The effect of nonlinear observation operators for visible and infrared radiances in ensemble data assimilation

Dataset to accompany the manuscript "The effect of nonlinear observation operators for visible and infrared radiances in ensemble data assimilation"

Contains 

raw_datanature run initial conditions (WRF format)forecast ensemble initial conditions (WRF format)

diagnosticsobs_seq.final for each experiment (DART format)- linear posterior with ending "-linear"- nonlinear posterior with ending "-evaluate" at 30s after analysis time

codescript to read "obs_seq.final"-files into pandas.DataFrame (python format)config files DART-WRF for each experiment (python format)obs_seq.out file for single observation experiment examples (DART format)

Experiment naming:VIS ... visible reflectance 0.6 micrometer assimilationWV73 ... infrared 7.3 micrometer assimilationobs10 ... observation density: 1 observation per 10x10 km of domain areaobs30 ... 1 observation per 30x30 kmloc10 ... localization radius: 10 kmno-inflation ... no prior nor posterior covariance inflation in the assimilationreject-small-FGD ... not assimilating observations with a small first-guess departure <= 0.03

Figure - Data:Fig 2a: VIS_obs-i211_loc20_no-inflation

Fig 2b: VIS_obs-i360_loc20_no-inflation

Fig 3: VIS_obs30_loc14_no-inflation

Fig 4, 5, 6: VIS_obs10_loc20_no-inflation, VIS_obs10_loc20_no-inflation_reject-small-FGD

Fig 7: VIS_obs10_loc20_no-inflation

Fig 8: WV73_obs10_loc20_no-inflation