Validation of US Navy Polar Ice Prediction (PIPS) Model using Cryosat Data

1. Validation of US Navy Polar Ice Prediction (PIPS) Model using Cryosat Data Kim Partington1, Towanda Street2, Mike Van Woert2, Ruth Preller3 and PamPosey3 1Vexcel UK, Newbury, United Kingdom 2US National Ice Center, Washington DC, USA 3Naval Research Laboratories, MS, USA 1. Summary 4. PIPS: Assessments to Date Until recently, PIPS assessment focused on ice drift validation using Arctic drifting buoys (Preller and Posey, 1996). Van Woert et al. (2003) carried out a formal assessment of PIPS 2.0 using forecast skill methodology adapted from the meteorological community. Their assessment focused on sea ice concentration fields for a 25 month period in 2000-2002. The US Navy Polar Polar Ice Prediction System, PIPS 3.0, is a state of the art coupled ice-ocean model that will shortly replace its predecessor, PIPS 2.0, and will be used to generate forecasts of ice conditions in the Arctic for operational purposes. To date, assessments of PIPS have been constrained by the lack of information on sea ice thickness. We plan to evaluate PIPS 3.0 using Cryosat sea ice thickness data in conjunction with other sources of data and to use the results to guide future improvement of sea ice forecasting. 2. PIPS: Application The US National Ice Center has a mandate to provide timely information on sea-ice conditions, globally. The provision of such information by necessity includes forecasts and PIPS was developed for the purpose of providing forecasts in the northern hemisphere. The forecasts include information on ice concentration, ice thickness and ice drift and are provided to analysts at NIC. The forecasts are not provided directly to users, but are an important information source for analysts in preparing ice charts and their own text forecasts. Figure 3. Distribution of skillful forecasts (blue) and non-skillful forecasts for PIPS 2.0, based on an assessment of ice concentration. (a) December 2000 and (b) December 2001 (from Van Woert et al., 2003) Van Woert et al. (2003) found that performance of the 24 hours forecast was in general better than persistence, climatology or a combination of the two for the 25 month period, except from December 2000 – January 2001, though the ability to forecast areas of melt-out was relatively poor and areas of ice concentration reduction or increase showed modest performance. In short, there is significant room for improvement in the forecasting capabilities of PIPS that an assessment against ice thickness would support. Figure 1. Spatial domain and grid of PIPS 2.0 in the Arctic. 3. PIPS: Development PIPS has been available for forecasting in versions up to 2.0 for the last 15 years. PIPS 2.0, used by the US National Ice Center for forecasts in northern ice-infested seas, is a coupled ice-ocean model with spatial resolution of 0.28 degrees (17 -33 km) and 15 vertical z-levels in the ocean, as well as sophisticated ice thermodynamics. PIPS 2.0, run at the Naval Oceanographic Office at Stennis Space Center, MS, is forced by the Navy Operational Global Atmospheric Prediction System (NOGAPS) atmospheric fields and generates a 72-hour forecast of ice drift, ice concentration and ice thickness (as shown below). In its most recent version (3.0) it supports non-linear vertical ice temperature profile, vertically varying salinity, the addition of a snow layer, brine pocket parameterization and assimilation of ice motion and satellite derived ice concentration data. PIPS 3.0 is expected to become operational late in 2005. 5. PIPS: Proposed Assessment Activities • We propose to address the following questions by comparison of PIPS 3.0 forecast fields with Cryosat sea ice products. • Is the spin-up ice thickness realistic in terms of mean, distribution and variability and do any initial spin-up biases get removed or enhanced over the season? • Are the changes in ice thickness over time realistic and how do they compare to basic combinations of persistence and climatology as investigated for PIPS 2.0 by Van Woert et al. (2003)? • Can we diagnose the causes of changes in ice thickness in the model and tie these same causes into observations, i.e. in terms of advection, compaction or melt? • Finally, what are the implications of these results for the implementation and design of PIPS and perhaps other approaches to modeling? Ice drift forecast Ice thickness forecast Acknowledgements This work is planned to be carried out under Contract NRL N00173-01-P-6204 with the US Naval Research Laboratories, Stennis, MS. The authors acknowledge the support of ESA in the expected provision of data from Cryosat. divergence convergence References Ice concentration forecast Figure 2. PIPS 2.0 forecasts of Ice thickness, ice drift and Ice concentration for March 3, 2005. Van Woert, M., Zou, C-Z., Meier, M., Hovey, P., Preller, R. and Posey, P., 2003, “Forecast verification of the Polar Ice Prediction System sea ice concentration fields”. J. Atmos. Ocean. Tech.., 21, 944-957. Preller, R.H. and P.G. Posey, 1996, “Validation Test Report for a Navy Sea Ice Forecast System: The Polar Ice Prediction System 2.0”. Naval Research Laboratory NRL/FR/7322—95-9634.