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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Influence of Lake Ice Biases in Reanalysis Data on Downscaled Climate Simulations over the Great Lakes Region

This data package contains observation-based and model-simulated datasets (all provided in NetCDF format) for evaluating how wintertime lake-ice representation affects regional weather and climate over the Laurentian Great Lakes (freshwater lake ecosystem) during the high–ice-cover winter of 2009. The observational component includes: (1) Stage IV gridded precipitation at 4 km, hourly resolution for January–February 2009 over the Great Lakes region (radar–gauge multisensor precipitation analyses); (2) Great Lakes Surface Environmental Analysis (GLSEA) satellite-derived lake-ice coverage at 1.3 km, daily resolution for the 2009 winter months, providing ice coverage over Lakes Superior, Michigan, Huron, Erie, and Ontario; and (3) in situ measurements at the Standard Rock site on Lake Superior from the Great Lakes Evaporation Network (GLEN) at hourly resolution, including near-surface atmospheric variables and sensible and latent heat fluxes (air–lake exchange) at a fixed point location. The modeling component provides corresponding fields from two simulations, both archived at 4 km, hourly resolution: a standalone Weather Research Forecasting model (WRF) run driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5), and a two-way coupled model using WRF and the Finite Volume Community Ocean Model (WRF-FVCOM, a 3-D hydrodynamic lake model). These outputs include variables relevant to air–lake interaction and lake-effect processes (e.g., near-surface temperature, humidity, wind, precipitation, and surface turbulent fluxes), enabling direct comparison with the observational datasets. Users can analyze and visualize these NetCDF files with common tools such as Python (e.g., xarray, netCDF4, numpy, pandas), NCO/CDO, Panoply, or ncview; NetCDF variables can also be converted to other formats (e.g., CSV, GeoTIFF) using these utilities.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗
DOE OSTI2013

Assessment of Land Surface Model Performance in WRF for Simulating Wind at Heights Relevant to the Wind Energy Community

The Weather Research and Forecasting (WRF) model was used to investigate the impact of land surface model (LSM) physics on the simulated surface energy balance and the near surface wind profile, including heights reached by a modern wind turbine. Simulations were made for a domain centered over the Department of Energy (DOE) Southern Great Plains (SGP) Atmospheric Radiation Measurement Program (ARM) Central Facility in northern Oklahoma. High-resolution measurements of surface fluxes and profiles of wind speed, direction and turbulence were available for model validation. We tested 10 common LSM configurations in WRF including Noah, Noah-MP, SSiB, Pleim-Xiu, RUC, and others to evaluate (1) the accuracy of simulated surface energy fluxes, (2) the accuracy of forecasted rotor-disk height wind speeds, and (3) the sensitivity of rotor disk wind speed to the choice of LSM. WRF was run for four, two-week periods covering different canopy, surface meteorology and soil moisture conditions. LSM performances varied by simulation period and errors were greatest during periods with high soil moisture and live crop cover, indicating highest LSM sensitivity when PBL behavior is most coupled to land-atmosphere exchange. Higher wind speed errors also occurred at night during the spring, possibly from the difficulty with simulating nocturnal low-level jets. We found that choice of land surface model led to a ~10% improvement in simulating hub-height wind speed. Errors in wind shear were also sensitive to the choice of LSM. Overall the best performing models were Noah and Noah-MP. The variability of LSM performance across different soil moisture and vegetation canopy conditions suggests LSM representation of surface energy exchange processes in WRF remains a large source of model uncertainty. Furthermore, our results indicate the choice of LSM impacts simulated wind fields in WRF at heights relevant to the wind industry, at least for the Southern Great Plains region.

