This workshop brought together experts to discuss and propose ways forward in representing the stratosphere in current and future numerical weather prediction models (1-50 km resolution, forecast lead times from medium-range to seasonal), and pathways by which better treatment of the stratosphere can improve predictive skill in the troposphere. The topics included understanding and diagnosing stratosphere-troposphere interactions, improved parametrizations and numerical schemes, the role of water vapour and ozone, observational evaluation and data assimilation. The aim of the workshop was to provide guidance to ECMWF on the priorities for representing the stratosphere in the coming decade.
Over the past 20 years the notion that the stratosphere is intimately involved in tropospheric predictability has evolved from fanciful hypothesis to established fact. The physical timescales are such that the stratosphere can provide a source of internal atmospheric predictability on subseasonal to seasonal timescales, and many studies have shown that the impact on the troposphere can be of first-order importance. Current scientific questions now revolve around identifying the relevant physical mechanisms, improving the representation of the stratosphere (and of stratosphere-troposphere coupling) in atmospheric models, and understanding how deficiencies in the models affect the predictions. The benefits of this work reach beyond extended-range prediction to decadal prediction and climate change, as they help interpret the role of the stratosphere in those applications by providing a more causal, process-oriented perspective. This talk will give an overview of the results from the ECMWF Stratosphere Task Force and a perspective on opportunities for further progress in this area.
Stratospheric variability is increasingly being investigated as a potential source of tropospheric predictive skill on sub-seasonal to seasonal (S2S) timescales. Here we provide a broad overview of stratosphere-troposphere coupling processes in the S2S prediction systems. We consider both the predictability of the stratosphere itself, and the influence of stratospheric variability on the predictive skill of surface climate. We apply this framework to different types of extratropical stratospheric variability, such as sudden stratospheric warmings and final stratospheric warmings. We highlight issues in the S2S models, such as the loss of the Quasi-biennial Oscillation signal within 1-2 weeks after initialization. Finally, we will discuss future experiments using the S2S models that are being proposed to the modeling community to better isolate the role of the stratosphere in surface climate predictability.
On sub-seasonal timescales, coupling between the stratosphere and troposphere represents a significant source of skill for northern mid and high-latitudes. Previous studies have examined this skill either on a case-by-case basis or from the perspective of the additional skill present during sudden stratospheric warming (SSW) or strong polar vortex events. Here we complement these approaches by fitting a simple statistical model to the full hindcast set available from the S2S database. The statistical model used enable us to separate the predictable signal and noise in the annular mode present in each hindcast set and to compare the signal to noise ratio in the model and in observations. While all models in the S2S database exhibit some degree of stratosphere-troposphere coupling in the annular mode, there are significant differences between them. In the middle and lower stratosphere, models have high skill out to week four, with large signal to noise ratio. In the troposphere, annular mode skill is weaker in weeks three and four. In the lower stratosphere, many models have low spread and are over-confident. In the troposphere, there is similar overconfidence, particularly in week 3. The same statistical model also allows us to examine how the predictable signal varies between different events and different models.
This study investigates the influence of atmospheric initial conditions on winter seasonal forecasts of the North Atlantic Oscillation (NAO). Hindcast (or reforecast) experiments – which differ only in their initial conditions – are performed over the period 1960–2009, using prescribed sea surface temperature (SST) and sea‐ice boundary conditions. The first experiment (“ERA‐40/Int IC”) is initialized using the ERA‐40 and ERA‐Interim reanalysis datasets, which assimilate upper‐air, satellite and surface observations; the second experiment (“ERA‐20C IC”) is initialized using the ERA‐20C reanalysis dataset, which assimilates only surface observations. The ensemble mean NAO skill is largest in ERA‐40/Int IC (r = 0.54), which is initialized with the superior reanalysis data. Moreover, ERA‐20C IC did not exhibit significantly more NAO hindcast skill (r = 0.38) than in a third experiment, which was initialized with incorrect (shuffled) initial conditions. The ERA‐40/Interim and ERA‐20C initial conditions differ substantially in the tropical stratosphere, where the quasi‐biennial oscillation (QBO) of zonal winds is not present in ERA‐20C. The QBO hindcasts are highly skilful in ERA‐40/Int IC – albeit with a somewhat weaker equatorial zonal wind amplitude in the lower stratosphere – but are incorrect in ERA‐20C IC, indicating that the QBO is responsible for the additional NAO hindcast skill; this is despite the model exhibiting a relatively weak teleconnection between the QBO and NAO. Whilst ERA‐40/Int IC demonstrates a more skilful NAO hindcast, it appears to have a relatively weak predictable signal; this is the so‐called “signal‐to‐noise paradox” identified in previous studies. Diagnostically amplifying the (weak) QBO–NAO teleconnection increases the ensemble‐mean NAO signal with negligible impact on the NAO hindcast skill, after which the signal‐to‐noise problem seemingly disappears.
