ENHANCING HYDROMETEOROLOGICAL OBSERVING SYSTEMS THROUGHOUT CALIFORNIA7 OCTOBER 2020

PRESENTED BY ANNA WILSON, CW3E FIELD RESEARCH MANAGER, CW3E/SCRIPPS/UCSDWITH CONTRIBUTIONS FROM MANY OTHERSSWEPSYM 2020

FIRO Reservoirs (Preliminary)

FIRO Prototype Demonstrated

FIRO Planning underwayMajor deviation to be requested

Lake MendocinoRussian RiverSonoma WaterSize: 111 TAF

Prado DamSanta Ana RiverOrange County Water Dist.Size: 170 TAF

Oroville DamFeather RiverCA Dept. Water ResourcesSize: 3500 TAF

New Bullards BarYuba RiverYuba Water AgencySize: 996 TAF

FORECAST INFORMED RESERVOIR OPERATIONS

FORECAST-INFORMED RESERVOIR OPERATIONS

Co-Chairs, Lake Mendocino FIRO: F. Martin Ralph Jay Jasperse

Max Allowable Storage

Potential FIRO-Enabled Additional Water Supply

Reliability(Enough for 20,000 homes for a

year)

Due to Atmospheric river storms

Water Year 2013

Lake

Men

doci

no W

ater

Sup

ply

Stor

age

(acr

e-fe

et)

Hypothetical estimate of extra water retained unless an atmospheric river storm is predicted to hit the watershed; requires reliable AR prediction at 5-day lead time

Descent into drought

LAKE MENDOCINO

FORECAST-INFORMED RESERVOIR OPERATIONS

Co-Chairs, Lake Mendocino FIRO: F. Martin Ralph Jay Jasperse

Actual storage curve from 2020 when

FIRO was used operationally ~19% increase

in water supply as of

April 1

ERRORS IN PREDICTING THE STRUCTURE AND STRENGTH OF AN ATMOSPHERIC RIVER CAN CREATE MAJOR ERRORS IN FLOOD FORECASTS

A. Martin, F.M. Ralph, A. Wilson, L. DeHaan, B. Kawzenuk (J. Hydrometeor., 2019)

GUERNEVILLE

IV: Off-

shorerecon.

Tier III:Newer technology

Ex: Gap-filling radars,Buoy-mounted WPs

Tier I: Address well-defined needs with proven technology

Ex: Soil moisture sensors, GPS receivers of opportunity, snow-level radars

Tier II: Expand on well-defined needs with proven technology

Ex: Wind profilers (WP), Coastal Atmospheric river observatory

A Vision for next-generation observations to help address CA’s water resource issues (Ralph et al. 2008*)

Tier IV: Atmospheric River Reconnaissance led by Scripps Institution of Oceanography/CW3E, and NOAA/NCEP. Supported by U.S. Army Corps of Engineers, CA DWR.

Uses U.S. Air Force and NOAA aircraft for method prototyping 2016-2020

*Derived from Ralph et al. 2008 proposal from NOAA to California Dept. of Water Resources (DWR) based on findings from CalJet, PacJet and HMT. Developed in collaboration with Scripps Inst. of Oceanography and USGS. Major elements are included in

Ralph et al. (2014) Univ. Council on Water Resources report for the Western States Water Council.

Tiers I and II: Statewide network supported by DWR; created by

NOAA and Scripps Inst. of Oceanography between

2008-2014

Tier III: Specialized radars and modeling supports San Francisco Bay Area Integrated

Regional Water Management project. Funded by CA DWR. Led by SCWA, NOAA and CSU

from 2017-2020

Design Focus: Monitoring

atmospheric rivers and related conditions

Atmosp

heric ri

ver

Implementation (2018)

Concept (2008)

PI: F. Martin Ralph

From: “Atmospheric Rivers” (Book)

Ralph et al. 2020, Springer Publishing

California Extreme Precipitation Network

An Atmospheric River-focused long-term observing network was installed in CA as part of a 5-year project between CA Dept. of Water Resources (DWR), NOAA and Scripps Inst. Of Oceanography- Installed 2008-2014- >100 field sites

¼-scale 449-MHz wind profiler with RASS

FM-CW snow-level radar

GPS receiver forintegrated water vapor

Soil Moisture and Temperature

Probes

White et al. 2013 (J. Atmos. Oceanic

Tech.)

AROs ~250km apart: all impactful ARs hitting the west coast will be sampled with this “picket fence” approachHourly Obs: canpinpoint start & end times, peak

Unique Observational Network in CA

VALUE OF SENSOR NETWORKS

8Hatchett et al., 2020: Observations of an extreme atmospheric river storm with a diverse sensor network. Earth and Space Sciences.

● Evaluates a multi-tiered observational network in California during an extreme AR on 13-15 February 2019

● Illustrates the network ability to validate record precipitable water and detect key mesoscale atmospheric processes driving flood, snowfall, and mass wasting events

● Demonstrates that diverse, high frequency observational networks are valuable investments for water resource management and natural hazard mitigation, especially in context of a changing climate

ATMOSPHERIC RIVER RECONNAISSANCE – A RESEARCH AND OPERATIONS PARTNERSHIP

NOAA G-IVAir Force C-130 – Weather Recon

• Better weather observations over the Pacific can help AR landfall predictions and associated precipitation, water supply and flooding

• Better AR forecasts can support both flood preparations and water management decisions• AR Recon has been included in the National Winter Season Operations Plan directing NOAA and

AF to execute AR Recon, including in winter 2021• AR Recon Modeling and Data Assimilation Steering Committee is doing detailed impact studies

Atmospheric River Reconnaissance Sampling Concept and Example from 27 Jan 2018F. Martin Ralph (AR Recon PI; Scripps/CW3E), Vijay Tallaprgada (AR Recon Co-PI; NWS/NCEP) and AR Recon Team

In 2019, National Winter Season Operations Plan Includes Official Call for AR Reconnaissance Off the U.S. West Coast Starting in 2020 –Updated Plan Released July 2020

In Spring 2019, the interagency group that develops the NWSOP approved incorporation of AR Recon as a leading priority for addressing gaps in west coast storm prediction, specifically targeting ARs and their vicinity over the Pacific with NOAA and Air Force Recon capabilities.

