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Christman Field Latest Observations
Select Units
Date Time
MST
Temp
°F
RH
%
DewPt
°F
Wind
mph
Dir
°
Gust
mph
Dir
°
Press
in Hg
Solar
W/m^2
Prec
in
2023-01-31 22:40 9.3 76.1 3.3 4.2 333 7.4 333 24.900 0.0 0.00
2023-01-31 22:35 8.8 78.1 3.4 4.6 1 5.6 345 24.901 0.0 0.00
2023-01-31 22:30 10.8 76.4 4.8 2.3 288 3.2 288 24.900 0.0 0.00
2023-01-31 22:25 11.1 76.2 5.1 0.5 260 1.9 260 24.901 0.0 0.00
2023-01-31 22:20 11.5 75.5 5.2 2.1 217 3.1 261 24.898 0.0 0.00
2023-01-31 22:15 10.1 78.5 4.8 2.4 266 4.2 259 24.899 0.0 0.00
2023-01-31 22:10 10.6 78.0 5.1 2.2 216 4.9 244 24.900 0.0 0.00
2023-01-31 22:05 10.3 78.3 4.9 3.1 247 3.8 248 24.899 0.0 0.00
2023-01-31 22:00 9.5 80.2 4.6 4.5 219 5.5 255 24.897 0.0 0.00
2023-01-31 21:55 11.1 76.3 5.1 4.2 262 8.2 255 24.896 0.0 0.00
2023-01-31 21:50 9.0 86.9 5.9 5.5 251 8.9 253 24.898 0.0 0.00
2023-01-31 21:45 5.8 84.0 2.0 3.7 265 5.0 247 24.899 0.0 0.00
2023-01-31 21:40 6.2 83.5 2.2 3.5 259 4.4 247 24.897 0.0 0.00
2023-01-31 21:35 5.7 85.8 2.4 2.7 317 3.5 316 24.896 0.0 0.00
2023-01-31 21:30 5.3 84.5 1.7 3.1 299 4.3 261 24.899 0.1 0.00
2023-01-31 21:25 5.2 84.3 1.5 2.7 248 4.3 237 24.901 0.0 0.00
2023-01-31 21:20 5.3 82.4 1.1 1.8 249 3.2 249 24.899 0.0 0.00
2023-01-31 21:15 4.7 83.7 0.9 0.8 286 2.1 286 24.897 0.1 0.00
2023-01-31 21:10 4.9 82.6 0.7 1.8 343 2.4 351 24.898 0.1 0.00
2023-01-31 21:05 4.9 82.2 0.7 3.0 351 3.7 310 24.900 0.0 0.00
2023-01-31 21:00 5.1 80.8 0.5 3.2 310 3.9 326 24.900 0.0 0.00
2023-01-31 20:55 6.6 79.4 1.6 3.4 326 4.5 345 24.900 0.0 0.00
2023-01-31 20:50 7.8 78.0 2.3 3.6 1 4.2 4 24.895 0.0 0.00
2023-01-31 20:45 7.3 82.0 3.0 2.6 350 3.0 351 24.895 0.0 0.00
2023-01-31 20:40 5.6 83.8 1.8 2.1 288 2.8 299 24.897 0.0 0.00
2023-01-31 20:35 5.8 78.4 0.5 2.5 231 4.7 337 24.895 0.0 0.00
2023-01-31 20:30 6.4 82.6 2.3 4.9 337 5.8 349 24.894 0.0 0.00
2023-01-31 20:25 5.7 82.4 1.5 3.5 11 4.8 11 24.892 0.0 0.00
2023-01-31 20:20 5.8 81.1 1.3 2.3 356 3.8 12 24.889 0.0 0.00
2023-01-31 20:15 6.4 79.5 1.4 2.1 66 3.4 252 24.889 0.0 0.00
Date Time
