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At least 1,063 records · Page 59

Second SNPP Cal/Val Campaign: Environmental Data Retrieval Analysis

Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (Soumi NPP) satellite Environmental Data Records (EDRs) are retrieved from calibrated ultraspectral radiance or Sensor Data Records (SDRs). Understanding the accuracy of retrieved EDRs is critical. The second Suomi NPP Calibration/Validation field campaign was conducted during March 2015 with flights over Greenland. The NASA high-altitude ER-2 aircraft carrying ultraspectral interferometer sounders such as the National Airborne Sounder Testbed-Interferometer (NAST-I) flew under the Suomi NPP satellite that carries the Crosstrack Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). Herein we inter-compare the EDRs produced from different retrieval algorithms employed on these satellite and aircraft campaign data. The available radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses are used to assess atmospheric temperature and moisture retrievals from the aircraft and satellite platforms. Preliminary results of this experiment under a winter, Arctic environment are presented.

Zhou, Daniel K.↗

Effects of Convective Transport of Solute and Impurities on Defect-Causing Kinetics Instabilities

For in-situ studies of the formation and evolution of step patterns during the growth of protein crystals, we have designed and assembled an experimental setup based on Michelson interferometry with the surface of the growing protein crystal as one of the reflective surfaces. The crystallization part of the device allows optical monitoring of a face of a crystal growing at temperature stable within 0.05 C in a developed solution flow of controlled direction and speed. The reference arm of the interferometer contains a liquid-crystal element that allows controlled shifts of the phase of the interferograms. We employ an image processing algorithm which combines five images with a pi/2 phase difference between each pair of images. The images are transferred to a computer by a camera capable of capturing 6-8 frames per second. The device allows data collection data regarding growth over a relatively large area (approximately .3 sq. mm) in-situ and in real time during growth. The estimated dept resolution of the phase shifting interferometry is about 100 A. The lateral resolution, depending on the zoom ratio, varies between 0.3 and 0.6 micrometers. We have now collected quantitative results on the onset, initial stages and development of instabilities in moving step trains on vicinal crystal surfaces at varying supersaturation, position on the facet, crystal size and temperature with the proteins ferritin, apoferritin and thaumatin. Comparisons with theory, especially with the AFM results on the molecular level processes, see below, allow tests of the rational for the effects of convective flows and, as a particular case, the lack thereof, on step bunching.

Vekilov, Peter G.↗

Simulation of Propellant Loading System Senior Design Implement in Computer Algorithm

Propellant loading from the Storage Tank to the External Tank is one of the very important and time consuming pre-launch ground operations for the launch vehicle. The propellant loading system is a complex integrated system involving many physical components such as the storage tank filled with cryogenic fluid at a very low temperature, the long pipe line connecting the storage tank with the external tank, the external tank along with the flare stack, and vent systems for releasing the excess fuel. Some of the very important parameters useful for design purpose are the prediction of pre-chill time, loading time, amount of fuel lost, the maximum pressure rise etc. The physics involved for mathematical modeling is quite complex due to the fact the process is unsteady, there is phase change as some of the fuel changes from liquid to gas state, then conjugate heat transfer in the pipe walls as well as between solid-to-fluid region. The simulation is very tedious and time consuming too. So overall, this is a complex system and the objective of the work is student's involvement and work in the parametric study and optimization of numerical modeling towards the design of such system. The students have to first become familiar and understand the physical process, the related mathematics and the numerical algorithm. The work involves exploring (i) improved algorithm to make the transient simulation computationally effective (reduced CPU time) and (ii) Parametric study to evaluate design parameters by changing the operational conditions

Bandyopadhyay, Alak↗

Preface to Special Section: Validation of Atmospheric Infrared Sounder Observations

The papers described below demonstrate that the AIRS calibrated radiances and retrieved geophysical products generally meet or exceed the prelaunch specifications. The retrieved quantities show little variation in uncertainty as a function of cloud amount. However, AIRS retrieval yield is a rapidly decreasing function of cloud amount; at about 80% cloudiness essentially no infrared radiances are used in the retrieval processes. Also, AIRS performance has not been demonstrated for all conditions and products. Calibrated and forward calculated radiances meet performance specifications for conditions varying from the cold poles to warm tropics. The retrieval system performs well over extrapolar land in the free troposphere (~2-15 km above the surface) and over extrapolar oceans at all tropospheric altitudes. The AIRS retrieval algorithms have not been optimized for polar winter conditions, so no such results are presented in these papers.

temperature↗

General Purpose Fortran Program for Discrete-Ordinate-Method Radiative Transfer in Scattering and Emitting Layered Media: An Update of DISORT