In Spring 2019, the interagency group that develops the NWSOP approved incorporation of AR Recon as a leading priority for addressing gaps in west coast storm prediction, specifically targeting ARs and their vicinity over the Pacific with NOAA and Air Force Recon capabilities.

In Summer 2020, this group approved additional language highlighting the leadership of CW3E/Scripps.

The West is extremely susceptible to water shortages and surpluses. These

conditions pose a significant risk to the public, property, and commerce ... The intent of AR Recon is to support water

management decisions and flood forecasting through the execution of

targeted airborne dropsonde and buoy observations over the Central and Eastern Pacific Ocean to improve

forecasts of the landfall and impacts of ARs for civil authorities and DOD decision

makers along the U.S. West Coast

AR Recon in 2020 Conducted 17 IOPs3-aircraft: 4 IOPs2-aircraft: 6 IOPs1-aircraft: 7 IOPs

7 weeks: from 23 Jan through 11 Mar 2020

● Second year in a row with buoy deployment collaboration between NOAA Global Drifter Program (PI: Luca Centurioni), Scripps/CW3E AR Recon (PI: Marty Ralph) with planning support from the AR Recon Modeling and DA Steering Committee (Scripps/CW3E, NCEP, ECMWF, NRL, NCAR, CU Boulder)

● 2019: 32 buoys air-deployed by Air Force● 2020: 64 buoys – 40 deployed via ship of

opportunity; 24 deployed via Air Force● Evaluation ongoing

DRIFTING BUOY WITH PRESSURE SENSORS – AR RECON DEPLOYMENT

Leverages federal investments by upgrading instrumentation provided

through NOAA’s Global Drifter Program

AR Recon Impact

What is the documented impact on

forecasts of this targeted, gap-filling

data collection?

GFSv15 PRECIP: 24-h total - 2020022312-2020022412IC: 2020022100 (IOP 10) Fcst: 60h-84h

ctrl

deny

stage4

AR Recon helped GFS better predict the intense precipitation amounts

Slide provided by Vijay Tallapragada, NOAA/NWS/NCEP

RUSSIAN RIVER HYDROMET. OBSERVATION NETWORK

Terrain base maps showing the existing RHONET in the Russian R. Watershed and theimmediate surrounding areas.

Pictures showing some RHONET obs. sites and the map showing their locations in the Russian R. Watershed.

Image by CA DWR

Sumargo et al., 2020, BAMS

WHAT IS NEEDED TO CLOSE THE WATERSHED WATER BUDGET?

∆S = (P + GWin) – (Q + ET + GWout)

Terrain base maps showing precipitation/soil moisture obs. andstream gauges in the Russian R. Watershed (left) and LakeMendocino sub-region (right)

Flow chart describing the framework for identifying the event antecedent soil moisturethreshold where runoff starts to increase rapidly. The color code on the bottom rightplot denotes the event antecedent flow—a proxy for groundwater(unknown/unmeasured).Measured UnknownGPS?

Sumargo et al., 2020, Hydrol. Proc., in revision

FIRO AT PRADO

DAM

Surface MetGPS Water VaporNEXRAD 449-MHz AROFMCWExtant RadiosondePlanned RadiosondeDisdrometerMRR

Santa Ana River WatershedExisting and Planned Instrumentation

YUBA FEATHER FIROSite Name (Code) Site Type Latitude (°) Longitude (°) Elevation

(m)Install Status

Skyline Harvest (SKY)

SMOIL 39.47 -121.09 829 installed

Feather River College (FRC)

SMOIL 39.95 -120.97 1048 Installed

Downieville (DLA) RadMet 39.56 -120.58 901 Installed

New Bullards Bar (NBB)

RadMet 39.40 -121.14 634 Installed

Skyline Harvest

All sites have: air temperature, relative humidity, solar radiation, wind speed and direction, precipitation, and air pressure.

Measurements are recorded every 2 minutes.SMOIL sites have: soil moisture and

temperature at 6 depths (5, 10, 15, 20, 50, and 100 cm).

RadMet sites have: Micro Rain Radar, disdrometer, and GPS, but no soil

measurements

Cayan Hydroclimate Network: 20 sites in the Sierra and

White Mountainsmaintenance and upgrades

ongoing

ADDITIONAL OBSERVATION EFFORTS THROUGHOUT CALIFORNIASnow Level Radars – planned

additions throughout the Sierras

SUMMARY – ENHANCING OBSERVATIONS TO MEET WESTERN U.S. FORECASTING AND MONITORING NEEDS

• OFFSHORE AND ONSHORE• Leverage existing sites, work with others,

match station design• Dissemination!!

• Partnerships are crucial• Networks help monitor key quantities along with

enabling us to learn more about physical processes àbetter forecats

• Continuous evaluation needed to make sure observation network meets needs, and that we are using it to fullest extent