Mixed layer temperature response to the southern annular mode: Mechanisms and model representation

Previous studies have shown that simulated sea surface temperature (SST) responses to the southern annular mode (SAM) in phase 3 of the Coupled Model Intercomparison Project (CMIP3) climate models compare poorly to the observed response. The reasons behind these model inaccuracies are explored. The ocean mixed layer heat budget is examined in four of the CMIP3 models and by using observations- reanalyses. The SST response to the SAM is predominantly driven by sensible and latent heat flux and Ekman heat transport anomalies. The radiative heat fluxes play a lesser but nonnegligible role. Errors in the simulated SST responses are traced back to deficiencies in the atmospheric response to the SAM. The models exaggerate the surface wind response to the SAM leading to large unrealistic Ekman transport anomalies. During the positive phase of the SAM, this results in excessive simulated cooling in the 40°-65°S latitudes. Problems with the simulated wind stress responses, which relate partly to errors in the simulated winds themselves and partly to the transfer coefficients used in the models, are a key cause of the errors in the SST response. In the central Pacific sector (90°-150°W), errors arise because the simulated SAM is too zonally symmetric. Substantial errors in the net shortwave radiation are also found, resulting from a poor repre- sentation of the changes in cloud cover associated with the SAM. The problems in the simulated SST re- sponses shown by this study are comparable to deficiencies previously identified in the CMIP3 multimodel mean. Therefore, it is likely that the deficiencies identified here are common to other climate models

Atmospheric Circulation Response to Anomalous Siberian Forcing in October 2016 and its Long‐Range Predictability

Abstract: The warm Arctic-cold continent pattern was of record strength in October 2016, providing the opportunity to test its proposed influence on large-scale atmospheric circulation. We find a record weak polar stratospheric vortex and negative North Atlantic Oscillation in November-December 2016 and link them to increased planetary wave generation associated with cold Siberian anomalies followed by troposphere-stratosphere dynamical coupling. At the same time the warm Arctic anomalies, in particular those over the Barents-Kara Seas, do not appear to play an important role in forcing the atmospheric circulation. Long-range forecasts initialized on 1 October 2016 reproduced both the weak polar vortex and negative North Atlantic Oscillation, as well as their link with the Siberian temperatures. Our results support the stratospheric pathway for atmospheric circulation forcing associated with Siberian surface anomalies and uncover a source of skill for subseasonal forecasts from October to December. Plain Language Summary: The warm Arctic-cold continent pattern is an observed, large-scale pattern of near-surface temperatures where the Arctic is warmer than average and Siberia is colder than average. This pattern was of record strength in October 2016, providing the opportunity to test its influence on the Northern Hemisphere atmospheric circulation and the possibility of skillful long-range forecasts. It has been proposed that the warm Arctic-cold continent pattern can drive large atmospheric waves, which are able to travel from the troposphere into the stratosphere, where they weaken the strong wintertime winds that make up the stratospheric polar vortex. A weakened polar vortex can then lead to changes in the surface pressure that can affect weather patterns. We find a record weak polar stratospheric vortex in late autumn 2016 and link that to cold Siberian anomalies. At the same time the warm Arctic anomalies do not appear to play an important role in forcing the atmospheric circulation. Long-range forecasts initialized in October 2016 reproduced both the weak polar vortex and resulting surface pressure patterns. Our results support the stratospheric pathway for atmospheric circulation forcing by Siberian surface anomalies and uncover a source of skill for subseasonal forecasts in the Northern Hemisphere autumn.Peer reviewe

Predicting sudden stratospheric warming 2018 and its climate impacts with a multi‐model ensemble

Sudden stratospheric warmings (SSWs) are significant source of enhanced subseasonal predictability, but whether this source is untapped in operational models remains an open question. Here we report on the prediction of the SSW on 12 February 2018, its dynamical precursors, and surface climate impacts by an ensemble of dynamical forecast models. The ensemble forecast from 1 February predicted 3 times increased odds of an SSW compared to climatology, although the lead time for SSW prediction varied among individual models. Errors in the forecast location of a Ural high and underestimated magnitude of upward wave activity flux reduced SSW forecast skill. Although the SSW's downward influence was not well forecasted, the observed northern Eurasia cold anomaly following SSW was predicted, albeit with a weaker magnitude, due to persistent tropospheric anomalies. The ensemble forecast from 8 February predicted the SSW, its subsequent downward influence, and a long‐lasting cold anomaly at the surface

