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model sensitivity result

Here's an early model sensitivity result from a series of runs I just did. I tested the model's sensitivity to two parameters:

1. The initial starting temperature: The base case has a uniform initial temperature of 3.8C, and I did two runs where everything else is identical, but I use an initial temperature of 2.8C or 4.8C. These are HUGE swings in initial heat content, but not completely unrealistic, based on observational data.
2. The air temperature. For the base case, I use a forcing field of AT, then I did two runs where I added and subtracted 1C.

I present the results in two different fashions:

1. Heat content, scaled to average temperature
2. Surface temperature at the location of the western NOAA buoy.

here are the results:


The first row shows the case where I start with a different initial condition. What I'm really interested in here is, since they are all being forced identically, they should all eventually approach the same solution. Here we can see that after a year, they are still separated by ~0.1C or so. Most of the difference goes away in the fall cooling period at the end of the year- much of the difference is retained through the winter and much of the summer. It also clearly makes a huge impact on the date of summer overturn.

In the case where I start with an identical initial condition but vary the air temperature by +/- 1C, there is remarkably little difference, but it has just occurred to me that I may not have done these right. For now, ignore the bottom row.