RWIS Atmospheric / Surface Data Download

Backend Documentation
Network Selection
1. Select Station(s)
Data Request Configuration
2. Select Start/End Time

Times are in timezone you select in step 5 below.

Year Month Day Hour
Start:
End:
3. Select Variables

The label value within parenthesis is the output column name.

See below for discussion on "Pavement Sensor Condition"
4. How to view?
5. Timezone of Timestamps

This controls the timezone used for presenting the timestamps in the downloaded file.

6. Data Delimitation

How shall the output values be separated?

7. Include Lat / Lons? GIS Ready
8. Submit Form

Pavement Sensor Condition Explanation

The data is taken from the Vaisala FP2000. These readings can be lumped into four general categories: wet, dry, snow/ice, error. The sensor gives quite a few more, especially in the snow/ice realm but functionally it is difficult to distinguish clear differences between them.

From the glossary:
Status Description
Snow/Ice Warning Continuous film of ice and water mixture at or below freezing (32°F / 0°C) with insufficient chemical to keep the mixture from freezing. This status can only be reported at Vaisala ESP and SP sites when precipitation occurs.
Ice Warning Continuous film of ice and water mixture at or below freezing (32°F / 0°C) with insufficient chemical to keep the mixture from freezing. This status can only be reported at NTCIP sites.
Snow Warning This status can be reported at NTCIP sites, but will not be reported by Vaisala NTCIP sites.
Wet Below Freezing Moisture on pavement sensor with a surface temperature below freezing (32°F / 0°C). This status will only be reported at Vaisala SCAN Detector sites.
Ice Watch Thin or spotty film of moisture at or below freezing (32°F / 0°C). This status can only be reported at NTCIP sites when precipitation is not occurring.
Snow/IceWatch Thin or spotty film of moisture at or below freezing (32°F / 0°C). This status can only be reported at Vaisala ESP and SP sites when precipitation is not occurring.
Snow Watch This status can be reported at NTCIP sites, but is not detected at Vaisala NTCIP sites.
Frost Moisture on pavement at or below freezing (32°F / 0°C) with a pavement temperature at or below the dew point temperature. This status can only be reported by Vaisala ESP, SP, and NTCIP sites when precipitation is not occurring.
Chemical Wet Continuous film of water and ice mixture at or below freezing (32°F or 0°C) with enough chemical to keep the mixture from freezing. This status can only be reported by Vaisala ESP, SP, and NTCIP sites when precipitation occurs.
Wet Continuous film of moisture on the pavement sensor with a surface temperature above freezing (32°F or 0°C). This status can be reported by Vaisala ESP, SP, SCAN Detector, and NTCIP sites when precipitation has occurred.
Damp Thin or spotty film of moisture above freezing (32°F or 0°C). This status can only be reported by Vaisala ESP, and SP sites when precipitation is not occurring.
Trace Moisture Thin or spotty film of moisture above freezing (32°F or 0°C). Surface moisture occurred without precipitation being detected. This status will only be reported at NTCIP sites when precipitation is not occurring.
Absorption at Dew Point, Absorption, & Dew These statuses can be reported at NTCIP sites, but are not currently detected at Vaisala NTCIP sites.
Dry Absence of moisture on the surface sensor. This status can be reported by Vaisala ESP, SP, SCAN Dectector, and NTCIP sites.
Other Other is the standard NTCIP ESS surface condition code to handle conditions not explicitly included in this table. This status will only be reported NTCIP by sensors installed at NTCIP ESS sites.
No Report The surface sensor is not operating properly and requires maintenance. This status will only be reported by Vaisala ESP and SP sites.
Error The surface sensor is not operating properly and requires maintenance. This status will only be reported by NTCIP sites.

Publications Citing IEM Data (View All)

These are the most recent 10 publications that have cited the usage of data from this page. This list is not exhaustive, so please let us know if you have a publication that should be added.

  • Ashraf, M. and K. Dey. 2026, Multiscale model for road weather information system location selection considering road weather characteristics and network topology. Transportation Research Part A: Policy and Practice. https://doi.org/10.1016/j.tra.2025.104741
  • Urbiztando, M., M. Wu, et al. 2025, Advancing winter road maintenance: An AI-driven web platform for real-time road condition monitoring and spatial analysis. Transportation Research Interdisciplinary Perspectives. Volume 33 https://doi.org/10.1016/j.trip.2025.101575
  • Sharma, D., et al. 2025, Safety Impacts of Road Weather Information Systems (RWIS) – A State-wide Cost Effectiveness Case Study Journal of Traffic and Transportation Engineering https://jtte.chd.edu.cn/en/article/pdf/preview/c2bdf818-88a9-4203-a554-a5b97a9930b0.pdf
  • Khan, M. 2025, Toward a Predictive Blowing Snow Model: Analysis of Road Surface Condition Using Teconer RCM511 Along I-80 Wyoming, Master of Science, Civil and Architectural Engineering and Construction Management. University of Wyoming Thesis https://www.proquest.com/docview/3243225253
  • Mahedi, M., D. Rajewski, et al. 2024, Have climate change and warmer winters altered freeze-thaw patterns? Transportation Geotechnics. Volume 46 https://doi.org/10.1016/j.trgeo.2024.101250
  • Biswas, S., D. Sharma, et al. 2022, Safety Impact Assessment of Optimal RWIS Networks—An Empirical Examination. Sustainability 15(1). https://doi.org/10.3390/su15010327
  • Wong, A. and T. Kwon. 2021, Advances in Regression Kriging-Based Methods for Estimating Statewide Winter Weather Collisions: An Empirical Investigation. Future Transp. 2021, 1(3), 570-589 https://doi.org/10.3390/futuretransp1030030
  • Rigabadi, A, M. Herozi, et al. 2021, An attempt for development of pavements temperature prediction models based on remote sensing data and artificial neural network. International Journal of Pavement Engineering https://doi.org/10.1080/10298436.2021.1873334
  • Biswas, S. and T. Kwon. 2020, Developing Statewide Optimal RWIS Density Guidelines Using Space-Time Semivariogram Models. Journal of Sensors. https://doi.org/10.1155/2020/1208692
  • Genc, D., J. Ashlock, et al. 2020, Analysis of In Situ Soil Thermal and Hydraulic Data from a Subgrade Sensor Network under a Granular Roadway. Geo-Congress 2020: Modeling, Geomaterials, and Site Characterization (GSP 317) https://doi.org/10.1061/9780784482803.016