This update reports a state-of-the-art discrete ordinate algorithm for monochromatic unpolarized radiative transfer in non-isothermal, vertically inhomogeneous, but horizontally homogeneous media. The physical processes included are Planckian thermal emission, scattering with arbitrary phase function, absorption, and surface bidirectional reflection. The system may be driven by parallel or isotropic diffuse radiation incident at the top boundary, as well as by internal thermal sources and thermal emission from the boundaries. Radiances, fluxes, and mean intensities are returned at user-specified angles and levels. DISORT has enjoyed considerable popularity in the atmospheric science and other communities since its introduction in 1988. Several new DISORT features are described in this update: intensity correction algorithms designed to compensate for the 8-M forward-peak scaling and obtain accurate intensities even in low orders of approximation; a more general surface bidirectional reflection option; and an exponential-linear approximation of the Planck function allowing more accurate solutions in the presence of large temperature gradients. DISORT has been designed to be an exemplar of good scientific software as well as a program of intrinsic utility. An extraordinary effort has been made to make it numerically well-conditioned, error-resistant, and user-friendly, and to take advantage of robust existing software tools. A thorough test suite is provided to verify the program both against published results, and for consistency where there are no published results. This careful attention to software design has been just as important in DISORT's popularity as its powerful algorithmic content.

Tsay, Si-Chee↗

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Simon, Donald L.↗

Probability Index of Low Stratus and Fog at Dawn using Dual Geostationary Satellite Observations from COMS and FY-2D near the Korean Peninsula

We developed a new remote sensing method for detecting low stratus and fog (LSF) at dawn in terms of probability index (PI) of LSF from simultaneous stereo observations of two geostationary-orbit satellites; the Korean Communication, Ocean, and Meteorological Satellite (COMS; 128.2°E); and the Chinese FengYun satellite (FY-2D; 86.5°E). The algorithm was validated near the Korean Peninsula between the months of April and August from April 2012 to June 2015, by using surface observations at 45 meteorological stations in South Korea. The optical features of LSF were estimated by using satellite retrievals and simulated data from the radiative transfer model. The PI was calculated using the combination of three satellite-observed variables: 1) the reflectance at 0.67 μm (R(0.67)) from COMS, and 2) the FY-2D R(0.67) minus the COMS R(0.67) (△R(0.67)) and (3) the FY-2D-COMS difference in the brightness temperature difference between 3.7 and 11.0 μm (ΔBTD(3.7-11)). The three variables, adopted from the top three probability of detection (POD) scores for their fog detection thresholds: △R(0.67) (0.82) > ΔBTD(3.7-11) (0.73) > R(0.67) (0.70) > BTD(3.7-11) (0.51). The LSF PI for this algorithm was significantly better in the two case studies compared to that using COMS only (i.e., R(0.67) or BTD(3.7-11)), so that this improvement was due to △R(0.67) and ΔBTD(3.7-11). Overall, PI in the LSF spatial distribution has the merits of a high detection rate, a specific probability display, and a low rate of seasonality and variability in detection accuracy. Therefore, PI would be useful for monitoring LSF in near-real-time, and to further its forecast ability, using next-generation satellites.

fog↗

On the application of nonlinear load elements to thermal analyses using the NASTRAN thermal analyzer

The nonlinear load elements in thermal analysis are used to simulate an undocumented nonlinear thermal boundary condition. The treatment of the nonlinearity arising from the temperature-dependent convective film coefficients is shown in detail. As an illustration, emphasis is placed on the modeling techniques and their interrelationships with the solution accuracy as affected by a specific integration algorithm of the transient thermal analysis used in the NASTRAN Thermal Analyzer. Briefly shown is the underlying theory on which the maneuvering of terms pertinent to the modeling depends. This demonstration provides some insight into the intricacies of the method that would be general to all applications. A recommendation is also made to modify a nonlinear load element that will enhance the solution capability and broaden the scope of application.

Lee, H. P.↗

Defining the Polar Vortex Edge Using an N2O: Potential Temperature Correlation Versus the Nash Criterion: A Comparison

A prerequisite to study phenomena in the winter stratospheric polar vortex is the separation of measurements inside and outside the dynamical barrier of the vortex edge. We describe a technique to accurately determine the inner edge of the vortex boundary region from measurements of potential temperature and a trace gas, such as N2O, and apply it to in situ aircraft and balloon measurements from the SOLVE/THESE02000 Arctic campaign. The method may be used to refine the Nash algorithm, which, due to the inherently coarser resolution of potential vorticity on which it is dependent, may misidentify the inner edge by up to 466 km, and omit the identification of small, extra-vortex filaments within the vortex.