Several recent studies have suggested that the stratosphere can be a source of subseasonal-to-seasonal predictability of Southern Hemisphere circulation during the austral spring and early summer seasons, through its influence on the eddy-driven jet. We exploit the large sample size afforded by the hindcasts from the European Centre for Medium-Range Weather Forecasts Integrated Forecast System to address a number of unanswered questions. It is shown that the picture of coherent seasonal variability of the coupled stratosphere-troposphere system apparent from the reanalysis record during the spring/early summer period is robust to sampling uncertainty, and that there is evidence of nonlinearity in the case of the most extreme variations. The effect of El Niño-Southern Oscillation on the eddy-driven jet during this time of year is found to occur via the stratosphere, with no evidence of a direct tropospheric pathway. A simple two-state statistical model of the stratospheric vortex is introduced to estimate the subseasonal-to-seasonal predictability associated with shifts of the seasonal cycle in the SH extratropical atmosphere. This simple model, along with a more general model, are subsequently used to interpret skill scores associated with hindcasts made using the full seasonal forecast model. Together the results provide evidence of tropospheric predictability on subseasonal-to-seasonal timescales from at least as early as August 1, and show no evidence of a ‘signal-to-noise paradox’ between the full seasonal forecast model and the reanalysis.
Early ideas on the dynamics of stratosphere-troposphere coupling involved planetary-waves directly coupling both regions. However, recent work has largely focused on coupling via the zonal-mean flow as observed during Stratospheric Sudden Warmings (SSWs). Here, the dynamics of planetary-wave coupling is revisited in the context of extreme positive and negative wave-1 stratospheric heat flux events which are associated with an equatorward and poleward shift of the North-Atlantic jet, respectively. Ensemble spectral nudging experiments in a dry-dynamical core model are performed to determine the mechanisms underlying the events, including their coupling with the tropospheric circulation and their links to SSWs. The results suggest extreme stratospheric wave-1 heat flux events are consistent with the paradigm of linear vertically propagating waves but also reveal an unexpected role for non-linearities involving higher-order wavenumbers. It is argued that planetary-wave coupling is a key dynamical pathway linking the stratosphere with the troposphere and provides insight on the dynamics of zonal-mean flow coupling.
Sudden stratospheric warming (SSW) events significantly disrupt the stratospheric circulation, and are a major mode of subseasonal variability in the winter atmosphere. Major SSWs appear as dramatic polar-cap warmings of 20K or more, accompanied by weakening of the circumpolar zonal wind and reversal from the normal westerly to easterly wind. SSW anomalies can develop rapidly over days, descend in time over 1-2 weeks, and persist at the tropopause for 1-2 months. These stratospheric wind changes affect the vertical and latitudinal propagation of planetary waves throughout the atmosphere and are statistically associated with anomalous southward shifts in the storm tracks and associated changes in surface temperature and precipitation patterns. Previous work has suggested enhanced prediction skill at 16-60 day forecast range when forecasts are initialized during SSW events. However, prediction of the onset of SSWs themselves has been poor beyond ~10-day lead times.
We examine historical SSW events as forecasts of opportunity in NASA’s seasonal-to-subseasonal (S2S) forecasting system. The work examines GEOS-S2S Version 2 (V2) developed in NASA’s Global Modeling and Assimilation Office (GMAO) at Goddard Space Flight Center. Compared to GMAO’s previous S2S system, V2 runs at higher atmospheric resolution (approximately 1/2-deg globally), contains a substantially improved model of the cryosphere, includes additional interactive aerosol model components, and the ocean data assimilation system has been replaced with a Local Ensemble Transform Kalman Filter. A set of retrospective 45-day forecasts was initialized based on the MERRA-2 reanalysis at 5-day intervals throughout years 1999 to present, with four ensemble members per initialization date. Our analysis of these retrospective forecasts reveals surface anomaly patterns in the ~30-day period following the onset of SSW events, and compares skill in forecasts initialized during an SSW to those initialized during normal winter conditions. We investigate how far in advance the GEOS-S2S-V2 system can forecast major SSW events themselves. We also examine the roles of extratropical wave activity, stratospheric wind biases, and parameterized gravity wave drag on forecast skill.
This talk presents an overview of evidence, from the Met Office seasonal to decadal forecasting team, of the impact of the stratosphere on surface climate in observations and models. Stratospheric sudden warmings can be predicted deterministically almost two weeks in advance, impact the North Atlantic Oscillation, and enhance skill in seasonal forecasts. ENSO, and the Quasi-Biennial Oscillation in the tropical stratosphere, both also impact the winter north Atlantic via stratospheric teleconnection pathways. In the southern hemisphere, the southern annular mode is impacted by stratospheric anomalies with a two month lead time. Finally, stratospheric water vapour concentrations, influenced in models by ozone, clouds, convection, and advection schemes, are known to impact on surface climate. Thus an accurate representation of the modelled stratospheric climatology and variability, via model resolution, upper boundary height, and a good representation of physical processes, is essential to increase the skill of seasonal forecasts.