The tropical influence on sub‐seasonal predictability of wintertime stratosphere and stratosphere–troposphere coupling

A unique set of relaxation experiments with a forecast model initialized during December–January 1999–2019 is used to explore tropical influence on the Northern Hemisphere polar stratosphere and stratosphere–troposphere coupling, to quantify predictability benefits due to the perfect knowledge of the tropical variability. On average, predictability of the polar stratosphere, as represented by the 50 hPa geopotential height anomalies north of 50°N (Z50), increases from 17 days in freely running (control) forecasts to 21 days in the tropical relaxation experiments. At sub‐seasonal time‐scales, a statistically significant improvement in weekly mean skill scores can be demonstrated in 14%–20% of individual forecast ensembles, mostly in cases when the skill of the corresponding control forecast is worse than average. In these forecasts, root‐mean‐square errors and forecast spread of Z50 during forecast weeks 3–5 are decreased by 10%–15%. Stratospheric improvements are detected during periods of both vortex strengthening and vortex weakening, including most major Sudden Stratospheric Warmings that occurred during the study period, via modulation of the upward wave activity fluxes. An active Madden–Julian Oscillation (MJO) is found in most of these events with MJO phase 5–7 preceding vortex weakening and MJO phase 3–4 preceding vortex strengthening. Forecasts with improved stratospheric circulation also have improved tropospheric circulation during and after the periods when improvements are detected in the stratosphere. We attribute these improvements to both stratosphere–troposphere coupling and tropospheric tropical teleconnections

A minimal model to diagnose the contribution of the stratosphere to tropospheric forecast skill

Many recent studies have confirmed that variability in the stratosphere is a significant source of surface sub-seasonal prediction skill during Northern Hemisphere winter. It may be beneficial, therefore, to think about times in which there might be windows-of-opportunity for skillful sub-seasonal predictions based on the initial or predicted state of the stratosphere. In this study, we propose a simple, minimal model that can be used to understand the impact of the stratosphere on tropospheric predictability. Our model purposefully excludes state dependent predictability in either the stratosphere or troposphere or in the coupling between the two. Model parameters are set up to broadly represent current sub-seasonal prediction systems by comparison with four dynamical models from the Sub-Seasonal to Seasonal Prediction Project database. The model can reproduce the increases in correlation skill in sub-sets of forecasts for weak and strong lower stratospheric polar vortex states over neutral states despite the lack of dependence of coupling or predictability on the stratospheric state. We demonstrate why different forecast skill diagnostics can give a very different impression of the relative skill in the three sub-sets. Forecasts with large stratospheric signals and low amounts of noise are demonstrated to also be windows-of-opportunity for skillful tropospheric forecasts, but we show that these windows can be obscured by the presence of unrelated tropospheric signals

Improving Antarctic Total Ozone Projections by a Process-Oriented Multiple Diagnostic Ensemble Regression

Accurate projections of stratospheric ozone are required because ozone changes affect exposure to ultraviolet radiation and tropospheric climate. Unweighted multimodel ensemble-mean (uMMM) projections from chemistry–climate models (CCMs) are commonly used to project ozone in the twenty-first century, when ozone-depleting substances are expected to decline and greenhouse gases are expected to rise. Here, the authors address the question of whether Antarctic total column ozone projections in October given by the uMMM of CCM simulations can be improved by using a process-oriented multiple diagnostic ensemble regression (MDER) method. This method is based on the correlation between simulated future ozone and selected key processes relevant for stratospheric ozone under present-day conditions. The regression model is built using an algorithm that selects those process-oriented diagnostics that explain a significant fraction of the spread in the projected ozone among the CCMs. The regression model with observed diagnostics is then used to predict future ozone and associated uncertainty. The precision of the authors’ method is tested in a pseudoreality; that is, the prediction is validated against an independent CCM projection used to replace unavailable future observations. The tests show that MDER has higher precision than uMMM, suggesting an improvement in the estimate of future Antarctic ozone. The authors’ method projects that Antarctic total ozone will return to 1980 values at around 2055 with the 95% prediction interval ranging from 2035 to 2080. This reduces the range of return dates across the ensemble of CCMs by about a decade and suggests that the earliest simulated return dates are unlikely

