Stratosphere-troposphere coupling enhances subseasonal predictability of Northern Eurasian cold spells

Here we explore the stratospheric influence on the predictability of Eurasian cold-spell events using the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble hindcasts obtained from the Subseasonal-to-Seasonal (S2S) archive. To isolate the stratospheric influence, we subsampled two groups of hindcasts according to the strength of the stratospheric polar vortex preceding the cold spells at the surface. The predicted probability of cold spells, defined as the lowest 10th percentile of weekly mean temperature anomalies over northern Eurasia (10 degrees W-130 degrees E and 50 degrees N-65 degrees N), is systematically higher, by 0.05-0.2, at lags 7-24 days in the forecasts initialized during the weak stratospheric vortex compared to the strong stratospheric vortex group, extending the predictability of cold spells by 3-5 days. Our results suggest that, in the case of the weak polar vortex, stratosphere-troposphere coupling favors the negative Northern Annular Mode (NAM) regime and the cold-air outbreaks in Eurasia. As a consequence, the long stratospheric predictability extends the predictability of the cold spells. On the other hand, when the polar vortex is strong, the stratospheric anomalies do not favor the observed negative NAM regime, which thus results from the internal tropospheric processes only. In this case the predictability of cold-air spells is limited. Furthermore, we show that the extended predictability of cold spells arising from the stratosphere-troposphere coupling is captured by a simple statistical model, suggesting that governing large-scale dynamics behave effectively linearly over some limited periods. Quantified contribution of the stratosphere-troposphere coupling to the enhanced skill of the extended-range cold-spell forecasts documented in our paper may prove useful in the development of forecasting tools.Peer reviewe

Boundary-layer height and surface stability at Hyytiälä, Finland, in ERA5 and observations

We investigate the boundary-layer (BL) height at Hyytiala in southern Finland diagnosed from radiosonde observations, a microwave radiometer (MWR) and ERAS reanalysis. Four different, pre-existing algorithms are used to diagnose the BL height from the radiosondes. The diagnosed BL height is sensitive to the method used. The level of agreement, and the sign of systematic bias between the four different methods, depends on the surface-layer stability. For very unstable situations, the median BL height diagnosed from the radiosondes varies from 600 to 1500 m depending on which method is applied. Good agreement between the BL height in ERAS and diagnosed from the radiosondes using Richardson-number-based methods is found for almost all stability classes, suggesting that ERAS has adequate vertical resolution near the surface to resolve the BL structure. However, ERAS overestimates the BL height in very stable conditions, highlighting the ongoing challenge for numerical models to correctly resolve the stable BL. Furthermore, ERAS BL height differs most from the radiosondes at 18:00 UTC, suggesting ERAS does not resolve the evening transition correctly. BL height estimates from the MWR are also found to be reliable in unstable situations but often are inaccurate under stable conditions when, in comparison to ERAS BL heights, they are much deeper. The errors in the MWR BL height estimates originate from the limitations of the manufacturer's algorithm for stable conditions and also the misidentification of the type of BL. A climatology of the annual and diurnal cycle of BL height, based on ERA5 data, and surface-layer stability, based on eddy covariance observations, was created. The shallowest (353 m) monthly median BL height occurs in February and the deepest (576 m) in June. In winter there is no diurnal cycle in BL height; unstable BLs are rare, yet so are very stable BLs. The shallowest BLs occur at night in spring and summer, and very stable conditions are most common at night in the warm season. Finally, using ERA5 gridded data, we determined that the BL height observed at Hyytiala is representative of most land areas in southern and central Finland. However, the spatial variability of the BL height is largest during daytime in summer, reducing the area over which BL height observations from Hyytiala would be representative.Peer reviewe

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

Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems

The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lower-stratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system\u27s climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for subseasonal-to-seasonal forecast systems and further our understanding of the role of the stratosphere in predictive skill in the troposphere

Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems

The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lower-stratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system's climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for subseasonal-to-seasonal forecast systems and further our understanding of the role of the stratosphere in predictive skill in the troposphere

Simulation of the ENSO influence on the extra-tropical middle atmosphere

Abstract The impact of the El Niño Southern Oscillation (ENSO) on the Northern Hemisphere mid-winter zonal wind, temperature, and stationary planetary waves (SPWs) is evaluated using the Middle and Upper Atmosphere Model and Modern-Era Retrospective Analysis for Research and Applications (MERRA). The composites determined using simulated ensembles and MERRA winters with different ENSO phases show that the mean zonal wind in the stratosphere at higher-middle latitudes is weaker and polar region is warmer, and the activity of SPW1 is higher during El Niño events. The simulated and observed SPW2 amplitude behaves in the opposite way, and it is stronger in the stratosphere during La Niña. The observed changes of SPW1 and SPW2 amplitudes under La Niña and El Niño events should affect an efficiency of the stratosphere–troposphere coupling in different longitudinal sectors through the changes in horizontal distributions of the downward wave activity flux

Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems

The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lower-stratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system's climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for subseasonal-to-seasonal forecast systems and further our understanding of the role of the stratosphere in predictive skill in the troposphere.ISSN:2698-402