PPE results - Precipitation and LHFLX #282
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Broadly we have too much precipitation in NorESM3, and this got worse with b06: The PPE spans a broad range of global mean precip values, but these follow to some degree the TREFHT, which is too low: |
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@MichaelSchulzMETNO @benmsanderson the regional precipitation used for the regression plots above can be downloaded as csv here and are saved as netcdf in The masks are not perfect, with the oceanmask using a snapshot of the ice edge and the Amazon including the Andes, so keep that in mind: |
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Here's my quick analysis of the amazon PPE parameter dependencies from the PPE thread. TLDR: @kjetilaas , maybe try this: Constraining by RESTOM, global PRECT and salinity trend gives some scope for tuning amazon precip- but we do cut off the high end:
The parameter responses for global and amazon precip are similar, apart from C0 - where the effect is reversed. Hence reducing C0 should increase Amazon precip, but decrease global precip on average
the actual regression prediction for the amazon is a little noisier than the global case, but still enough to illustrate predictability. Finally, here's an attempt to maximise amazon precip within the constraints of global precip and RESTOM. The below plot shows the initial global parameter constraint(green) and the top 10th percentile range of amazon precip. And here's the mean parameter values in that subset of amazon maximising runs: Parameter Mean Valuemicro_mg_dcs 0.000578 Here's another pespective - we have this trade-off of c0_ocn and c8 which allows us maintain RESTOM=0. within that space, if we choose combinations with low c0ocn and low c8, that tends to increase Amazon precip. Similarly, dcs and tiedke_add should be on the lower end.
mapping back to our original ensemble - run #69 is the best of our current extended simulations, but that actually has middle-of the road values for co_ocn and c8 and there are higher variants in the 15 year set. I think it's possible the mean parameters above might be able to push it up further than anything in the current ensemble. I think it is possible that we don't have a member which simulataneously maxes out all the degrees of freedom for amazon precip.
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I think reducing c0_ocn to 0.005 is fine, but I do not think we should go much further down. It will likely result in more sea-ice however so the ocean parameters need to counter that. c8 can likely also be reduced. It may increase climate sensitivity though. The increase in c0_ocn from CAM5 and onwards compared to earlier versions was done in order to mimic the "iris" effect in the warm Pacific (Warming of SST may decrease high cloud cover so a negative cloud feedback) |
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Also although I would ideally like to keep the dcs value in the middle of the road I do not think we can go further down than 0.0006. Even that vale will likely give a too low LWCF. tiedke_add may potential counter that. |
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Following @adagj example, I am starting a new discussion based on the PPE results, focusing on precipitation and more generally the hydrological cycle.
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