“…To look more at the issue of causality, we return to the ensembles of GCM simulations of the 100 day adjustment of the circulation to an instantaneous insertion of ENSO SST anomalies. Early in these simulations, the mean-flow anomalies are primarily driven by the anomalies in tropical heating and it is only after a week or two that the transient eddies begin to respond and, subsequently after that, to impact the mean flow (Harnik et al, 2010). By running the storm-track model with basic states from different times within the 100 day GCM simulations, we can examine how transient eddy propagation and the eddy fluxes evolve after the initial turn-on of an ENSO SST anomaly.…”
Section: Results From the Nonlinear Storm-track Model With Basic Statmentioning
confidence: 99%
“…This recalls the idea of Branstator (1995) that on longer than synoptic time-scales it will be those flow anomalies that excite a positive feedback between waves and the mean flow that will persist. However, the eddy response is not simply a positive feedback but also incites an evolution over time of the mean and transient circulation (Harnik et al, 2010). The refraction argument for changes in paths of transient eddy propagation is outlined in some detail in Seager et al (2003).…”
Section: Results From the Nonlinear Storm-track Model With Basic Statmentioning
confidence: 99%
“…Further, while we have emphasized the possibility of explaining observed changes in terms of wave refraction, it is also quite likely that changes in seeding, baroclinic energy conversion and wave breaking also play a role (Orlanski, 2005;Shapiro et al, 2001) in establishing the mean and transient circulation response to ENSO. In a follow-up article (Harnik et al, 2010) we will make more use of the large ensembles of seasonal GCM simulations subject to turn-ons of ENSO SST anomalies, together with a simple quasi-geostrophic model of transient eddies, to determine the exact sequence of cause and effect in the adjustment of the mean and transient atmospheric circulation. There it will be shown that a cooperative interaction between the mean flow, wave refraction and eddy fluxes, on a time-scale of weeks to months, leads to the establishment, intensification and evolution of the circulation response and its transmission to higher latitudes.…”
Section: Discussionmentioning
confidence: 99%
“…To examine wave propagation, we use the daily data from each individual ensemble member. The evolution of the simulations is examined further in Harnik et al (2010).…”
Section: Data and Modelsmentioning
confidence: 99%
“…In a follow-up article (Harnik et al, 2010) we will develop a causal account of tropical forcing of the mean flow, the impact on eddies and the subsequent feedback into the mean flow that constitutes a theory for the TMME mechanism.…”
“…To look more at the issue of causality, we return to the ensembles of GCM simulations of the 100 day adjustment of the circulation to an instantaneous insertion of ENSO SST anomalies. Early in these simulations, the mean-flow anomalies are primarily driven by the anomalies in tropical heating and it is only after a week or two that the transient eddies begin to respond and, subsequently after that, to impact the mean flow (Harnik et al, 2010). By running the storm-track model with basic states from different times within the 100 day GCM simulations, we can examine how transient eddy propagation and the eddy fluxes evolve after the initial turn-on of an ENSO SST anomaly.…”
Section: Results From the Nonlinear Storm-track Model With Basic Statmentioning
confidence: 99%
“…This recalls the idea of Branstator (1995) that on longer than synoptic time-scales it will be those flow anomalies that excite a positive feedback between waves and the mean flow that will persist. However, the eddy response is not simply a positive feedback but also incites an evolution over time of the mean and transient circulation (Harnik et al, 2010). The refraction argument for changes in paths of transient eddy propagation is outlined in some detail in Seager et al (2003).…”
Section: Results From the Nonlinear Storm-track Model With Basic Statmentioning
confidence: 99%
“…Further, while we have emphasized the possibility of explaining observed changes in terms of wave refraction, it is also quite likely that changes in seeding, baroclinic energy conversion and wave breaking also play a role (Orlanski, 2005;Shapiro et al, 2001) in establishing the mean and transient circulation response to ENSO. In a follow-up article (Harnik et al, 2010) we will make more use of the large ensembles of seasonal GCM simulations subject to turn-ons of ENSO SST anomalies, together with a simple quasi-geostrophic model of transient eddies, to determine the exact sequence of cause and effect in the adjustment of the mean and transient atmospheric circulation. There it will be shown that a cooperative interaction between the mean flow, wave refraction and eddy fluxes, on a time-scale of weeks to months, leads to the establishment, intensification and evolution of the circulation response and its transmission to higher latitudes.…”
Section: Discussionmentioning
confidence: 99%
“…To examine wave propagation, we use the daily data from each individual ensemble member. The evolution of the simulations is examined further in Harnik et al (2010).…”
Section: Data and Modelsmentioning
confidence: 99%
“…In a follow-up article (Harnik et al, 2010) we will develop a causal account of tropical forcing of the mean flow, the impact on eddies and the subsequent feedback into the mean flow that constitutes a theory for the TMME mechanism.…”
A 26 year high-resolution dynamical downscaling over the Wasatch Mountains of Utah, USA, was performed using the Weather Research and Forecasting model with initial and boundary conditions derived from Climate Forecast System Reanalysis. Precipitation validation was conducted on the inner (4 km resolution) domain with Snowpack Telemetry (SNOTEL) and Parameter-elevation Regressions on Independent Slopes Model data sets. Analysis of seasonal performance reveals the model's overall good skill at reproducing the spatial distribution of precipitation. Annual precipitation validates within ∼20% of SNOTEL. The largest monthly biases occurred in December-January (∼+30%) stemming from a small set of high-precipitation events. Composite analysis of cold season days with large positive or negative precipitation biases reveals two distinct synoptic regimes with significantly different moisture, temperature, and circulation patterns that respectively enhanced geopotential height and moisture biases consistent with the sign of their mean precipitation biases. The number of cold season days with large (>5 mm) positive precipitation bias was negatively correlated with El Niño (r = −0.55), indicating storm track-related effects on the sign of the bias consistent with the distinct synoptic regimes revealed by the above-noted composite analyses.
The temporal stationarity of the teleconnection between the tropical Pacific Ocean and North America (NA) is analyzed in atmosphere‐only, and coupled last‐millennium, historical, and control runs from the Coupled Model Intercomparison Project Phase 5 data archive. The teleconnection, defined as the correlation between December‐January‐February (DJF) tropical Pacific sea surface temperatures (SSTs) and DJF 200 mb geopotential height, is found to be nonstationary on multidecadal timescales. There are significant changes in the spatial features of the teleconnection over NA in continuous 56‐year segments of the last millennium and control simulations. Analysis of atmosphere‐only simulations forced with observed SSTs indicates that atmospheric noise cannot account for the temporal variability of the teleconnection, which instead is likely explained by the strength of, and multidecadal changes in, tropical Pacific Ocean variability. These results have implications for teleconnection‐based analyses of model fidelity in simulating precipitation, as well as any reconstruction and forecasting efforts that assume stationarity of the observed teleconnection.
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