Sudden stratospheric warming (SSW) events can have significant impacts on surface weather that can prevail for several weeks. However, not all SSW events have a surface impact, and the timing of this impact can vary strongly between SSW events. Mechanisms both in the lower stratosphere and in the troposphere have been suggested to be responsible for the distinct downward influence of different SSW events. At the same time, despite these often long-lived surface impacts, the timing of SSW events themselves is not predictable beyond deterministic lead times of a few days, and significant differences are found in the predictability of different SSW events. Both tropospheric precursors and stratospheric mechanisms such as resonance have been suggested to lead to SSW events, and are here suggested to impact their predictability. This contribution aims to discuss the link between the predictability of SSW events and their dynamical causes and impacts.
Accurate representation of the stratospheric circulation in numerical weather prediction models is important for tropospheric predictability on medium-range and seasonal timescales. However, operational forecast systems at the European Centre for Medium Range Weather Forecasts suffer from a number of stratospheric biases, two of which are highlighted in this talk: i) The cold polar tropopause bias, which maximizes in the Northern Hemisphere summer and is common to most numerical weather and climate prediction models; and ii) The global-mean cold bias in the stratosphere that amplifies with increase in the horizontal resolution without concomitant increase in the vertical resolution. The reasons behind these biases are discussed and solutions to alleviate them are proposed. More importantly, it is illustrated that eradicating the biases results in improved forecast skill in the troposphere at extended and seasonal forecast ranges motivating the need for further work in reducing stratospheric biases in numerical weather prediction models.
Sudden stratospheric warmings (SSWs) are the largest instance of the wintertime polar stratosphere and constitute one of the clearest examples of stratosphere-troposphere coupling in both directions. They are preceded by anomalously high upward-propagating wave activity, whose sources are located in the troposphere. In turn, SSWs also impact the tropospheric circulation up to two months after the occurrence of the event. Thus, a better understanding and model representation of SSWs processes would help to improve medium-long range surface weather forecasts.
This talk focuses on the representation of SSWs in reanalyses with a special focus on their tropospheric effects near-surface. First, we present an inter-reanalyses assessment of the representation of the most important aspects of SSWs by reanalyses. Our results reveal a very good agreement among all reanalyses for representing SSWs in the satellite era. However, larger discrepancies appear in the preceding period, probably due to the smaller number of observational data to assimilate and so, the stronger influence of the characteristics of the reanalysis models.
As a second step, we show the extraordinary rainy and windy conditions of March 2018 in southwestern Europe that ended the most severe drought in southwestern Europe. This anomalous weather happened after the occurrence of an intense SSW and our analysis gives evidence that it played a relevant role in the record-breaking precipitation event.
Recent studies have proposed that regional Arctic sea-ice anomalies influence
planetary wave propagation into the stratosphere and so affect the strength and
location of the stratospheric polar vortex. The polar stratosphere, in turn, is
known to significantly influence polar and midlatitude tropospheric weather
patterns, including affecting the likelihood of cold-air outbreaks and blocking
events. This `stratospheric pathway' connecting Arctic sea-ice and midlatitude
weather is therefore an important potential source of predictability over
seasonal time scales.
Here I will discuss some recent and ongoing work aimed at understanding the
mechanisms and robustness of the connection between Arctic sea-ice and the polar
stratosphere. First I will discuss an analysis of decadal trends using two large
ensembles of historical simulations with coupled climate models. This reveals
that while several ensemble members simulate a weakening and shift of the
stratospheric polar vortex similar to that observed, there is no robust
connection between polar vortex strength and regional or pan-Arctic sea-ice
anomalies in either ensemble. This is somewhat surprising given that several
recent modelling studies with imposed regional sea-ice anomalies have found such
a connection. I will then discuss some ongoing work, aimed at understanding this
discrepancy, using an idealised atmospheric model. This focuses both on the
impact of the model's representation of the stratosphere on the
sea-ice-stratosphere pathway, as well as the effect of sea-ice anomalies
imposed in different regions of the Arctic.