Greenblatt, Jeffery B.↗

Development and Testing of Data Mining Algorithms for Earth Observation

The new algorithms developed under this project included a principled procedure for classification of objects, events or circumstances according to a target variable when a very large number of potential predictor variables is available but the number of cases that can be used for training a classifier is relatively small. These "high dimensional" problems require finding a minimal set of variables -called the Markov Blanket-- sufficient for predicting the value of the target variable. An algorithm, the Markov Blanket Fan Search, was developed, implemented and tested on both simulated and real data in conjunction with a graphical model classifier, which was also implemented. Another algorithm developed and implemented in TETRAD IV for time series elaborated on work by C. Granger and N. Swanson, which in turn exploited some of our earlier work. The algorithms in question learn a linear time series model from data. Given such a time series, the simultaneous residual covariances, after factoring out time dependencies, may provide information about causal processes that occur more rapidly than the time series representation allow, so called simultaneous or contemporaneous causal processes. Working with A. Monetta, a graduate student from Italy, we produced the correct statistics for estimating the contemporaneous causal structure from time series data using the TETRAD IV suite of algorithms. Two economists, David Bessler and Kevin Hoover, have independently published applications using TETRAD style algorithms to the same purpose. These implementations and algorithmic developments were separately used in two kinds of studies of climate data: Short time series of geographically proximate climate variables predicting agricultural effects in California, and longer duration climate measurements of temperature teleconnections.

Glymour, Clark↗

A Generalized Logical Format for Inter-Calibrated Brightness Temperatures for the Global Precipitation Measurement Mission

An important aspect of the GPM mission is the merging of precipitation data from multiple radiometers on different satellites. This requires that each radiometer be consistently calibrated and that each be intercalibrated with a mission reference standard. For GPM the reference standard is to be the core satellite carrying a dual frequency precipitation radar and a well calibrated conically scanning radiometer. This paper describes a common format for representing these intercalibrated brightness temperatures which will be used for all radiometer products from GPM partner satellites. The use of common formats ensures that users obtain all the required information and also facilitates the rain retrieval algorithm code preparation as it can always except to have the data that it needs for the retrieval.

Stocker, Erich Franz↗

Forecasting Evaluation of WindSat in the Coastal Environment

WindSat has demonstrated that measurements from polarimetric space-based microwave radiometers can be used to retrieve global ocean surface vector winds. Since the date of launch in 2003, substantial incremental improvements have been made to WindSat data processing, calibration, and retrieval algorithms. The retrievals now have higher resolution, improved wind vector ambiguity removal, and enhanced capability to represent high winds. Utilization of WindSat retrievals (wind vectors, total precipitable water, rainrate and sea surface temperature) will be demonstrated in the context of operational weather forecasting applications, especially the monitoring of topographically-forced winds. Examples will be presented from various parts of the world, including inland seas, midlatitude oceans, the tropics, and the United States. We will illustrate retrievals in extreme high- and extreme low-wind regimes, both of which can be problematic. Rain contamination will be addressed. We will include a comparison of WindSat vector maps to corresponding maps from the QuikScat scatterometer. We will discuss how near-realtime data from WindSat is being transitioned to specific offices within the National Weather Service.

Lee, Thomas F.↗

Development and Assessment of the SMAP Enhanced Passive Soil Moisture Product

Launched in January 2015, the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) observatory was designed to provide frequent global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using a radar and a radiometer operating at L-band frequencies. Despite a hardware mishap that rendered the radar inoperable shortly after launch, the radiometer continues to operate nominally, returning more than two years of science data that have helped to improve existing hydrological applications and foster new ones.Beginning in late 2016 the SMAP project launched a suite of new data products with the objective of recovering some high-resolution observation capability loss resulting from the radar malfunction. Among these new data products are the SMAP Enhanced Passive Soil Moisture Product that was released in December 2016, followed by the SMAPSentinel-1 Active-Passive Soil Moisture Product in April 2017.This article covers the development and assessment of the SMAP Level 2 Enhanced Passive Soil Moisture Product (L2_SM_P_E). The product distinguishes itself from the current SMAP Level 2 Passive Soil Moisture Product (L2_SM_P) in that the soil moisture retrieval is posted on a 9 km grid instead of a 36 km grid. This is made possible by first applying the Backus-Gilbert optimal interpolation technique to the antenna temperature (TA) data in the original SMAP Level 1B Brightness Temperature Product to take advantage of the overlapped radiometer footprints on orbit. The resulting interpolated TA data then go through various correctioncalibration procedures to become the SMAP Level 1C Enhanced Brightness Temperature Product (L1C_TB_E). The L1C_TB_E product, posted on a 9 km grid, is then used as the primary input to the current operational SMAP baseline soil moisture retrieval algorithm to produce L2_SM_P_E as the final output. Images of the new product reveal enhanced visual features that are not apparent in the standard product. Based on in situ data from core validation sites and sparse networks representing different seasons and biomes all over the world, comparisons between L2_SM_P_E and in situ data were performed for the duration of April 1, 2015 October 30, 2016. It was found that the performance of the enhanced 9 km L2_SM_P_E is equivalent to that of the standard 36 km L2_SM_P, attaining a retrieval uncertainty below 0.040 m(exp 3)/m(exp 3) unbiased root-mean-square error (ubRMSE) and a correlation coefficient above 0.800. This assessment also affirmed that the Single Channel Algorithm using the V-polarized TB channel (SCA-V) delivered the best retrieval performance among the various algorithms implemented for L2_SM_P_E, a result similar to a previous assessment for L2_SM_P.

