1. PIPS Development/Validation and a path to automated ice charts
Michael Van Woert
U.S. National Ice Center
IICWG-IV, St. Petersburg
7 April 2003

2. PIPS History PIPS 1.0 (1980’s) -- Regional
Hibler ice model
Climatological ocean (currents and heat fluxes).
Separate models for the Barents and Greenland Seas (25 km).
PIPS 2.0 (1996) Northern hemisphere
Coupled Hibler ice model/Cox ocean model
0.28 degree grid resolution (17-34 km)
15 vertical levels
Solid wall boundaries
Ocean loosely constrained to Levitus climatology
Initialized with NIC/SSMI analysis.

3. Cox Ocean Model Hibler Ice Model
Polar Ice Prediction System 2.0
Forecast Restart
(ice-ocean) or
Climatology
and
SSMI
Ice Concentration
Atmospheric Forcing
NOGAPS
Cox Ocean
Model
Hibler Ice
Model
Model Output
Ice Drift
Ice Thickness
Ice Concentration
Ocean Currents
Ocean Temps
Ocean Salinity
24-hour Forecast
for Ice-Ocean
Restart

4. PIPS Data Initialization
Model initialized daily from SSM/I ice concentration (CAL/VAL algorithm)
PIPS ice concentration is replaced only at locations where observed ice concentration is >80% or <50% and the difference between the two fields is >10% or >5% respectively
PIPS ice thickness and ocean mixed layer temperature fields are adjusted to be consistent with the SSM/I observations
CAL/VAL 2/26/02
PIPS Analysis 2/26/02
12/7/2018
IAHR

5. PIPS 2.0 Atmospheric Forcing
Model uses daily NOGAPS fields (1 degree resolution)
Fields used: Surface Pressure, Surface Air Temperature, Surface Vapor Pressure, Net Shortwave Radiation and Downwelling Longwave Radiation, surface wind stress

6. Operational Oceanography
The norm for ocean forecast verification…
“It looks like the ocean,
it must be correct.”

7. For Dec 30, 2000
a) IABP buoy
drift and pressure
b) PIPS ice drift
c) PIPS ice
concentration
d) PIPS ice
thickness

8. Forecast Skill Scores #1
Af = error of the forecast system
Ap = error of a perfect forecast
Ar = error of a reference forecast
In this formulation SS represents the improvement in accuracy of the forecast with respect to the reference forecast, relative to the total improvement in accuracy.

9. Forecast Skill Scores #2
Error defined as:
Skill score becomes
f = Forecast field
O = Observed or analyzed field
R = Reference field (Yet to be defined)
P = Perfect forecast field (Forecast = Observed)
Note: MSE for a perfect forecast is 0. That is: MSE(P,O) = 0.

10. Forecast Skill Scores #3
Perfect forecast SS=1; MSE(f,O)=0
No forecast skill SS=0; MSE(f,O)=MSE(R,O)
In general:
SS>0 (skillful) when MSE(f,O) < MSE(R,O)
SS<0 (unskillful) when MSE(f,O) > MSE(R,O)
MSE(R,O) is the yardstick for measuring skill!

11. Climatological Skill Scores
5% Threshold
SS24 (Solid line) ~ 0.8
PIPS Does much better than a climatological forecast

12. Persistence Skill Scores
5% Threshold
SS24 (solid line) ~ 0.1 to 0.3
PIPS slightly better than a persistence forecast in most months

13. CLIPER Skill Scores 5% Threshold SS24 (solid line) ~ -0.2 to 0.2
Linear combination of CLImatology and PERsistence does better than
PIPS during the months of Oct-Feb!
PIPS only slightly better than CLI-PER during other months
Forecast model must be exceptional to add significant skill!

14. PIPS Goal
New ice model based on technology gained in the 1990’s. Include the ability to forecast regions of lead formation (anisotropic rheology)
Coupled to an updated ocean model
Using improved atmospheric forcing
Improved data assimilation
10 km grid resolution

15. Global Ocean Model (NCOM) CICE Model
Polar Ice Prediction System 3.0
Forecast Restart
(ice-ocean) or
Ocean Analysis/
SSMI Ice
Concentration
and
Satellite Ice
Drift
Atmospheric Forcing
NOGAPS
Global Ocean
Model (NCOM)
CICE
Model
Model Output
Ice Drift
Ice Thickness
Ice Concentration
Ice conv/div
Ice strength
Ocean Currents
Ocean Temps
Ocean Salinity
24-hour Forecast
for Ice-Ocean
Restart

16. PIPS 3.0 – Global Ocean Model
PIPS 3.0 will be coupled to the NCOM global ocean model (includes daily data assimilation)
1/8 degree resolution with polar cap
Arctic resolution ~10 km
Model run time (with analysis) – 12 min/day using 128 processors (IBM Winterhawk 2)----5 days = 60 hours, 8 days = 96 hours

