Come and work for COSIMA! This is an opportunity for a software engineer to work at the cutting edge of computer science and ocean-sea ice modelling:
Please contact Andy Hogg for details.
The global ocean overturning circulation is the planetary-scale movement of waters in the vertical and north-south directions. It is the principal mechanism by which the oceans absorb, sink, and redistribute heat and carbon from the atmosphere, thereby regulating Earth’s climate. Despite its importance, it is impossible to observe directly, and must be inferred from sparse and infrequent proxy measurements. The main upward branches of the overturning circulation are located in the Southern Ocean, where strong westerly winds upwell waters from below. Thus, changes in these westerly winds will lead to changes in the overturning circulation, and, subsequently, Earth’s climate.
In a recently submitted paper, we introduce a new tool that we call the Ekman streamfunction to analyse the change of the winds in a framework that is directly comparable with the overturning circulation. We test the Ekman streamfunction with model output from ACCESS-OM2-01 in which the overturning circulation is measured directly. We find throughout much of the Southern Ocean, the Ekman streamfunction provides a robust indicator of the strength and variability of the overturning circulation, with exceptionally high correlation. Our new tool provides a novel approach for reexamining existing datasets of winds measured from satellites, to infer recent changes in the overturning circulation.
“The Ekman Streamfunction: a wind-derived metric to quantify the Southern Ocean overturning circulation”; Stewart, Hogg, England, Waugh & Kiss, Submitted to Geophysical Research Letters.
Unreviewed submission available here: https://www.essoar.org/doi/abs/10.1002/essoar.10506547.1
NH: Testing spack. On lightly supported cluster. Installed WRF and all dependencies with 2 commands. Only system dependency was compiler and libc. Automatically detects compilers. Can give hints to find others. Tell it compiler to use for build. Can use system modules using configuration files. AH: Directly supported modules based on Lmod. Talked to some of the NCI guys about Lmod, as the raijin version of modules was so out of date. C modules has been updated, so they installed on gadi. Lmod has some nice features, like modules based on compiler toolchain. Avoids problem with Intel/GNU subdirectories that exist on gadi. NCI said they were hoping to support spack, by setting up these configs so users could spack build things. Didn’t happen, but would have been a very nice way to operate to help us.
NH: Primary use case in under supported system where can’t trust anything to work. Just want to get stuff working. Couldn’t find an MPI install using latest/correct compiler. gadi well maintained. See spack as a portability tool. Containment is great.
AH: Was particularly interested in concretisation, id of build, allows reproducibility of build and identification of all components.
NH: Rely on MPI configured for system. Not going to have our own MPI version. AH: Yes. Would be nice if someone like Dale made configs so we could use spack. Everything they think is important to control and configure they can do so. Probably not happy with people building their own SSL libraries. Thought it would improve NCI own processes around building software. Dale said he found the system a but fragile, too easy to break. When building for a large number of users they weren’t happy with that. Thought it was a great idea for NCI, to specify builds, and also easy to create libraries for all compiler toolchains programmatically.
AG: Haven’t tried recently.
RY: Stripe count affects non-compressed more than compressed. PIO doesn’t work perfectly with Lustre, fails with very large stripe count. With large file sizes (2TB) can be faster to write compressed IO due to less IO time.
RY: Early stage of work. Many compression libraries available. Here only used zlib. Other libraries will lead to smaller size and faster compress times. Can be used as external HDF filter. File created like this requires filter to be compiled into library.
NH: How big is measurement variability? RY: Can be very different, took shortest one. Sometimes double. TEST_MPP_IO is much more stable. Real case much less so.
NH: Experiencing similar variability with ACCESS model with CICE IO. Anything we can do? Buffering? RY: Can increase IO data size and see what happens. Thinking it is lustre file system. More stripe counters touches more lustre servers. Limit to performance as increase stripe counters, as increase start to get noise from system. NH: What are the defaults, and how do you set stripe counters? RY: Default is 1, which is terrible. Can set using MPI Hints, or use lfs_setstripe on a directory. Any file created in that directory will use that many stripe counters. OMPIO and ROMIO have different flags for setting hints. Set stripe is persistent between reboots. Use lfs_getstripe to check. AH: Needs to be set to appropriate value for all files written to that directory.
