1. Selected CalWater AR Accomplishments

2. AR-SBJ IOPs 3-7 in Feb/Mar 2011 AR-SBJ IOPs 1-2 in Dec 2010 2

3. Summary – three field seasons from 2009-2011 13 Sierra Barrier Jet events observed during IOPs – 4 strong (> 25 m/s) – 7 moderate (15-25 m/s) – 2 weak (< 15 m/s) 10 Atmospheric river events observed during IOPs – 1 strong – 7 moderate – 2 weak 3

4. Kinematic and Thermodynamic Structures of Sierra Barrier Jets and Overrunning Atmospheric Rivers during a Land-falling Winter Storm in Northern California Kingsmill, Neiman, Moore, Hughes, Yuter and Ralph Journal of Hydrometeorology, 2013 Observing network clearly monitored both the AR and SBJ during two sub- periods within the 2-day IOP –SBJ western edge detected –SBJ deepened toward the north –AR rode up and over the SBJ Landfalling storm 14-16 February 2011 –Multi-Doppler scanning-radar retrievals –Multi-wind-profiler time series diagnostics –Balloon soundings

5. Neiman, Hughes, Moore, Ralph, and Sukovich MWR 2013, in press (July 2013) *Schematic based on a composite of the 13 strongest SBJ cases observed at the SHS profiler between 2009-2011. *Profilers at CCO, CFC, and CCR also recorded data and composited during these SBJ cases. *A 6-km regional reanalysis dataset from the WRF model provided additional information. *The SBJ parallels the Sierra over the eastern Central Valley (CV): core 1 km above ground. *The SBJ core increases in altitude up Sierra windward slope and poleward over Nern CV. *Inland penetration of AR through San Francisco Bay gap contributes to SBJ deepening/moistening over Nern CV. *Aloft, AR airstream rides over SBJ. *Sierra-perpendicular vapor fluxes linked to heavy precip. along Sierra’s windward slope, & SBJ-parallel fluxes tied to heavy precip. at N end of CV. Sierra Barrier Jets, Atmospheric Rivers, and Precipitation Characteristics in Northern California: A Composite Perspective Based on a Network of Wind Profilers

6. Representation of the Sierra Barrier Jet in 11 years of a high- resolution dynamical reanalysis downscaling compared with long-term wind profiler observations. Hughes, M., P. J. Neiman, E. Sukovich and F. M. Ralph, 2012, J. Geophys. Res. – Atmos., 117 NARR 32 km grid sizeRD 6 km grid size Method 11 years of profiler-observed SBJs (256) Compared with reanalyses ranging from 275 km, 32 km, 10 km to 6 km grid sizes Results NNRP (275 km) does not have SBJs NARR (32 km) and CARD (10 km) SBJ is 2 times as deep as observed WRF RD (6 km) has 80% of SBJs SBJs in WRF RD (6 km) are best match to observed strength and depth WRF RD misses stable layer below 500 m MSL in SBJs (compared to radiosondes) Vapor transport in 6-km WRF-RD differs greatly from 32-km NARR NARR 35% too much flux into Sierra NARR 20% too little flux along Sierra

7. Atmospheric Rivers in IPCC-AR4 climate- change projections by 7 modern GCMs Dettinger, M.D., 2011, Climate change, atmospheric rivers and floods in California—A multimodel analysis of storm frequency and magnitude changes: Journal of American Water Resources Association, 47, 514-523. Water Vapor & Low-Level Winds Obs case By end of 21 st Century, most GCMs yield: More atmospheric vapor content, but weakening westerly winds  Net increase in “intensity” of extreme AR storms Warmer ARs (+1.8 C)  snowline raised by about 1000 feet on average Lengthening of AR seasons (maybe?)

8. 10 longest duration ARs (>31 h) Average of all 91 ARs Observed Impacts of Duration and Seasonality of Atmospheric- River Landfalls on Soil Moisture and Runoff F. M. Ralph 1, T. Coleman 2, P.J. Neiman 1, R. Zamora 1, and M. D. Dettinger 3 (J.Hydrometeor., 2013)

9. Validation of AR Forecasts – Results/Implications While overall occurrence well forecast out to 10 days, landfall is less well predicted and the location is subject to significant errors, especially at longer leads Errors in location increase to over 800 km at 10-day lead Errors in 3-5 day forecasts comparable with current hurricane track errors Model resolution a key factor Models provide useful heads-up for AR impact and IWV content, but location highly uncertain Location uncertainty highlights limitations in ability to predict extreme precipitation and flooding Improvements in predictions clearly desirable RMS Error in Forecast AR Landfall Location From Wick et al., 2013, Weather and Forecasting

