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NASA NTRS2015

A New Lunar Digital Elevation Model from the Lunar Orbiter Laser Altimeter and SELENE Terrain Camera

We present an improved lunar digital elevation model (DEM) covering latitudes within +/-60 deg, at a horizontal resolution of 512 pixels per degree ( approx.60 m at the equator) and a typical vertical accuracy approx.3 to 4 m. This DEM is constructed from approx.4.5 ×10(exp 9) geodetically-accurate topographic heights from the Lunar Orbiter Laser Altimeter (LOLA) onboard the Lunar Reconnaissance Orbiter, to which we co-registered 43,200 stereo-derived DEMs (each 1 deg×1 deg) from the SELENE Terrain Camera (TC) ( approx.10(exp 10) pixels total). After co-registration, approximately 90% of the TC DEMs show root-mean-square vertical residuals with the LOLA data of < 5 m compared to approx.50% prior to co-registration. We use the co-registered TC data to estimate and correct orbital and pointing geolocation errors from the LOLA altimetric profiles (typically amounting to < 10 m horizontally and < 1 m vertically). By combining both co-registered datasets, we obtain a near-global DEM with high geodetic accuracy, and without the need for surface interpolation. We evaluate the resulting LOLA + TC merged DEM (designated as "SLDEM2015") with particular attention to quantifying seams and crossover errors.

Barker, M. K.↗

NASA NTRS1976

A comparison between Nimbus 5 THIR and ITPR temperatures and derived winds with rawinsonde data obtained in the AVE 2 experiment

During the period of May 11 and 12, 1974, NASA conducted its second Atmospheric Variability Experiment (AVE II) over the eastern United States. In this time interval, two Nimbus 5 orbits crossed the AVE II area, providing a series of ITPR soundings as well as THIR data. Horizontal temperature mapping of the AVE II cloud field is examined using two grid print map scales. Implied cloud top heights are compared with maximum radar-echo top reports. In addition, shelter temperatures in areas of clear sky are compared with the surface temperatures as determined from 11.5 micrometer radiometer data of the THIR experiment. The ITPR sounding accuracy is evaluated using interpolated radiosonde temperatures at times nearly coincident with the ITPR soundings. It was found that mean differences between the two data sets were as small as 1.3 C near 500 mb and as large as 2.9 C near the tropopause. The differences between ITPR and radiosonde temperatures at constant pressure levels were sufficient to induce significant differences in the horizontal temperature gradient. Cross sections of geostrophic wind along the orbital tracks were developed using a thermal wind buildup based on the ITPR temperature data and the radiosonde temperature data. Differences between the radiosonde and ITPR geostrophic winds could be explained on the basis of differences in the ITPR and radiosonde temperature gradients.

Arnold, J. E.↗

NASA NTRS1984

Interpolation problems in meteor radar analysis, part 7.6A

Meteor echoes come from random points in the observation volume, and are irregularly spaced in time. This precludes the use of fast fourier transformations (FFT) techniques on the raw data to give the spectrum of waves that are present. One way around this obstacle is to restrict our interest to a particular class of waves, and fit a corresponding model to the raw data. It is assumed that there is no horizontal variation across the observation volume for tides, but in the vertical this is certainly not the case. If, in addition, we are interested in other types of waves which may be present and whose periods are unknown, then examining the raw line-of-sight velocities does not tell us how to modify the model, since the line-of-sight direction is not fixed. This is the motivation for interpolation. Interpolation takes a temporal series of line-of-sight velocities, and transforms it to a temporal series of wind velocities for each orthogonal direction. The velocities along a given direction can then be examined readily for any waves in addition to tides.

Tetenbaum, D.↗

NASA NTRS1984

Accuracy of diagnostic heat and moisture budgets using SESAME-79 field data as revealed by observing system simulation experiments

Observing system simulation experiments are used to investigate the accuracy of diagnostic heat and moisture budgets which employ the AVE-SESAME 1979 data. The time-including, four-dimensional data set of a mesoscale model is used to simulate rawinsonde observations from AVE-SESAME 1979. The 5 C/day (heat budget) and 2 g/kg per day (moisture budget) magnitudes of error obtained indicate difficulties in the diagnosis of the heating rate in weak convective systems. The influences exerted by observational frequency, objective analysis, observational density, vertical interpolation, and observational errors on the budget are also studied, and it is found that the temporal and spatial resolution of the SESAME regional network is marginal for diagnosing convective effects on a horizontal time scale of 550 x 550 km.