NH: Did you change MPI IO aggregators or aggregator buffer size. RY: Yes. Buffer size doesn’t matter too much. Aggregator does matter. Previous work based on raijin with 16 cores. Now have 48 cores, so experience doesn’t apply to gadi. Aggregator default is 1 per node for ROMIO. Increase aggregator, doesn’t change too much, doesn’t matter for gad. OMPIO can change aggregator, doesn’t change too much.
NH: Why deflate level 4? Tried any others? RY: 4 is default. 1 and 4 doesn’t change too much. Time doesn’t change too much either. Don’t use 5 or 6 unless good reason as big increase in compression time. 4 is good balance between performance and compression ratio.
NH: Using HDR 5 c1.12.x. With previous version of HDF, any performance differences? RY: No performance difference. More features. Just more stable with lustre. Using single stripe counter both work, as soon as increase stripe counter v1.10 crashes. Single stripe counter performance is bad. Built my own v1.12 didn’t have problem.
NH: Will look into using this for CICE5. AH: Won’t work with system HDF5 library?
AH: Special options for building HDF5 v1.12? RY: Only if you need to keep compatibly with v1.10. Didn’t have any issues myself, but apparently not always readable without adding this flag. Very new version of the library.
AH: Will this be installed centrally? RY: Send a request to NCI help. Best for request to come from users.
AH: Worried about the chunk shapes in the file. Best performance with contiguous chunks in one dimension, could lead to slow read access for along other dimensions. RY: If chunks too small number of metadata operations blow out. Very large chunks use more memory and parallel compression is not so efficient. So need best chunk layout. AH: Almost need a mask on optimisation heat map to optimise performance within a useable chunk size regime. RY: Haven’t done this. Parallel decompression is not new, but do need to think about balance between IO and memory operations.
RF: Chunk size 50 in vertical will make it very slow for 2D horizontal slices. A global map would require reading in the entire dataset. RY: For write not an issue, for read yes a big issue. If include z-direction in chunk layout optimisation would mean a large increase in parameter space.
NH: AK has been running 0.1 seeing a lot of variation in run time due to IO performance in CICE. More than half the submits are more than 100%worse than the best ones. Is this system variability we can’t do much about? Also all workers are also doing IO. Don’t have async IO, don’t have IO server. Looking at this with PIO. Have no parallelism in IO so any system problem affects our whole model pipeline. RY: Yes IO server will mean you can send IO and continue calculations. Dedicated PE for IO. UM has IO server. NH: Ok, maybe go down this path AH: Code changes in CICE? NH: Exists in PIO library. Doesn’t exist in fortran API for the version we’re using. Does exist for C code. On their roadmap for the next release. A simple change to INIT call and use IO servers for asynchronous IO. Currently uses a stride to tell it how many IO servers per compute. AH: Are CICE PEs aligned with nodes? Talked about shifting yam, any issues with CICE IO PEs sharing nodes with MOM. NH: Fastest option is every CPU doing it’s own IO. Using stride > 1 doesn’t improve IO time. RY: IO access a single server, doesn’t have to jump to different file system server. There is some overhead when touching multiple file system servers when using striping for example.
AH: Run time instability too large? AK: Variable but satisfactory. High core count for a week. 2 hours for 3 months. AH: Still 3 month submits? AK: Still need to sometimes drop time step. 200KSU/year. Was 190KSU/year, but also turned off 3D daily tracer output. AH: More SUs, not better throughput? AK: Was hitting walltime limits with 3D daily tracer output. Possibly would work to run 3 months/submit with lower core count without daily tracers.
AK: Queue time is negligible. 3 model years/day. Over double previous throughput. Variability of walltime is not too high 1.9-2.1 hours for 3 months. Like 10% variability.
AH: Any more crashes? Previously said 10-15% runs would error but could be resubmitted. AK: Bad node. Ran without a hitch over weekend. NH: x77 scratch still an issue? AK: Not sure. AH: Had issues, thought they were fixed, but still affected x77 and some other projects. Maybe some lustre issues? AK: Did claim it was fixed a number of times, but wasn’t.
