Jet Propulsion Laboratory
California Institute of Technology
AR Science Gaps/Objectives
Duane Waliser on behalf of Calwater 2 SSG
Jet Propulsion Laboratory/Caltech
Pasadena, CA
CalWater 2015 – ACAPEX Campaign Planning Workshop
Scripps Institution of Oceanography
La Jolla, California
22-24 April 2014
AR Science Considerations
 Landfall, overland and topography considerations
 Water Budgets over ocean and land
 Energy and Momentum budgets
 Synoptic Meteorology & Vapor Sources
 Multi-scale interactions (e.g. ENSO to mesoscale)
 Climate change implications
 Microphysical considerations
 Modeling Improvements (microphysical to multi-scale)
 Predictability and Prediction Skill
 Air Sea Interaction
AREX* Landfall Science Targets
• Barrier Jet occurrence, dynamics & modulation
of precipitation
• Variations and factors influence the “melting
layer”
• “Dividing Streamline”
• Soil moisture pre-conditioning (HMT & SMAP)
* A SIO/UCSD & JPL proposal to NASA
New Measurements of AR processes are key
to improving the model forecasts
Scripps/UCSD & JPL are proposing AREX* to NASA’s Earth Ventures
Suborbital Campaign opportunity to use advanced remote sensing
instruments to directly measure the processes that determine the flow
and direction of AR moisture in order to improve model forecasts.
* A SIO/UCSD & JPL proposal to NASA
Water Vapor Transport = Wind * Water Vapor
Imagery generated by Prof. Jason Cordeira
(Plymouth State University) and Dr. Marty
Ralph (CW3E/UCSD) unless otherwise noted.
Precipitation Total
Through Saturday
NCEP Weather Prediction Center: http://www.hpc.ncep.noaa.gov/qpf/p120i.gif
Forecast of Water Vapor
Transport on Wednesday
In this regard
shouldn’t an
understanding of
the Momentum
Budget be at least
as relevant as the
Water Vapor
Budget
What conditions
effect different
aspects of the
source/sink terms?
Meteorology of an AR
Observational studies by Ralph et al. (2004, 2005, 2006) extend model results:
1)
2)
3)
4)
Long, narrow plumes of IWV >2 cm measured by SSM/I satellites considered proxies for ARs.
These plumes (darker green) are typically situated near the leading edge of polar cold fronts.
P-3 aircraft documented strong water vapor flux in a narrow (400 km-wide) AR; See section AA’.
Airborne data also showed 75% of the vapor flux was below 2.5 km MSL in vicinity of LLJ.
cold air
Enhanced vapor flux
in Atmos. river
warm air
IWV > 2 cm
Atmos. river
cold
air
Courtesy Marty Ralph, U. Calif, San Diego
Warm,
Humid
400 km
Canonical Water Vapor Sources via Back Trajectories
Water vapor source regions
/ processes still to be fully
characterized including
dependencies on
• synoptic conditions
&
• target rainfall region
Ryoo, Waliser,
Waugh, Wong,
Fetzer, 2014, TBD
Common Climate Modes Linked to
Atmospheric River Frequency
500 mb
Geopotential
Height
Anomalies
“Arctic Oscillation”
(AO)
Typical
frequency
of ARs
Changes in AR frequency by AO & PNA
“Pacific North
American” (PNA)
Circulation anomaly when
both PNA and AO in
“negative” phase
•
On average 6-7 Atmospheric River (AR) events
provided 30-40% of total seasonal snow water
equivalent (SWE) accumulation in most years
•
When PNA & AO are in “negative” phases, there is a
doubling of the frequency of ARs
•
Since PNA&AO exhibit some predictability from days to
months, it may be possible to extend forecasts of ARs
How does this influence/relate to predictability on
synoptic and seasonal timescales?
Guan, Molotch, Waliser, Fetzer, Neiman, 2014, Water Resources Review, in press.
Forecast Skill, Dependencies & What
about Predictability?
For example: at 5-6 day lead time, global weather forecasts
cannot determine if it will hit LA or San Francisco
RMS Error in Forecast
AR Landfall Location
Wick et al. 2013
What is the upper bound?
What synoptic/climate factors influence predictability?
ARM Cloud Aerosol Precipitation
Experiment (ACAPEX)
PI : R. Leung/PNNL/DOE
AR Science Questions:
What influences the evolution and structure of AR and
its associated cloud and precipitation?
 To what extent does water vapor in ARs originate from the
tropics? What role does tropical convection play in this?
 What are the roles of air-sea fluxes and ocean mixed layer
processes in AR evolution?
 What are the key dynamical processes that modulate
cloud and precipitation from landfalling ARs?
AR Science Considerations
 Landfall, overland and topography considerations
 Water Budgets over ocean and land
 Energy and Momentum budgets
 Synoptic Meteorology & Vapor Sources
 Multi-scale interactions (e.g. ENSO to mesoscale)
 Climate change implications
 Microphysical considerations
 Modeling Improvements (microphysical to multi-scale)
 Predictability and Prediction Skill
 Air Sea Interaction