“OLYMPEX”

1. “OLYMPEX” • November-December 2014 • Physical validation • Precipitation estimation • Hydrological applications PMM Hydrology Telecon, 22 October 2010

2. Contributors • W. Peterson • R. Cifelli • T. Schneider • D. Lettenmaier • N. Voison • N. Schraner • J. Lundquist • S. Medina • S. Brodzik

3. Maximum The Olympic Peninsula is a“natural laboratory”for precipitation studies Extremely large precipitation accumulation produced as the moist SWly flow impinges on coastal terrain Annual average precipitation (PRISM)

4. Detailed Climatology 5-yr MM5 Nov-Jan precipitation climatology (mm) Verified by gauges: Minder et al. 2008

5. Frequency of occurrence 0°C level (km)  rain at low elevations, snow at higher levels Low 0ºC level Distribution of Nov-Jan 0°C level for flow that is onshore and moist at low levels (KUIL sounding)Mean 0°C level during storms = 1.5 kmSee this full range in individual storms! Plot provided by Justin Minder

6. Persistent southwesterly flow during the winter provides a reliable source of moisture NCEP long-term mean sea level pressure (mb) for winter (December to January) and topography

7. NWS WSR-88D radar to be in place ~2012

8. Data from vertically-pointing S-band radar NOAA Mobile Atmospheric River Monitoring System in Westport (since 2009) Signal-to- noise ratio Height Radial velocity Height Time

9. Detailed gauge network UW fine-scale observing network across a southwestern Olympics ridge Minder et al. 2008

10. UW Real Time Regional Environmental Modeling (Mass & Lettenmaier) • WRF • Ensemble mode • 1.33 resolution • Data assimilation

11. UW Real Time Regional Environmental Modeling (Mass & Lettenmaier) Real time hydrological prediction driven by the UW WRF simulations Also—ESRL will be doing parallel modeling

12. Overview of OLYMPEX layout

13. (Global Hawk?) +NSF Facilities!!?? SNOTEL RAWS S-Band profiler Atmos. River Observatory NPOL WSR-88D Quillayute Rawinsonde

14. Detail of Quinault Valley

16. (i.e. are physical assumptions in GPM algorithms robust under different conditions) Physical validation of rain and snow retrievals • Rain-snow transition on sloping terrain • Melting layer effect on algorithm performance • Different storm sectors—prefrontal, frontal, postfrontal • Different surface conditions—ocean, land, coast, hills, mountains

17. Rain and snow measurement(i.e. validation of its accuracy from satellite instruments mounted on aircraft) • Do precipitation measurements transition accurately from • ocean to land • land to mountains? • Do they handle the orographic enhancementof precipitation? • Can satellite rain measurements be downscaled accurately relative to the topography?

18. Hydrologic applications(i.e. testing whether GPM data can improve streamflow forecasting in complex terrain) • Can satellite rain estimates over hills and mountains provide useful input to real-time hydrologic forecasting? • Does downscaling relative to topography improve hydrologic forecasting? • Can assimilation of satellite rain estimates into regional forecasting models improve hydrological forecasts?

19. Summary OLYMPEX is a fully integrated GV experiment • Physical validation • Rain and snow measurement • Assimilation of GPM measurements into hydrologic forecasts The climatology, terrain, and existing infrastructure have all the ingredients for hosting an integrated campaign This research was supported by NASA grant NNX10AH70G