weather conditions and the dominant presence of thick perennial ice in the region. The advent of satellite remote sensing systems since the 1960s, however, enabled the acquisition of synoptic data that depict in good spatial detail the temporal changes of many Arctic surface parameters. Among the surface parameters that have been studied using space based systems are surface temperature, sea ice concentration, snow cover, surface albedo and phytoplankton concentration. Associated atmospheric parameters, such as cloud cover, temperature profile, ozone concentration, and aerosol have also been derived. Recent observational and phenomenological studies have indeed revealed progressively changing conditions in the Arctic during the last few decades (e g , Walsh et al. 1996; Serreze et al 2000; Comiso and Parkinson 2004). The changes included declines in the extent and area of surfaces covered by sea ice and snow, increases in melt area over the Greenland ice sheets, thawing of the permafrost, warming in the troposphere, and retreat of the glaciers. These observations are consistent with the observed global warming that has been associated with the increasing concentration of greenhouse gases in the atmosphere (Karl and Trenberth 2003) and confirmed by modeling studies (Holland and Bitz, 2003). The Arctic system, however, is still not well understood complicated by a largely fluctuating wind circulation and atmospheric conditions (Proshutinsky and Johnson 1997) and controlled by what is now known as the Arctic Oscillation (AO) which provides a measure of the strength of atmospheric activities in the region (Thompson and Wallace 1998). Meanwhile, the observed Arctic conditions since the 1970s have been shown to exhibit a linear behavior that directly contradicts what has been expected from the A0 (Overland, 2005). The decade of the 1990s has been regarded as the warmest decade in the last century and current data indicates that the 2000s may be even a warmer decade than the 1990s further supporting the linear variability. In this paper, we use satellite data to gain insights into the warming Arctic and how the abnormally warm conditions during the last few years are reflected in the region.
Surface diffuseness parameter used in Woods-Saxon form of potential have been extracted from a large number of experimentally studied neutron-rich fusion cross sections at near barrier energies. The results of our systematic study reveals that the extracted diffuseness parameter depend linearly on the N/Z ratio of the fusing nuclei. Further, we demonstrated that the extracted values of surface diffuseness parameter lies within the range a = 0.40 to 0.77 fm as compared to commonly accepted value form scattering i.e. 0.63 fm.
The bulk aerodynamic parameters associated with the absorption of surface momentum by vegetated landscapes are theoretically estimated within the context of Raupach's roughness sublayer formulation. The parameters include the bulk plant drag coefficient, maximum u*/U(sub h), sheltering coefficient, and canopy area density at onset of sheltering. Parameters are estimated for the four principal IGBP land cover classes within the U.S. Southern Great Plains: evergreen needleleaf forests, grasslands, croplands, and open shrublands. The estimation approach applies the Method of Moments to roughness data from several international field experiments and other published sources. The results provide the necessary land surface parameters for satellite-based estimation of momentum aerodynamic roughness length and zero-plane displacement height for seasonally variable vegetation fields employed in most terrestrial and atmospheric simulation models used today. Construction of sample displacement and roughness maps over the Southern United States using MODIS land products demonstrates the potential of this approach for regional to global applications.
In the past the effect of soil roughness was often considered secondary within the determination of soil moisture from remote sensing data. Several studies showed that accurate determination of soil roughness leads to an improved estimation of soil moisture. Two default parameters to describe the surface roughness are the standard deviation of the surface height variation 𝑠 and the surface correlation length 𝑙 with its corresponding autocorrelation function. Both parameters (𝑠,𝑙) affect the emissivity measured by radiometers as well as the backscattering observed by radars. In this study, we develop a physics-based approach to retrieve 𝑠 and 𝑙 by combining both microwave signals based on active-passive microwave covariation. To test the approach, containing a forward model and a retrieval algorithm, we used active/passive microwave data measured with the ComRAD truck-based SMAP simulator at L-band. Results and validations with corresponding field measurements on ground show that 𝑠 and 𝑙 can be estimated simultaneously when using this approach. The physics-based retrieval algorithm works robustly for two investigated test fields having an RMS-Error of 0.68 cm and 0.69 cm between the microwave-based and field-measured 𝑠-values, and of 3.13 cm and 3.04 cm for 𝑙-values. The first validation of the results reveals that the influence of the autocorrelation function, needed within the retrieval, is distinct.
A model of wind and turbulence has been described for the surface boundary layer. The wind structure in the surface layer is considered to be a function of the surface parameters, stability, and height. The surface parameters considered are: (1) the surface roughness length; (2) the surface friction velocity; and (3) the zero plane displacement height. The stability parameter, Z/L, where L is the Monin-Obukov stability length, describes the thermal effect on the wind profile. The logarithmic wind profile is used to describe the mean wind field in the neutral boundary layer, and a logarithmic profile with a stability defect is used to describe the stable and unstable atmospheric conditions. For the very stable conditions, the logarithmic wind law does not hold. Under this condition, the layers of the atmosphere become disconnected and large scale frontal motions are the predominate factor in defining the wind profile. Figures are presented which represent some typical wind profiles in the very stable condition.