AH: Across tripole seam one of the velocity fields wasn’t in the right direction, caused weird flow. AK: Not a crash issue. Just shouldn’t happen, occurs occasionally. The velocity field isn’t affected, seen in some derived terms, or coupling terms. Do sometimes get excess shear along that line. RF: There is some inconsistencies with how some fields are being treated. Should come out ok. Heat fluxes slightly off, using wrong winds. They should be interpolated. What gets sent back to MOM is ok, aligned in the right spot. No anti-symmetry being broken. AK: Also true for CICE? RF: Yeah, winds are being done on u cells correctly. Don’t think CICE sees that. AH: If everything ok, why does it occur? RF: Some other term not being done correctly, either in CICE or MOM. Coupling looks ok. Some other term not being calculated correctly.
AH: How much has our version of CICE changed from the version CSIRO used for ACCESS-ESM-1.5 NH: Our ICE repo has full git history which includes the svn history. Either in the git history or in a file somewhere. Should be able to track everything. Can also do a diff. I don’t know what they’ve done, so can’t comment. Have added tons of stuff for libaccessom2. Have back-ported bug fixes they don’t have. We have newest version of CICE5 up to when development stopped which include bug fixes. As well as CICE6 back ports. AH: Can see you have started on top of Hailin’s changes. NH: They have an older version of CICE5, we have a newer version which includes some bug fixes which affect those older versions.
RF: Also auscom driver vs access driver. Used to be quite similar, ours has diverged a lot with NH work on libaccessom2. We do a lot smarter things with coupling, with orange peel segment thing. There is an apple and an orange. We use the orange. NH: Only CICE layout they use is slender. They don’t use special OASIS magic to suppler that. Definitely improves things a lot in quarter degree. Our quarter degree performance a lot better because of our layout. AH: The also have 1 degree UM, so broadly similar to a quarter degree ocean. NH: Will make a difference to efficiency. AH: Efficiency is probably a second order concern, just get running initially.
AH: Congratulations to work to improve init and termination time. RF: Mostly NH work. I have just timed it. NH: PIO? RF: Mostly down to reading in restart fields on each processor. Knocked off a lot of time. A minute or so. PIO also helped out a lot. Pavel doing a lot of IO with CICE. Timed work with doing all netCDF definitions first and then the writing, taking 14s including to gather on to a single node and write restart file. The i2o.nc could be done easily with PIO. Also implemented same thing for MOM, haven’t submitted that. Taking 4s there. Gathering global fields is just bad. Causes crashes at the end of a run. There are two other files, cicemass and ustar do the same thing, but single file, single variable, so don’t need special treatment.
RF: Setting environment variable turns off UCX messages. Put into payu? Saves thousands of lines in output file.
The Australian Research Council (ARC) recently announced $1.1M of funding for a new 4-year COSIMA project. The new project is funded under the ARC’s Linkage Project scheme, and is supported by 4 industry partners: The Department of Defence, Bureau of Meteorology, Australian Antarctic Division and CSIRO. This funding will continue to support the Australian ocean and sea ice modelling community to develop and distribute open source model configurations.
The aims of the proposal are to:
Work on the new project is expected to begin in 2021, initially focussing on the adoption of the MOM6 ocean model for regional applications. A schematic of the intended workflow can be found in the figure below.
As well as developing new model configurations, the new COSIMA project will have a stronger emphasis on developing tools for data analysis, data sharing and publication. The new project will start with a kick-off meeting in the first half of 2021 (details to be announced).
Announcement (updated 17 June 2021):
140TB of model output data from three consecutive 61-year (1958-2018) runs with COSIMA’s ACCESS-OM2-01 0.1-degree global coupled ocean – sea ice model is now available for anyone to use (see conditions below).
We recommend using the COSIMA Cookbook to access and analyse this data, which is all catalogued in the default cookbook database. A good place to start is the data explorer, which will give an overview of the data available.
Alternatively, the data can be directly accessed at NCI, mostly from
and with a few fields (see details below) from
You will need to be a member of the cj50 and ik11 groups to access this data directly or via the cookbook – apply at https://my.nci.org.au/mancini/project-search if needed.
