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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Computationally Efficient Modeling and Data Assimilation of Near-Surface Variability

Near-surface (< 20m) ocean exhibits high variability due to coupled interactions, for e.g., with the atmosphere, sea ice, land, etc. Here we focus on atmospheric heat and momentum (wind) forcing, which are known to cause diurnal variability within the mixed layer. Only recently with a combination of sufficiently high vertical/horizontal resolution (75L, 1/4deg) and sub-daily atmospheric forcing fields, ocean models are starting to resolve this diurnal variability. However, the computation expense of such a high vertical resolution is burdensome in the context of coupled modeling and data assimilation. An alternative approach is to parameterize this diurnal variability with a prognostic model, that is embedded into the ocean model.In the first part of this presentation, we will demonstrate results with the above two approaches, by comparing them to profiles of near-surface temperature and salinity. In the context of data assimilation and reanalysis, this modeling capability opens the door to re-examine and perhaps improve specification of background (or, ensemble) error characteristics. The second half of this talk will focus on illustrating diurnally varying errors within an ensemble DA, and possible approaches to improve localization (horizontal/vertical) to extract maximum possible observational information content from in-situ and satellite observations of sea surface temperature.

Akella, Santha↗
NASA NTRS2012

Quantifying Interannual Variability of the UTLS Ozone Using Assimilation of Satellite Data

An accurate representation of spatial and temporal variability of the Upper Troposphere Lower Stratosphere (UTLS) ozone is essential for understanding both the tropospheric ozone budget and ozone s contribution to radiative forcing. The complex, dynamically driven structure of trace gas fields in the UTLS presents a challenge to data-based and modelling studies. Small features are not fully resolved in data from limb-sounding instruments such as the Microwave Limb Sounder on EOS-Aura (the EOS-MLS), but are captured in assimilation of those data as vertical structure is added from the assimilated meteorology. This will be demonstrated using a multi-year assimilation of EOS-MLS observations in the Goddard Earth Observing System, Version 5 (GEOS-5) data assimilation system. The results demonstrate the realism of the seasonal and year to year variability of laminar structures in the mid-latitudinal ozone field between years 2005-2007, for which independent validation data are available from the HIRDLS instrument. The analysis is done in the context of the underlying large scale dynamics. The lifetimes of most research instruments are too short for them to be used throughout the duration of long-term (at least 3 decades) reanalyses. For example, the EOS-MLS instrument has operated since mid-2004 until present. By contrast, Solar Backscatter Ultra Violet (SBUV) measurements provide continuous data since late 1978, but their vertical resolution is insufficient to represent the profile shape in the UTLS. Assimilation of these SBUV/2 observations in the GEOS-5 data assimilation system has hitherto not captured a realistic ozone structure in the UTLS, even though transport studies using GEOS-5 wind fields do show such structures. We show that careful construction of the background error covariance structure in GEOS-5 can lead to more realistic UTLS ozone fields when assimilating SBUV/2 observations. The reasoning behind this will be discussed, emphasizing the need to retain the sharp gradient of ozone concentrations across the tropopause. We analyze the UTLS ozone distributions in multi-year SBUV/2 assimilation experiments, comparing the results against the independent HIRDLSdataset and, for a longer period, with the MLS assimilation and discuss the consequences for tropospheric ozone and radiative forcing.

Wargan, K.↗
NASA NTRS1993

Variability in the Gulf of Alaska from Geosat altimetry data

Satellite altimetry was used to examine annual and interannual variability in the Gulf of Alaska region. Crossover data from the Geosat Geodetic Mission (GM) and collinear data from the Exact Repeat Mission (ERM) were processed separately to form sea surface height anomalies at grid points. The time series from the GM and ERM were then combined to produce a 3.75-year data set. The time series from the ERM data set agreed fairly well with hydrographic dynamic heights at several locations, with an average correlation of 0.70 between the two data sets. The combined and ERM altimetric data sets were analyzed using empirical orthogonal functions (EOFs). These revealed variability that occurs primarily on annual and interannual time scales. A comparison with EOF analysis of the atmospheric pressure field during the same time periods showed that the annual variation in pressure seemed to be reflected in both the combined and ERM altimetric data sets. The amplitude time series of the first mode in the combined data set was very similar to the North Pacific pressure index during the 1985-1989 time frame. The maximum correlation was at a lag of 250 days. Finally, an interannual mode was present in all three data sets which was closely linked to the baroclinic variations measured by the hydrographic data.

