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
2020-07-15 20:40 69.9 62.4 56.5 5.0 142 8.0 164 24.949 0.0 0.00
2020-07-15 20:35 69.8 63.7 56.9 4.4 179 7.0 178 24.950 0.0 0.00
2020-07-15 20:30 69.8 63.9 57.1 3.6 162 5.4 185 24.950 0.0 0.00
2020-07-15 20:25 70.1 63.9 57.3 4.2 166 6.3 178 24.949 0.0 0.00
2020-07-15 20:20 70.7 63.0 57.5 3.3 172 5.2 164 24.948 0.0 0.00
2020-07-15 20:15 71.2 61.7 57.4 3.8 165 6.9 150 24.946 0.0 0.00
2020-07-15 20:10 71.1 61.2 57.1 5.8 145 8.7 156 24.946 0.0 0.00
2020-07-15 20:05 71.2 61.5 57.3 4.7 172 5.9 142 24.945 0.0 0.00
2020-07-15 20:00 71.3 61.3 57.3 4.5 139 6.3 158 24.945 0.1 0.00
2020-07-15 19:55 71.5 61.0 57.4 3.7 141 5.3 128 24.943 0.4 0.00
2020-07-15 19:50 71.9 60.0 57.2 4.9 145 6.6 135 24.944 1.4 0.00
2020-07-15 19:45 72.1 59.2 57.1 5.4 128 7.7 137 24.944 5.0 0.00
2020-07-15 19:40 72.2 59.0 57.1 5.2 146 6.9 142 24.942 10.7 0.00
2020-07-15 19:35 72.4 58.5 57.1 5.5 151 8.2 139 24.944 11.8 0.00
2020-07-15 19:30 72.5 58.2 57.0 5.5 141 9.5 127 24.945 11.2 0.00
2020-07-15 19:25 72.7 58.4 57.2 6.4 114 8.8 133 24.945 12.3 0.00
2020-07-15 19:20 72.8 58.3 57.3 5.2 134 8.8 128 24.945 17.1 0.00
2020-07-15 19:15 73.0 57.9 57.3 3.3 120 6.4 132 24.945 19.3 0.00
2020-07-15 19:10 73.3 57.2 57.2 4.4 127 8.0 132 24.944 22.6 0.00
2020-07-15 19:05 73.3 56.8 57.1 6.0 125 9.8 144 24.941 26.1 0.00
2020-07-15 19:00 73.4 56.3 57.0 7.4 144 11.0 142 24.940 27.1 0.00
2020-07-15 18:55 73.5 56.1 56.9 7.6 137 11.4 157 24.942 32.3 0.00
2020-07-15 18:50 73.6 55.7 56.8 7.0 142 11.4 138 24.942 35.3 0.00
2020-07-15 18:45 73.7 55.4 56.7 5.9 151 8.9 126 24.939 37.6 0.00
2020-07-15 18:40 73.8 54.8 56.6 6.4 154 8.9 167 24.941 48.2 0.00
2020-07-15 18:35 74.0 54.6 56.6 6.2 146 9.4 137 24.941 60.5 0.00
2020-07-15 18:30 74.1 54.0 56.4 7.5 157 9.6 157 24.942 71.1 0.00
2020-07-15 18:25 74.2 53.2 56.0 7.5 141 10.8 136 24.941 78.2 0.00
2020-07-15 18:20 74.2 53.4 56.2 6.6 96 13.5 145 24.942 85.5 0.00
2020-07-15 18:15 74.2 52.6 55.8 5.9 149 12.3 149 24.940 96.7 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.