The cj50 subset of the data (111TB) can be downloaded from here for those not on NCI.
The first cycle (01deg_jra55v140_iaf) was run under interannually-varying JRA55-do v1.4.0 forcing from 1 Jan 1958 to 31 Dec 2018, starting from rest with World Ocean Atlas 2013 v2 climatological temperature and salinity. The run configuration history is in the 01deg_jra55v140_iaf branch in the 01deg_jra55_iaf repository. It is based on that used for Kiss et al. (2020) but has many improvements to the forcing, initial conditions, parameters and code which will be documented soon. Summary details of each submitted run are tabulated (and searchable) here.
The second cycle (01deg_jra55v140_iaf_cycle2) continues from the end of the first cycle, with an identical configuration except that its initial condition was the final ocean and sea ice state of the first cycle, and some differences in the output variables. The run configuration history is in the 01deg_jra55v140_iaf_cycle2 branch and summary details of each submitted run are here.
Similarly, the third cycle (01deg_jra55v140_iaf_cycle3) continues from the end of cycle 2, with different output variables. The run configuration history is in the 01deg_jra55v140_iaf_cycle3 branch and summary details of each submitted run are here.
There are many outputs available for the entire run, with additional outputs available only in selected years (see below for details).
MOM5 ocean model outputs are saved under self-explanatory filenames in
and CICE5 sea ice model outputs are in
(if there are too many files to list with
ls, narrow it down, e.g. by including the year, e.g.
Annual restarts (on 1 Jan each year) are also available at
for anyone who may wish to re-run a segment with different diagnostics or branch off a perturbation experiment.
Conditions of use:
We request that users of this or other COSIMA model code or output data:
Details of model outputs available
ty_trans_int_zdiagnostic was incorrect and has therefore been deleted from cycles 1 and 2. Workarounds are given here.
bottom_tempare conservative temperature, rather than the potential temperature specified in the OMIP protocol (Griffies et al., 2016) – see this discussion. If you need potential temperature, use
Cycle 3: mostly in
/g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v140_iaf_cycle3 but with some (marked in italics) in
An increasingly important aspect of model simulations is to be able to share our data. Over the last few years we have been working on methods to routinely publish our most important simulations. This publication process is designed to allow any users, worldwide, to be able to pick up our model output and test hypotheses against our results. It will also allow journal publications to be able to cite our model output.
Currently we have 5 different datasets within the headline COSIMA Model Output Collection, which can be found here:
For users with NCI access this data is housed under the cj50 project.
We are planning to add new datasets in the coming months.
(Paul’s report is attached at the end)
PL: Looking at scaling. Started with ACCESS-OM2, but went to testing MOM5 directly with MOM5-SIS. Using POM25, global 0.25 model with NYF forcing. The model MW developed for testing scaling prior to ACCESS-OM2. Had to add specify min_thickness in ocean_topog_nml.
PL: Tested the scaling of 960/1920/3840/7680/15360, with no masking. Scales well up to some point between 7680 and 15360.
PL: Tested effect of vectorising options (AVX2/AVX512/AVX512-REPRO). Found no difference in runtime with 15360 cores. MW: Probably communication bound at the CPU count. Repro did not change time.
MW: Never seen significant speed up from vectorisation. Typically only a few percent improvement. Code is RAM bound, so cannot provide enough data to make use of vectorisation. Still worth working toward a point where we can take advantage of vectoeisatio.
PL: Had one “slow” run outlier out of 20 runs. Ran 20% slower. Ran on different nodes to other jobs, not sure if that is significant. MW: IO can cause that. AH: Andy Hogg also had some slow jobs due to a bad node. AK: Job was 20x slower. Also RYF runs become consistently slower a few weeks ago. MW: OpenMPI can prepend timestamps in front of output, can help to identify issues.