Bhaskaran, Shyam↗
NASA NTRS1990

Thermodynamic structure of the stratocumulus-capped boundary layer on 7 July, 1987

As part of project First ISCCP Regional Experiment (FIRE), a mission was carried out on 7 July 1987 to study the thermodynamic structure of a boundary layer which is in transition from a clear to a cloudy state. The National Center for Aeronautical Research (NCAR) Electra flew a pattern in tight coordination with the NASA ER-2 aircraft near 122 West, 31.6 North off the coast of California. A description is given here of the thermodynamic structure. The purpose is to derive the entrainment rate and the fluxes of the thermodynamic variables. To this end researchers represent the data in conserved variable diagrams.

Boers, Reinout↗
NASA NTRS1993

Radar Ocean Wave Spectrometer (ROWS) preprocessing program (PREROWS2.EXE). User's manual and program description

This Technical Memorandum is a user's manual with additional program documentation for the computer program PREROWS2.EXE. PREROWS2 works with data collected by an ocean wave spectrometer that uses radar (ROWS) as an active remote sensor. The original ROWS data acquisition subsystem was replaced with a PC in 1990. PREROWS2.EXE is a compiled QuickBasic 4.5 program that unpacks the recorded data, displays various variables, and provides for copying blocks of data from the original 8mm tape to a PC file.

Vaughn, Charles R.↗
NASA NTRS2008

Skill Assessment in Ocean Biological Data Assimilation

There is growing recognition that rigorous skill assessment is required to understand the ability of ocean biological models to represent ocean processes and distributions. Statistical analysis of model results with observations represents the most quantitative form of skill assessment, and this principle serves as well for data assimilation models. However, skill assessment for data assimilation requires special consideration. This is because there are three sets of information in the free-run model, data, and the assimilation model, which uses Data assimilation information from both the flee-run model and the data. Intercom parison of results among the three sets of information is important and useful for assessment, but is not conclusive since the three information sets are intertwined. An independent data set is necessary for an objective determination. Other useful measures of ocean biological data assimilation assessment include responses of unassimilated variables to the data assimilation, performance outside the prescribed region/time of interest, forecasting, and trend analysis. Examples of each approach from the literature are provided. A comprehensive list of ocean biological data assimilation and their applications of skill assessment, in both ecosystem/biogeochemical and fisheries efforts, is summarized.

Gregg, Watson W.↗
NASA NTRS1989

Continuously-Variable Vernier Scale

Easily fabricated device increases precision in reading graphical data. Continuously-variable vernier scale (CV VS) designed to provide greater accuracy to scientists and technologists in reading numerical values from graphical data. Placed on graph and used to interpolate coordinate value of point on curve or plotted point on figure within division on each coordinate axis. Requires neither measurement of line segments where projection of point intersects division nor calculation to quantify projected value. Very flexible device constructed with any kind of scale. Very easy to use, requiring no special equipment of any kind, and saves considerable amount of time if numerous points to be evaluated.

Miller, Irvin M.↗
NASA NTRS1988

Determination of low-level precipitable water variability from split window channel radiance data

A technique has been developed for the quantitative definition of low-level precipitable water vapor from radiance measurements. High resolution data from the airborne Multispectral Atmospheric Mapping Sensor (MAMS) have been used in conjunction with this technique to define variability down to the lower end of the mesoscale. MAMS measures reflected radiation from the earth's surface and clouds in eight visible bands, and thermal emission from the earth's surface, clouds, and atmospheric water vapor in three IR bands. The present technique is found to be applicable to existing satellite sensors, but will not yield the mesoscale resolution furnished by the aircraft data.

Jedlovec, Gary J.↗
NASA NTRS2003

Multi-Decadal Pathfinder Data Sets of Global Land Biophysical Variables from AVHRR and MODIS and their Use in GCM Studies of Biogeophysics and Biogeochemistry

The problem of how the scale, or spatial resolution, of reflectance data impacts retrievals of vegetation leaf area index (LAI) and fraction absorbed photosynthetically active radiation (PAR) has been investigated. We define the goal of scaling as the process by which it is established that LAI and FPAR values derived from coarse resolution sensor data equal the arithmetic average of values derived independently from fine resolution sensor data. The increasing probability of land cover mixtures with decreasing resolution is defined as heterogeneity, which is a key concept in scaling studies. The effect of pixel heterogeneity on spectral reflectances and LAI/FPAR retrievals is investigated with 1 km Advanced Very High Resolution Radiometer (AVHRR) data aggregated to different coarse spatial resolutions. It is shown that LAI retrieval errors at coarse resolution are inversely related to the proportion of the dominant land cover in such pixel. Further, large errors in LAI retrievals are incurred when forests are minority biomes in non-forest pixels compared to when forest biomes are mixed with one another, and vice-versa. A physically based technique for scaling with explicit spatial resolution dependent radiative transfer formulation is developed. The successful application of this theory to scaling LAI retrievals from AVHRR data of different resolutions is demonstrated

