The Antarctic Mesoscale Prediction System

1. The Antarctic Mesoscale Prediction System David H. Bromwich, Andy Monaghan Polar Meteorology Group Byrd Polar Research Center The Ohio State University Columbus, Ohio, USA Jordan G. Powers Mesoscale and Microscale Meteorology Group National Center for Atmospheric Research Boulder, Colorado, USA 20 September, 2006

2. AMPS Overview

3. AMPS: The Antarctic Mesoscale Prediction System • Nested NWP system dedicated to supporting • the operations of the U.S. Antarctic Program • and International programs. • Employs “Polar MM5”, a limited-area atmospheric model adapted for high-latitude applications by Ohio State University’s Polar Meteorology Group at the Byrd Polar Research Center. • Project began in October 2000 as a small collaboration between 2 U.S. institutions, and since has grown into an international program. • Other nations are developing similar systems (Aust., Italy)

4. Current AMPS domains (60-km, 20-km, 6.7-km, 2.2-km) 60-km 20-km 6.7-km (Ross Island) 2.2-km (Ross Island) 6.7-km (South Pole) 6.7-km (Ant. Penin.)

5. 60-km 20-km 60-km 6.7-km (South Pole) 6.7-km (Ant. Penin.)

6. AMPS Accomplishments

7. Rescue of the Magdalena Oldendorff in June 2002 • German supply vessel became trapped in thickening sea ice with 107 aboard • South Africa sent the S.A. Agulhas to rescue the passengers. • AMPS forecasts were used by the South African Weather Service (SAWS) for Agulhas’ southward journey • AMPS indicated a brief window of favorable weather during which the passengers were airlifted to safety Oldendorff and Argentina’s Almirante Irizar X AMPS Sea Level Pressure and precipitation (green)

8. AMPS NWP for S.A. Agulhas in 2005/2006 Austral Summer • South Africa’s S.A. Agulhas makes an annual relief voyage to Antarctica • AMPS provides tailored forecast products to SAWS • 20-km domain over SANAE • 15-km domain over ship track • AMPS visibility and wind forecasts have proven especially valuable • AMPS products are freely available to the international community Materials courtesy I. Hunter, SAWS press release, 2 February 2006

9. AMPS Validation Work

10. Validation AMPS Forecasts of Clouds LEFT: AMPS 00z 13 Dec forecasted integrated cloud liquid water (blue – gray shades) and cloud ice (white shades). RIGHT: Low resolution IR satellite composites from the UW-AMRC archive Materials courtesy R. Fogt and D. Bromwich, BPRC

11. 5.1 : 5.3 4.6 : 6.0 4.4 : 4.7 1.8 : 2.1 5.2 : 4.2 2.7 : 4.1 4.2 : 3.0 6.4 : 5.1 9.9 : 8.4 8.3 : 10.1 3.0 : 2.1 5.4 : 4.4 10.3 : 8.3 9.9 : 12.8 3.8 : 4.5 1.8 : 1.5 3.3 : 2.5 4.5 : 4.6 3.9 : 3.9 1.5 : 2.6 Using Self Organizing Maps (SOMs) to compare the frequency of ‘observed’ and forecast circulation features in AMPS Right: A 5x4 SOM array is employed to characterize the sea level pressure over the Ross Sea (inset below) into 20 distinct patterns. Then the 060 hour forecasts are compared to the analyses (000) to determine modeled circulation biases in AMPS/ AMPS Frequency of Occurrence (000 : 060) Materials courtesy J. Cassano, CIRES, U. Colorado, USA

12. Analyzing Mountain Waves in the complex terrain near McMurdo Station during intense wind storms • Downslope windstorm on lee slopes from large-amplitude mountain waves • Hydraulic jump downstream as flow adjusts to ambient conditions • Incorrect flow pattern sets up a deflection zone over the McMurdo area • Hydraulic jump located at interface of deflection zone, which is upstream of McMurdo, causing wind speeds to be too low there McMurdo 0000 UTC 16 May 2004 sea-level pressure (hPa) and surface streamlines. Steinhoff et al. (2006)

13. Evaluating AMPS 500-hPa Performance (12-36 hr forecasts) • High correlations for temperature, geopotential height, and wind speed. • Biases are typically small, and either +/- (not systematic) • Lower skill in dewpoint forecasts – may be due to low absolute humidity at 500 hPa, which makes small errors look big. Geopotential Hgt Temperature Dewpoint Temp Wind Speed Bromwich et al. (2005)

14. Evaluating the AMPS 10-km vs 3.3-km domain (24-36 hr forecasts) Observed=thick gray 3.3-km = solid black 10-km = dashed black Ratio of 3.3-km standard deviation to 10-km standard deviation (normalized) Spectral Density vs frequency for wind speed at 2 AWS sites near McMurdo Conclusion – The 3.3-km domain is more sensitive and more accurate than the 10-km domain Bromwich et al. (2005)