Enhanced↗

Machine Learning Applications to Metal-Silicate Equilibria and their Insights into Core Formation

An extensive number of studies have experimentally investigated how elements distribute between metal and silicate phases, to better constrain core-mantle chemical equilibrium. Here, we present a new database compiling all (to our knowledge) experimental data on liquid metal-silicate partitioning from 118 peer-reviewed publications. We applied various machine learning techniques to gain further insights into these partitioning equilibria and their dependencies. We performed a network analysis to investigate the relationship between experiments and partition coefficients, which enables visualizing gaps in the experimental dataset and biases related to varying experimental conditions and analytical setup. In addition, semi-empirical thermodynamic models are commonly used to extrapolate these chemical reactions to the wide range of pressure, temperature and compositional conditions of planetary differentiation. These models are based on linear regressions that assume continuous relationship between partition coefficients and experimental variables. Here, we considered random forest regressions, which are algorithms based on ensembles of decision trees and does not consider continuous effects of each variable. The application of this regression significantly improves the prediction of metal-silicate partitioning for several elements including Ni, Si and Cr. We will show how this new approach improves our understanding of elemental exchange between metal and silicate and their implications for the Earth’s core formation.

siderophile element↗

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global CCMs where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AtmOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) chemistry-climate model through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗

Analytical study of mixing and reacting three-dimensional supersonic combustor flow fields

An analytical investigation is presented of mixing and reacting hydrogen jets injected from multiple orifices transverse and parallel to a supersonic airstream. The COMOC computer program, based upon a finite-element solution algorithm, was developed to solve the governing equations for three-dimensional, turbulent, reacting, boundary-region, and confined flow fields. The computational results provide a three-dimensional description of the velocity, temperature, and species-concentration fields downstream of hydrogen injection. Detailed comparisons between cold-flow data and results of the computational analysis have established validity of the turbulent-mixing model based on the elementary mixing-length hypothesis. A method is established to initiate computations for reacting flow fields based upon cold-flow correlations and the appropriate experimental parameters of Mach number, injector spacing, and pressure ratio. Key analytical observations on mixing and combustion efficiency for reacting flows are presented and discussed.

Baker, A. J.↗

U-2 water vapor burden observations through the tropopause

A U-2 aircraft provided a platform for an infrared radiometer inferring water vapor burdens associated with the Intertropical Convergence Zone. Flight altitudes were 16 to 23 km. The radiometer system, coupled with an algorithm to produce an inverse solution of the radiative transfer equation, resulted in an rms error of 20 percent in the inferred water vapor burden. A unique, bivariate solution including radiance and vertical temperature profiles produced an essentially real-time solution for the water vapor burden. Results of the July 1977 missions over the Canal Zone region between latitudes 7.5 degrees N and 11.0 degrees N are presented.

Kuhn, P. M.↗

Temperature retrievals from TIROS-N

A nonstatistical, nonlinear iterative scheme, has been developed, based on the methods of Chahine (1970), to retrieve surface temperature, vertical temperature profile and cloud distribution from TIROS-N HIRS 2/MSU observations. Fundamental to the technique is the ability to accurately calculate clear column radiances given atmospheric and surface characteristics. The cloud filtering algorithm, making simultaneous use of IR 15 micron channels and microwave channels, allows accurate infrared retrievals in the presence of up to 80 percent cloud cover. Details for the iterative scheme are presented together with preliminary results from analysis of TIROS-N data.

Susskind, J.↗