Selected CalWater AR Accomplishments - PowerPoint Presentation

Slide1

Selected CalWater AR AccomplishmentsSlide2

AR-SBJ IOPs 3-7 in Feb/Mar 2011

AR-SBJ IOPs 1-2 in Dec 2010

2Slide3

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 IOPs1 strong7 moderate2 weak

3Slide4

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 northAR rode up and over the SBJ

Landfalling storm 14-16 February 2011

Multi-Doppler scanning-radar retrievals Multi-wind-profiler time series diagnosticsBalloon soundingsSlide5

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 ProfilersSlide6

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., 117NARR 32 km grid sizeRD 6 km grid sizeMethod11 years of profiler-observed SBJs (256)Compared with reanalyses ranging from 275 km, 32 km, 10 km to 6 km grid sizesResultsNNRP (275 km) does not have SBJsNARR (32 km) and CARD (10 km) SBJ is 2 times as deep as observedWRF RD (6 km) has 80% of SBJsSBJs in WRF RD (6 km) are best match to observed strength and depthWRF 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 NARRNARR 35% too much flux into SierraNARR 20% too little flux along SierraSlide7

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 WindsObs caseBy end of 21st 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?)Slide8

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. Zamora1, and M. D. Dettinger3 (J.Hydrometeor., 2013)Slide9

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 desirableRMS Error in Forecast AR Landfall Location

From Wick et al., 2013, Weather and ForecastingSlide10

Planetary- and synoptic-scale conditions in a

March 2005 case

From Ralph et al. 2011,

Mon.

Wea. Rev.Slide11

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 precipitationSlide12

Atmospheric Rivers, Floods and the Water Resources of California

by Mike

Dettinger

, Marty Ralph, ,

Tapash Das, Paul Neiman, Dan Cayan

Water, 201125-35% of annual precipitation in the Pacific Northwest fell in association with atmospheric river events35-45% of annual precipitation in California fell in association with atmospheric river eventsAn average AR transports the equivalent of 7.5 times the average discharge of the Mississippi River, or ~10 M acre feet/daySlide13

What is the

Palmer Drought Severity Index (PDSI)

doing (on average) in the months before & after

drought

breaks?

1895-2010Dettinger, Michael D., 2013: Atmospheric Rivers as Drought Busters on the U.S. West Coast. J. Hydrometeor, 14, 1721–1732.Slide14

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.Slide15

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 yearFlight area for NOAA’s G-IV aircraft on 8 Feb 2014Goal: 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”Slide16

NOAA G-IV Flight CrewSlide17

IOP 5 Integrated Vapor Transport (kg m

-1

sec

-1

)Start: 13-Feb-2014 18:33Z End: 13-Feb-2014 20:58Z

Total AR transportIVT threshold: 6.9 x108 kg s-1IWV threshold: 4.3 x108 kg s-1IVT > 250 kg m-1 s-1Slide18

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)Slide19

4

5

6

789

101112131415

161718192072.55.89CASE 1(N=17)4681012141618201455.85(-1%)CASE 2(N=9)481216

20290

5.54(-6%)

CASE 3(N=5)412205804.89(-17%)CASE 4(N=3)411205806.43(+9%)CASE 4A(N=3)Avg Spacing (km)AR Transport (108 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)Slide20

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

, 320–342Uncertainty 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.