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NASA NTRS2000

Tropospheric Ozone Pollution from Space: New Views from the TOMS (Total Ozone Mapping Spectrometer) Instrument

New products from the TOMS (Total Ozone Mapping Spectrometer) >satellite instrument can resolve pollution events in tropical and mid-latitudes, Over the past several years, we have developed tropospheric ozone data sets by two methods. The modified-residual technique [Hudson and Thompson, 1998; Thompson and Hudson, 1999] uses v. 7 TOMS total ozone and is applicable to tropical regimes in which the wave-one pattern in total ozone is observed. The TOMSdirect method [Hudson et at., 2000] represents a new algorithm that uses TOMS radiances to extract tropospheric ozone in regions of constant stratospheric ozone and tropospheric ozone displaying high mixing ratios and variability characteristic of pollution, Absorbing aerosols (dust and smoke; Herman et at., 1997 Hsu et al., 1999), a standard TOMS product, provide transport and/or source marker information to interpret tropospheric ozone. For the Nimbus 7/TOMS observing period (1979-1992), modified-residual TTO (tropical tropospheric ozone) appears as two maps/month at I-degree latitude 2-degree longitude resolution at a homepage and digital data are available (20S to 20N) by ftp at http://metosrv2. umd.edu/~tropo/ 14y_data.d. Preliminary modified-residual TTO data from the operational Earth-Probe/TOMS (1996- present) are posted in near-real-time at the same website. Analyses with the new tropospheric ozone and aerosol data are illustrated by the following (I)Signals in tropical tropospheric ozone column and smoke amount during ENSO (El Nino-Southern Oscillation) events, e.g. 1982-1983 and the intense ENSO induced biomass fires of 1997-1998 over the Indonesian region [Thompson et a[, 2000a, Thompson and Hudson, 1999]. (2) Trends in tropospheric ozone and smoke aerosols in various tropical regions (Atlantic, Pacific, Africa, Brazil). No significant trends were found for ozone from1980-1990 [Thompson and Hudson, 19991 although smoke aerosols increased during the period [Hsu et al.,1999]. (3) Temporal and spatial offsets ("paradoxes") in tropical tropospheric ozone and smoke aerosol in regions of greatest tropical biomass burning [Thompson et at., 1996;2000b]. (4) Trans-boundary pollution tracking. With an air parcel (trajectory) model, smoke aerosol and ozone and dust plumes can be tracked across oceans (e.g., Asia to North America; North America to Europe) and national boundaries, e.g. Indonesia to Singapore and Malaysia during the 1997 ENSO fires.

Thompson, Anne M.↗
NASA NTRS2005

Dynamic wake prediction and visualization with uncertainty analysis

A dynamic wake avoidance system utilizes aircraft and atmospheric parameters readily available in flight to model and predict airborne wake vortices in real time. A novel combination of algorithms allows for a relatively simple yet robust wake model to be constructed based on information extracted from a broadcast. The system predicts the location and movement of the wake based on the nominal wake model and correspondingly performs an uncertainty analysis on the wake model to determine a wake hazard zone (no fly zone), which comprises a plurality of wake planes, each moving independently from another. The system selectively adjusts dimensions of each wake plane to minimize spatial and temporal uncertainty, thereby ensuring that the actual wake is within the wake hazard zone. The predicted wake hazard zone is communicated in real time directly to a user via a realistic visual representation. In an example, the wake hazard zone is visualized on a 3-D flight deck display to enable a pilot to visualize or see a neighboring aircraft as well as its wake. The system substantially enhances the pilot's situational awareness and allows for a further safe decrease in spacing, which could alleviate airport and airspace congestion.