10. Planetary- and synoptic-scale conditions in a March 2005 case From Ralph et al. 2011, Mon. Wea. Rev.

11. 11 Guan et al. (2012; Mon. Wea. Rev.) Snowpack in the Sierra acts as a natural and Important reservoir for CA. Snowfall often comes in powerful winter storms, sometimes with Atmospheric Rivers. The MJO modulates snowfall Rates. Phase 3 -> + 30-50% Phase 8 -> - 30-50% Implied Predictability? Source of moisture? Snowpack in the Sierra acts as a natural and Important reservoir for CA. Snowfall often comes in powerful winter storms, sometimes with Atmospheric Rivers. The MJO modulates snowfall rates. Phase 3 -> + 30-50% Phase 8 -> - 30-50% Implied Predictability? Source of moisture? Madden Jullian Oscillation impacts Sierra Snow: Guan et al. (2012; Mon. Wea. Rev.) The MJO is a large-scale phenomenon that could also influence Russian River precipitation

12. Atmospheric Rivers, Floods and the Water Resources of California by Mike Dettinger, Marty Ralph,, Tapash Das, Paul Neiman, Dan Cayan Water, 2011 25-35% of annual precipitation in the Pacific Northwest fell in association with atmospheric river events 35-45% of annual precipitation in California fell in association with atmospheric river events An average AR transports the equivalent of 7.5 times the average discharge of the Mississippi River, or ~10 M acre feet/day

13. What is the Palmer Drought Severity Index (PDSI) doing (on average) in the months before & after drought breaks? 1895-2010 Dettinger, Michael D., 2013: Atmospheric Rivers as Drought Busters on the U.S. West Coast. J. Hydrometeor, 14, 1721–1732.

14. Distributions of average PDSI steps across PDSI=-2 at 344 climate divisions Percentage of Persistent Drought Breaks, 1950-2010 40% of NorCal drought breaks involved ARs Dettinger, Michael D., 2013: Atmospheric Rivers as Drought Busters on the U.S. West Coast. J. Hydrometeor, 14, 1721–1732.

15. CalWater-2* “Early Start” field campaign 3-25 February 2014 Summary Courtesy of Marty Ralph UCSD/Scripps/Center for Western Weather and Water Extremes Up to > 12 inches of rain – some drought relief This AR increased precipitation-to-date from 16% to 40% of normal in < 4 days in key Northern California watersheds, but runoff was muted due to dry soils. *CalWater-2 is a 5-year program (from 2015-2019) proposed to focus on West Coast precipitation processes and how a changing climate will affect them. It is led by UCSD/Scripps with partners from DWR, CEC, NOAA, NASA, DOE and others. SSM/I satellite observations of water vapor on 8 Feb 2014 (Courtesy G. Wick, NOAA) Russian River’s highest flow in > 1 year Flight area for NOAA’s G-IV aircraft on 8 Feb 2014 Goal: developing AR flight method to sample a “frontal wave” that can cause an AR to stall over one area at landfall (G-IV PI: Chris Fairall – NOAA; Mission Scientists: Marty Ralph – Scripps, Ryan Spackman – STC) Hawaii “Frontal wave”

16. NOAA G-IV Flight Crew

17. IOP 5 Integrated Vapor Transport (kg m -1 sec -1 ) Start: 13-Feb-2014 18:33Z End: 13-Feb-2014 20:58Z Total AR transport IVT threshold: 6.9 x10 8 kg s -1 IWV threshold: 4.3 x10 8 kg s -1 IVT > 250 kg m -1 s -1

18. IOP 5 23 Total Sondes Deployed Use 17 Sondes that were approx equally spaced AND where AR criteria met (IVT > 250 kg m -1 sec -1 ) => sondes 4 thru 20 (white box)

19. 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 72.5 5.89 CASE 1 (N=17) 4 6 8 10 12 14 16 18 20 145 5.85 (-1%) CASE 2 (N=9) 4 8 12 16 20 290 5.54 (-6%) CASE 3 (N=5) 4 12 20 580 4.89 (-17%) CASE 4 (N=3) 4 11 20 580 6.43 (+9%) CASE 4A (N=3) Avg Spacing (km) AR Transport (10 8 kg sec -1 ) Vary sonde resolution and recalculate total IVT across AR section Maintain same physical width of AR section control 4 13 20 580 4.64 (-21%) CASE 4B (N=3)

20. Doyle, James D., Clark Amerault, Carolyn A. Reynolds, P. Alex Reinecke, 2014: Initial Condition Sensitivity and Predictability of a Severe Extratropical Cyclone Using a Moist Adjoint. Mon. Wea. Rev., 142, 320–342 Uncertainty in predicted extreme surface winds found to be associated with an AR “The sensitivity maxima are found in the low- and midlevels, oriented in a sloped region along the warm front, and maximized within the warm conveyor belt. The moisture sensitivity indicates that only a relatively small filament of moisture within an atmospheric river present at the initial time was critically important for the development of Xynthia.” Adjoint sensitivity valid at the initial time of 1200 UTC 26 Feb 2010 at 700 mb for water vapor (color coded). Hatched area is water vapor mixing ration >4 g kg -1.