skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • NSF Public Access
  • Search Results
  • Meteorological data source comparison—a case study in geospatial modeling of potential environmental exposure to abandoned uranium mine sites in the Navajo Nation
Title: Meteorological data source comparison—a case study in geospatial modeling of potential environmental exposure to abandoned uranium mine sites in the Navajo Nation
Abstract Meteorological (MET) data is a crucial input for environmental exposure models. While modeling exposure potential using geospatial technology is a common practice, existing studies infrequently evaluate the impact of input MET data on the level of uncertainty on output results. The objective of this study is to determine the effect of various MET data sources on the potential exposure susceptibility predictions. Three sources of wind data are compared: The North American Regional Reanalysis (NARR) database, meteorological aerodrome reports (METARs) from regional airports, and data from local MET weather stations. These data sources are used as inputs into a machine learning (ML) driven GIS Multi-Criteria Decision Analysis (GIS-MCDA) geospatial model to predict potential exposure to abandoned uranium mine sites in the Navajo Nation. Results indicate significant variations in results derived from different wind data sources. After validating the results from each source using the National Uranium Resource Evaluation (NURE) database in a geographically weighted regression (GWR), METARs data combined with the local MET weather station data showed the highest accuracy, with an average R 2 of 0.74. We conclude that local direct measurement-based data (METARs and MET data) produce a more accurate prediction than the other sources evaluated in the study. This study has the potential to inform future data collection methods, leading to more accurate predictions and better-informed policy decisions surrounding environmental exposure susceptibility and risk assessment.  more » « less
Award ID(s):
2019609
PAR ID:
10441244
Author(s) / Creator(s):
; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Environmental Monitoring and Assessment
Volume:
195
Issue:
7
ISSN:
0167-6369
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; (, Frontiers in Earth Science)
    The intensity and frequency of wildfires in California (CA) have increased in recent years, causing significant damage to human health and property. In October 2007, a number of small fire events, collectively referred to as the Witch Creek Fire or Witch Fire started in Southern CA and intensified under strong Santa Ana winds. As a test of current mesoscale modeling capabilities, we use the Weather Research and Forecasting (WRF) model to simulate the 2007 wildfire event in terms of meteorological conditions. The main objectives of the present study are to investigate the impact of horizontal grid resolution and planetary boundary layer (PBL) scheme on the model simulation of meteorological conditions associated with a Mega fire. We evaluate the predictive capability of the WRF model to simulate key meteorological and fire-weather forecast parameters such as wind, moisture, and temperature. Results of this study suggest that more accurate predictions of temperature and wind speed relevant for better prediction of wildfire spread can be achieved by downscaling regional numerical weather prediction products to 1 km resolution. Furthermore, accurate prediction of near-surface conditions depends on the choice of the planetary boundary layer parameterization. The MYNN parameterization yields more accurate prediction as compared to the YSU parameterization. WRF simulations at 1 km resolution result in better predictions of temperature and wind speed than relative humidity during the 2007 Witch Fire. In summary, the MYNN PBL parameterization scheme with finer grid resolution simulations improves the prediction of near-surface meteorological conditions during a wildfire event. 
    more » « less
  2. ; ; (, Journal of Renewable and Sustainable Energy)
    Wind farm design generally relies on the use of historical data and analytical wake models to predict farm quantities, such as annual energy production (AEP). Uncertainty in input wind data that drive these predictions can translate to significant uncertainty in output quantities. We examine two sources of uncertainty stemming from the level of description of the relevant meteorological variables and the source of the data. The former comes from a standard practice of simplifying the representation of the wind conditions in wake models, such as AEP estimates based on averaged turbulence intensity (TI), as opposed to instantaneous. Uncertainty from the data source arises from practical considerations related to the high cost of in situ measurements, especially for offshore wind farms. Instead, numerical weather prediction (NWP) modeling can be used to characterize the more exact location of the proposed site, with the trade-off of an imperfect model form. In the present work, both sources of input uncertainty are analyzed through a study of the site of the future Vineyard Wind 1 offshore wind farm. This site is analyzed using wind data from LiDAR measurements located 25 km from the farm and NWP data located within the farm. Error and uncertainty from the TI and data sources are quantified through forward analysis using an analytical wake model. We find that the impact of TI error on AEP predictions is negligible, while data source uncertainty results in 0.4%–3.7% uncertainty over feasible candidate hub heights for offshore wind farms, which can exceed interannual variability. 
    more » « less
  3. (, Environmental Data Initiative)
    This data package contains 5-minute air temperature and wind summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-2 met station. Average air temperature, wind speed, and wind direction are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This is a subset of baseline weather data collected at the 15 Jornada Basin LTER CSIS study blocks, New Mexico. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. The met station variables measured include air temperature, precipitation, relative humidity, wind direction, wind speed. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively . This is an ONGOING dataset. 
    more » « less
  4. (, Environmental Data Initiative)
    This data package contains 5-minute air temperature and wind summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-1 met station. Average air temperature, wind speed, and wind direction are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This is a subset of baseline weather data collected at the 15 Jornada Basin LTER CSIS study blocks, New Mexico. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. The met station variables measured include air temperature, precipitation, relative humidity, wind direction, wind speed. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively . This is an ONGOING dataset. 
    more » « less
  5. (, Environmental Data Initiative)
    This data package contains 5-minute air temperature and wind summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-3 met station. Average air temperature, wind speed, and wind direction are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This is a subset of baseline weather data collected at the 15 Jornada Basin LTER CSIS study blocks, New Mexico. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. The met station variables measured include air temperature, precipitation, relative humidity, wind direction, wind speed. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively . This is an ONGOING dataset. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email