Using the Land Ice V&V package to evaluate SMB

Size: px

Start display at page:

Download "Using the Land Ice V&V package to evaluate SMB"

Damian Robertson
5 years ago
Views:

Using the Land Ice V&V package to evaluate SMB Kate Evans

Forrester (PhD student @ Colorado school of mines), Dan Lu

(UCI), Miren Vizcaino (TU Delft) Marguerite, Glacier Bay

1 Using the Land Ice V&V package to evaluate SMB Kate Evans (ORNL, presenting), Joe Kennedy (ORNL, main developer), Mary M. Forrester (PhD Colorado school of mines), Dan Lu (ORNL), Steve Price (LANL), Jeremy Fyke (LANL), Charlie Zender (UCI), Miren Vizcaino (TU Delft) Marguerite, Glacier Bay National Park Thanks to SciDAC BER/ASCR program, PISCEES project for support!

2 LIVVkit Land Ice Verification and Validation toolkit Verification Build confidence during development Python-based, extensible, modular Software, numerical, and performance verification & validation Applied to CISM2 to prepare for release (Lipscomb et al., in prep) Validation Coupled model postprocessing capability matches evaluation for assessing CESM1 with CISM1, Now targeting ACME v1 Now within Earth V&V Evaluation (EVE) which handles ensembles of simulations Includes metrics to compare both gridded and localized in-situ obs and reanalysis data products

3 LIVVkit Land Ice Verification and Validation toolkit: Validation Validation of coupled ESM variables that drive ISM Completed a validation of software using a baseline simulation of CESM1 (first presented in Vizcaino et al., 2013) to validate the methodology and implementation Comparison of a coupled model to a regional model RACMO2.3 to provide capability Inclusion of new SMB data for comparison Current work and Next steps: CESM2 and CISM-Albany 1km runs currently targeted BISICLES assessment of Antarctica is underway POPSICLES, in prep for ACME v1, is a future target

4 Priority: Postprocessing NCO (4.6.5+) scripts postprocess model data by time frequency, years, etc. Creates needed variables (e.g. velnorm from u and v) Submit pbs jobs if memory is an issue Creates annual and seasonal climatologies, areal and daily averages, sums, and time series Performs masking and remapping for comparisons Data is stored in one location for later analysis and comparison. Executing LIVV2.1 will create plots from postprocessed data to show visual differences between model/model or model/other data (RACMO)

5 Traditional Validation Examples of the coupled model

A first look at BISICLES, Antarctica Left: Elevation changes (mmwe/yr) for a 1996-8 POPSICLES* Antarctic simulation.

6 A first look at BISICLES, Antarctica Left: Elevation changes (mmwe/yr) for a POPSICLES* Antarctic simulation. Middle: Elevation changes observed over Antarctica for from CryoSat-2** Right: POPSICLES versus CryoSat-2 data *POPCICLES data courtesy D. Martin and X. Asay-Davis. ** courtesy of M. McMillan and A. Shepherd for validation purposes (McMIllan et al., 2015)

Surface Mass Balance Analysis SMB from CESM1 versus in-situ data, similar to Vizcaino et al. 2013 Includes new data from ice cores or snow pits from Bales et al. (2001); Bales et al.

7 Surface Mass Balance Analysis SMB from CESM1 versus in-situ data, similar to Vizcaino et al Includes new data from ice cores or snow pits from Bales et al. (2001); Bales et al. (2009); and newly available from the ablation zone, Macguth et al. (2016). Within LIVV: execute script to grab data and postprocess for comparison. *New station data is included if it contains elevation, observation start/end records and location, and has a sufficiently long observation record.

Surface Mass Balance in LIVVkit: Basin-scale analysis Map describing the datasets used in model surface mass balance validation. 8 Drainage basins were denoted by Zwally et al. (2012).

8 Surface Mass Balance in LIVVkit: Basin-scale analysis Map describing the datasets used in model surface mass balance validation. 8 Drainage basins were denoted by Zwally et al. (2012). Altimetry data were obtained from the IceBridge project (Lewis et al., 2017) and SMB values along transects represent the annual average. Core/snow pit estimates are sized by the length of their temporal record.

9 Surface Mass Balance in LIVVkit: Basin-scale analysis Model SMB versus PROMICE data* in the ablation zone (SMB<0). Colors correspond to the eight major drainage basins. A 1:1 line is drawn in blue. Same, but from accumulation zone (SMB>0) data** kg m -2 yr -1 *Machguth et al., 2016 *Cogley et al and Bales et al. 2009

Surface Mass Balance in LIVVkit: Basin-scale analysis Histograms of differences between modeled and observed annual SMB at core and snow pit locations ablation and accumulation in GrIS.

10 Surface Mass Balance in LIVVkit: Basin-scale analysis Histograms of differences between modeled and observed annual SMB at core and snow pit locations ablation and accumulation in GrIS. More values near zero imply greater model agreement with core data. All basins values above (below) this line indicate that the model overestimates (underestimates) observations. Basin specific

Right: same but with core and snow pit locations, accumulation and ablation zones.

11 Surface Mass Balance in LIVVkit: By elevation by basin Left: Model elevation vs modeled annual SMB. Right: same but with core and snow pit locations, accumulation and ablation zones. Details: Each point represents a cell location at which an estimate is available. Size of the point represents the number of years in the field record, and all are least one year of data.

12 Surface Mass Balance in LIVVkit: By elevation by transect SMB as a function of elevation (m) at four transect locations in the ablation zone. Red dots: modeled SMB and elevation Blue dots: observed SMB and elevation from snow pit and core field estimates.

13 Surface Mass Balance in LIVVkit: Altimetry transects Modeled vs. observed annual SMB along IceBridge altimetry transects. Blue (red) indicates locations at which the model overestimates (underestimates) surface mass balance relative to IceBridge estimates in accumulation zones.

14 Trying out LIVV Software release with the functionality mentioned here with paper submission in the next month+ Want to be a beta tester? Lots more data and analysis possible. Fork the repo and start validating git clone git@github.com:livvkit/livvkit.git Software details for those who care: Python 3 package Dependencies satisfied by Anaconda/Miniconda Command-line interface Python 2 and 3 cross-compatibility soon Command line interface with 3 main options Analysis scheduler, and run in parallel Components verification, numerics, performance, and validation Extensions infrastructure Custom Analyses JSON config files and python code Minimal working example provided Output website Self contained and portable HTML and javascript

LIVVkit 2.1: Automated and extensible ice sheet model validation

LIVVkit 2.1: Automated and extensible ice sheet model validation Katherine J. Evans 1, Joseph H. Kennedy 1, Dan Lu 1, Mary M. Forrester 2, Stephen Price 3, Jeremy Fyke 3,a, Andrew R. Bennett 4, Matthew