Xia Li (Univ. of Utah): Effects of sea ice leads on low clouds in winter Arctic
Vivian Chao (Texas A&M Univ.): Impacts of the pattern effect on the cloud feedback
Angshuman Modak (Stockholm Univ.): Assessing the historical pattern effect estimates and climate sensitivity based on different temperature datasets
Marc Alessi (Colorado State): Accounting for uncertainty of projected SST patterns in coupled climate models
Diego Jiménez (MPI-Meteorology): Tropical stratospheric upwelling sets the tropical equilibrium climate sensitivity by reducing the effective forcing
Moritz Günther (MPI-Metorology): Climate sensitivity to volcanic aerosol forcing
09:09:30 From Cristian Proistosescu : Hm. I thought he only big difference between AMIPII dataset the HadISST was an adjustment such that the monthly mean of reinterpolated data preserves monthly means? (The ‘bcgen’ adjustment). When applying the other datasets are you doing this adjustment?
09:10:11 From Gavin Schmidt : I missed what constraint is being used here? Is it from the historical warming record?
09:12:30 From angshuman.modak@misu.su.se : Yes, historical warming record used 1871-2017
09:12:54 From Diego Jiménez de la Cuesta Otero : Vaccaro dataset then is showing a efficacy of the heat uptake lower than one in terms of the Winton Model?
09:15:16 From angshuman.modak@misu.su.se : Vaccaro does shows an opposite when entire period but agrees for the recent period
09:19:51 From Kyle Armour : Really interesting, Marc. If you did this exercise in a coupled setup (nudging SSTs in these regions, instead of using the Green’s functions) would you get the same answer as this? It seems the answers might differ, but I’m not sure.
09:20:58 From Timothy Merlis, Dr. : Marc, you have many realizations for the future. Have you or others looked at spread across large ensembles for the historical period?
09:21:40 From Yue Dong : Hi Marc, great talk! Have you compared the projected feedbacks/SST patterns between high emission scenario vs low emission scenario (eg rcp2.6)?
09:23:07 From Marc Alessi (speaker; he/him) : @Timothy We have to a first degree looked at historical internal variability/climatological biases to get an idea of how to motivate our future projections, but that’s really the extent of what we’ve done for the historical
09:24:40 From Duncan Watson-Parris : Hi Marc, great talk! You’ve convinced me of the importance of these effects for projections, but do we have sufficient observations to improve these patterns in our models? It seems a tall order given the large internal variability
09:25:46 From Marc Alessi (speaker; he/him) : @Yue Thanks! We actually have looked at incorporating this uncertainty between different emissions scenarios, and it ends up being quite substantial depending on what region is simulated incorrectly. What I mean by “substantial” is that this SST pattern uncertainty adjusts the uncertainty of each emissions scenario to the point where the emissions scenarios overlap in their temperature projections much longer than what we currently understand. We are comparing our new uncertainty not just to internal variability, but also scenario and model uncertainty (which I didn’t have time to show today)
09:28:04 From Diego Jiménez de la Cuesta Otero : @ Li-Wei it seems than in ceres the change is lambda is more extratropical, why is that?
09:28:52 From Eric DeWeaver : @Li-Wei, how come the CMIP6 lambda map has no negative delta lambda centers?
09:29:36 From Marc Alessi (speaker; he/him) : @Duncan Thanks! I agree it will be difficult to fix this SST pattern uncertainty, and I haven’t exactly thought much about it… separating internal variability and an inability of a coupled model to correctly simulate an SST pattern is already hard to argue, but I think Seager et al 2019 does a good job
09:29:37 From Subbiah Renganathan, Monisha Natchiar : @Li-Wei Only 27% of \Delta \lambda is reproduced by the CMIP6 models? Didn't fully understand that slide.
09:30:42 From Mark Zelinka : Vivian — nice analysis. If you relax the constraint that the chunks of time over which lambda is computed are adjacent (consecutive), does the model distribution of delta lambda change at all?
09:36:24 From Jonah Bloch-Johnson (he/him) : Will there be fewer frozen leads in the future?