Holforty, Wendy L.↗
NASA NTRS2018

Evaluation of a High-Resolution Numerical Weather Prediction Model’s Simulated Clouds Using Observations from CloudSat, GOES-13 and in Situ Aircraft

This study aimed to assess tropical cloud properties predicted by Environment and Climate Change Canada’s Global Environmental Multiscale (GEM)modelwhen run with the Milbrandt–Yau double-moment cloud microphysical scheme and one-way nesting that culminated at a (∼300 km)2 inner domain with 0.25 km horizontal grid spacing. The assessment utilized satellite and in situ data collected during the High Ice Water Content (HIWC) and High Altitude Ice Crystals (HAIC) projects for a mesoscale convective system on 16May 2015 over French Guiana.Data fromCloud- Sat’s cloud-profiling radar and GOES-13’s imager were compared to data either simulated directly by GEM or produced by operating on GEM’s cloud data with both the CFMIP (Cloud Feedback Model Intercomparison Project) Observation Simulator Package (COSP) instrument simulator and a three-dimensional Monte Carlo solar radiative transfer model. In situ observations were made from research aircraft – Canada’s National Research Council Convair-580 and the French SAFIRE Falcon-20 – whose flight paths were aligned with CloudSat’s ground-track. Spatial and temporal shifts of clouds simulated by GEM compared well to GOES-13 imagery. There are, however, differences between simulated and observed amounts of high and low cloud. While GEM did well at predicting ranges of ice-water content (IWC) near 11 km altitude (Falcon-20), it produces too much graupel and snow near 7 km (Convair-580). This produced large differences between CloudSat’s and COSP-generated radar reflectivities and two-way attenuations. On the other hand, CloudSat’s inferred values of IWC agree well with in situ samples at both altitudes. Generally, GEM’s visible reflectances exceeded GOES-13’s on account of having produced too much low-level liquid cloud. It is expected that GEM’s disproportioning of cloud hydrometeors will improve once it includes a better representation of secondary ice production.

Qu, Zhipeng↗
NASA NTRS1999

GPS Altimetry

The advent of satellite altimetry has greatly improved our ability to observe global ocean circulation. However, the swath of a single, nadir-viewing satellite altimeter is only a few km and the track spacing is several hundred km to resolve the two-dimensional structure of ocean eddies. Our goal is to increase spatial and temporal coverage by monitoring Global Positioning System (GPS) signals reflected from the ocean. A constellation of spacecraft would each carry a GPS receiver capable of recording 8 reflections simultaneously. The reflections are well distributed in azimuth and elevation and can be tracked continuously while the satellite is in view, and another is then acquired, as illustrated below. The diagram depicts a new approach at altimetry measurements where ocean surface reflected GPS signals are simultaneously tracked and processed in a GPS flight receiver in space. The reflected GPS signals from the ocean must be compared precisely with the direct GPS signals in order to infer the characteristics of the ocean from the combined data set. Understanding the features and accuracy of GPS altimetry measurement is crucial to establishing its suitability for oceanography. Preliminary work has enabled us to theoretically model the signal output of the correlator for a variety of system parameters such as wind speed (sea roughness), receiver height, incidence angle, receiver range and Doppler filter bandwidth and antenna gain. Expected signal-to-noise ratio has been estimated from which we have inferred, to a first approximation, the basic receiver gain requirements for a space-based altimeter and the expected range raw error. In 1998, work on a different task led to the extraction of the first reflected GPS signal observed from a spaceborne receiver during the 1995 Space Transportation System-68 (STS-68) Shuttle Radar Laboratory-2 (SRL-2) high resolution synthetic aperture radar mission. Good comparisons with our signal models have been obtained. Having established that only modest signal-to-noise ratios are obtainable unless very high gain antennas are used, we expect that single measurements might not provide an estimate of sea state parameters as accurate as that obtainable with traditional remote sensing instruments, if costs are limited. Therefore spatial and temporal averaging of many measurements is required. Since the receiving satellite tracks do not repeat, measurements in a given area will be used to refine the local solution as a function of time, and will define the spatial resolution. In order to make this instrument viable in space, we need to detect and process many scattered signals. In 1998 we made a first step at understanding what configurations of antenna gain and orientations capture the largest number of viable signals to be used in the subsequent spatial/temporal averaging process. Additional information is contained in the original.

