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CliMA · Sep 10, 2024 · 840cc12 · 840cc12
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diff --git a/experiments/calibration/README.md b/experiments/calibration/README.md
@@ -1,10 +1,6 @@
 # ClimaLand calibration
 
-This folder contains scripts to perform calibration on ClimaLand simulations, using [ClimaCalibrate.jl](https://github.com/CliMA/ClimaCalibrate.jl).
-
-Like other ClimaLand/experiments scripts, the Julia environment (Project.toml) is located in .buildkite
-
-The structure of this folder currently mimics [ClimaAtmos.jl/calibration](https://github.com/CliMA/ClimaAtmos.jl/tree/main/calibration).
+This folder contains scripts to perform calibration on ClimaLand simulations.
 
 ## Documentation
 

diff --git a/experiments/calibration/minimal_working_example/minimal_working_example.jl b/experiments/calibration/minimal_working_example/minimal_working_example.jl
@@ -47,3 +47,18 @@ rng = Random.MersenneTwister(rng_seed) # Ollie: pseudo-random number?
 initial_ensemble = EKP.construct_initial_ensemble(rng, prior_g1, N_ensemble) # Ollie: what does this do?
 
 ensemble_kalman_process = EKP.EnsembleKalmanProcess(initial_ensemble, y, Γ, Inversion(); rng = rng) # Ollie: do we need y and Γ?
+
+# We are now ready to carry out the inversion. At each iteration, we get the ensemble from the last iteration, apply
+# ClimaLand_lhf(g1) to each ensemble member, and apply the Kalman update to the ensemble.
+
+for i in 1:N_iterations
+    params_i = get_ϕ_final(prior_g1, ensemble_kalman_process)
+
+    ClimaLand_ens = hcat([ClimaLand_lhf(params_i[:, i]) for i in 1:N_ensemble]...)
+
+    EKP.update_ensemble!(ensemble_kalman_process, ClimaLand_ens)
+end
+
+# Done! Here are the parameters:
+
+final_ensemble = get_ϕ_final(prior_g1, ensemble_kalman_process)