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Overview of AMPS-Polar MM5 real-time forecasting for Antarctica and plans for the assimilation of EOS data David H. Bromwich Polar Meteorology Group, Byrd.

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Presentation on theme: "Overview of AMPS-Polar MM5 real-time forecasting for Antarctica and plans for the assimilation of EOS data David H. Bromwich Polar Meteorology Group, Byrd."— Presentation transcript:

1 Overview of AMPS-Polar MM5 real-time forecasting for Antarctica and plans for the assimilation of EOS data David H. Bromwich Polar Meteorology Group, Byrd Polar Research Center, The Ohio State University, Columbus, Ohio

2 Polar MM5 Overview:  Polar MM5 is an atmospheric mesoscale model adapted for high latitude applications.  Based on the PSU/NCAR fifth generation mesoscale model (MM5)  The polar modifications were developed by BPRC’s Polar Meteorology Group as a result of many years of research  Published validations show high skill over Antarctica and Greenland  Details and code at:  Polar modifications also available to the scientific community through v3.6 MM5 at NCAR

3 What makes Polar MM5?  Polar Meteorology Group optimized MM5 for use over extensive ice sheets:  Modified the ice cloud prediction parameterization  Improved cloud-radiation interaction  Optimized stable boundary layer treatment  Improved calculation of heat transfer through snow and ice surfaces  Added fractional sea-ice surface type.  Recent Modifications:  Developed and implemented nudging upper boundary condition that reduces temperature, wind, and surface pressure biases due to spurious wave reflection at the model top.  Improved calculation of horizontal pressure gradient force over steep topography. This results in improved simulation of orographic precipitation maxima.

4 Polar MM5 Applications:  Precipitation and surface mass balance estimates over Greenland, Iceland, and Antarctica  Arctic river basin modeling  Studies of recent climate variability  Paleoclimate (atmospheric conditions over North America during the Last Glacial Maximum)  Real-time forecasting for high-latitude regions (Antarctic Mesoscale Prediction System)….

5 90-km AMPS domains (90-km, 30-km, 10-km, 3.3-km) 3.3-km (Ross Island) 10-km (South Pole) 10-km (Ross Island)30-km 10-km (Ant. Penin.)

6 AMPS Details:  After the early-season medical evacuation of Dr. Jerri Nielsen from South Pole in October 1999 (Nielsen 2001), the U.S. Antarctic Program (USAP) desired to improve numerical weather forecasting capabilities to support Antarctic aircraft operations.  Soon after, in May 2000, the National Science Foundation (NSF) sponsored the Antarctic Numerical Weather Prediction Workshop at the Byrd Polar Research Center of The Ohio State University (Bromwich and Cassano 2001).  As a result of that meeting and trial runs established earlier in the year at OSU which showed the feasibility of real-time mesoscale atmospheric modeling for Antarctica, the Antarctic Mesoscale Prediction System (AMPS) was implemented in October  AMPS is a collaborative effort between NCAR’s MMM group and Ohio State’s PMG. The role of MMM is to run AMPS twice-daily, provide a web interface and model products to the U.S. and international forecasting community, and maintain the model code. The role of PMG is to continue development of the model physics and to evaluate the system’s performance.  The first guess fields for the initial and boundary conditions are provided by the Global Forecasting System (previously called AVN). Then, an objective analysis of AWS, manned, and limited satellite products (Quikscat, cloud-track winds – 90-km domain only) are integrated into the first guess fields. 3DVAR assimilation system is in testing mode.  AMPS is run twice-daily (00Z and 12Z) at NCAR. The forecasts are available at

7 Model Performance

8 AMPS Bias, Correlation, and NRMSE (statistics for Sep 2001-Aug 2003) 2-m TemperatureSurface Pressure

9 Implementing the Nudging UBC in AMPS: Temperature and Wind Speed Soundings (36-60 hr, averaged over all stations) Nudges the AVN forecast temperature fields in the top 7 levels of the model. In general, correlations and RMS errors are improved throughout model column Temperature biases reduced (become cooler) in top layers of model Winds become stronger throughout column

10 Rescues

11 Rescue of the Dr Ronald Shemenski in April 2001 AMPS (colored) versus observed (bold) winds A medical doctor seriously ill with pancreatitis was evacuated from the South Pole in late autumn, 2001, amid -70 o F temperatures, blowing snow, and near 24 hour darkness. AMPS aided in predicting a window of calm winds (left) for the landing of the Twin Otter (below)

12 Rescue of the Magdalena Oldendorff in June 2002 AMPS Sea Level Pressure and precipitation (green) 28 crew and 79 Russian scientists were evacuated by helicopter to a nearby rescue ship which could not reach the vessel. AMPS aided in predicting a brief window of opportunity during an intense storm (left) for the helicopter flights. The ship could not be freed from the ice until spring (below).

13 Plans for Assimilation of EOS Data

14 Overview:  3-y NASA funded project to study the impacts of data assimilation of EOS products into real-time forecasts 1.Employ high-resolution (Level 2) retrievals of atmospheric temperature and humidity profiles from AIRS (~13km res. at nadir), AMSU-A (~40km res.) and MODIS (~1km res.) as well as atmospheric products from HSB and AMSR-E (5-60km res.) 2.GPS radio occultation data in near real-time 3.MODIS atmospheric motion vectors in near real-time (J. Key) 4.Investigate the impact of the direct assimilation of Level 1B cloud-cleared radiances (time permitting).

15 AMSU Products: 500mb temperature (K: left) and total precipitable water (mm: right) retrievals from the AMSU instrument aboard NOAA-17 daily average for 10 April The region is centered on the Weddell- Sea area of Antarctica. Regional map produced from online NOAA/NESDIS data at

16 GPS Occultations: Projected GPS radio occultation soundings from CHAMP (green filled circles) and SAC-C (violet filled circles) over one-day periods (00 UTC 11 – 00 UTC 12 (left) and 12 UTC 13 – 12 UTC 14 (right), December 2001). Contours designate mean sea level pressure (hPa) of AVN analysis and color shadings represent AVN-ECMWF mean sea level pressure (hPa).

17 Summary:  Polar MM5 has demonstrated considerable skill for a wide range of applications  Real-time forecasting for high-latitude regions (AMPS)  Integral to the success of several rescues  Plans for the assimilation of EOS Data  Various Terra/Aqua (and future X-band?) products  GPS radio occultations  MODIS cloud-track winds

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