Lichten, Stephen M.↗
NASA NTRS2022

Multisensor Machine Learning to Retrieve High Spatiotemporal Resolution Land Surface Temperature

Climate change is making heat waves more frequent, long-lasting, and severe. While multiple satellite types provide data to monitor surface temperature, geostationary (GEO) sensors provide near-continuous, continental-scale observations which can better capture the diurnal variability of land surface temperature (LST) than intermittent observations from low-earth orbit (LEO) sensors. However, standard products from GEO satellites are available at coarsened spatial and temporal resolutions compared to the native sensor resolution. Using datasets from the NASA Earth Exchange, we leveraged co-located, co-temporal observations from LEO and GEO satellites to learn a data-driven mapping using a convolutional neural network. The resulting NASA Earth eXchange Artificial Intelligence LST (NEXAI-LST) achieved a mean absolute error of 1.73 K relative to the target LEO product and improves on both spatial and temporal resolution [2 km, 10 minute] compared to the GEO full disk standard product [10 km, hourly]. In validation against measurements from a ground-based sensor network, NEXAI-LST achieves similar or better fit than both LEO and GEO standard products, while depending none of the prior knowledge of land surface and atmospheric states required by physical-statistical models. Further, application of the model to unseen LEO and GEO satellites demonstrates robust generalization of the model across spatial region, time of day, and sensor. In support of NASA’s open-source science initiative, we make our NEXAI-LST product, model, and codes available to facilitate data exploration and further studies.

Kate Marie Duffy↗
NASA NTRS2010

Modeling Fire Severity in Black Spruce Stands in the Alaskan Boreal Forest Using Spectral and Non-Spectral Geospatial Data

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.

Barrett, K.↗
NASA NTRS2003

A New Objective Technique for Verifying Mesoscale Numerical Weather Prediction Models

This report presents a new objective technique to verify predictions of the sea-breeze phenomenon over east-central Florida by the Regional Atmospheric Modeling System (RAMS) mesoscale numerical weather prediction (NWP) model. The Contour Error Map (CEM) technique identifies sea-breeze transition times in objectively-analyzed grids of observed and forecast wind, verifies the forecast sea-breeze transition times against the observed times, and computes the mean post-sea breeze wind direction and speed to compare the observed and forecast winds behind the sea-breeze front. The CEM technique is superior to traditional objective verification techniques and previously-used subjective verification methodologies because: It is automated, requiring little manual intervention, It accounts for both spatial and temporal scales and variations, It accurately identifies and verifies the sea-breeze transition times, and It provides verification contour maps and simple statistical parameters for easy interpretation. The CEM uses a parallel lowpass boxcar filter and a high-order bandpass filter to identify the sea-breeze transition times in the observed and model grid points. Once the transition times are identified, CEM fits a Gaussian histogram function to the actual histogram of transition time differences between the model and observations. The fitted parameters of the Gaussian function subsequently explain the timing bias and variance of the timing differences across the valid comparison domain. Once the transition times are all identified at each grid point, the CEM computes the mean wind direction and speed during the remainder of the day for all times and grid points after the sea-breeze transition time. The CEM technique performed quite well when compared to independent meteorological assessments of the sea-breeze transition times and results from a previously published subjective evaluation. The algorithm correctly identified a forecast or observed sea-breeze occurrence or absence 93% of the time during the two- month evaluation period from July and August 2000. Nearly all failures in CEM were the result of complex precipitation features (observed or forecast) that contaminated the wind field, resulting in a false identification of a sea-breeze transition. A qualitative comparison between the CEM timing errors and the subjectively determined observed and forecast transition times indicate that the algorithm performed very well overall. Most discrepancies between the CEM results and the subjective analysis were again caused by observed or forecast areas of precipitation that led to complex wind patterns. The CEM also failed on a day when the observed sea- breeze transition affected only a very small portion of the verification domain. Based on the results of CEM, the RAMS tended to predict the onset and movement of the sea-breeze transition too early and/or quickly. The domain-wide timing biases provided by CEM indicated an early bias on 30 out of 37 days when both an observed and forecast sea breeze occurred over the same portions of the analysis domain. These results are consistent with previous subjective verifications of the RAMS sea breeze predictions. A comparison of the mean post-sea breeze winds indicate that RAMS has a positive wind-speed bias for .all days, which is also consistent with the early bias in the sea-breeze transition time since the higher wind speeds resulted in a faster inland penetration of the sea breeze compared to reality.