Extreme stratospheric polar events, in the form of Sudden Stratospheric Warmings (SSWs), have been shown to impact weather at the surface in the Northern Hemisphere, so an ability to accurately forecast them would improve forecast skill. Many studies have shown that statistical skill can be gained from knowledge of the QBO, ENSO and solar cycle phase but in rather general terms, telling us only if one is likely to occur sometime during the winter. Current seasonal forecast models are unable to forecast the timing of warming events, even though they are initialised e.g. with the correct phase of the QBO. In this study we examine factors that influence the timing of SSWs. We use 2 years as case studies, one with a displaced vortex (2005/6) and one with a split vortex (2008/9). The Met Office Unified Model is initialised with observations in early winter and then run with imposed observed sea surface temperatures. Various experiments are performed in which different regions of the atmosphere are nudged towards reality, with the main diagnostic being the timing of the simulated SSW and depth to which it extends. We find, perhaps not surprisingly, that the correct initialised QBO plus nudging throughout the troposphere alone is insufficient to accurately forecast the timing or depth of the SSW. Further experiments highlight the importance of achieving a good simulation of the upper equatorial stratosphere.
One of the key questions in the air quality and climate sciences is how will tropospheric ozone concentrations change in the future. This will depend on two factors: changes in stratosphere-to-troposphere transport (STT) and changes in tropospheric chemistry. Here we aim to identify robust changes in STT using simulations from the Chemistry Climate Model Initiative (CCMI) under a common climate change scenario (RCP 6.0). We use two idealized stratospheric tracers to isolate changes in transport: stratospheric ozone (O3S), which is exactly like ozone but has no chemical sources in the troposphere, and st80, a passive tracer with constant concentrations in the stratosphere. We find a robust increase in the tropospheric columns of these two tracers throughout the 21st century and analyze the underlying transport mechanisms in the Transformed Eulerian Mean (TEM) framework. Future STT is enhanced in the subtropics due to the strengthening of the Brewer-Dobson circulation in the lower stratosphere and of the top of the Hadley cell in the upper troposphere. In addition, enhanced isentropic eddy mixing increases STT in middle latitudes. It is shown that these STT changes are dominated by greenhouse gas increases, while ozone recovery only partly offsets the trends in the SH upper troposphere. A higher emission scenario (RCP 8.5) produces qualitatively similar but stronger STT trends.
The transport of trace gases through the stratosphere impacts surface climate. Small changes in stratospheric water vapor, on the order of one part per million, can impact surface temperature by as much as a tenth of a degree. A sudden drop in stratospheric water vapor of this magnitude – a response to internal variability of the atmosphere – was observed in 2000. Chemistry climate model simulations of stratospheric ozone also depend critically on the transport of ozone and ozone depleting substances, and biases in transport are a leading source of uncertainty in the recovery of stratospheric ozone. Volcanic aerosols (and the possibility of injecting sulfur into the stratosphere for climate intervention) provides another example of the importance of stratospheric tracer transport for the climate at the surface.
In this talk, I'll present evidence that observations of trace gases provide an opportunity to improve our ability to characterize and understand the circulation of the stratosphere. In particular, recent work enabled a measurement based estimate of the overturning circulation of the stratosphere, a first order climatological quantity that has been a challenge for atmospheric reanalyses. This suggests that incorporation of trace gas measurements into reanalyses could improve their ability to capture the dynamics and circulation of the stratosphere.
In the second half, I'll focus on the challenge tracer transport presents to numerical atmospheric models. A simple benchmark test of atmospheric model dynamical cores reveals the sensitivity of both the circulation and tracer transport to numerics and resolution. State-of-the-art numerical cores developed by GFDL and NCAR struggle to capture a consistent representation of stratospheric transport, even when differences in the treatment of atmospheric physics (i.e., radiative transfer, gravity wave drag, and chemistry) are controlled. We conclude that model development, and the details of numerical schemes, are still very important for accurate climate projection.
A key region of the stratosphere is the tropical tropopause layer (TTL) -- the main entry region of air from the troposphere to the stratosphere. Temperatures at the cold point in this region modulated the concentrations of stratospheric water vapour. The strength of the upwelling in this region affects the transport of chemical tracers across the tropopause. These factors determine composition and chemistry in the stratosphere, and subsequent the radiative impact on the troposphere. The TTL is a complex system where the properties are determined by radiative, dynamical and chemical interactions. In the presentation, we will examine, using ERA-Interim reanalysis data, the processes in the TTL on various timescales and their effect on the rest of the atmosphere. An important aspect of the TTL is how radiative changes arising from ozone and water vapour changes affect the circulation. By analysing the momentum and thermodynamics balances, we will describe the feedbacks occurring in the TTL both in the steady state, seasonal cycle and interannual variations. We will estimating the upwelling in the TTL from the wave torques by imposing it as a forcing in the zonally symmetric dynamical equations, linearised about the annual mean state and with a linearised radiation scheme. This calculation forms part of a hierarchy of model calculations that will allow the different interactions to be separated. These calculations will also be used to understand the impacts of composition changes arising from chemical processes.