Kuo, Y.-H.↗

DOE OSTI2020

Benzene homologues contaminants in a former herbicide factory site: distribution, attenuation, risk, and remediation implication

Benzene homologues often used as organic raw materials or as detergents in chemical industry are prone to accidental release into the environment which can cause serious long-term soil pollutions. In a large former herbicide factory site, we investigated 43 locations for benzene homologues contaminations in soil, soil gas, and groundwater; and studied the hydrogeological conditions. An inverse distance weighted interpolation method was employed to determine the pollutants three-dimensional spatial distribution in the soils. Results showed that benzene homologues residues were mainly originated from the herbicide production workshop; and that the pollution had horizontally expanded at the deeper soil layer. Contaminants had already migrated 15m downward from ground surface. Contaminant phase distribution study showed that NAPL was the primary phase (>99%) for the pollutants accumulated in the unsaturated zone; while it had not migrated to groundwater. The primary mechanism for contaminant transport and attenuation included dissolution of “occluded” NAPL into pore water and pollutant volatilization into soil pore space. Risk assessment revealed that the pollutants brought unacceptable high carcinogenic and non-carcinogenic risks to public health. In order to convert this former chemical processing factory site into a residential area, a remediation to the polluted production workshop sites is urgently required.

Yang, Shuo↗

NASA NTRS1991

Assimilation of global cloud imagery from multiple satellites

Synoptic images of the global cloud field are created from measurements of IR radiation taken aboard four geostationary and two polar-orbiting platforms simultaneously observing the earth's cloud field. A series of spatial and temporal interpolations, together with data reliability criteria, are used to map synoptic measurements from the geostationary satellites and asynoptic measurements from the polar-orbiting satellites. The synoptic global cloud imagery (GCI) that results has a horizontal resolution of 0.7 deg in longitude by 0.35 deg in latitude and a temporal resolution of 3 h, providing an unprecedented view of the global cloud pattern. Each composite image represents a nearly instantaneous snapshot of the entire earth's cloud field. Collectively, the composite imagery resolve, on a global basis, most of the variability inherent to organized convection, including several harmonics of the diurnal cycle. Because of its homogeneous properties, the GCI lends itself easily to a variety of space-time analyses useful for studying global cloud behavior.

Tanaka, Ken↗

NASA NTRS1999

Frequency and Angular Variations of Land Surface Microwave Emissivities: Can we Estimate SSM/T and AMSU Emissivities from SSM/I Emissivities?

To retrieve temperature and humidity profiles from SSM/T and AMSU, it is important to quantify the contribution of the Earth surface emission. So far, no global estimates of the land surface emissivities are available at SSM/T and AMSU frequencies and scanning conditions. The land surface emissivities have been previously calculated for the globe from the SSM/I conical scanner between 19 and 85 GHz. To analyze the feasibility of deriving SSM/T and AMSU land surface emissivities from SSM/I emissivities, the spectral and angular variations of the emissivities are studied, with the help of ground-based measurements, models and satellite estimates. Up to 100 GHz, for snow and ice free areas, the SSM/T and AMSU emissivities can be derived with useful accuracy from the SSM/I emissivities- The emissivities can be linearly interpolated in frequency. Based on ground-based emissivity measurements of various surface types, a simple model is proposed to estimate SSM/T and AMSU emissivities for all zenith angles knowing only the emissivities for the vertical and horizontal polarizations at 53 deg zenith angle. The method is tested on the SSM/T-2 91.655 GHz channels. The mean difference between the SSM/T-2 and SSM/I-derived emissivities is less than or equal to 0.01 for all zenith angles with an r.m.s. difference of approx. = 0.02. Above 100 GHz, preliminary results are presented at 150 GHz, based on SSM/T-2 observations and are compared with the very few estimations available in the literature.

Prigent, Catherine↗

NASA NTRS2019

Earth Global Reference Atmospheric Model (GRAM) Overview and Comparison to Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)

Earth-GRAM (Earth-Global Reference Atmospheric Model) Overview: Provides monthly statistics at any point in the atmosphere; Monthly, geographic, altitude variation; Current Version - Earth-GRAM 2016, C++; Output Includes - pressure, density, temperature, horizontal and vertical winds, speed of sound, atmospheric constituents; Used by engineering community to create atmospheric dispersions at a rapid runtime; Not a forecast model. MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2) Background: Developed by NASA Goddard Modelling and Assimilation Office; Horizontal Resolution: 0.625 degrees by 0.5 degrees longitude-by-latitude grid (NCEP (National Centers for Environmental Prediction) reanalysis I vs. 2.5 degrees by 2.5 degrees currently used in Earth-GRAM); Vertical resolution: 72 model layers or interpolated to 42 pressure levels to 0.1 hectopascals (hPa) (NCEP reanalysis I, surface to 10hPa at 17 pressure levels).

