Christman Field Latest Observations
Date Time
MST
Temp
°F
RH
%
DewPt
°F
Wind
mph
Dir
°
Gust
mph
Dir
°
Press
in Hg
Solar
W/m^2
Prec
in
2019-09-16 14:30 89.2 12.1 30.1 5.1 150 8.7 149 24.728 725.2 0.00
2019-09-16 14:25 89.9 12.0 30.6 6.2 146 9.2 139 24.748 772.6 0.00
2019-09-16 14:20 89.8 12.1 30.6 7.0 122 11.3 134 24.740 770.1 0.00
2019-09-16 14:15 89.8 12.8 32.1 5.5 72 9.3 121 24.763 802.0 0.00
2019-09-16 14:10 90.7 12.3 31.7 7.0 109 11.9 118 24.757 857.0 0.00
2019-09-16 14:05 91.5 11.6 31.0 6.0 121 17.9 179 24.745 887.0 0.00
2019-09-16 14:00 89.5 11.8 29.8 2.4 176 6.1 230 24.738 905.0 0.00
2019-09-16 13:55 88.4 11.8 29.1 6.1 244 8.2 220 24.723 839.0 0.00
2019-09-16 13:50 87.9 12.5 30.1 6.8 264 10.4 233 24.750 679.2 0.00
2019-09-16 13:45 88.4 12.5 30.4 4.6 302 6.7 213 24.752 834.0 0.00
2019-09-16 13:40 88.1 12.5 30.1 4.7 241 8.3 191 24.760 847.0 0.00
2019-09-16 13:35 88.9 12.6 30.9 6.1 135 10.6 141 24.764 883.0 0.00
2019-09-16 13:30 88.8 12.6 30.9 5.5 235 9.6 202 24.766 906.0 0.00
2019-09-16 13:25 89.1 12.1 30.2 4.8 135 7.5 151 24.766 907.0 0.00
2019-09-16 13:20 87.3 12.7 29.9 3.4 151 8.1 136 24.767 790.1 0.00
2019-09-16 13:15 86.4 13.1 30.0 4.5 141 7.0 137 24.768 453.6 0.00
2019-09-16 13:10 85.9 14.2 31.5 3.4 144 7.7 116 24.769 385.8 0.00
2019-09-16 13:05 85.9 12.9 29.2 3.5 78 7.7 93 24.770 329.3 0.00
2019-09-16 13:00 86.2 13.4 30.5 5.3 93 8.7 125 24.771 325.0 0.00
2019-09-16 12:55 87.3 13.2 30.9 5.6 115 8.3 81 24.771 386.8 0.00
2019-09-16 12:50 88.0 12.9 30.8 4.9 82 7.3 82 24.773 818.0 0.00
2019-09-16 12:45 87.2 13.2 30.7 6.1 138 9.1 154 24.774 832.0 0.00
2019-09-16 12:40 86.2 13.6 30.8 6.2 92 10.0 142 24.775 556.3 0.00
2019-09-16 12:35 85.4 13.6 30.1 6.8 124 10.8 126 24.774 452.3 0.00
2019-09-16 12:30 85.4 14.5 31.7 7.3 141 12.1 133 24.773 431.1 0.00
2019-09-16 12:25 85.6 14.2 31.3 8.1 152 11.0 149 24.771 415.6 0.00
2019-09-16 12:20 85.7 13.1 29.3 5.8 119 9.6 127 24.771 494.2 0.00
2019-09-16 12:15 86.6 12.7 29.3 5.6 156 9.8 127 24.775 456.1 0.00
2019-09-16 12:10 87.6 12.9 30.6 7.2 131 10.6 130 24.776 888.0 0.00
2019-09-16 12:05 87.1 13.4 31.1 6.5 151 10.7 164 24.776 875.0 0.00
CIRA

Cooperative Institute for Research in the Atmosphere

Fassnacht, Steven

Steven Fassnacht

CIRA Fellow

Job Title:
Professor, Colorado State University
About Me:

Research Interests:

Prof. Fassnacht’s research interests include improving our understanding of snow and cold land hydrological processes, especially considering different complexities of models. These models are used for water resources forecasting, hydrological simulations, and climate modelling. My focuses are improving the data used for modelling and understanding the sensitivity of process formulations. We have tried to improve weather radar estimation of snowfall for hydrological modelling.  We have created a time series of snow water equivalent maps for the Western United States that together with fractional snow covered area data have been assimilated into a hydrological model.  We have examined how wind influences precipitation measurements (as snow) compared to snowpack losses via sublimation and blowing snow.

 

Hydrological and meteorological data exist at various spatial and temporal scales that can influence our analysis.  Use of specific data can tell us a specific story that may not be relevant in the bigger picture. For example, a series of large snow storms in January of 1999 created havoc for transportation in Southern Ontario and early indications were that severe flooding was likely. However, due to several preceeding dry years and a dry spring, the lowest peak flows on record were observed. 

 

We have examined the scales for snow depth sampling using fractal analysis, looked at averaging and sub-setting of large datasets, and investigated the interannual consistency of snowpack distribution patterns.  Together with Nolan Doesken at the Colorado Climate Center, we have examined the measurement of snow depth using Ultra Sonic Snow Depth Sensors.   

Recent work on snow crystals has translated into investigating snow surface roughness. We have developed a method to use digital photography to analysis snow surface roughness and have compared different evaluation metrics.  We have shown how the snowpack surface roughness changes over time, has directionality, scales over space, and is influenced by dust on snow.