This presentation reports on recent and ongoing model development work at DWD to improve the dynamical core and the physics parameterizations for model tops above the middle mesosphere, and to reduce systematic model biases in the lower stratosphere.
In the framework of a research group on multi-scale dynamics of gravity waves funded by the German Science Foundation (DFG), the dynamical core of the ICON model has been extended by an option to solve the deep-atmosphere equations. Idealized dynamical core tests were successfully used to validate the correctness of the numerical implementation. In addition, the physics parameterization packages of ICON have been extended to account for processes becoming relevant above the middle mesosphere, e.g. molecular diffusion and frictional heating. The results available so far indicate that short-to-medium-range NWP applications may not sufficiently benefit from these extensions to warrant the additional computational expenses, but is expected that future applications considering seasonal or longer timescales will take advantage of them.
Recent work on reducing model biases in the lower stratosphere has focused on the cold bias right above the extratropical troposphere, which is particularly pronounced in northern hemispheric summer, and on biases in the tropical tropopause region, which exhibit a much more complex structure in space and time. We were able to reduce the extratropical cold bias by introducing a simple ozone-tropopause coupling, which is based on diagnosing the thermal tropopause at each radiation call and modifying the climatological ozone profile such as to introduce an ozone jump across the tropopause if it is well-defined. This was also found to have a beneficial impact on tropospheric forecast skills. Ongoing work focuses on reducing the numerical diffusivity of the moisture transport scheme, as verification against radiosonde data indicates a moist bias growing with forecast lead time in this region. In the tropics, switching to a more recent ozone climatology has reduced the annual cycle of the lower-stratospheric temperature bias. Ongoing work focuses on improving remote-sensing based diagnostics.
Full stratospheric chemistry models are moderately expensive, and not suitable for high resolution ensemble forecasting at long lead times. Linear ozone models are cheap, but can suffer from biases compared to the latest ozone reanalyses, since they are traditionally calculated by linearizing a full chemistry model which is itself imperfect. These biases are an obstacle to using interactive ozone in the model radiative calculations. An alternative approach is to base the coefficients of a linear scheme on the latest re-analyses of ozone and temperature. Such a scheme is introduced, based on a hybrid approach combining mean terms derived from analyses and sensitivity coefficients derived from full chemistry models. Particular attention is given to deriving the mean production term from analysis data, and to ensuring consistency between all terms.
Results are highly encouraging, with the ozone model reproducing not only the analysed mean state, but also interannual and synoptic variability. Some of the benefits of including ozone variability in the model radiative calculations are illustrated. The benefits of other model improvements, such as the impact of increased vertical resolution on the QBO, will also be briefly discussed.
Atmospheric teleconnections play a key role in long-range climate predictability. Important question is how well these teleconnections are represented in forecast models which usually have biased climate with respect to observations. Here we investigate the effect of systematic model biases on teleconnections influencing the Northern Hemisphere wintertime circulation. We perform a two-step nudging/bias-correcting scheme where annually repeating bias-correction terms are added to the dynamic variables of the ECHAM6 atmospheric model to reduce errors in the annual climatology, relative to ERA Interim. This results in a reduction of errors in the DJF zonal stratospheric winds by up to 60%, in particular in an increase in the strength of the Northern Hemisphere wintertime stratospheric polar vortex during early winter.
We compare the responses in the bias-corrected and control runs to two factors: an increased Siberian snow cover in October, and a Quasi-Biennial Oscillation (QBO) in equatorial stratospheric zonal winds. For both factors, we find considerable differences between teleconnections in bias-corrected and control simulations. In the case of QBO teleconnection, bias corrected model shows stronger response of extratropical circulation to QBO variability, better reproducing the observed response than the original biased model. In the case of Siberian snow forcing - a forcing that has been suggested as a factor weakening the stratospheric polar vortex and inducing negative Arctic oscillation in winter – we find differences in the stratosphere-troposphere coupling, downward propagation of the signal, and subsequent surface response. Our results demonstrate the importance of atmospheric basic state for simulating teleconnections.
Abrupt breakdowns of the polar winter stratospheric circulation such as sudden stratospheric warmings (SSWs) are a manifestation of strong two-way interactions between upward propagating planetary waves and the mean flow. While tropospheric precursors to SSWs have often been noted, SSWs have also been shown to spontaneously arise due to fortuitous coupling of a fixed wave field provided by the troposphere and the concurrently evolving state of the stratosphere. Here we present further evidence based on climate model simulations and reanalyses that the explosive dynamics associated with SSWs primarily take place within the stratosphere. The crucial dynamics for forcing SSWs appear to take place in the ''communication layer'' just above the tropopause. We also isolate a sub-class of SSWs that are associated with anomalous wave fluxes from the troposphere and provide details on their distinct evolution. Lastly, the downward coupling following the different categories of SSWs will be discussed.