09:36:24 From Chao, Li-Wei : @Subbiah We found 27% of delta lambda from the CMIP6 control runs fall in the uncertainty range of the observations. This suggests that the pattern effect is strong and can be captured by the models. I’m willing to discuss the details with you.
09:36:27 From Chris Holloway : Xia - Nice talk. More leads also appeared to increase the higher cloud amount, do you know why this might be, and does this also affect lower clouds?
09:37:01 From Diego Jiménez de la Cuesta Otero : @Xia Li Maybe I miss it, but what is the spatial scale of the sea-ice leads? Do a GCM can simulate that spatial scale? Or they are fully parameterised?
09:39:40 From Chao, Li-Wei : @Mark Zelinka We have tested to calculate the cloud feedback in different length (10-year, 11-year, etc) and found the results are similar.
09:43:19 From Chao, Li-Wei : @Eric DeWeaver I didn’t go in the details due to the time interests. When calculating delta lambda in climate models, we always select the larger lambda and minus the smaller lambda to make it consistent and easier to compare with the observations. That’s why we only see positive delta lambda in the distribution plot.
09:44:43 From Keith Shine : Is it water vapour change as a result of the BDC change that drives the ECS change. Or is it clouds?
09:45:12 From XIA LI : @ Diego. I may forget to mention this. Leads are usually several m to several km in width and hundreds m to hundreds of km in length. So in most current GCMs, it’s fully parameterized (mainly the area fraction)
09:45:46 From Gavin Schmidt : Some models don’t have stratospheric ozone feedbacks - does that complicate how you interpret the changes in the CMIP6 models?
09:45:54 From Keith Shine : Thank you - very interesting!
09:46:46 From isaacheld : Diego, is your 1D estimate meant to be a tropical mean or for the equatorial region of strongest upwelling?
09:46:46 From Subbiah Renganathan, Monisha Natchiar : how do you separate circulation changes in the troposphere from that in the stratosphere to study their impact on ECS?
09:46:51 From Chao, Li-Wei : @Diego I believe that could be due to the changes in surface warming pattern in the observations is also more extratropical. But we do not have much understanding on the reason yet.
09:47:05 From Gavin Schmidt : There was an issue in the preliminary HadGem3 model I think
09:47:31 From Eric DeWeaver : @Diego: there is a recent attempt to estimate the BDC during the LGM that finds a weakening by 4-10% depending level. I wonder if that’s enough to matter. https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2019GL086271
09:49:27 From Diego Jiménez de la Cuesta Otero : @issacheld it is a mean representation of the tropics -30N to 30N. It is also clear sky.
09:50:31 From Diego Jiménez de la Cuesta Otero : The circulation change is represented as a cooling term applied from the convective top upwards. Then we are not simulating tropospheric circulation changes.
09:51:46 From Diego Jiménez de la Cuesta Otero : @Eric DeWeaver Thanks for the reference, that seems really interesting.
09:52:15 From Karsten Haustein : @Moritz: So this is for (CMIP) models, isn’t it? Would you say that it works the same way in the real world?
09:54:10 From Allegra N. LeGrande : Have you looked at volmip ?
09:54:14 From Timothy Merlis, Dr. : comment: the short timescale more negative response to volcanic eruption forcing has implications for geoengineering
09:56:25 From Eric DeWeaver : @angshuman: can you look at the different SST datasets and guess which is which? Or are the differences more subtle?
09:56:43 From Ceppi, Paulo A : For Moritz: was there no difference in cloud feedbacks across time periods? That would be different from what we find in 4xCO2 simulations.
09:57:00 From Yuan-Jen Lin : @Moritz, thanks for the great talk! I wonder how rapid adjustments affect your results shown here.
09:58:45 From Cristian Proistosescu : Not a question about the talks but given the captive audience, I’m going to plug in the CLIVAR Pattern effect workshop that will happen in may. Abstracts opened today, and a tentative agenda is up. https://usclivar.org/meetings/pattern-effect-workshop.
10:02:02 From Ceppi, Paulo A : Makes sense, thanks!
10:02:42 From Yuan-Jen Lin : thank you Moritz!