White, Patrick W.↗

NASA NTRS2015

High-Resolution Mesoscale Model Setup for the Eastern Range and Wallops Flight Facility

Mesoscale weather conditions can have an adverse effect on space launch, landing, ground processing, and weather advisories, watches, and warnings at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally-driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. These convective processes often last 60 minutes or less and pose a significant challenge to the local forecasters. Surface winds during the transition seasons (spring and fall) pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned local data assimilation (DA) and forecast model at a high resolution is needed to provide improved capability. To accomplish this, a number of sensitivity tests were performed using the Weather Research and Forecasting (WRF) model in order to determine the best DA/model configuration for operational use at each of the space launch ranges to best predict winds, precipitation, and temperature. A set of Perl scripts to run the Gridpoint Statistical Interpolation (GSI)/WRF in real-time were provided by NASA's Short-term Prediction Research and Transition Center (SPoRT). The GSI can analyze many types of observational data including satellite, radar, and conventional data. The GSI/WRF scripts use a cycled GSI system similar to the operational North American Mesoscale (NAM) model. The scripts run a 12-hour pre-cycle in which data are assimilated from 12 hours prior up to the model initialization time. A number of different model configurations were tested for both the ER and WFF by varying the horizontal resolution on which the data assimilation was done. Three different grid configurations were run for the ER and two configurations were run for WFF for archive cases from 27 Aug 2013 through 10 Nov 2013. To quantify model performance, standard model output will be compared to the Meteorological Assimilation Data Ingest System (MADIS) data. The MADIS observation data will be compared to the WRF forecasts using the Model Evaluation Tools (MET) verification package. In addition, the National Centers for Environmental Prediction's Stage IV precipitation data will be used to validate the WRF precipitation forecasts. The author will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for each space launch range.

Watson, Leela R.↗

DOE OSTI2023

Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications

To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided. This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes. GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions. **To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Tabulated Database of Closed-Loop Geothermal Systems Performance for Cloud-Based Technical and Economic Modeling of Heat Production and Electricity Generation: Preprint

To better understand the heat production, electricity generation performance and economic viability of closed loop geothermal systems in hot-dry-rock, the Closed Loop Geothermal Group, a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and super-critical CO2) while varying seven continuous independent parameters of interest (i.e., mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an Organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the TEA (techno-economic analysis) script are provided.

co-axial↗

NASA NTRS1984

Assessment of Thematic Mapper Band-to-band Registration by the Block Correlation Method

The design of the Thematic Mapper (TM) multispectral radiometer makes it susceptible to band-to-band misregistration. To estimate band-to-band misregistration a block correlation method is employed. This method is chosen over other possible techniques (band differencing and flickering) because quantitative results are produced. The method correlates rectangular blocks of pixels from one band against blocks centered on identical pixels from a second band. The block pairs are shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient for each shift position is computed. The displacement corresponding to the maximum correlation is taken as the best estimate of registration error for each block pair. Subpixel shifts are estimated by a bi-quadratic interpolation of the correlation values surrounding the maximum correlation. To obtain statistical summaries for each band combination post processing of the block correlation results performed. The method results in estimates of registration error that are consistent with expectations.

Card, D. H.↗

NASA NTRS2014

Assimilation of Dual-Polarimetric Radar Observations with WRF GSI

Dual-polarimetric (dual-pol) radar typically transmits both horizontally and vertically polarized radio wave pulses. From the two different reflected power returns, more accurate estimate of liquid and solid cloud and precipitation can be provided. The upgrade of the traditional NWS WSR-88D radar to include dual-pol capabilities will soon be completed for the entire NEXRAD network. Therefore, the use of dual-pol radar network will have a broad impact in both research and operational communities. The assimilation of dual-pol radar data is especially challenging as few guidelines have been provided by previous research. It is our goal to examine how to best use dual-pol radar data to improve forecast of severe storm and forecast initialization. In recent years, the Development Testbed Center (DTC) has released the community Gridpoint Statistical Interpolation (GSI) DA system for the Weather Research and Forecasting (WRF) model. The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this study explores regional assimilation of the dual-pol radar variables from the WSR-88D radars for real case storms. Our presentation will highlight our recent effort on incorporating the horizontal reflectivity (ZH), differential reflectivity (ZDR), specific differential phase (KDP), and radial velocity (VR) data for initializing convective storms, with a significant focus being on an improved representation of hydrometeor fields. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to dual-pol variables. Beyond the dual-pol variable assimilation procedure developing within a GSI framework, highresolution (≤1 km) WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. Further details of the methodology of data assimilation, the impact of different dual-pol variables, the influence on precipitation forecast will be presented at the conference.