17 WIND ENERGY↗
DOE OSTI2025

The Role of Leaf Area Changes Within Plant CO 2 Physiological Impacts on the Global Hydrological Cycle

Rising atmospheric CO 2 concentrations enhance greenhouse warming and drive changes to plant physiology, leading to innumerable climate impacts. This study explores the impacts of plant responses on hydrological cycling at 2x preindustrial CO 2 concentrations by analyzing simulations that isolate plant physiological effects using the Community Earth System Model versions 1 and 2. We find that leaf area growth increases canopy evaporation, which offsets transpiration declines, and dampens changes in global mean evapotranspiration, precipitation, and runoff in a CESM2 experiment with dynamic leaf area. These leaf area impacts are also evident in the differences between CESM1 and CESM2, with CESM2 better capturing observed leaf area magnitudes but potentially overestimating leaf area-CO 2 sensitivity, highlighting the importance of plant CO 2 physiology on hydrological cycle changes and the need to improve its representation in climate models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Remote Sensing of Above Cloud Aerosols

The direct and indirect radiative effects of aerosols suspended in the atmosphere above clouds (ACA) are a highly uncertain component of both regional and global climate. Much of this uncertainty is observational in nature most orbital remote sensing algorithms were not designed to simultaneously retrieve aerosol and cloud optical properties in the same vertical column. Thus the climate modeling community has limited data to inform model development efforts, which encapsulate the current understanding of climate. Furthermore, field measurements have identified regions with consistent ACA, and regional simulations show that the radiative forcing may be significant. For this reason, there has been a recent push to develop the ability to determine ACA distribution, optical properties and cloud interactions, while also providing a means to validate models. Several algorithms have been created that utilize existing instruments for these purposes. However, the observational data sources, algorithm characteristics, geophysical assumptions and retrieved products from these methods are highly variable. This chapter is a review of these techniques, their uncertainties, and the associated validation efforts. We will also discuss the future of ACA remote sensing, both with regards to new instruments and the potential for new algorithms.

Aerosols↗
NASA NTRSDate not supplied

Technical Committee on Noise: Researchers and Practitioners

The Technical Committee on Noise (TCNS) includes researchers and industry practitioners interested in understanding noise generation from a variety of sources, its propagation, and its impact on structures, objects, and people. The goal of reducing the impact of this noise, i.e. unwanted sound, has led to innovative model development, measurement techniques, mitigation strategies, and input towards the establishment of regulations. Community noise definition and abatement is of particular interest and motivates the advancement of research on a variety of topics, such as transportation noise, hearing protection, jet and rocket noise, building systems noise and vibration, atmospheric sound propagation, soundscapes, and low-frequency sound. The diverse technical background of TCNS members is essential, given the interdisciplinary nature of this research, and it is mirrored in the topics of special sessions typically held jointly with other ASA technical committees.

noise↗
NASA NTRSDate not supplied

Assessment of Retrieved GMI Emissivity Over Land, Snow and Sea Ice in the GEOS System

Measurements from microwave sounders and imagers provide a valuable source of information including atmospheric temperature and water vapor in Numerical Weather Prediction (NWP) systems that assimilate these observations directly over water surfaces (oceans and other large water bodies). In a recent decadal survey, targeted observables in the Planetary Boundary Layer (PBL) were cited as a key need for future observations (NASEM, 2018). Microwave observations which sense in the PBL are currently available, however, utilizing surface-sensitive microwave observations for atmospheric data assimilation remains a challenge over land, snow and sea ice. This is in part due to the inability of surface emissivity models used by NWP data assimilation systems to simulate observations with sufficient accuracy. The GEOS-ADAS (Todling and el Akkraoui, 2018) which utilizes the Community Radiative Transfer Model (CRTM) (Han, 2006; Chen 2009) is no exception. The ECMWF system has retrieved instantaneous surface emissivity from surface-sensitive channels for SSMI/S and MHS radiance observations, and apply these estimates to the closest channels higher in frequency (Baordo and Geer 2016) in the calculation of simulated radiances. This approach currently is also being tested in the GEOS-ADAS for AMSU-A and ATMS radiances (Zhu et al. 2021). No or minimal emissivity spectral variability has been assumed in the above-mentioned studies. Recently, work by Munchak et al., 2020 (hereby referred to as M2020) provided a new database for emissivity over land, snow and sea ice retrieved from the NASA Global Precipitation Mission (GPM). Compared with Tool to Estimate Land Surface Emissivities at Microwave (TELSEM2; Wang et al., 2017), M2020 provides emissivities for more frequencies(i.e., 10.7 GHz V/H). Moreover, this database is unique in that it utilizes both active and passive data to retrieve surface emissivity and normalized radar cross section. While the emissivity values may be useful for other sensors, they are most applicable to the GPM Microwave Imager (GMI). In this work the GEOS-ADAS is modified to utilize emissivity values from Munchak et al, 2020 in place of values used by CRTM. Presently, only GMI radiances over ocean are used in the operational GEOS-ADAS. This study will focus on the GMI radiances over land, snow, and ice, as a first attempt to evaluate GMI radiances over these non-water surface types. Two cases are then presented, one with one week of observation minus background departures using the modified GEOS-ADAS, and one utilizing the original GEOS-ADAS. It should be noted that the surface emissivity models in CRTM are not state of the art and are scheduled to be replaced by the Community Surface Emissivity Module (CSEM; Chen and Weng, 2016). Simulations using default CRTM emissivity values are used merely as reference comparing against M2020, and is not a thorough comparison against other more state of the art modules such as CSEM.