The stratosphere presents several challenges to the assimilation system, including systematic biases in models and observations, gravity wave dynamics affecting the balance of the analysis and limited amount of humidity observations. Recent developments have made it possible to address some of these challenges more directly, leading to improvements in the stratospheric analysis.
Model errors were not included in the assimilation system in the past and in the stratosphere all of the difference between model and observations was accounted for by observation bias correction. The leading term of the model error in the stratosphere is a large scale bias, which can be modelled as geographically varying but constant in time over the length of the assimilation window. This model bias is estimated within the weak-constraint formulation of our 4D-Var system and evolves from day to day. Compared with previous versions, the key is to constrain the model error to large scales, and this leads to systematic improvement in the stratospheric analysis and forecasts.
Another key issue is the dynamic balance of the analysis. When the analysis increment is added to create a new initial state, the resulting forecast can be unbalanced and generate gravity waves during a spin-down period. More importantly, these gravity waves make it difficult for the global analysis to converge to an accurate state. The analysis increment consists of two parts, an unbalanced increment uncorrelated to other variables plus a balanced increment (derived from dynamic balances between increments) correlated with other variables. A pragmatic solution to this problem is to turn off the balanced part of the increments from the lower stratosphere to the top of the model. It has long been known however that a main cause of the lack of convergence in the analysis due to stratospheric gravity waves is the different propagation speed of gravity waves in the inner and outer loops of 4D-Var, when these use different timesteps. It has not been affordable to reduce the timesteps of the inner loops in the past due to operational constraints, but recent developments on a new configuration of 4D-Var called Continuous Data Assimilation have made it possible to use the same timesteps in the inner and outer loops. With this change, it is now possible to turn on the balanced part of the stratospheric increments without degradation of the analysis, and experiments are now evaluating this.
An analogous situation is that the humidity increments above the tropopause are turned off to prevent a drift of humidity due to lack of vertically resolved and unbiased humidity sensitive observations in the stratosphere. This, in combination with a methane oxidation source parameterization, is enough to prevent drift of humidity. Microwave limb-sounders, like MLS-AURA have not been used in the analysis due to not being available in real time. Recently, we have re-evaluated the drift of humidity in the system when humidity increments are allowed everywhere. We found they were less of an issue than before, possibly due to better bias corrections of satellite radiances, which in the past would cause ghost increments in the lower stratosphere for channels sensitive to humidity in the upper troposphere. Currently we are looking at options to better account for stratospheric humidity in the analysis.
Stratospheric changes, with a timescale of a few weeks, are associated with substantial effects on surface weather and climate, especially on the Northern Annular Mode (NAM) with associated long-lasting shifts in the jet streams, storm tracks, and precipitation. Despite unambiguous observations of this phenomenon, as well as numerical simulations, a quantitative physical explanation of this downward coupling remains elusive. Stratospheric variability triggers a tropospheric feedback mechanism that amplifies polar surface pressure anomalies. The tropospheric flux of heat into the polar cap is modulated by stratospheric variability, leading to low-level polar temperature anomalies which oppose those in the stratosphere. Polar cold anomalies induce higher pressure, while warm anomalies induce lower pressure. These surface pressure anomalies are of the same sign as those in the stratosphere, thus amplifying the stratospheric signal.
These results have practical implications for climate and weather models. Beyond an understanding of how the troposphere modifies stratospheric variability, we now have a quantitative diagnostic too assess how well a model’s stratosphere–troposphere coupling compares to observations.
The two leading empirical orthogonal functions (EOFs) of zonal-mean zonal wind describe north–south fluctuations, and intensification and narrowing, respectively, of the midlatitude jet. Under certain circumstances, these two leading EOFs cannot be regarded as independent but are in fact manifestations of a single, coupled, underlying mode of the dynamical system describing the evolution in time of zonal wind anomalies. The true modes are revealed by the principal oscillation patterns (POPs). The leading mode and its associated eigenvalue are complex, its structure involves at least two EOFs, and it describes poleward (or equatorward) propagation of zonal-mean zonal wind anomalies. In this propagating regime, the principal component (PC) time series associated with the two leading EOFs decay nonexponentially, and the response of the system to external forcing in a given EOF does not depend solely on the PC decorrelation time nor on the projection of the forcing onto that EOF. These considerations are illustrated using results from an idealized dynamical core model. Results from Southern Hemisphere ERA-Interim data are partly consistent with the behavior of the model’s propagating regime. Among other things, these results imply that the time scale that determines the sensitivity of a model to external forcing might be different from the decorrelation time of the leading PC and involves both the rate of decay of the dynamical mode and the period associated with propagation.