Case, Jonathan L.↗
NASA NTRS2004

Towards a High Temporal Frequency Grass Canopy Thermal IR Model for Background Signatures

In this paper, we present our first results towards understanding high temporal frequency thermal infrared response from a dense plant canopy and compare the application of our model, driven both by slowly varying, time-averaged meteorological conditions and by high frequency measurements of local and within canopy profiles of relative humidity and wind speed, to high frequency thermal infrared observations. Previously, we have employed three-dimensional ray tracing to compute the intercepted and scattered radiation fluxes and for final scene rendering. For the turbulent fluxes, we employed simple resistance models for latent and sensible heat with one-dimensional profiles of relative humidity and wind speed. Our modeling approach has proven successful in capturing the directional and diurnal variation in background thermal infrared signatures. We hypothesize that at these scales, where the model is typically driven by time-averaged, local meteorological conditions, the primary source of thermal variance arises from the spatial distribution of sunlit and shaded foliage elements within the canopy and the associated radiative interactions. In recent experiments, we have begun to focus on the high temporal frequency response of plant canopies in the thermal infrared at 1 second to 5 minute intervals. At these scales, we hypothesize turbulent mixing plays a more dominant role. Our results indicate that in the high frequency domain, the vertical profile of temperature change is tightly coupled to the within canopy wind speed In the results reported here, the canopy cools from the top down with increased wind velocities and heats from the bottom up at low wind velocities. .

Ballard, Jerrell R., Jr.↗
NASA NTRS2001

Observations of Ocean Primary Productivity Using MODIS

Measuring the magnitude and variability of oceanic net primary productivity (NPP) represents a key advancement toward our understanding of the dynamics of marine ecosystems and the role of the ocean in the global carbon cycle. MODIS observations make two new contributions in addition to continuing the bio-optical time series begun with Orbview-2's SeaWiFS sensor. First, MODIS provides weekly estimates of global ocean net primary productivity on weekly and annual time periods, and annual empirical estimates of carbon export production. Second, MODIS provides additional insight into the spatial and temporal variations in photosynthetic efficiency through the direct measurements of solar-stimulated chlorophyll fluorescence. The two different weekly productivity indexes (first developed by Behrenfeld & Falkowski and by Yoder, Ryan and Howard) are used to derive daily productivity as a function of chlorophyll biomass, incident daily surface irradiance, temperature, euphotic depth, and mixed layer depth. Comparisons between these two estimates using both SeaWiFS and MODIS data show significant model differences in spatial distribution after allowance for the different integration depths. Both estimates are strongly dependence on the accuracy of the chlorophyll determination. In addition, an empirical approach is taken on annual scales to estimate global NPP and export production. Estimates of solar stimulated fluorescence efficiency from chlorophyll have been shown to be inversely related to photosynthetic efficiency by Abbott and co-workers. MODIS provides the first global estimates of oceanic chlorophyll fluorescence, providing an important proof of concept. MODIS observations are revealing spatial patterns of fluorescence efficiency which show expected variations with phytoplankton photo-physiological parameters as measured during in-situ surveys. This has opened the way for research into utilizing this information to improve our understanding of oceanic NPP variability. Deriving the ocean bio-optical properties places severe demands on instrument performance (especially band to band precision) and atmospheric correction. Improvements in MODIS instrument characterization and calibration over the first 16 mission months have greatly improved the accuracy of the chlorophyll input fields and FLH, and therefore the estimates of NPP and fluorescence efficiency. Annual estimates now show the oceanic NPP accounts for 40-50% of the global total NPP, with significant interannual variations related to large scale ocean processes. Spatial variations in ocean NPP, and exported production, have significant effects on exchange of CO2 between the ocean and atmosphere. Further work is underway to improve both the primary productivity model functions, and to refine our understanding of the relationships between fluorescence efficiency and NPP estimates. We expect that the MODIS instruments will prove extremely useful in assessing the time dependencies of oceanic carbon uptake and effects of iron enrichment, within the global carbon cycle.