GMI↗
NASA NTRS2007

Uncertainty Analysis of Historical Hurricane Data

An analysis of variance (ANOVA) study was conducted for historical hurricane data dating back to 1851 that was obtained from the U. S. Department of Commerce National Oceanic and Atmospheric Administration (NOAA). The data set was chosen because it is a large, publicly available collection of information, exhibiting great variability which has made the forecasting of future states, from current and previous states, difficult. The availability of substantial, high-fidelity validation data, however, made for an excellent uncertainty assessment study. Several factors (independent variables) were identified from the data set, which could potentially influence the track and intensity of the storms. The values of these factors, along with the values of responses of interest (dependent variables) were extracted from the data base, and provided to a commercial software package for processing via the ANOVA technique. The primary goal of the study was to document the ANOVA modeling uncertainty and predictive errors in making predictions about hurricane location and intensity 24 to 120 hours beyond known conditions, as reported by the data set. A secondary goal was to expose the ANOVA technique to a broader community within NASA. The independent factors considered to have an influence on the hurricane track included the current and starting longitudes and latitudes (measured in degrees), and current and starting maximum sustained wind speeds (measured in knots), and the storm starting date, its current duration from its first appearance, and the current year fraction of each reading, all measured in years. The year fraction and starting date were included in order to attempt to account for long duration cyclic behaviors, such as seasonal weather patterns, and years in which the sea or atmosphere were unusually warm or cold. The effect of short duration weather patterns and ocean conditions could not be examined with the current data set. The responses analyzed were the storm latitude, longitude and intensity, as recorded in the data set, 24 or 120 hours beyond the current state. Several ANOVA modeling schemes were examined. Two forms of validation were used: 1) comparison with official hurricane prediction performance metrics and 2) cases studies conducted on hurricanes from the 2005 season, which were not included within the model construction and ANOVA assessment. In general, the ANOVA technique did not perform as well as the established official prediction performance metrics published by NOAA; still, the technique did remarkably well in this demonstration with a difficult data set and could probably be made to perform better with more knowledge of hurricane development and dynamics applied to the problem. The technique provides a repeatable prediction process that eliminates the need for judgment in the forecast.

Green, Lawrence L.↗
NASA NTRS2002

A Tool for Low Noise Procedures Design and Community Noise Impact Assessment: The Rotorcraft Noise Model (RNM)

To improve aircraft noise impact modeling capabilities and to provide a tool to aid in the development of low noise terminal area operations for rotorcraft and tiltrotors, the Rotorcraft Noise Model (RNM) was developed by the NASA Langley Research Center and Wyle Laboratories. RNM is a simulation program that predicts how sound will propagate through the atmosphere and accumulate at receiver locations located on flat ground or varying terrain, for single and multiple vehicle flight operations. At the core of RNM are the vehicle noise sources, input as sound hemispheres. As the vehicle "flies" along its prescribed flight trajectory, the source sound propagation is simulated and accumulated at the receiver locations (single points of interest or multiple grid points) in a systematic time-based manner. These sound signals at the receiver locations may then be analyzed to obtain single event footprints, integrated noise contours, time histories, or numerous other features. RNM may also be used to generate spectral time history data over a ground mesh for the creation of single event sound animation videos. Acoustic properties of the noise source(s) are defined in terms of sound hemispheres that may be obtained from theoretical predictions, wind tunnel experimental results, flight test measurements, or a combination of the three. The sound hemispheres may contain broadband data (source levels as a function of one-third octave band) and pure-tone data (in the form of specific frequency sound pressure levels and phase). A PC executable version of RNM is publicly available and has been adopted by a number of organizations for Environmental Impact Assessment studies of rotorcraft noise. This paper provides a review of the required input data, the theoretical framework of RNM's propagation model and the output results. Code validation results are provided from a NATO helicopter noise flight test as well as a tiltrotor flight test program that used the RNM as a tool to aid in the development of low noise approach profiles.

