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
2020-09-18 16:10 74.0 40.4 48.5 4.5 85 6.4 72 0.000 119.9 0.00
2020-09-18 16:05 74.3 38.0 47.0 5.0 83 7.1 95 0.000 122.3 0.00
2020-09-18 16:00 74.7 37.7 47.2 5.4 83 7.9 78 0.000 156.1 0.00
2020-09-18 15:55 74.6 37.4 46.9 5.3 78 6.6 88 0.000 284.1 0.00
2020-09-18 15:50 73.9 38.8 47.3 5.1 85 7.8 96 0.000 225.6 0.00
2020-09-18 15:45 74.1 39.3 47.8 4.6 78 6.4 89 0.000 137.1 0.00
2020-09-18 15:40 74.5 38.5 47.6 4.3 106 7.8 122 0.000 160.0 0.00
2020-09-18 15:35 74.6 37.7 47.1 4.0 90 6.6 154 0.000 188.9 0.00
2020-09-18 15:30 74.7 37.2 46.9 6.9 131 9.2 127 0.000 147.0 0.00
2020-09-18 15:25 75.6 35.4 46.3 8.1 135 11.1 108 0.000 201.0 0.00
2020-09-18 15:20 76.3 34.5 46.2 6.0 144 8.8 140 0.000 363.1 0.00
2020-09-18 15:15 76.1 33.1 45.0 7.0 141 10.0 143 0.000 391.3 0.00
2020-09-18 15:10 76.1 33.6 45.5 6.9 140 10.5 137 0.000 342.5 0.00
2020-09-18 15:05 76.5 32.1 44.6 7.2 122 9.6 98 0.000 443.5 0.00
2020-09-18 15:00 76.7 32.8 45.3 5.6 84 10.4 98 0.000 505.7 0.00
2020-09-18 14:55 76.2 34.6 46.3 5.8 78 10.1 135 0.000 541.6 0.00
2020-09-18 14:50 75.4 32.4 43.9 7.4 142 11.7 140 0.000 411.1 0.00
2020-09-18 14:45 76.1 32.5 44.5 6.1 112 9.4 159 0.000 309.1 0.00
2020-09-18 14:40 75.8 33.4 45.0 5.1 107 8.9 104 0.000 526.2 0.00
2020-09-18 14:35 75.4 35.8 46.5 4.8 131 7.2 120 0.000 393.2 0.00
2020-09-18 14:30 75.1 36.1 46.5 5.2 107 7.1 121 0.000 296.1 0.00
2020-09-18 14:25 74.6 37.1 46.8 5.2 107 8.5 102 0.000 314.8 0.00
2020-09-18 14:20 74.8 34.0 44.6 5.4 130 9.2 121 0.000 408.9 0.00
2020-09-18 14:15 74.9 34.0 44.7 5.8 147 12.6 123 0.000 400.4 0.00
2020-09-18 14:10 75.1 33.0 44.0 7.5 121 13.5 121 0.000 553.1 0.00
2020-09-18 14:05 75.2 33.3 44.4 7.2 167 11.3 162 0.000 582.5 0.00
2020-09-18 14:00 74.7 34.2 44.6 9.8 168 15.0 142 0.000 606.9 0.00
2020-09-18 13:55 74.7 34.2 44.7 8.7 136 13.1 137 0.000 618.4 0.00
2020-09-18 13:50 74.1 36.6 45.9 8.2 159 12.1 103 0.000 608.9 0.00
2020-09-18 13:45 74.3 35.8 45.4 7.9 86 13.6 95 0.000 617.9 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.