Myneni, Ranga↗
NASA NTRS1996

Multiple Use One-Sided Hypotheses Testing in Univariate Linear Calibration

Consider a normally distributed response variable, related to an explanatory variable through the simple linear regression model. Data obtained on the response variable, corresponding to known values of the explanatory variable (i.e., calibration data), are to be used for testing hypotheses concerning unknown values of the explanatory variable. We consider the problem of testing an unlimited sequence of one sided hypotheses concerning the explanatory variable, using the corresponding sequence of values of the response variable and the same set of calibration data. This is the situation of multiple use of the calibration data. The tests derived in this context are characterized by two types of uncertainties: one uncertainty associated with the sequence of values of the response variable, and a second uncertainty associated with the calibration data. We derive tests based on a condition that incorporates both of these uncertainties. The solution has practical applications in the decision limit problem. We illustrate our results using an example dealing with the estimation of blood alcohol concentration based on breath estimates of the alcohol concentration. In the example, the problem is to test if the unknown blood alcohol concentration of an individual exceeds a threshold that is safe for driving.

Krishnamoorthy, K.↗
NASA NTRSDate not supplied

Keywords for All People: How Keyword Governance and Coordination with the NASA ESDIS Standards Coordination Office (ESCO) Improves GCMD Keywords for Discuvery and Use

The Global Change Master Directory (GCMD) Keywords, initiated over twenty years ago, are a hierarchical set of controlled Earth Science vocabularies that help ensure Earth science data, services, and variables are described in a consistent and comprehensive manner and allow for the precise searching of metadata and subsequent retrieval of data, services, and variables. GCMD keywords are periodically analyzed for relevancy and will continue to be refined and expanded in response to user needs. The periodic analysis is a result of successful coordination with the ESDIS Standards Coordination Office (ESCO), which is responsible for standards activities across ESDIS, and assists with providing valuable stakeholder and subject matter expert (SME) feedback on GCMD vocabularies. The ESCO is also turning to the GCMD to discuss how the keyword review process can be improved and more streamlined. In addition to the ESCO, keyword requests and feedback are also received through the GCMD Keyword Forum.

Tyler Stevens↗
NASA NTRS2000

BL-Lacs in X-Ray Outburst

We conducted a multifrequency campaign for the TeV blazar Markarian 421 in 1998 April. The campaign started from a pronounced high-amplitude flare recorded by BeppoSAX and Whipple; the Advanced Satellite for Cosmology and Astrophysics (ASCA) observation started three days later. In the X-ray data, we detected multiple flares, occurring on timescales of about one day. ASCA data clearly reveal spectral variability. The comparison of the data from ASCA, the Extreme Ultraviolet Explorer, and the Rossi X-Ray Timing Explorer indicates that the variability amplitudes in the low-energy synchrotron component are larger at higher photon energies. In TeV and gamma-rays, large intraday variations-which were correlated with the X-ray flux-were observed when results from three Cerenkov telescopes were combined. The rms variability of TeV and gamma-rays was similar to that observed in hard X-rays, above ten keV. The X-ray light curve reveals flares that are almost symmetric for most cases, implying that the dominant timescale is the light crossing time through the emitting region. The structure function analysis based on the continuous X-ray light curve of seven days indicates that the characteristic timescale is approx. 0.5 days. The analysis of ASCA light curves in various energy bands appears to show both soft (positive) and hard (negative) lags. These may not be real, as systematic effects could also produce these lags, which are all much smaller than an orbit. If the lags of both signs are real, these imply that the particle acceleration and X-ray cooling timescales are similar.

Remillard, Ronald A.↗
NASA NTRS2005

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

MCKissick, Burnell T.↗
NASA NTRS2012

Using NASA Remotely Sensed Data to Help Characterize Environmental Risk Factors for National Public Health Applications

This project has dual goals in decision ]making activities .. Providing information to decision makers about associations between environmental exposures and health conditions in a large national cohort study. Enriching the CDC Wide ]ranging Online Data for Epidemiologic Research (WONDER) system by integrating environmental exposure data. .. Develop daily high ]quality spatial data sets of environmental variables for the conterminous U.S. for the years 2003-2008 utilizing NASA data (Objective 1). Fine Particulates (PM2.5) (NASA MODIS and EPA AQS). Land Surface Temperature (NASA MODIS). Solar Insolation and Heat ]related Products (Reanalysis Data). Link these environmental variables with public health data from a national cohort study and examine environmental health relationships (Objective 2). Cognitive Function. Hypertension. Make the environmental datasets available to public health professionals, researchers and the general public via the CDC WONDER system (Objective 3).

Al-Hamdan, Mohammad↗