Li, Xuanli↗

NASA NTRS2014

Assimilation of Dual-Polarimetric Radar Observations with WRF GSI

Li, Xuanli↗

NASA NTRS2012

Projections of Declining Surface-Water Availability for the Southwestern United States

16 of the CMIP5 models had all the data needed for this work for at least one simulation that was continuous from 1950 to 2040. Details of the models analyzed here are provided in Table S1. The model data analyzed here are available at http://strega.ldeo.columbia.edu:81/expert/home/.naomi/.AR5/.v2/.historical:rcp85/.mmm16/ a. Assessing the climatology of the models Despite increases in horizontal resolution of many models compared to their CMIP3 counterparts none of these models can adequately resolve the topography of the south west United States, such as the Sierra Nevada and Rocky Mountains and the associated orographic precipitation. This requires that caution be used when interpreting the results presented here. To assess the ability of the models to simulate the current hydroclimate, in Figure S1 we show the observed (from the Global Precipitation Climatology Centre gridded rain gauge data, (1)) monthly climatology of precipitation and the same for all the models and the multimodel mean for the California-Nevada, Colorado headwaters and Texas regions. The GPCC data uses rain gauges only and interpolates to regular grids of which we used the 1◦ by 1◦ one. Details of the data set can be found in (2). While the models apparently overestimate precipitation in California and Nevada the seasonal cycle with wet winters and dry summers is very well represented. It is also possible that the rain gauge observations are biased low by inadequately sampling the higher mountain regions. How ever the models might also be expected to underestimate orographic precipitation due to inadequate horizontal resolution. The 25 models are also too wet in the Colorado headwaters region but correctly represent the quite even distribution though the year. The bimodal distribution of precipitation in Texas, with peaks in May and September, and the absolute amounts, are well modeled but with the September peak too weak. The positive precipitation bias translates into a positive runoff bias for the Colorado headwaters as also shown in Figure S1. Here the observed runoff values are taken from simulations of the Variable Infiltration Capacity (VIC) land surface-hydrology model (3) forced by observed meteorology (5) that were conducted as part of the North American Land Data Assimilation System project phase 2 ( (NLDAS-2), http://www.emc.ncep.noaa.gov/mmb/nldas/. Runoff for California-Nevada is better simulated but there is a positive bias over Texas despite no strong precipitation bias. To check whether regional climate models better simulate P and runoff in these regions we analyzed the historical simulation with the Regional Climate Model version 3 driven by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 available from the North American Regional Climate Change Assessment Program (http://www.narccap.ucar.edu). This model configuration retained these biases in P and runoff although they were reduced in amplitude. Given these varying biases we plot P and P − E changes in actual values but apply the simplest bias correction possible to the runoff and soil moisture values and show the modeled changes in terms of percentages of the 20th Century model climatologies. A thorough assessment of the simulation of North American climate in CMIP5 models is conducted in Sheffield at al. (North American Climate in CMIP5 Experiments. Part I: Evaluation of 20th Century Continental and Regional Climatology, manuscript submit ted to J. Climate, available at http://www.climate.noaa.gov/index.jsp?pg=./cpo pa/ mapp/cmip5 publications.html). Sheffield et al. analyze the climatology of precipitation, surface air temperature, low level winds, moisture fluxes, runoff etc. and conclude that the main features of the hydrological cycle, including characteristics of the atmospheric moisture balance and its seasonality, are captured in the CMP5 models subject to biases in total precipitation amounts. We chose to use all available models instead of selecting some and rejecting others based on an assessment of model realism. This is in accord with the suggestions of Mote et al. for CMIP3 (4) but future work needs to revisit this matter for the case of the CMIP5 ensemble.