Stratosphere–troposphere interactions are conventionally characterized using the first empirical orthogonal function (EOF) of fields such as zonal-mean zonal wind. Perpetual-winter integrations of an idealized model are used to contrast the vertical structures of EOFs with those of principal oscillation patterns (POPs; the modes of a linearized system governing the evolution of zonal flow anomalies). POP structures are shown to be insensitive to pressure weighting of the time series of interest, a factor that is particularly important for a deep system such as the stratosphere and troposphere. In contrast, EOFs change from being dominated by tropospheric variability with pressure weighting to being dominated by stratospheric variability without it. The analysis reveals separate tropospheric and stratospheric modes in model integrations that are set up to resemble midwinter variability of the troposphere and stratosphere in both hemispheres. Movies illustrating the time evolution of POP structures show the existence of a fast, propagating tropospheric mode in both integrations, and a pulsing stratospheric mode with a tropospheric extension in the Northern Hemisphere–like integration.
The ECMWF IFS (European Centre for Medium-Range Weather Forecasts – Integrated Forecasting System) and other numerical weather prediction models are known to be affected by a moist bias in the polar lowermost stratosphere. This results in an overestimation of long wave cooling and therefore to a cold bias. We use airborne GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) observations during the PGS (POLSTRACC/GW-LCYLCE-II/SALSA) campaign to quantify the moist bias in IFS data under Arctic winter conditions. For this purpose, we analyze GLORIA data and corresponding high resolution (TCo1279L137) IFS analysis and short-term forecast data associated with 5 research flights in the region around Scandinavia and Greenland from January to March 2016. Using vertical cross-sections of gas-phase water vapour measured by GLORIA and ECMWF data, we identify air masses associated with polar sub-vortex region and correlate the GLORIA observations with IFS analysis and forecast data. We diagnose a systematic moist bias by up to ~50 % at potential vorticity levels between about 6 to 10 PVU and peaking typically around measured water vapour mixing ratios of ~5 ppmv. Sensitivity runs involving finer time steps, lower horizontal resolution and higher/lower vertical resolution hardly affect the comparison and suggest that the initial conditions play an important role in the short-term forecasts.
In order to derive global distributions of gravity waves (GWs) and gravity wave momentum flux (GWMF), temperature observations from various satellite instruments are analyzed for fluctuations. Temperature amplitudes and horizontal and vertical wavelengths are inferred. From these, GWMF is calculated via the polarization relations. This requires different analysis methods for along-track data from limb-sounders, for which current instruments can provide only absolute GWMF, and 3D data from nadir sounders, which allow also to infer the horizontal propagation diretion. The analysis leads to global distributions of GWMF. Qualitatively, global distributions of GWs resolved in the ECMWF-IFS are in good agreement with satellite observations. The salient features in the mid-stratosphere are subtropical convective maxima in summer and enhanced GWMF in the winter polar vortices. There, localized maxima above major mountain ranges show particularly high and intermittent GWMF. The source for the generally enhanced GWMF in particular in the southern polar vortex is still not completely understood. Evidence is presented that oblique propagation of GWs in the upper troposphere and lower stratosphere transfers GWMF from the storm tracks and from orography around 40°S into the polar vortex centered around 60°S. Other mountain regions, such as the Rocky Mountains and the Himalayas are visible only in the lower stratopshere. These waves cannot propagate to higher altitudes because of directional wind shear or wind reversal in the lower stratopshere. In addition to GW filtering, the background winds are shaping the distribution by shifting the vertical wavelengths in and out of the observational filter, in particular for nadir sounding instruments observing only GWs of very long vertical wavelengths. A quantitative assessment of GWMF is not trivial. The global distributions deduced from satellite measurements are influenced by the instruments observational filter. However, even for model fields which provide regular sampling and all dynamical variables, inferred GWMF has uncertainties. This is because pseudomeomentum flux is formulated for single GWs of well defined amplitude whereas in reality (or in high-resolution model fields) there is a superposition of multiple scales and high spatial and temporal variation. Finally, we want to revisit previous work by Lane et al. (2005) indicating that grey-zone simulations may highly overestimate GWMF from short horizontal wavelengths.
Stratospheric mountain waves will be observed during the planned SOUTHTRAC campagin in southern Argentinia in September/October 2019. First observational highlights from the airborne observations are presented. The selected results will be set in context with analyses of the ECMWF's IFS. Additionally, high-resolution numerical simulations will be presented for the selected cases.