Esaias, Wayne E.↗
NASA NTRS2019

How Well Does NASA GEOS Model Perform in Simulating Dust Deposition into the Tropical Atlantic Ocean?

Massive dust emitted from North Africa can transport long distances across the tropical Atlantic Ocean, reaching the Americas. Dust deposition along the transit adds microorganisms and essential nutrients to marine ecosystem, which has important implications for biogeochemical cycle and climate. However, assessing the dust-ecosystemclimate interactions has been hindered in part by the paucity of dust deposition measurements and large uncertainties associated with oversimplified representations of dust processes in current models. We have recently produced a unique dataset of seasonal dust deposition flux and dust loss frequency into the tropical Atlantic Ocean at a nominal resolution of 200 km x 500 km by using the decade-long (2007-2016) record of aerosol three-dimensional distribution from four satellite sensors, namely CALIOP, MODIS, MISR, and IASI. On the basis of the ten-year average, the yearly dust deposition into the tropical Atlantic Ocean is estimated at 98-153 Tg. The dust deposition shows large spatial and temporal (on seasonal and interannual scale) variability. The satellite observations also yield an estimate of annual mean dust loss frequency of 0.052 ~ 0.078 d-1, a useful diagnostic that makes it possible to disentangle the dust transport and removal processes from the dust emissions when identifying the major factors contributing to the uncertainties and biases in the model simulated dust deposition. In this study, we use the dataset along with in situ and remote sensing observations to assess how well NASA GEOS model performs in simulating trans-Atlantic dust transport and deposition. We found that the GEOS modeling of dust deposition falls within the range of satellite-based estimates. However, this reasonable agreement in dust deposition is a compensation of the model's underestimate of dust emissions and overestimate of dust removal efficiency. Further, the overestimate of dust removal efficiency results largely from the model's overestimate of rainfall rate. Our results provide insights into the model's deficiencies at process level, which could better guide model improvements.

Yu, Hongbin↗
NASA NTRS1972

Applications of remote sensing to stream discharge predictions

A feasibility study has been initiated on the use of remote earth observations for augmenting stream discharge prediction for the design and/or operation of major reservoir systems, pumping systems and irrigation systems. The near-term objectives are the interpolation of sparsely instrumented precipitation surveillance networks and the direct measurement of water loss by evaporation. The first steps of the study covered a survey of existing reservoir systems, stream discharge prediction methods, gage networks and the development of a self-adaptive variation of the Kentucky Watershed model, SNOPSET, that includes snowmelt. As a result of these studies, a special three channel scanner is being built for a small aircraft, which should provide snow, temperature and water vapor maps for the spatial and temporal interpolation of stream gages.

Krause, F. R.↗
NASA NTRS1989

Interannual variability in phytoplankton pigment distribution during the spring transition along the west coast of North America

A 5-year time series of coastal zone color scanner imagery (1980-1983, 1986) is used to examine changes in the large-scale pattern of chlorophyll pigment concentration coincident with the spring transition in winds and currents along the west coast of North America. The data show strong interannual variability in the timing and spatial patterns of pigment concentration at the time of the transition event. Interannual variability in the response of pigment concentration to the spring transition appears to be a function of spatial and temporal variability in vertical nutrient flux induced by wind mixing and/or the upwelling initiated at the time of the transition. Interannual differences in the mixing regime are illustrated with a one-dimensional mixing model.

Thomas, A. C.↗
NASA NTRS1991

Network for the detection of stratospheric change (NDSC)

The notion of a ground-based long-term measuring network specifically designed to provide the earliest possible detection of changes in the composition and structure of the stratosphere and to understand the causes of those changes is examined. The network's short-term goals are: to study the temporal and spatial variability of atmospheric composition and structure; to provide the basis for ground truth and complementary measurements for satellite systems such as the NASA Upper Atmosphere Research Satellite; and to critically test multidimensional stratospheric models and provide the broad data base required for improved model development. Priorities, instrumentation, station considerations, and site requirements are also discussed.

