Background

OOPS Observation Processing Flow

The flow of H(x) computation and QC filters application in OOPS is shown in the figure below.

Fig. 14 Flow chart for computing H(x) and running QC filters

The Observer calls the preProcess method of ObsFilters before the loop over time steps. After the loop, it calls the priorFilter and postFilter methods just before and just after calling the simulateObs method of ObsOperator. The observation filters are very generic and can perform a number of tasks, but mostly they are used for quality control.

In variational data assimilation, the above flow happens inside of the observation term of the cost function (J_o) evaluation.

Observation Filters

Observation filters have access to:

• Observation values and metadata

• Model values at observations locations (GeoVaLs)

• Simulated observation value (for post-filter)

• Their own private data

Most filters are written once and used with many observation types; several such generic filters already exist and are decribed below. Filters applied to observations from a specific ObsSpace need to be listed in the observations.obs filters section of the input YAML configuration file, together with any options controlling their behavior. Example:

observations:
- obs space:
    name: AMSUA-NOAA19
    obsdatain:
      obsfile: Data/obs/testinput_tier_1/amsua_n19_obs_2018041500_m.nc4
    simulated variables: [brightness_temperature]
    channels: 1-15
  obs filters:
  - filter: Bounds Check
    filter variables:
    - name: brightness_temperature
      channels: 1-15
    minvalue: 100.0
    maxvalue: 500.0
  - filter: Background Check
    filter variables:
    - name: brightness_temperature
      channels: 1-15
    threshold: 3.0