Northern hemisphere stratosphere‐troposphere circulation change in CMIP6 models: 1. inter‐model spread and scenario sensitivity

Projected changes in the Northern Hemisphere stratospheric polar vortex are analyzed using Climate Model Intercomparison Project Phase 6 experiments. Previous studies showed that projections of the wintertime zonally averaged polar vortex strength diverge widely between climate models with no agreement on the sign of change, and that this uncertainty contributes to the regional climate change uncertainty. Here, we show that there remains large uncertainty in the projected strength of the polar vortex in experiments with global warming levels ranging from moderate (SSP245 runs) to large (Abrupt-4xCO2 runs), and that the uncertainty maximizes in winter. Partitioning of the uncertainty in wintertime polar vortex strength projections reveals that, by the end of the 21st century, model uncertainty contributes half of the total uncertainty, with scenario uncertainty contributing only 10%. Regression analysis shows that up to 20% of the intermodel spread in projected precipitation over the Iberian Peninsula and northwestern US, and 20%–30% in near-surface temperature over western US and northern Eurasian, can be associated with the spread in vortex strength projections after accounting for global warming. While changes in the magnitude and sign of the zonally averaged vortex strength are uncertain, most models (>95%) predict an eastward shift of the vortex by 8°–20° degrees in longitude relative to its historical location with the magnitude of the shift increasing for larger global warming levels. There is less agreement across models on a latitudinal shift, whose direction and magnitude correlate with changes in the zonally averaged vortex strength so that vortex weakening/strengthening corresponds to a southward/poleward shift

Revisiting the Mystery of Recent Stratospheric Temperature Trends

Simulated stratospheric temperatures over the period 1979–2016 in models from the Chemistry-Climate Model Initiative are compared with recently updated and extended satellite data sets. The multimodel mean global temperature trends over 1979–2005 are -0.88 ± 0.23, -0.70 ± 0.16, and -0.50 ± 0.12 K/decade for the Stratospheric Sounding Unit (SSU) channels 3 (~40–50 km), 2 (~35–45 km), and 1 (~25–35 km), respectively (with 95% confidence intervals). These are within the uncertainty bounds of the observed temperature trends from two reprocessed SSU data sets. In the lower stratosphere, the multimodel mean trend in global temperature for the Microwave Sounding Unit channel 4 (~13–22 km) is -0.25 ± 0.12 K/decade over 1979–2005, consistent with observed estimates from three versions of this satellite record. The models and an extended satellite data set comprised of SSU with the Advanced Microwave Sounding Unit-A show weaker global stratospheric cooling over 1998–2016 compared to the period of intensive ozone depletion (1979–1997). This is due to the reduction in ozone-induced cooling from the slowdown of ozone trends and the onset of ozone recovery since the late 1990s. In summary, the results show much better consistency between simulated and satellite-observed stratospheric temperature trends than was reported by Thompson et al. (2012, https://doi.org/10.1038/nature11579) for the previous versions of the SSU record and chemistry-climate models. The improved agreement mainly comes from updates to the satellite records; the range of stratospheric temperature trends over 1979–2005 simulated in Chemistry-Climate Model Initiative models is comparable to the previous generation of chemistry-climate models

The role of the stratosphere in subseasonal to seasonal prediction part I: predictability of the stratosphere

The stratosphere has been identified as an important source of predictability for a range of processes on subseasonal to seasonal (S2S) timescales. Knowledge about S2S predictability within the stratosphere is however still limited. This study evaluates to what extent predictability in the extratropical stratosphere exists in hindcasts of operational prediction systems in the S2S database. The stratosphere is found to exhibit extended predictability as compared to the troposphere. Prediction systems with higher stratospheric skill tend to also exhibit higher skill in the troposphere. The analysis also includes an assessment of the predictability for stratospheric events, including early and mid‐winter sudden stratospheric warming (SSW) events, strong vortex events, and extreme heat flux events for the Northern Hemisphere, and final warming events for both hemispheres. Strong vortex events and final warming events exhibit higher levels of predictability as compared to SSW events. In general, skill is limited to the deterministic range of one to two weeks. High‐top prediction systems overall exhibit higher stratospheric prediction skill as compared to their low‐top counterparts, pointing to the important role of stratospheric representation in S2S prediction models