Kurylo, Michael J.↗
NASA NTRS1999

Planar Strain-Rate-Free Diffusion Flames: Initiation, Properties, and Extinction

An effectively strain-rate-free diffusion flame constitutes the most vigorous laminar combustion of initially unmixed reactive gases. Such a diffusion flame is characterized by a relatively long residence time and by a relatively large characteristic length scale. If such a flame were also planar, providing high symmetry, it would be particularly suitable for experimental and theoretical investigations of key combustion phenomena, such as multicomponent diffusion, chemical kinetics, and soot inception, growth, and oxidation. Unfortunately, a planar strain-rate-free diffusion flame is highly disrupted in earth-gravity (e.g., in a counterflow-diffusion-flame apparatus) because of the very rapid onset (approx. 100 ms) of gravity-induced instability. Accordingly, a specially dedicated apparatus was designed, fabricated, and initially checked out for the examination of a planar strain-rate-free diffusion flame in microgravity. Such a diffusion flame may be formed within a hollowed-out squat container (initially configured as 25 cm x 25 cm x 9 cm), with isothermal, noncatalytic, impervious walls. At test initiation, a thin metallic sheet (approx. 1 mm in thickness) that separates the internal volume into two equal portions, each of dimensions 25 cm x 25 cm x 4.5 cm, is withdrawn, by uniform translation (approx. 50 cm/s) in its own plane, through a tightly fitting slit in one side wall. Thereupon, diluted fuel vapor (initially confined to one half-volume of the container) gains access to diluted oxygen (initially with the same pressure, density, and temperature as the fuel, but initially confined to the other half-volume). After a brief delay (approx. 10 ms), to permit limited but sufficient-for-flammability diffusional interpenetration of fuel vapor and oxidizer, burning is initiated by discharge of a line igniter, located along that side wall from which the trailing edge of the separator withdraws. The ignition spawns a triple-flame propagation across the 25 cm x 25 cm centerplane. When a diffusion flame is emplaced in the centerplane, any subsequent travel, and change in temperature, of that planar diffusion flame may be tracked, along with the effectively spatially uniform but temporally evolving pressure within the container. Eventually, nearly complete depletion of the stoichiometrically deficient reactant, along with heat loss to the container surfaces, effects extinction. These data afford an opportunity to check theoretical models of diffusion and chemical kinetics under conditions ranging from intense burning to flame out, or, alternatively, to evolve simple empirical representations of these phenomena. Thus, the project sought to utilize microgravity testing to elucidate commonly encountered phenomenology, arising in the commonly-encountered mode of combustion (whether related to heating, manufacturing, boiling, and propulsion, or to uncontrolled, free-burning fire in structures and wildland vegetation), of those commonly utilized fuels usually categorized as gaseous fuels (such as hydrogen, natural gas, and propane, which are gaseous under atmospheric conditions).

Fendell, Francis↗
NASA NTRS2003

Spectral Retrieval of Latent Heating Profiles from TRMM PR Data: Comparison of Look-Up Tables