Conner, David A.↗
NASA NTRS2020

Assessment of Lidar XCH4 Measurements During ACT-America 2019 for Boundary Layer Methane and Emission Model Constraint

Atmospheric methane is a potent and abundant greenhouse gas (GHG) with increasing importance due to rising emissions and their subsequent impact on radiative forcing, indicating an important driving role in climate change. The recent Earth Science Decadal Survey called for further understanding of the sources and sinks of atmospheric methane, the processes that will affect their future concentrations, and identified the need for advanced observing capabilities to elucidate these issues. HALO, a combined methane Differential Absorption Lidar and Aerosol/Cloud High Spectral Resolution Lidar participated in the ACT-America summer 2019 campaign to help constrain the emissions and transport of GHGs in the atmosphere to address some of the aforementioned science goals. In this presentation we will discuss the utility of using an in-situ point measurement versus lidar column measurement for inventory and source identification applications. Comparisons between column measurements of methane from in-situ and lidar will be made to assess whether point measurements are useful when the assumption of a well-mixed boundary layer, a practice commonly used in the community, is valid. We will also show that a lidar column measurement can apportion boundary layer methane from the column and has the ability to identify boundary layer methane enhancements in fair weather conditions using atmospheric backscatter signals, a measurement capability that has the potential to transform the observational strategies of future airborne carbon cycle science investigations. We will also present on the differences and utility of constraining emission models using an in-situ versus lidar column and asses the resulting uncertainties of each.

Rory A Barton-Grimley↗
DOE OSTI2026

A total of 19 months of daily weather logging on the US east coast: the WFIP3 event log

The Third Wind Forecast Improvement Project (WFIP3) is a multi-institutional field campaign designed to advance the understanding and prediction of the offshore atmospheric boundary layer along the US east coast. Extending from February 2024 through August 2025, WFIP3 combines long-term coastal and offshore measurements with targeted modeling and forecasting efforts. This data paper presents the WFIP3 event log, a curated record of 578 d of meteorological phenomena and field observations that complements the campaign's extensive high-frequency datasets. The event log provides both manually documented daily weather discussions and automatically derived indicators of atmospheric processes – including low-level jets, wind ramps, extreme wind veer, and weak wind conditions – based on observations from scanning lidars deployed at three coastal and offshore sites. The dataset offers structured metadata, standardized time and site identifiers, and consistent terminology to facilitate its integration with WFIP3's observational and modeling data products. The log supports diverse applications, from model evaluation and forecast verification to the selection of case studies on offshore boundary-layer dynamics. The WFIP3 event log is publicly available through the US Department of Energy's Wind Data Hub, providing the research community with a transparent and enduring contextual reference for the interpretation and use of WFIP3 measurements.

17 WIND ENERGY↗
DOE OSTI2014

Correcting for telluric absorption: Methods, case studies, and release of the TelFit code

Ground-based astronomical spectra are contaminated by the Earth's atmosphere to varying degrees in all spectral regions. We present a Python code that can accurately fit a model to the telluric absorption spectrum present in astronomical data, with residuals of ∼3%-5% of the continuum for moderately strong lines. We demonstrate the quality of the correction by fitting the telluric spectrum in a nearly featureless A0V star, HIP 20264, as well as to a series of dwarf M star spectra near the 819 nm sodium doublet. We directly compare the results to an empirical telluric correction of HIP 20264 and find that our model-fitting procedure is at least as good and sometimes more accurate. The telluric correction code, which we make freely available to the astronomical community, can be used as a replacement for telluric standard star observations for many purposes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Crop physiology calibration in the CLM

Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurements of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Atmospheric effects on sonic boom: A program review

