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The tropical tropopause layer (TTL) temperature balance is of considerable interest for its control over the amount of water entering the stratosphere. The upwelling branch of the Brewer‐Dobson circulation (BDC) directly affects these temperatures through adiabatic cooling. BDC upwelling also indirectly affects TTL temperatures through the influence of ozone transport on radiative heating. We investigate this latter feedback using a single‐column radiative‐convective equilibrium model coupled with a model of simplified stratospheric ozone chemistry and vertical transport. We find that BDC ozone transport is of first‐order importance for TTL temperatures. Additionally, we estimate the effect of ozone transport on cold point tropopause temperature responses to changes in upwelling. We find that the feedback is responsible for approximately 20% of the response to perturbations on time scales longer than about half a year but that this contribution can be neglected for time scales shorter than about a week. Interactive ozone chemistry is applied in a single‐column radiative‐convective equilibrium model to investigate transport processesOzone transport by Brewer‐Dobson circulation upwelling is of first‐order importance for temperature structure of tropical tropopause layerTransport‐radiation feedback: increased (decreased) upwelling reduces (increases) ozone −20% of the total cooling (warming) from upwelling

The current generation of subseasonal operational model forecasts has, on average, low skill for leads beyond 3 weeks. This is likely a fundamental property of the climate system, due to the relative high amplitude of unpredictable weather variability compared to potentially predictable, but generally weaker, climate signals. Thus, for subseasonal forecasts to be useful, their high versus low skill events should be identified at time of forecast. We show that a linear inverse model (LIM), an empirical‐dynamical model constructed from covariability statistics of wintertime (December–March) weekly averaged observational analyses, can be used to identify, a priori, the expected extratropical subseasonal surface and midtropospheric forecast skill. The LIM's predicted signal‐to‐noise ratio identifies the subset (10%–30%) of Weeks 3–6 forecasts—of the LIM and two operational models from the National Centers for Environmental Prediction and the European Centre for Medium‐Range Weather Forecasts—with relatively higher skill versus the much larger remainder of forecasts whose skill cannot be distinguished from random chance. Our current understanding of weather prediction is that usable daily forecasts cannot be made more than 15 days in advance. This is a consequence of chaos: Any small initial uncertainty in our picture of the atmosphere (e.g., wind, temperature, and pressure) when the forecast is made will lead to errors growing to become as large as the weather we are trying to predict. Recently, however, focus has turned to “subseasonal” forecasts, predictions of weekly averaged weather made 3 to 6 weeks ahead, because climate phenomena (e.g., El Niño) sometimes produce persistent weather patterns that might be predicted even though individual storms within them cannot be. To identify when these “forecasts of opportunity” will occur, we developed a statistical subseasonal forecast model capable of predicting when its own forecasts—and those of sophisticated physical models from U.S. and European operational centers—will be usable. Our model successfully identifies the 20%–30% of forecasts at Weeks 3 and 4 and 10% of forecasts at Weeks 5 and 6 that are usable. Our results show a path forward to develop techniques for identifying usable subseasonal forecasts beforehand, so that practical forecast guidance may be given to end users in a variety of societal contexts. Subseasonal predictability is largely due to shifts in the ensemble‐mean signal, at least for the Northern Hemisphere extratropical winterWhile some individual subseasonal forecasts have high skill, so can random chance, underlining the need to determine skill a prioriA linear inverse model identifies the high skill subset (10%‐30%) of operational model forecasts at Weeks 3‐6, and both have similar skill

Factors governing the strength and frequency of stratospheric ozone intrusions over the Pacific‐North American region are considered for their role in modulating tropospheric ozone on interannual timescales. The strength of the association between two major modes of climate variability—the El Niño–Southern Oscillation (ENSO) and the Northern Annular Mode (NAM)—and the amount of ozone contained in stratospheric intrusions are tested in the context of two mechanisms that modulate stratosphere‐to‐troposphere transport (STT) of ozone: (StratVarO3) the winter season buildup of ozone abundances in the lowermost stratosphere (LMS) and (JetVar) Pacific jet and wave breaking variability during spring. In essence, StratVarO3corresponds to variability in the amount of ozone per intrusion, while JetVar governs the frequency of intrusions. The resulting analysis, based on two different reanalysis products, suggests that StratVarO3is more important than JetVar for driving interannual variations in STT of ozone over the Pacific‐North American region. In particular, the abundance of ozone in the LMS at the end of winter is shown to be a robust indicator of the amount of ozone that will be contained in stratospheric intrusions during the ensuing spring. Additionally, it is shown that the overall strength of the winter season stratospheric NAM is a useful predictor of ozone intrusion strength. The results also suggest a nuanced relationship between the phase of ENSO and STT of ozone. While ENSO‐related jet variability is associated with STT variability, it is wave breaking frequency rather than typical ENSO teleconnection patterns that is responsible for the ENSO‐STT relationship. Stratospheric variability exerts a stronger influence on ozone intrusions than tropospheric jet variabilityOzone intrusion frequency is more related to wave breaking frequency than it is to teleconnection patternsThe strength of the winter stratospheric Northern Annular Mode is indicative of spring ozone intrusion strength