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Siler, N, Kosaka Y, Xie SP, Li XC.  2017.  Tropical ocean contributions to California's surprisingly dry El Nino of 2015/16. Journal of Climate. 30:10067-10079.   10.1175/jcli-d-17-0177.1   AbstractWebsite

The major El Nino of 2015/16 brought significantly less precipitation to California than previous events of comparable strength, much to the disappointment of residents suffering through the state's fourth consecutive year of severe drought. Here, California's weak precipitation in 2015/16 relative to previous major El Nino events is investigated within a 40-member ensemble of atmosphere-only simulations run with historical sea surface temperatures (SSTs) and constant radiative forcing. The simulations reveal significant differences in both California precipitation and the large-scale atmospheric circulation between 2015/16 and previous strong El Nino events, which are similar to (albeit weaker than) the differences found in observations. Principal component analysis indicates that these ensemble-mean differences were likely related to a pattern of tropical SST variability with a strong signal in the Indian Ocean and western Pacific and a weaker signal in the eastern equatorial Pacific and subtropical North Atlantic. This SST pattern was missed by the majority of forecast models, which could partly explain their erroneous predictions of above-average precipitation in California in 2015/16.

Merrifield, A, Lehner F, Xie SP, Deser C.  2017.  Removing Circulation Effects to Assess Central US Land-Atmosphere Interactions in the CESM Large Ensemble. Geophysical Research Letters. 44:9938-9946.   10.1002/2017gl074831   AbstractWebsite

Interannual variability of summer surface air temperature (SAT) in the central United States (U.S.) is influenced by atmospheric circulation and land surface feedbacks. Here a method of dynamical adjustment is used to remove the effects of circulation on summer SAT variability over North America in the Community Earth System Model Large Ensemble. The residual SAT variability is shown to reflect thermodynamic feedbacks associated with land surface conditions. In particular, the central U.S. is a hot spot of land-atmosphere interaction, with residual SAT accounting for more than half of the total SAT variability. Within the hot spot, residual SAT anomalies show higher month-to-month persistence through the warm season and a redder spectrum than dynamically induced SAT anomalies. Residual SAT variability in this region is also shown to be related to preseason soil moisture conditions, surface flux variability, and local atmospheric pressure anomalies.

Merrifield, AL, Xie SP.  2016.  Summer US surface air temperature variability: controlling factors and AMIP simulation biases. Journal of Climate. 29:5123-5139.   10.1175/jcli-d-15-0705.1   AbstractWebsite

This study documents and investigates biases in simulating summer surface air temperature (SAT) variability over the continental United States in the Atmospheric Model Intercomparison Project (AMIP) experiment from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Empirical orthogonal function (EOF) and multivariate regression analyses are used to assess the relative importance of circulation and the land surface feedback at setting summer SAT over a 30-yr period (1979-2008). Regions of high SAT variability are closely associated with midtropospheric highs, subsidence, and radiative heating accompanying clear-sky conditions. The land surface exerts a spatially variable influence on SAT through the sensible heat flux and is a second-order effect in the high-variability centers of action (COAs) in observational estimates. The majority of the AMIP models feature high SAT variability over the central United States, displaced south and/or west of observed COAs. SAT COAs in models tend to be concomitant and strongly coupled with regions of high sensible heat flux variability, suggesting that excessive land-atmosphere interaction in these models modulates U.S. summer SAT. In the central United States, models with climatological warm biases also feature less evapotranspiration than ERA-Interim but reasonably reproduce observed SAT variability in the region. Models that overestimate SAT variability tend to reproduce ERA-Interim SAT and evapotranspiration climatology. In light of potential model biases, this analysis calls for careful evaluation of the land-atmosphere interaction hot spot region identified in the central United States. Additionally, tropical sea surface temperatures play a role in forcing the leading EOF mode for summer SAT in models. This relationship is not apparent in observations.