The program goals were determined after consideration of the weaknesses in our understanding of atmospheric effects on sonic boom waveforms left in the wake of the cancellation of the U.S. SST in the 70's and the advancements in acoustics and atmospheric science since that time. For example, a considerable body of knowledge on molecular absorption has built up in the acoustics community over the last 15 years and this has not been incorporated into the sonic boom theory. Further, it was felt that the understanding of atmospheric turbulence had also advanced considerably during that time period. Therefore, key elements of the current program are the development of an improved atmospheric absorption model and an improved atmospheric turbulence model. The advances made in computer power over the last 15 years were also considered, and will be utilized to remove restrictions on the analytical model for turbulence effects on sonic boom waveforms. Although the majority of disturbing sonic booms will not occur at focuses or caustics, it was felt that this was an area that required further understanding, thus it will be looked into. Finally, in order to insure that the current effort, which is basically analytical in nature, retains a firm grasp on reality, a data base of sonic boom waveforms and associated weather data is being compiled, and a set of scale model experiments is being planned to guide the overall efforts.

Mcaninch, Gerry L.↗
NASA NTRS2011

Terra and Aqua MODIS Design, Radiometry, and Geometry in Support of Land Remote Sensing

The NASA Earth Observing System (EOS) mission includes the construction and launch of two nearly identical Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. The MODIS proto-flight model (PFM) is onboard the EOS Terra satellite (formerly EOS AM-1) launched on December 18, 1999 and hereafter referred to as Terra MODIS. Flight model-1 (FM1) is onboard the EOS Aqua satellite (formerly EOS PM-1) launched on May 04, 2002 and referred to as Aqua MODIS. MODIS was developed based on the science community s desire to collect multiyear continuous datasets for monitoring changes in the Earth s land, oceans and atmosphere, and the human contributions to these changes. It was designed to measure discrete spectral bands, which includes many used by a number of heritage sensors, and thus extends the heritage datasets to better understand both long- and short-term changes in the global environment (Barnes and Salomonson 1993; Salomonson et al. 2002; Barnes et al. 2002). The MODIS development, launch, and operation were managed by NASA/Goddard Space Flight Center (GSFC), Greenbelt, Maryland. The sensors were designed, built, and tested by Raytheon/ Santa Barbara Remote Sensing (SBRS), Goleta, California. Each MODIS instrument offers 36 spectral bands, which span the spectral region from the visible (0.41 m) to long-wave infrared (14.4 m). MODIS collects data at three different nadir spatial resolutions: 0.25, 0.5, and 1 km. Key design specifications, such as spectral bandwidths, typical scene radiances, required signal-to-noise ratios (SNR) or noise equivalent temperature differences (NEDT), and primary applications of each MODIS spectral band are summarized in Table 7.1. These parameters were the basis for the MODIS design. More details on the evolution of the NASA EOS and development of the MODIS instruments are provided in Chap. 1. This chapter focuses on the MODIS sensor design, radiometry, and geometry as they apply to land remote sensing. With near-daily coverage of the Earth's surface, MODIS provides comprehensive measurements that enable scientists and policy makers to better understand and effectively manage the natural resources on both regional and global scales. Terra, the first large multisensor EOS satellite, is operated in a 10:30 am (local equatorial crossing time, descending southwards) polar orbit. Aqua, the second multisensor EOS satellite is operated in a 1:30 pm (local equatorial crossing time, ascending northwards) polar orbit. With complementing morning and afternoon observations, the Terra and Aqua MODIS, together with other sensors housed on both satellites, have greatly improved our understanding of the dynamics of the global environmental system.

Xiong, Xiaoxiong↗
NASA NTRS2019

First ALMA Millimeter-wavelength Maps of Jupiter, with a Multiwavelength Study of Convection

We obtained the first maps of Jupiter at 1–3 mm wavelength with the Atacama Large Millimeter/Submillimeter Array (ALMA) on 2017 January 3–5, just days after an energetic eruption at 16fdg5S jovigraphic latitude had been reported by the amateur community, and about two to three months after the detection of similarly energetic eruptions in the northern hemisphere, at 22.2°–23.0°N. Our observations, probing below the ammonia cloud deck, show that the erupting plumes in the South Equatorial Belt bring up ammonia gas from the deep atmosphere. While models of plume eruptions that are triggered at the water condensation level explain data taken at uv–visible and mid-infrared wavelengths, our ALMA observations provide a crucial, hitherto missing, link in the moist convection theory by showing that ammonia gas from the deep atmosphere is indeed brought up in these plumes. Contemporaneous Hubble Space Telescope data show that the plumes reach altitudes as high as the tropopause. We suggest that the plumes at 22.2°–23.0°N also rise up well above the ammonia cloud deck and that descending air may dry the neighboring belts even more than in quiescent times, which would explain our observations in the north.