PL: Getting some segfaults in ompi_request_wait_completion, caused by pmpi_wait and pmpi_bcast. Both called from the coupler. NH: Could be a bad bit of memory in the buffer, and if it tries to copy it can segfault. PL: Thinking to run again using valgrind, but would require compiling own version of valgrind wrapper for OpenMPI 4.0.2. Would be easier to Intel MPI, but no-one else has use this. Saw some cases similar when searching which were associated with UCX, but sufficiently different to not be sure. These issues are with highest core count. MW: Often see a lot of problems at high core counts. NH: Finding bugs can be a never ending bug. Use time wisely to fix bugs that affect people. MW: Quarter degree at 15K cores would have very small tile sizes. Could be the source of the issue. AH: This is not a configuration that we would use, so it is not worth spending time chasing bugs.
PL: Next testing target is 0.1 degree, but not sure which configuration and forcing data to use. Will not use MOM5-SIS, but will use ACCESS-OM2 for direct comparison purposes. AK: Configurations used in the model description paper have not been ported to gadi. Moving on to a new iteration. Andy Hogg is running a configuration that is quite similar, but moving to new configurations with updated software and forcing. Those are not quite ready.
PL: Need a starting configuration for testing. Want to confine to scalability testing and compiler flags. NH: ACCESS-OM2 is setup to be well balanced for particular configurations. Can’t just double CPUs on all models as load imbalance between submodels will dominate any other performance changes. Makes it a problematic config for clean configurations for things like compiler flags. MW: Useful approach was to check scalability of sub-model components independently. Required careful definition of timers to strategically ignore coupling time. MOM was easy, CICE was more difficult, but work with Nic’s timers helped a lot. Try to time the bits of code that are doing computation and separate from code that waits on other parts. Coupled model is a real challenge to test. Figure out what timers we used and trust those. Can reverse engineer from my old scripts.
PL: Should do MOM-SIS scalability work? MW: Easier task, and some lessons can be learned, but runtime will not match between MOM-SIS and ACCESS-OM2. Would be more of a practice run. PL: Maybe getting out of scope. Would need 0.1 MOM-SIS config. RY: Yes we have that one. If PL wanted to run ACCESS-OM2-01 is there a configuration available? AK: Andy Hogg’s currently running configuration would work. PL: Next quarter need to free up time to do other things.
MW: Might be valuable to get some score-p or similar numbers on current production model. Useful to have a record of those timings to share. Scaling test might be too much, but a profile/timing test is more tractable. RY: Any issues with score-p? Overhead? MW: Typical, 10-20%, so skews numbers but get in-depth view. Can do it one sub-model at a time. Had to hack a lot scripts, and get NH to rewrite some code to get it to work. score-p is always done at compile time. Doesn’t affect payu. Try building MOM-SIS with score-p, then try MOM within ACCESS-OM2. Then move on to CICE and maybe libaccessom2. PL: Build script does include some score-p hooks. MW: Even without score-p MOM has very good internal timers. Not getting per-rank times. score-p is great for measuring load imbalance. AH: payu has a repeat option, which repeats the same time, which removes variability due to forcing. Need to think about what time you want to repeat as far as season. AK: CICE has idealised initial ice, evolves rapidly. MW: My earlier profile runs had no ice, which affects performance. MW: Not sure it is huge, maybe 10-20%, but not huge.
MW: Overall surprised at lack of any speed up with vectorisation, and lack of slow-down with repro. PL: Will verify those numbers with 960 core config.
AH: Surprised how well it scaled. Did it scale that well on raijin? MW: The performance scaling elbow did show up lower. AH: 3x more processors per node has an effect? MW: Yes, big part of it. AH: 0.1 scaled well on raijin, so should scale better on gadi. 1/30th should scale well. Only bottleneck will be if the library can handle that many ranks.
NH: If repro flags don’t change performance that is interesting. Seem to regularly have a “what trade off does repro flags have?”, would be good to avoid. MW: Probably best to have an automated pipeline calculating these numbers. NH: People have an issue with fp0 flag. MW: Shouldn’t affect performance. NH: Make sure fp0 is in there. MW: Agree 100%.
AH: Do we have a gadi compatible master branch on gadi? AK: No, not currently. NH: At a previous TWG meeting I self-assigned getting master gadi compatible. Merged all gadi-transition branches and tested, seemed to be working ok. Subsequent meeting AK said there were other changes required, so stopped at that point. gadi-transition branches still exist, but much has already been merged and tested on a couple of configurations. Have since moved to working on other things.