Seager, Richard↗

NASA NTRS2002

Anomalous Heat Budgets in the Interior Pacific Ocean on Seasonal- to -Timescales and Gyre Spacescales

This study quantifies uncertainties in closing the seasonal cycle of diabatic heat storage over the Pacific Ocean from 20 degrees S to 60 degrees N through the synthesis of World Ocean Circulation Experiment (WOCE) products over 7 years from 1993-1999. We utilize WOCE reanalysis products from the following sources: diabatic heat storage (DHS) from the Scripps Institution of Oceanography (SIO); near-surface geostrophic and Ekman currents from the Earth and Space Research (ESR); and air-sea heat fluxes from Comprehensive Ocean-Atmosphere Data Set (COADS), National Centers for Environmental Prediction (NCEP), and European Center for Mid-Range Weather Forecasts (ECMWF). We interpolate these products onto a common grid, allowing the seasonal cycle of DHS to be modeled for comparison with that observed. Everywhere latent heat flux residuals dominate sensible heat flux residuals and shortwave heat flux residuals dominate longwave heat flux residuals, both comparable in magnitude to the residual horizontal heat advection. We find the root-mean-square (RMS) of the differences between observed and model residual DHS tendencies to be less than 15 W per square meters everywhere except in the Kuroshio extension. Comparable COADS and NCEP products perform better than ECMWF products in the extra-tropics, while the NCEP product performs best in the tropics. Radiative and turbulent air-sea heat flux residuals computed from ship-born measurements perform better than those computed from satellite cloud and wind measurements. Since the RMS differences derive largely from biases in measured wind speed and cloud fraction, least-squares minimization is used to correct the residual Ekman heat advection and air-sea heat flux. Minimization reduces RMS differences less than 5 W per square meters except in the Kuroshio extension, suggesting how winds, clouds, and exchange coefficients in the NCEP, ECMWF, and ESR products can be improved.

White, Warren↗

NASA NTRS2003

Tropospheric Wind Observations with Doppler Lidars

Simpson Weather Associates has continued its efforts on the tools which operate the DLSM's s line-of-sight output products file. Due to the long model run times which were revealed in last month's benchmark tests, four model options for the LSM's atmospheric inputs are now included in the LSM. The user can choose to either spatially and/or temporally interpolate the inputs or use inputs closest to the DWL shot. A problem in the terrain assignment from the GADS was corrected. A database conversion tool was added to convert DWL line-of-sight ASCII files into database format for the graphic display models. Efforts have continued in simulating DWL horizontal wind components using the DAO ficcm Nature Run. Experiments 2 and 3 (40 days worth) were completed and sent to the DAO for their use in bracketing OSSE experiments. In addition, in order to investigate differences in the way regional (MM5) and global scale (ECMWF T213) models treat features such as clouds and subgrid scale variability, a gridded Mesoscale Atmospheric Data Set (MADS) was created and ready to be incorporated into simulation experiments.

Source record↗

NASA NTRS2004

Simulating Virtual Terminal Area Weather Data Bases for Use in the Wake Vortex Avoidance System (Wake VAS) Prediction Algorithm

During the research project, sounding datasets were generated for the region surrounding 9 major airports, including Dallas, TX, Boston, MA, New York, NY, Chicago, IL, St. Louis, MO, Atlanta, GA, Miami, FL, San Francico, CA, and Los Angeles, CA. The numerical simulation of winter and summer environments during which no instrument flight rule impact was occurring at these 9 terminals was performed using the most contemporary version of the Terminal Area PBL Prediction System (TAPPS) model nested from 36 km to 6 km to 1 km horizontal resolution and very detailed vertical resolution in the planetary boundary layer. The soundings from the 1 km model were archived at 30 minute time intervals for a 24 hour period and the vertical dependent variables as well as derived quantities, i.e., 3-dimensional wind components, temperatures, pressures, mixing ratios, turbulence kinetic energy and eddy dissipation rates were then interpolated to 5 m vertical resolution up to 1000 m elevation above ground level. After partial validation against field experiment datasets for Dallas as well as larger scale and much coarser resolution observations at the other 8 airports, these sounding datasets were sent to NASA for use in the Virtual Air Space and Modeling program. The application of these datasets being to determine representative airport weather environments to diagnose the response of simulated wake vortices to realistic atmospheric environments. These virtual datasets are based on large scale observed atmospheric initial conditions that are dynamically interpolated in space and time. The 1 km nested-grid simulated datasets providing a very coarse and highly smoothed representation of airport environment meteorological conditions. Details concerning the airport surface forcing are virtually absent from these simulated datasets although the observed background atmospheric processes have been compared to the simulated fields and the fields were found to accurately replicate the flows surrounding the airport where coarse verification data were available as well as where airport scale datasets were available.

Kaplan, Michael L.↗