15. Evaluating AMPS Performance in data-sparse regions with COSMIC GPS radio occultation soundings • When GPS satellites communicate, their signals travel through slices of earth’s atmosphere. • The atmosphere refracts the GPS signals a small amount depending temperature, humidity, and pressure. • Thus, the refractivity residuals from these communications can be converted to soundings of temperature and humidity. • Conversely, as shown here, modeled temperature and humidity fields can be converted to refractivity and compared to COSMIC soundings. Location of COSMIC Soundings over Southern Ocean from 50-60o S. Courtesy of K. Manning, NCAR, USA

16. Evaluating AMPS Performance in data-sparse regions with COSMIC GPS radio occultation soundings • When GPS satellites communicate, their signals travel through slices of earth’s atmosphere. • The atmosphere refracts the GPS signals a small amount depending temperature, humidity, and pressure. • Thus, the refractivity residuals from these communications can be converted to soundings of temperature and humidity. • Conversely, as shown here, modeled temperature and humidity fields can be converted to refractivity and compared to COSMIC soundings. Above: Comparison of WRF and MM5 refractivity statistics versus COSMIC soundings from 50-60oS for the 60-km AMPS domain for a 22-forecast period during austral winter, 2006. Both MM5 and WRF are currently being run side-by-side in AMPS in order to compare the skill of WRF versus MM5 as it undergoes development. This figure indicates that that WRF is comparable to MM5 over the Southern Ocean, and that the lowest skill in both models occurs in the lower troposphere. This suggests attention should be focused on resolving marine stratus and the treatment of the PBL within the models. Location of COSMIC Soundings over Southern Ocean from 50-60o S. Courtesy of K. Manning, NCAR, USA

17. Ongoing AMPS Development

18. Developing Polar WRF to replace Polar MM5 in AMPS (testing done over Greenland) RunCorrelationBias WRF - Swiss Camp 0.865 0.47 MM5 – Swiss Camp 0.938 4.32 WRF - Summit 0.863 1.83 MM5 – Summit 0.896 2.34 WRF simulations with Hall-Thompson microphysics, YSU PBL, Noah LSM, Dudhia shortwave and RRTM longwave radiation, and AVN-driven boundary conditions MM5 simulations with Eta PBL, Reisner microphysics and ECMWF-driven boundary conditions Bromwich, Hines, and Bai, 2006

19. Variational and Ensemble Data Assimilation in AMPS • Motivation: • Antarctica is a challenge for Data Assimilation. • Implementation of 3D-Var in AMPS. • Research advanced DA techniques. • Investigate data impact (GPS, AWS, AIRS, MODIS). • Modeling Systems: • MM5 (currently testing WRF ARW). • WRF-Var (3D- in 2005, 4D- in 2006). • Ensemble Square Root Filter (EnSRF). 00 UTC 15th May 2004 (+/-2hrs): Thinned AIRS obs (above), MODIS AMV obs (below) Materials courtesy D. Barker, NCAR

20. Assimilating MODIS cloud-track winds into AMPS ms-1 ms-1 34 34 • 25 25 L L Sfc Winds (ms-1) SLP (hPa) L STD MOD1 Standard AMPS forecast AMPS forecast with MODIS Winds • Use of MODIS winds dramatically increases number of upper-air observations over an otherwise data-sparse continent • Preliminary results show a statistically significant positive impact Materials courtesy J. Powers, NCAR

21. Cold Start (AVN) No GPS GPS MM5 4D-Var Assimilation of GPS Radio Occultation data over Antarctica 1200 UTC 11 + 66H Wee et al. (2006) Wee et al. (2006) assimilated 50+ GPS RO soundings from CHAMP and SAC-C over the Antarctic over a two-day period and demonstrated positive impact on the prediction of an intense Antarctic cyclone out to 3 days. The GPS RO soundings account for ~3% of the data used. The recently-launched COSMIC constellation will record many daily RO soundings over Antarctic for years to come. Solid contour: Predicted Sea Level Pressure by MM5 using different initial conditions. Dashed lines are verifying ECMWF analysis.

22. AMPS forecast archive used for science

23. Climate of the McMurdo region based on 1-year of AMPS 3.3-km forecasts • Key Points: • First high-resolution model climatology of the rugged McMurdo region. • Time-mean vortices occur in the lee of Ross Island, perhaps a factor in the high incidence of mesoscale cyclogenesis noted in this area. • The first-ever detailed precipitation maps of the region. • Orographic precipitation maxima occur on the southerly slopes of Ross Island and mountains to the southwest. • A precipitation-shadow effect for the McMurdo Dry Valleys. Annual Mean Fields: Monaghan et al. (2005)

25. Websites • Realtime live action server for AMPS: • http://www.mmm.ucar.edu/rt/mm5/amps/ • http://polarmet.mps.ohio-state.edu/PolarMet/antarcticnwp.html • AMPS archives based at NCAR • Multiple domains, 3 or 1 hourly forecast data • AMPS-related publications by Bromwich’s group: • http://polarmet.mps.ohio-state.edu/PolarMet/abstracts.html • 2006 Antarctic Meteorological Observation, Modeling, and Forecasting Workshop • http://www.mmm.ucar.edu/events/antarctic06/index.php

26. Antarctic & Southern Ocean Regional Reanalysis • “This is an idea that I am developing for the NSF IPY call with a probable submission date of February 2007.” • “The spatial resolution will likely be 20 km for the modern satellite era and 60 km before that.” (Bromwich)