NH: Close if AK has all the things he wants into gadi-transition branch. Previous merge didn’t include all the things AK wanted in there. Happy to spend more time on that after finishing JRA55 v1.4 stuff.
NH: Made code changes in all the models, but have not checked existing experiments are unchanged with modified code.
NH: v1.4 has a new coupling field, ice calving. Passing this through to CICE as a separate field. In CICE split into two fields, liquid water flux and a heat flux. MOM in ACCESS-CM2 already handles both these fields. Just had to change preprocessor flags to make it work for ACCESS-OM2 as well.
NH: Lots of options. Possible to join liquid and solid ice at atmosphere and becomes the same as we have now. Can join in CICE and have a water flux but not a heat flux.
AH: A quick update with Navid’s error. Made a little mpi4python script to run before payu to check status of nodes, and all but root node had a stale version of the work directory. Like it hadn’t been archived. Link to executable was gone, but everything else was there. Reported to NCI, Ben Menadue does not know why this is happening. Also tried a delay option between runs and this helped somewhat, but also had some strange comms errors trying to connect to exec nodes. Will next try turning off all input/output can find in case it is a file lock error. Have been told Lustre cannot be in this state.
MW: In old driver do a lot of moving directories from work to archive, and then relabelling. Is it still moving directories around to archive them? Maybe replace with hard copy of directory to archive. MOM6 driver is the MOM5 driver, so maybe all old drivers are doing this. Definitely worth understanding, but a quick fix to copy rather than move.
NH: Filesystem and symbolic links might be an issue MW: Maybe symbolic links are an issue on these mounted filesystems. AH: There was a suggestion it might be because it was running on home which is NFS mounted, but that wasn’t the problem. MW: Often with raijin you just got the same nodes back when you resubmit, so maybe some sort of smart caching.
Version 1.0.7 is now installed in conda/analysis3-20.01 (analysis3-unstable
AH: payu is now 100% gadi compatible. Default cpus/node is now 48 and memory 192GB/node. Python interpreter, short path and manifests are scanned to automatically determined from model config and manifests. Using qsub_flags to manually specify storage flags no longer works, as automatically determined storage flag option is appended and the manually specified one no longer works.
RF: Paul Sandery having issues getting 0.1 deg model working. [AH: turns out it was a typo in config.yam]
AH: No need for the number of cpus in a payu job to be divisible by the number of CPUS in a node. Request however many the job uses, and payu will pad the request to make sure the PBS submission is requesting an integer number of nodes if ncpus is greater than the number in a single node. PL: Rounds up for each model? AH: No, just the total. MW: Will spread models across ranks, so a rank can have different models on it.
AH: Andy Hogg ran out 80 odd submits with the tenth model. Occasional hang, resubmit ok. Might be more stable than raijin.
AH: Navid has MOM6 model that cannot run more than a couple of submits without it crashing with an error that it cannot find the executable. Weird error, let me know if you see anything similar.
re. gadi-transition, we could proceed like so:– we’ve also been transitioning libaccessom2 to use submodules for its dependencies instead of cmake https://github.com/COSIMA/libaccessom2/issues/29 which would require this commit https://github.com/COSIMA/libaccessom2/tree/53a86efcd01672c655c93f2d68e9f187668159de (not currently in gadi-transition branch)– get the libaccessom2 tests working https://github.com/COSIMA/libaccessom2/issues/36– there’s a gadi-transition branch libaccessom2, cice and mom that could be merged into master. They use openMPI4.0.2– there’s also a gadi-transition branch for all the primary (ie JRA, non-minimal) configurations but the exe paths would need to be updated before merging to master– the access-om2 gadi-transition branch would then need to be updated to use the correct submodules for model components and configurations. We also want to remove the core and minimal config submodules https://github.com/COSIMA/access-om2/issues/183also fyi the current gadi build instructions are here
This report summarises the fourth meeting of the Consortium for Ocean Sea Ice Modelling in Australia (COSIMA), held in Canberra on 3-4 September 2019. Shweta Sharma has provided a more informal (and entertaining) report here.