MST
Temp
°C
RH
%
DewPt
°C
Wind
m/s
Dir
°
Gust
m/s
Dir
°
Press
hPa
Solar
W/m^2
Prec
mm
2023-01-31 22:40 -12.6 76.1 -15.9 1.9 333 3.3 333 843.20 0.0 0.00
2023-01-31 22:35 -12.9 78.1 -15.9 2.1 1 2.5 345 843.24 0.0 0.00
2023-01-31 22:30 -11.8 76.4 -15.1 1.0 288 1.4 288 843.19 0.0 0.00
2023-01-31 22:25 -11.6 76.2 -15.0 0.2 260 0.9 260 843.24 0.0 0.00
2023-01-31 22:20 -11.4 75.5 -14.9 1.0 217 1.4 261 843.16 0.0 0.00
2023-01-31 22:15 -12.2 78.5 -15.1 1.1 266 1.9 259 843.17 0.0 0.00
2023-01-31 22:10 -11.9 78.0 -15.0 1.0 216 2.2 244 843.20 0.0 0.00
2023-01-31 22:05 -12.0 78.3 -15.0 1.4 247 1.7 248 843.19 0.0 0.00
2023-01-31 22:00 -12.5 80.2 -15.2 2.0 219 2.5 255 843.12 0.0 0.00
2023-01-31 21:55 -11.6 76.3 -14.9 1.9 262 3.7 255 843.06 0.0 0.00
2023-01-31 21:50 -12.8 86.9 -14.5 2.5 251 4.0 253 843.13 0.0 0.00
2023-01-31 21:45 -14.6 84.0 -16.7 1.7 265 2.2 247 843.17 0.0 0.00
2023-01-31 21:40 -14.4 83.5 -16.5 1.5 259 2.0 247 843.12 0.0 0.00
2023-01-31 21:35 -14.6 85.8 -16.5 1.2 317 1.5 316 843.06 0.0 0.00
2023-01-31 21:30 -14.8 84.5 -16.8 1.4 299 1.9 261 843.18 0.1 0.00
2023-01-31 21:25 -14.9 84.3 -16.9 1.2 248 1.9 237 843.23 0.0 0.00
2023-01-31 21:20 -14.8 82.4 -17.2 0.8 249 1.4 249 843.16 0.0 0.00
2023-01-31 21:15 -15.2 83.7 -17.3 0.4 286 0.9 286 843.11 0.1 0.00
2023-01-31 21:10 -15.1 82.6 -17.4 0.8 343 1.1 351 843.16 0.1 0.00
2023-01-31 21:05 -15.1 82.2 -17.4 1.3 351 1.6 310 843.23 0.0 0.00
2023-01-31 21:00 -14.9 80.8 -17.5 1.4 310 1.7 326 843.21 0.0 0.00
2023-01-31 20:55 -14.1 79.4 -16.9 1.5 326 2.0 345 843.21 0.0 0.00
2023-01-31 20:50 -13.5 78.0 -16.5 1.6 1 1.9 4 843.03 0.0 0.00
2023-01-31 20:45 -13.7 82.0 -16.1 1.2 350 1.3 351 843.05 0.0 0.00
2023-01-31 20:40 -14.7 83.8 -16.8 1.0 288 1.3 299 843.11 0.0 0.00
2023-01-31 20:35 -14.6 78.4 -17.5 1.1 231 2.1 337 843.04 0.0 0.00
2023-01-31 20:30 -14.2 82.6 -16.5 2.2 337 2.6 349 843.00 0.0 0.00
2023-01-31 20:25 -14.6 82.4 -16.9 1.5 11 2.2 11 842.94 0.0 0.00
2023-01-31 20:20 -14.5 81.1 -17.1 1.0 356 1.7 12 842.83 0.0 0.00
2023-01-31 20:15 -14.2 79.5 -17.0 0.9 66 1.5 252 842.84 0.0 0.00
CIRA

