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
2020-04-09 16:25 55.9 32.8 27.0 9.5 124 14.7 140 24.883 368.2 0.00
2020-04-09 16:20 56.3 32.6 27.2 9.3 134 15.1 135 24.883 385.4 0.00
2020-04-09 16:15 56.4 33.2 27.8 7.9 143 13.1 107 24.882 400.9 0.00
2020-04-09 16:10 56.3 31.7 26.6 7.7 116 11.0 129 24.883 419.8 0.00
2020-04-09 16:05 56.5 32.1 27.1 6.4 132 11.0 123 24.883 434.2 0.00
2020-04-09 16:00 56.3 32.1 26.9 5.4 88 9.7 104 24.886 451.3 0.00
2020-04-09 15:55 56.4 32.2 27.1 4.3 63 9.1 80 24.886 468.4 0.00
2020-04-09 15:50 56.8 32.3 27.5 8.1 175 13.9 93 24.887 483.7 0.00
2020-04-09 15:45 56.3 35.2 29.2 5.5 78 8.7 143 24.889 498.9 0.00
2020-04-09 15:40 55.6 33.3 27.2 6.4 92 11.4 154 24.892 513.6 0.00
2020-04-09 15:35 55.5 32.4 26.4 7.1 146 13.0 168 24.894 528.4 0.00
2020-04-09 15:30 56.2 31.7 26.5 9.3 124 14.8 139 24.894 544.6 0.00
2020-04-09 15:25 56.6 30.4 25.9 7.4 153 13.2 78 24.894 559.7 0.00
2020-04-09 15:20 56.3 31.1 26.1 5.8 59 11.8 97 24.896 574.5 0.00
2020-04-09 15:15 55.5 32.5 26.5 6.3 138 10.7 95 24.897 588.4 0.00
2020-04-09 15:10 56.0 32.6 27.0 8.1 89 11.8 103 24.900 601.9 0.00
2020-04-09 15:05 55.1 33.6 27.0 7.5 121 11.7 116 24.901 615.0 0.00
2020-04-09 15:00 55.4 32.9 26.7 8.5 133 12.2 142 24.901 628.7 0.00
2020-04-09 14:55 55.6 31.3 25.7 8.1 39 11.8 118 24.902 641.2 0.00
2020-04-09 14:50 55.8 32.8 26.9 6.9 163 12.2 161 24.905 654.3 0.00
2020-04-09 14:45 55.6 35.9 29.0 8.2 177 10.9 146 24.909 666.2 0.00
2020-04-09 14:40 55.8 32.7 26.9 4.3 88 10.2 88 24.911 679.2 0.00
2020-04-09 14:35 55.0 33.5 26.8 6.3 191 10.7 185 24.911 689.9 0.00
2020-04-09 14:30 55.0 35.2 28.0 9.2 208 14.8 167 24.911 702.2 0.00
2020-04-09 14:25 55.0 35.5 28.2 7.5 151 13.9 89 24.916 712.1 0.00
2020-04-09 14:20 55.1 33.3 26.7 8.3 93 14.4 83 24.917 722.5 0.00
2020-04-09 14:15 54.5 32.9 25.9 7.4 115 10.7 89 24.917 732.3 0.00
2020-04-09 14:10 54.9 33.4 26.7 8.7 87 15.0 92 24.915 744.5 0.00
2020-04-09 14:05 54.8 35.3 27.9 6.5 101 8.8 122 24.917 754.4 0.00
2020-04-09 14:00 54.2 35.4 27.4 5.0 97 8.3 173 24.920 763.7 0.00
CIRA

Cooperative Institute for Research in the Atmosphere

Data Assimilation


The future state of a dynamical system is typically calculated by integrating a numerical model, and depends on parameters such as initial conditions, model errors, empirical parameters of the model, and possibly on lateral boundary conditions. Observations add new information that can be combined with model prediction to produce optimal values of dynamical system parameters and reduce their uncertainty. A mathematical methodology that can accomplish this is called data assimilation.

 

Data assimilation is fundamentally probabilistic since the uncertainty of dynamical system parameters can be described by a probability density function. Since dynamical models add valuable prior information, data assimilation is commonly based on Bayes theorem and thus represents a Bayesian inference. Data assimilation is also nonlinear since dynamical prediction models and observation operators can be highly nonlinear.

 

CIRA data assimilation research has the following goals:

  1. develop new and improved data assimilation methodologies,
  2. apply data assimilation to high-dimensional problems in geosciences and engineering, including carbon cycle, weather, climate, and hydrology.

Since we are primarily interested in geosciences applications to high-dimensional dynamical systems, the high-performance computational component of data assimilation is also of great importance to our research.

 

Typical data assimilation methodologies developed and improved at CIRA are variational, ensemble, and hybrid ensemble-variational methodologies, but we are also exploring other avenues. Our research is encompassing a wide range of applications including carbon cycle, hydrology, climate, and cloud-resolving processes. We are also actively supporting NOAA research and development by conducting data assimilation research using NOAA operational systems and observations.