The primary goal of the Tropical Rainfall Measuring Mission (TRMM) is to use the information about distributions of precipitation to determine the four dimensional (i.e., temporal and spatial) patterns of latent heating over the whole tropical region. The Spectral Latent Heating (SLH) algorithm has been developed to estimate latent heating profiles for the TRMM Precipitation Radar (PR) with a cloud- resolving model (CRM). The method uses CRM- generated heating profile look-up tables for the three rain types; convective, shallow stratiform, and anvil rain (deep stratiform with a melting level). For convective and shallow stratiform regions, the look-up table refers to the precipitation top height (PTH). For anvil region, on the other hand, the look- up table refers to the precipitation rate at the melting level instead of PTH. For global applications, it is necessary to examine the universality of the look-up table. In this paper, we compare the look-up tables produced from the numerical simulations of cloud ensembles forced with the Tropical Ocean Global Atmosphere (TOGA) Coupled Atmosphere-Ocean Response Experiment (COARE) data and the GARP Atlantic Tropical Experiment (GATE) data. There are some notable differences between the TOGA-COARE table and the GATE table, especially for the convective heating. First, there is larger number of deepest convective profiles in the TOGA-COARE table than in the GATE table, mainly due to the differences in SST. Second, shallow convective heating is stronger in the TOGA COARE table than in the GATE table. This might be attributable to the difference in the strength of the low-level inversions. Third, altitudes of convective heating maxima are larger in the TOGA COARE table than in the GATE table. Levels of convective heating maxima are located just below the melting level, because warm-rain processes are prevalent in tropical oceanic convective systems. Differences in levels of convective heating maxima probably reflect differences in melting layer heights. We are now extending our study to simulations of other field experiments (e.g. SCSMEX and ARM) in order to examine the universality of the look-up table. The impact of look-up tables on the retrieved latent heating profiles will also be assessed.

Shige, Shoichi↗
NASA NTRS2004

Numerical Study of Flow Past a Circular Cylinder Using RANS, Hybrid RANS/LES and PANS Formulations

Two multiscale type turbulence models are implemented in the PAB3D solver. The models are based on modifying the Reynolds Averaged Navier-Stokes (RANS) equations. The first scheme is a hybrid RANS/LES model utilizing the two-equation (k(sub epsilon)) model with a RANS/LES transition function dependent on grid spacing and the computed turbulence length scale. The second scheme is a modified version of the partially averaged Navier-Stokes (PANS) model, where the unresolved kinetic energy parameter (f(sub k)) is allowed to vary as a function of grid spacing and the turbulence length scale. Solutions from these models are compared to RANS results and experimental data for a stationary and rotating cylinder. The parameter f(sub k) varies between zero and one and has the characteristic to be equal to one in the viscous sub layer, and when the RANS turbulent viscosity becomes smaller than the LES viscosity. The formulation, usage methodology, and validation example are presented to demonstrate the enhancement of PAB3D's time-accurate and turbulence modeling capabilities. The models are compared to RANS results and experimental data for turbulent separated flows (TS) and laminar separated flows (LS) around stationary and rotating cylinders. For a stationary cylinder, the TS case is accurately simulated using the general two-equation k(sub epsilon) turbulence model (eddy-viscosity model). PAB3D accurately predicts the drag coefficient (CD), lift coefficient (CL) and the Strouhal number (St). The LS case was a challenge for the RANS computation with an eddy-viscosity turbulence model. The RANS/LES and PANS performed well and showed marked improvements over the RANS solution. The modified PANS model was the most accurate. For the rotating cylinder, the spin ratio varied from zero to one, and the PANS results were in good agreement with published experimental data. RANS/LES and PANS capture both temporal and spatial fluctuations and produce large-scale structures that do not occur in the RANS simulation. The current results show promise for the capability of PANS in simulating unsteady and complex flow phenomena.

Elmiligui, Alaa A.↗
NASA NTRSDate not supplied

International Satellite Cloud Climatology Project

The International Satellite Cloud Climatology Project (ISCCP) was established as the first project of the World Climate Research Programme (WCP-2) to collect and analyze satellite radiance measurements to infer the global distribution of cloud radiative properties and their diurnal and seasonal variations. The operational phase of ISCCP began in July 1983 and is currently planned to continue through June 2010. [Mission Objectives] To produce a global, reduced resolution, infrared and visible, calibrated and normalized radiance data set containing basic information on the radiative properties of the atmosphere from which cloud parameters can be derived. To stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models. To promote research using ISCCP data and contributing to improved understanding of the Earth's radiation budget (top of the atmosphere and surface) and hydrological cycle. [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

Rossow, William B.↗
NASA NTRS2017

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When coupled with large scale, distributed hardware and software, STARE-based data access reduces pre-analysis data preparation costs by offering a convenient means to align different datasets spatiotemporally without specialized effort in parallel computing or distributed data management.

Kuo, Kwo-Sen↗