Cooperative Institute for Research in the Atmosphere

Team

Core members of the CIRA ML team


  • Imme Ebert-Uphoff (CIRA – ML group lead, faculty – ECE):  ML for satellite applications, image-to-image translation, explainable AI (XAI), ethics & AI.
  • Jason Apke (CIRA): Optical flow for environmental science applications.
  • Akansha Singh Bansal (CIRA postdoc):  Self-supervised learning, Deep learning, ML for satellite applications
  • Galina Chirakova (CIRA): ML for tropical cyclones.
  • Mark DeMaria (CIRA): ML for tropical cyclones.
  • Eric Goldenstern (ATS Ph.D. student): ML for precipitation retrieval from satellites
  • John M. Haynes (CIRA): ML for satellite applications
  • Katherine Haynes (CIRA): ML for satellite applications, ML for tropical cyclones
  • Kyle Hilburn (CIRA): ML for satellite applications
  • Ryan Lagerquist (CIRA,NOAA-GSL): ML for satellite applications, ML for radiative transfer, explainable AI (XAI)
  • Yoonjin Lee (CIRA postdoc): ML for satellite applications
  • Yingzhao Ma (CIRA): Bayesian ML for radar applications
  • Marie McGraw (CIRA postdoc): ML for tropical cyclones
  • Steve Miller (CIRA director, faculty – Atmospheric Science): ML for Day-Night Band.
  • Kate Musgrave (CIRA): ML tropical cyclones
  • Yoo-Jeong Noh (CIRA): ML applications for satellite cloud detection and retrievals
  • Paul Roebber (CIRA): Distinguished Professor – Atmospheric Science, University of Wisconsin, Milwaukee.
  • Matt Rogers (CIRA): CIRA/ML outreach
  • Andrea Schumacher (CIRA): tropical cyclones, risk communication for ML
  • Charles White (CIRA postdoc): ML for satellite applications.

 

Close collaborators at NOAA


We work with the following NOAA scientists on almost a daily basis:

  • Chris Slocum (NOAA-NESDIS/STAR/RAMMB, located at CIRA): ML for tropical cyclones
  • John Knaff (NOAA-NESDIS, located at CIRA): tropical cyclones
  • Jebb Q. Stewart (NOAA-GSL): ML for satellite applications, ML for radiative transfer
  • Christina Kumler (NOAA-GSL / CIRES): ML for satellite applications
  • Dave Turner (NOAA-GSL): radiative transfer, clouds and model verification

Collaborators through the AI Institute


We also work closely with the following scientists through the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES).   See also the AI Institute page for more information:

Within CSU:

  • Chuck Anderson (faculty – Computer science, CSU):  machine learning
  • Elizabeth Barnes (faculty – Atmospheric science, CSU): climate science, incl. subseasonal-to-seasonal prediction, machine learning, incl. XAI and robust AI
  • Antonios Mamalakis (postdoc, Atmospheric science, CSU): machine learning for environmental sciences, explainable AI (XAI), benchmark development
  • Jason Stock (Ph.D. student, Computer science, CSU):  simplifying machine learning, interpretable-by-design, explainable AI
  • Lander Ver Hoef (Ph.D. student, Mathematics, CSU):  topological data analysis and applications to satellite data

Outside CSU:

  • Amy McGovern (Univ. of Oklahoma) – ML for environmental science, XAI, AI & ethics
  • David John Gagne (NCAR) – ML for environmental science, XAI, AI & ethics
  • Julie Demuth (NCAR) – weather risk communication
  • Ann Bostrom (Univ. of Washington) – risk communication, environmental policy
  • Plus many other members of the AI2ES team.

NOAA Center for AI (NCAI)


Through the AI Institute we also work closely with the NOAA Center for Artificial Intelligence (NCAI), e.g., to organize the NCAR Summer School on Trustworthy AI for Environmental Science (TAI4ES) (6/27-07/01/2022) and other training activities.