The annual COSIMA workshop aims to:
Attendees included Alberto Alberello (U Adelaide), Christopher Bladwell (UNSW), Fabio Boeira Dias (UTAS/CSIRO), Gary Brassington (BOM), Matt Chamberlain (CSIRO), Navid Constantinou (ANU), Prasanth Divakaran (BOM), Kelsey Druken (NCI), Matthew England (UNSW), Ben Evans (NCI), Hakase Hayashida (IMAS, UTAS), Petra Heil (AAD & AAPP), Andy Hogg (ANU), Ryan Holmes (UNSW), Maurice Huguenin (UNSW), Yi Jin (CSIRO), Andrew Kiss (ANU), Andreas Klocker (UTAS), Qian Li (UNSW), Kewei Lyu (CSIRO), Simon Marsland (CSIRO), Josue Martinez Moreno (ANU), Richard Matear (CSIRO), Ruth Moorman (ANU), Adele Morrison (ANU), Eric Mortenson (CSIRO), Jemima Rama (ANU), Paul Sandery (CSIRO), Abhishek Savita (UTAS/IMAS/CSIRO), Callum Shakespeare (ANU), Shweta Sharma (UNSW), Callum Shaw (ANU), Taimoor Sohail (ANU), Paul Spence (UNSW), Kial Stewart (ANU), Veronica Tamsitt (UNSW), Mirko Velic (BOM), Nick Velzeboer (ANU), Jingbo Wang (NCI), Xuebin Zhang (CSIRO), Xihan Zhang (ANU), Aihong Zhong (BOM), plus those who attended via video conference.
Andrew Kiss (ANU): ACCESS-OM2 update
Simon Marsland (CSIRO): ACCESS and CMIP6
Hakase Hayashida (IMAS, UTAS): Preliminary results of biogeochemistry simulation with ACCESS-OM2 and plans for OMIP-BGC and IAMIP
Ben Evans (NCI): Addressing the next HPC challenges for Climate and Weather
Veronica Tamsitt (UNSW): Lagrangian pathways and residence time of warm Circumpolar Deep Water on the Antarctic continental shelf
Ruth Moorman (ANU): Response of Antarctic ocean circulation to increased glacial meltwater
Kewei Lyu (CSIRO): Southern Ocean heat uptake and redistribution in theoretical framework and model perturbation experiments
Fabio Boeira Dias (UTAS/CSIRO): High-latitude Southern Ocean response to changes in surface momentum, heat and freshwater fluxes under 2xCO2 concentration
Xuebin Zhang (CSIRO): Dynamical downscaling of climate changes with OFAM3
Matt Chamberlain (CSIRO): Multiscale data assimilation in Bluelink Reanalysis
Paul Sandery (CSIRO): A data assimilation framework for ocean-sea-ice prediction
Prasanth Divakaran (Bureau of Meteorology): OceanMAPS 3.3 Developments
Ryan Holmes (UNSW): Atlantic ocean heat transport enabled by Indo-Pacific heat uptake and mixing
Eric Mortenson (CSIRO): Decoupling of carbon and heat uptake rates of the global ocean over the 21st century
Christopher Bladwell (UNSW): Diahaline transport in global ocean models
Abhishek Savita (UTAS, IMAS, CSIRO): Uncertainty in the estimation of global and regional ocean heat content since 1970
Gary Brassington (BOM): Comparison of ACCESS-OM2-01 to other models and observations
Xihan Zhang (ANU): Gulf Stream separation in ACCESS-OM2
Alberto Alberello (U Adelaide): Impacts of winter cyclones on sea ice dynamics
Petra Heil (AAD): Sea ice in the ACCESS-OM2-01: Exploring near-coastal processes
Open discussion highlighted a number of potential avenues for work in the near-term, as well as some suggestions for directions that could be included in a future COSIMA funding bid.
Additional discussion points are given here.
The COSIMA Most Selfless Contributor Awards for 2017, 2018 and 2019 were presented in absentia to
in appreciation of their tireless efforts which have greatly improved the software used by the COSIMA community.
Date: 14th August, 2019