17. NCOM Global Grid Northern Hemisphere
Use lat-long grid below 32 N (grid extends to 78.5 S).
Use curvilinear grid above 32 N to cover the arctic.
Use dx=dy locally from about 50 S to 32 N.
Grids tried:
1/2 deg (dx = 55.6 km at eq) from 72 S to 72 N (720 x 422 x 30).
2/3 deg (dx = 78.2 km at eq) global (512 x 320 x 30).
1/3 deg (dx = 39.1 km at eq) global (1024 x 640 x 20). ~1/4 deg avg.
1/6 deg (dx = 19.6 km at eq) global (2048 x 1280 x 40). ~ 1/8 deg avg.
AMOP 9; 1/8/01

18. Global NCOM Ocean Model
www7320.nrlssc.navy.mil/global_ncom
41 vertical sigma-z levels NOGAPS winds with the assimilation
1m z-level top, 20 sigma of MODAS synthetic T/S fields
48-hr forecast each day Polar Overlap

19. PIPS 3.0 Ice Model LANL model CICE –Hunke, Lipscomb, Dukowicz)
CICE, developed at Los Alamos National Laboratory( LANL), is available for public use via their website.

20. CICE – LANL Sea Ice Model
EVP (efficient, improved response to forcing)
Energy conserving Bitz and Lipscomb (1999) thermodynamics
Multi-category, linearly remapped ice thickness
Energy-based ice ridging
Other improvements to physics parameterizations

21. PIPS 3.0 – Atmospheric Forcing
PIPS 3.0 will be driven by the Navy’s global atmospheric model (NOGAPS)
NOGAPS commenced running at 50 km resolution on Sept 25, 2002

22. Planned Data Initialization /Assimilation
SSMI will be upgraded to the NASA Team 2 alogrithm
Assimilation of satellite derived ice drift and buoy drift data (Preller et al., Tos, 2002) if available.
Assimilation of ocean observations into the coupled ice ocean models can improve the sea ice forecast by improving the ocean model forecast

23. PIPS 3.0 March Ice Concentration

24. CICE results from
1-year simulation
using 1984 ECMWF
forcing

25. Model Initialization/Nowcast
Goal: To develop an fully automated sea ice chart (nowcast).
Minimum requirements: C, h, V
Current practices:
PIPS ice concentration (C)is updated at locations where observed ice
concentration is >80% or <50% and the difference between the two fields
is >10% or >5% respectively
PIPS ice thickness (h) and is adjusted to be consistent with the SSM/I
PIPS ice motion (V) is being update with Objective Interpolation
Issues:
Concentration and thickness sensitive to large SSM/I errors
Concentration observations not necessarily consistent with ice dynamics

26. Initialization Methods
Simple
Replace model with observations or employ basic weighting (Method for PIPS Sea Ice Conc. Initialization)
Statistical
Minimize errors in statistical (e.g. least squares) manner
Optimal Interpolation (PIPS 3.0, Ice Drift Assimilation)
Kalman Filter
Variational
Minimize cost function (e.g. disagreement between
model and observations) subject to constraints (e.g.,
model physics)
Complex and can be difficult to develop

27. The Model Velocity: Concentration: Thickness:
Sh is the total ice growth
Sc is the rate at which ice-covered area is
created by melting and freezing

28. Free Drift Model
Free Drift
2% of Wind speed
20o Right of wind

29. Variational Method
Data inputs:
Prior day’s, 24 hour forecasts of u24, v24, C24, h24
Current days 85 GHz drift (uo, vo)
Current day’s SSM/I ice concentrations Co
Impose constraints
fh(u,v,h)=0
fC(u,v,C)=0
The sprit of the approach is to keep the initialized fields
close to the observations while exactly satisfying the constraints.
l1 and l2 are unknown constant Lagrange Multipliers
the w’s are data-specific, user-defined weights

30. Conclusions T=PIPS 2.0 -- 24 hour Skill referenced to climo ~ 0.85
Due to daily reinitialization, PIPS provides good forecast relative to climo
T= PIPS hour Skill referenced to persist ~ 0.2 (Mar-Oct)
Sea ice fields most variable in the MIZ
Poor performance during “freeze-up” – MIZ parameterizations & forcing ?
T=24 hour PIPS Skill referenced to CLIPER ~ 0.1 (Mar-Oct)
Non-skillful forecasts Oct – Feb
During winter months linear combination of persistence & climo does best
PIPS 3.0 will come online shortly
Will include assimilation of sea ice motion
Further work is required to accurately initialize PIPS
Ancillary benefit will be an Automated Sea Ice Chart

31. The End