Imke de Pater↗
NASA NTRSDate not supplied

Toward Enhancing the Use of IASI and CrIS Surface-Sensitive Radiances Over Land in the NASA GMAO GEOS Data Assimilation Framework

Assimilating surface-sensitive radiances over land is still challenging for both infrared (IR) and microwave (WV) radiances essentially because of the large uncertainties of the land physical surface emissivity model used in the Community Radiative Transfer Model (CRTM) and the uncertainties of land surface state properties. Currently very few IR radiances are assimilated over land. Large number of IR radiances are rejected by the surface sensitivity checks as well as the cloud detection check. In this study, we identified the appropriate Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) surface-sensitive channels to retrieve Land Surface Temperature (LST). Then, we studied the impacts of these retrieved LST and retuned cloud detection on the simulation and assimilation of IASI and CrIS in the NASA GEOS in clear sky conditions. The preliminary results are shown to enhance the rate of IASI and CrIS assimilated channels over land. The impacts on the quality of the resulting analysis and subsequent forecast will be presented at the meeting.

Niama Boukachaba↗
DOE OSTI2017

6th Annual Earth System Grid Federation Face-to-Face Conference Report, December 5–9, 2016, Washington, D.C.

Since its inception in the late 1990s, the Earth System Grid Federation (ESGF) has evolved significantly as a system. As technology changed and its user base grew larger and more diverse, ESGF gradually developed into the state-of-the-art federated system it is today. Due to the enormity of its scope and the urgency of community needs, many features had to be tested in the real world during the expansion process. The rollout of Version 2.4 in 2016 culminated a series of releases and user feedback initiatives that began in 2013. During this 3-year period, ESGF hosted user group meetings to better understand how the system was being used; this information was then leveraged to begin Version 3.0 planning and preparations. The user meetings were collectively led and organized by the U.S. Department of Energy (DOE), the Infrastructure for the European Network for Earth System Modelling (IS-ENES), the U.S. National Aeronautics and Space Administration (NASA), the Australian National Computational Infrastructure (NCI), the U.S. National Oceanic and Atmospheric Administration (NOAA), and the U.S. National Science Foundation (NSF). The information emerging from the user group meetings influenced requirements, development, and operations. In 2015, representatives from a significant fraction of projects that use ESGF to disseminate and analyze data attended the Fifth Annual ESGF Face-to-Face (F2F) Conference (DOI: 10.2172/1253685). Attendees provided important feedback regarding current and future community data use cases. Discussions focused on maintaining essential operations while developing new and improved software to handle ever-increasing data variety, complexity, velocity, and volume—a task accomplished by the entire consortium.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

Integration for Airborne Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems

The objective of the program is to assess the feasibility of combining a dust transport model with MODIS derived phenology to study pollen transport for integration with a public health decision support system. The use of pollen information has specifically be identified as a critical need by the New Mexico State Health department for inclusion in the Environmental Public Health Tracking (EPHT) program. Material and methods: Pollen can be transported great distances. Local observations of plan phenology may be consistent with the timing and source of pollen collected by pollen sampling instruments. The Dust REgional Atmospheric Model (DREAM) is an integrated modeling system designed to accurately describe the dust cycle in the atmosphere. The dust modules of the entire system incorporate the state of the art parameterization of all the major phases of the atmospheric dust life such as production, diffusion, advection, and removal. These modules also include effects of the particles size distribution on aerosol dispersion. The model was modified to use pollen sources instead of dust. Pollen release was estimated based on satellite-derived phenology of key plan species and vegetation communities. The MODIS surface reflectance product (MOD09) provided information on the start of the plant growing season, growth stage, and pollen release. The resulting deterministic model is useful for predicting and simulating pollen emission and downwind concentration to study details of phenology and meteorology and their dependencies. The proposed linkage in this project provided critical information on the location timing and modeled transport of pollen directly to the EPHT> This information is useful to support the centers for disease control and prevention (CDC)'s National EPHT and the state of New Mexico environmental public health decision support for asthma and allergies alerts.

Luvall, J. C.↗