The Role Of The Pacific North American Pattern On The Pace Of Future Winter Warming Across Western North America.

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Presentation transcript:

The Role Of The Pacific North American Pattern On The Pace Of Future Winter Warming Across Western North America

Warming Trajectory Annual Mean Temperature Change for the Pacific NW (Mote and Salathe, 2010) What drives the pace of winter warming in the West? Linear trend in 1 Apr SWE ( ) Mote (2006) +.8 to +1.2°C

Pacific North American Pattern (PNA) What is it? Preferred atmospheric circulation regime Proxy of “ridginess” of large scale waves Positive phase: warm air into the West Comingles with ENSO and PDO Why does it matter? Strong influence on surface air temperature and snow-hydrology Weather regimes and associated impacts in PNW often tied to PNA phase 500hPa height pattern Associated Time Series

Example #1: Seasonal differences “Spring Warming, Autumn Not” Spring: +0.28˚C/decade Autumn: +0.07˚C/decade Abatzoglou and Redmond (2007) Mean Temperature 11 Western States 40% of the spring warming attributed to circulation changes Variability has masked regional warming in autumn GCM 20C3M to +0.2˚C/decade

Example #2: Loss of Mountain Snowpack m/decade ~ ˚C/decade, 50% more than projected changes

Pacific North American Pattern Responsible for about a third of snowpack loss in Cascades since 1958 Freezing level Rain + Melt Snow No Melt ±400m per PNA INDEX Abatzoglou (2011)Similar results to Casola et al., 2010 JFM Trend (%/decade, ) in Percent of Precipitation as Snow Observed Daily PNA Removed -50 5

Fundamental Research Question How will climate variability alter the pace of future winter warming across western North America? Can models simulate the PNA in today’s climate? Is the PNA sensitive to 21 st century anthropogenic forcing? What are the implications for mountain snowpack loss?

Methodology Models – 500hPa height, 12 CMIP3 GCMs, , A1B – Downscaled daily temperature and precipitation Diagnostics – Modified pointwise methods & one point correlation – Rotated Empirical Orthogonal Functions – Linear Least Squares Trend Analysis

Similar results using REOF Can GCMs Simulate the PNA in today’s climate? One-point correlation maps of JFM 500hPa height to NW N. America node NCEP-NCAR Reanalysis ( ) Different GCMs ( ) Most GCMs simulate PNA variance within 20% of observations.

Is the PNA sensitive to anthropogenic forcing? Monthly Linear Trends in the PNA ( ) Majority of models suggest a shift towards positive PNA regime in winter with anthropogenic forcing

PNA as a Pacemaker: Explained Variance of Winter Warming r=0.83

Implications for Mountain Snowpack % Change in Precipitation as Snow, Jan-Mar ( vs ) Composite of four GCM with largest PNA trend Composite of four GCM with smallest PNA trend “Allied” forcing could double the loss of mountain snowfall Downscaled output from MACA (Abatzoglou and Brown, 2011)

Summary Climate variability has played a significant role in modifying the pace of climate change and associated impacts in the western US GCMs suggest a shift toward the positive phase of the PNA with anthropogenic forcing: amplifier of regional change PNA explains a majority of variance in late-winter intermodel temperature variability across western North America Richer understanding of atm-ocean dynamics with anthropogenic forcing may lead to refinements in regional climate projections.

Similar results using REOF Can GCMs Simulate the PNA in today’s climate? One-point correlation maps Taylor Diagram: visual means of synthesizing pattern similarity Power-spectra of PNA needs to be analyzed Standardized Deviations (Normalized)