Delighted to announce our new paper on #Antarctica + estimates of surface mass balance is finally out in @EGU_TC
A quick thread on what it means 1/…
Surface mass balance (#SMB) is the budget between snow fall and snow/ice loss by melt + runoff and evaporation at the surface. It's the only way #glaciers + #icesheets can gain #ice - it also needs to balance the loss from calving #icebergs.
#SMB is very difficult to measure on the ground, especially over as large an area as #Antarctica, so usually output from a regional #ClimateModel is used. We looked at data from #HIRHAM #MAR #RACMO #COSMOCLM + #MetUM - to see if they agreed
What we found? well, they're kind of similar....

The range of estimates for the whole of Antarctica was from 1961 Gt/year to 2519 Gigatonnes per year, with an ensemble mean of 2483 Gt.
This is a range equivalent to 0.5 mm per year of global mean #SeaLevelRise
Biggest differences are over ice shelves + around coasts. Model resolution is important, but even models with similar totals over continent diverge as to where most snow falls.
See e.g #RACMO + #MAR, both widely used in #Antarctica
This has implications for ice sheet dynamics .
So can we attempt to say which #ClimateModel is "best"?
@c2kittel compiled a comprehensive dataset of #SMB observations and we compared them to the model output SMB.
Generally, how well a model performs depends on where you look...
Here's the table of statistics if that is your thing...
Unfortunately, we don't have many observations in large areas of #Antarctica, + especially in areas where models disagree a lot (generally because those areas are inaccessible). Bear this in mind if planning fieldwork in #Antarctica ! we REALLY need long time series too!
We also looked at how models perform compared to ground observations at weather stations.
Essentially, all models work pretty well compared to temperature, pressure and winds, though models with nudging (RACMO, MAR, COSMO-CLM) + daily reinitialisation (MetUM) give best results
We found no real trends in #SMB and the driving model - #EraInterim controls the (LARGE) interannual variability
So, what about present day #SeaLevelRise from #Antarctica? Scientists (e.g. #IMBIE) use observed ice change + #SMB from models to work out total change. Compared to annual SMB it's a rather small number, so a small change in SMB can have a big implication.…
In answer to a reviewer comment (ht 🙏 @lenaertsjan + @GorteTessa ) we added a figure comparing different models with the mass change calculated by #IMBIE + in a different paper by Rignot et al.
(note these studies both used RACMO2.3p2 for SMB hence it's not truly independent)
So if higher estimates of SMB (#HIRHAM #MAR) are correct, maybe #Antarctica is net losing a little less ice than previously thought, if COSMO-CLM or MetUM turn out to be more correct then Antarctica is losing *more* ice than estimated by #IMBIE, but it's not quite that simple...
... because #SMB is also important when it comes to ice sheet dynamics and how the #IceSheet flows. Ice shelves are also key buttresses. It's important therefore that we recognise these sources of uncertainty when assessing #SeaLevelRise budgets.

We clearly have more work to do.
Many thanks to fantastic co-authors for data, producing figures + giving me gentle reminders to get going. Also thanks 🙏 to extremely helpful reviewers @lenaertsjan @GorteTessa @MasashiNiwano, 1 anonymous +editor Ayako Abe-Ouchi, all of whom helped to improve the paper immensely
Co-authors (on here) include: @hansen_nicolaj @bjsimonsen @c2kittel @jmvanwessem @charles_amory @xavierfettweis @cecileagosta @nvanlipzig @AlexGossart @nielssouverijns + Fredrik Boberg, Andrew Orr, Tony Phillips, Erik van Meijgaard + Stuart Webster
Huge number of funding agencies, computing providers + coordinators to thank, but especially @esaclimate + #PolarCORDEX @WCRP_Cordex for bringing us together + @ProtectSlr @dmidk + the danish #NCKF (National center for Klima Forskning) for giving us time to finish it off
All data is openly accessible and available, driving model output can be had from @WCRP_Cordex and a processed chunk that ended up in @IPCC_CH #AR6 #Climate #Atlas section is also available on zenodo:


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More from @ruth_mottram

30 Jul 19
Amazing footage - apropos this and the Watson River flood of 2012, my colleagues and I were inspired to write a paper looking at the potential for high runoff events in the future in this paper…
In our future #climate simulations the region in western #Greenland that includes #Kangerlussuaq from the #icesheet to the shores of the #DavisStrait we show how melt + runoff of early 2000s was outpacing mid-century projections*

*Caveat: only one GCM #ECEARTH shown here
The more extreme the scenario - the more extreme the projected melting, but note the very high interannual variability.
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