Zachary Duane Lawrence

Two-way coupling between the stratosphere and troposphere is an important source of subseasonal predictability and can open windows of opportunity for improved forecasts. However, operational models used for subseasonal forecasting suffer from systematic biases due to insufficient resolution or poorly performing parameterizations: they underestimate the strength of upward coupling from the troposphere to the stratosphere, they overestimate downward coupling of the lower stratosphere to near-surface polar cap height, and the polar lower stratosphere is too cold. Using data from 22 operational subseasonal models, we explore the implications of these biases on the skill of the Northern and Southern Annular Modes (NAM and SAM) in both the troposphere and stratosphere and for regional surface impacts. Updated or upgraded model versions from nearly all modeling centers show higher skill in both the stratospheric and tropospheric NAM and SAM as compared to their earlier versions, and models with relatively higher skill for the stratospheric annular modes generally have higher skill for the tropospheric annular modes as well. Near-surface AM skill is significantly higher for initializations during strong vortex states, and to a lesser degree during weak vortex states. Models with particularly poor upward coupling strengths and with too-weak climatological heat flux at 100 hPa suffer from reduced stratospheric NAM and SAM skill. In contrast, mean state biases in the stratospheric polar vortex are relatively unimportant for stratospheric NAM and SAM skill. Even as downward coupling over the North Atlantic and Antarctica tends to be handled well by these models, they produce an overly zonal response with a fictitious center of action in the midlatitude North Pacific, while underestimating the midlatitude near-surface temperature impacts over Eurasia, Australia, and South America. Downward coupling in the North Pacific is particularly pronounced in models with overly strong variance in this region, and models underestimate the wave-3 pattern in Southern Hemisphere (SH) midlatitudes by a factor of three. These biases in downward coupling mirror biases in the midlatitude structure of the tropospheric NAM and SAM. Overall, models with finer vertical resolution near the tropopause, with a better representation of tropospheric quasi-stationary waves, and with a better representation of these coupling processes, are more skillful in both the stratosphere and troposphere. These findings have implications for future research directions of the Stratospheric Network for the Assessment of Predictability.

Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability and can open windows of opportunity for improved forecasts. Model biases can, however, lead to a poor representation of such coupling processes; drifts in a model's circulation related to model biases, resolution, and parameterizations have the potential to feed back on the circulation and affect stratosphere–troposphere coupling. We introduce a set of diagnostics using readily available data that can be used to reveal these biases and then apply these diagnostics to 22 S2S forecast systems. In the Northern Hemisphere, nearly all S2S forecast systems underestimate the strength of the observed upward coupling from the troposphere to the stratosphere, downward coupling within the stratosphere, and the persistence of lower-stratospheric temperature anomalies. While downward coupling from the lower stratosphere to the near surface is well represented in the multi-model ensemble mean, there is substantial intermodel spread likely related to how well each model represents tropospheric stationary waves. In the Southern Hemisphere, the stratospheric vortex is oversensitive to upward-propagating wave flux in the forecast systems. Forecast systems generally overestimate the strength of downward coupling from the lower stratosphere to the troposphere, even as most underestimate the radiative persistence in the lower stratosphere. In both hemispheres, models with higher lids and a better representation of tropospheric quasi-stationary waves generally perform better at simulating these coupling processes.

Subseasonal forecast models are shown to suffer from the same inconsistency found in climate models between the low strength of predictable signals and the relatively high level of agreement they exhibit with observed variability of the atmospheric circulation. That is, subseasonal forecast models show higher correlation with observed variability than with their own simulations, i.e., the signal-to-noise paradox. Also similar to climate models, this paradox is particularly evident in the North Atlantic sector. The paradox is not evident in week 1 or week 2 forecasts, and hence is limited to subseasonal timescales. The paradox appears to be related to overly fast decay of Northern Annular Mode regimes. Three possible causes of this overly fast decay and for the paradox in the Northern Hemisphere are identified: a too-fast decay of polar stratospheric signals, overly weak downward coupling from the stratosphere to the surface (in some models), and overly weak transient synoptic eddy feedbacks. While the paradox is clearly evident in the North Atlantic, things are qualitatively different in the Southern Hemisphere: Southern Annular Mode regimes persist realistically, the stratospheric signal is well maintained, and eddy feedback is, if anything, too strong and zonal.

Sudden stratospheric warmings (SSWs) are the most dramatic wintertime stratospheric phenomena. They are preceded by a sustained wave dissipation in the stratosphere that leads to the deceleration of the polar vortex. The signal from SSWs then typically propagates downward reaching the troposphere and inducing a negative phase of the Annular Mode that may persist several weeks up to two months. Incorporating then stratospheric information in subseasonal to seasonal (S2S) forecast systems has been shown to improve the skill of S2S predictions for surface climate. However, on average, present S2S forecast systems can only predict SSWs around two weeks before the onset of the event. A suggested strategy to increase their predictability is to improve the representation of triggering mechanisms of SSWs. However, while there is a consensus on the relevance of the wave activity for that, the origin of the rapid enhancement of stratospheric wave activity prior to SSWs is not sufficiently understood.The aim of this study is two-fold: to assess the ability of forecast systems to reproduce the stratospheric wave amplification during SSWs and to quantify the role of the stratosphere in this enhanced upward wave propagation. To do so, we analyze the triggering mechanisms of three different SSWs, the boreal SSWs of 2018 and 2019 and the austral minor SSW of 2019, by means of SNAPSI (Stratospheric Nudging And Predictable Surface Impacts) sets of forecast ensembles. These ensembles include free-evolving atmospheric runs and nudged simulations where the zonally-symmetric stratospheric state is nudged to either observations of a certain SSW or a climatological state. Our results show that models struggle to predict the SSW of 2018, as they are not able to capture the strong enhancement of wavenumber-2 wave activity around one week before the event. In contrast, most ensemble members of all models are able to simulate both SSWs of 2019, but with some common issues such as an early timing for the NH event and a weaker deceleration of the vortex in the case of the SH SSW. In the three cases, capturing both the tropospheric precursors and the interactions of waves with the stratospheric flow are revealed to be crucial for the occurrence of the phenomena. However, the relative role of each contribution is different depending on the individual event. This is a contribution of the Working Group 4 of the SNAPSI initiative.

Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability. Extratropical coupling between the stratosphere and the surface may modulate the tropospheric circulation in predictable ways and/or provide forecast windows of opportunity. S2S forecast models may struggle to represent such coupling processes; at longer lead times, drifts in a model’s circulation related to model configurations, biases, and parameterizations have the potential to feedback and affect stratosphere-troposphere coupling. This presentation will highlight results from an international SPARC-SNAP (Stratospheric Network for the Assessment of Predictability) community effort to diagnose and characterize biases in stratosphere-troposphere coupling in S2S models. We find that in the Northern Hemisphere, the S2S forecast systems struggle to reproduce the strength of observed upward coupling from the troposphere to the stratosphere, while downward coupling is mostly well represented. In the Southern Hemisphere, forecast systems generally overestimate downward coupling strength, despite underestimating radiative persistence in the lower stratosphere.

This study continues the evaluation of the prediction of MJO teleconnections in two versions of the NOAA Unified Forecast System (UFS): prototype 5 (UFS5) and prototype 6 (UFS6). The key difference between the two prototypes is in the number of vertical layers (127 in UFS6 vs. 64 in UFS5) and model top (80 km in UFS6 vs. 54 km in UFS5), and the role of this increased resolution for the stratospheric pathway of MJO teleconnections is explored. The higher resolution prototype (UFS6) displays larger biases in its representation of tropospheric stationary waves, though both simulate a reasonable flux of wave activity entering the stratosphere. The stratospheric polar vortex in both prototypes is overly-sensitive to incoming wave activity, while both simulate a reasonable downward propagation of vortex anomalies within the stratosphere and down to the troposphere. The net effect is that both simulate the stratospheric pathway of the MJO better than has been documented for any forecasting system, though the hindcast period available for UFS differs from that used in previous studies. This allows them to predict, e.g., near-surface temperature over Eurasia with some skill on subseasonal timescales (week 3 to 5). However, this success could be the result of “two wrongs making a right”, and as individual biases are fixed, skill could temporarily be reduced. Overall, the two prototypes show similar performance in simulating the stratospheric route, suggesting that in the UFS, the increase in model vertical resolution has a limited impact on the prediction of MJO teleconnections via the stratosphere.

We analyze the sources for spread in the response of the Northern Hemisphere wintertime stratospheric polar vortex (SPV) to global warming in Climate Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) model projections. About half of the intermodel spread in SPV projections by CMIP6 models, but less than a third in CMIP5 models, can be attributed to the intermodel spread in stationary planetary wave driving. In CMIP6, SPV weakening is mostly driven by increased upward wave flux from the troposphere, while SPV strengthening is associated with increased equatorward wave propagation away from the polar stratosphere. We test hypothesized factors contributing to changes in the upward and equatorward planetary wave fluxes and show that an across‐model regression using projected global warming rates, strengthening of the subtropical jet and basic state lower stratospheric wind biases as predictors can explain nearly the same fraction in the CMIP6 SPV spread as the planetary wave driving (r = 0.67). The dependence of the SPV spread on the model biases in the basic state winds offers a possible emergent constraint; however, a large uncertainty prevents a substantial reduction of the projected SPV spread. The lack of this dependence in CMIP5 further calls for better understanding of underlying causes. Our results improve understanding of projected SPV uncertainty; however, further narrowing of the uncertainty remains challenging.

Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability and can open windows of opportunity for improved forecasts. Model biases can, however, lead to a poor representation of such coupling processes; drifts in a model’s circulation related to model biases, resolution, and parameterizations have the potential to feed back on the circulation and affect stratosphere-troposphere coupling. In the Northern Hemisphere, nearly all S2S forecast systems underestimate the strength of the observed upward coupling from the troposphere to the stratosphere, downward coupling within the stratosphere, and the persistence of lower stratospheric temperature anomalies. While downward coupling from the lower stratosphere to the near surface is well represented in the multi-model ensemble mean, there is substantial inter-model spread likely related to how well each model represents tropospheric stationary waves. In the Southern Hemisphere, the stratospheric vortex is over-sensitive to upward propagating wave flux in the forecast systems. Forecast systems generally overestimate the strength of downward coupling from the lower stratosphere to the troposphere, even as they underestimate the radiative persistence in the lower stratosphere. In both hemispheres, models with higher lids and a better representation of tropospheric quasi-stationary waves generally perform better at simulating these coupling processes.