It is common practice in atmospheric models to parameterize gravity waves by pseudo-momentum or Eliassen-Palm flux convergence in the horizontal momentum equation. This approach is justified as long as resolved flow features of interest are in geostrophic and hydrostatic balance (Achatz et al 2017, Wei et al 2018). The present study probes the limits of this ‘pseudomomentum’ approach in a twofold manner. (1) For the case of unbalanced synoptic-scale and planetary-scale flows, e.g. the residual circulation, it is shown that the effect of mesoscale inertia-gravity waves is considerably better captured if (a) the momentum equation is forced by anelastic momentum-flux convergence and an elastic term taking into account the effect of gravity-wave density fluctuations and (b) thermodynamics is supplemented by an entropy-flux convergence term (Wei et al 2018). (2) For the case of subgrid-scale gravity waves in mesoscale-resolving models the theory for the corresponding parameterization is developed. It is shown that gravity waves with scales below the resolution of present-day weather-forecast models can affect the resolved flow, and that their parameterization is possible (Wilhelm et al 2018). In both cases (1) and (2), comparisons between gravity-wave resolving simulations and gravity-wave parameterizing WKB simulations, using an efficient Lagrangian ray-volume technique (Muraschko et al 2015), are used for demonstration. Hence, gravity-wave parameterizations in global and regional models should be modified accordingly.
Achatz, U., Ribstein, B., Senf, F., and R. Klein 2017: The interaction between synoptic-scale balanced flow and a finite-amplitude mesoscale wave field throughout all atmospheric layers: Weak and moderately strong stratification. Quart. J. Roy. Met. Soc., 143, 342–361
Muraschko, J., Fruman, M. D., Achatz, U., Hickel, S., and Y. Toledo, 2015: On the application of WKB theory for the simulation of the weakly nonlinear dynamics of gravity waves. Q. J. Roy. Meteorol. Soc., 141, 676–697
Wei, J., Bölöni, G., and U. Achatz: Efficient modelling of the interaction of mesoscale gravity waves with unbalanced large-scale flows: Pseudomomentum-flux convergence versus direct approach. J. Atmos. Sci., in revision
Wilhem, J., Akylas, T.R., Bölöni, G., Wei, J., Ribstein, B., Klein, R., and U. Achatz 2018: Interactions between meso- and sub-mesoscale gravity waves and their efficient representation in mesoscale-resolving models, J. Atmos. Sci., 75, 2257 - 2280
Part of gravity wave research is motivated by the need to improve the
representation of their impacts on the large-scale circulation in climate
models. As a major portion of the gravity wave spectrum is subgrid-scale,
parameterizations are responsible for this. Gravity wave parameterizations
generally share a common framework, which includes common assumptions on
their propagation (columnar only) and their sources (tropospheric only). These
assumptions are very justified to leading order and parameterizations have been
successful in allowing models to reproduce a number of middle atmospheric
features. Once this framework is setup, the choice of the characteristics of
the sources is a necessary step but it remains fairly arbitrary, particularly for
non-orographic sources, and hence constitutes a prime suspect for errors and
uncertainty. As sources are poorly constrained, they are conveniently tuned
to improve the modelled atmospheric circulation. Consequently, significant
efforts have been carried out to better quantify the sources of gravity
waves, combining modeling and observations. This has stimulated formidable
progress in our description and understanding of atmospheric gravity waves.
Transfer to parameterizations however is not straightforward: knowledge of the
characteristics of lower stratospheric gravity waves does not directly translate
into input parameters for parameterizations. The example of intermittency
is used to illustrate the potential impact of a shift in the parameterization
framework, leading to a redistribution of the resulting forcing in the middle
atmosphere. The better knowledge of atmospheric gravity waves, obtained
in recent years, highlights a number of phenomena which fall outside of
the classical framework of parameterizations, notably lateral propagation
and secondary generation. This growing evidence calls for investigations
to determine which of these phenomena may have systematic and robust
implications for the larger-scale flow.
The representation of the effects of mesoscale gravity waves (GWs) on the stratospheric circulation is a major source of uncertainty in general circulation models. Due to insufficient understanding of the generating mechanisms of GWs from frontal systems and flow imbalances, these are typically simplified in parameterizations by emitting GWs from a spatially-temporally uniform source at some tropospheric level.
In this presentation we will introduce a nonorographic GW parameterization that adapts a simple theory on spontaneous adjustment to emit GWs whose amplitudes are determined by grid-scale dynamics. For the parameterized vertical momentum flux, we will show that both the spatial distribution in the lower stratosphere and its temporal intermittency agree well with observations and/or GW-resolving global simulations. Some of the impacts of this parameterization on the simulated middle atmosphere are: 1) an improved equatorward tilt with height of the stratospheric jet in the Southern Hemisphere, a strongly alleviated Antarctic cold pole bias, and a considerably improved timing of the stratospheric final warming; 2) the parameterized GW drag has now a stronger seasonal cycle tied to that in their sources, leading to improvements in the seasonality of the Brewer-Dobson circulation; and 3) different to previous schemes, the emitted GW stress can respond to changes in climate.