Advances in computational power and model development have enabled the generation of global high-resolution models. These new models can resolve a large proportion of gravity waves (GWs) explicitly, reducing reliance on subgrid parametrizations. GWs are vital components of the middle and upper atmosphere, they transport energy and momentum both horizontally and vertically, driving the atmospheric circulation. Evaluating the realism of these resolved waves is a crucial step in advancing future model development.Here we provide the first global multi-model GW observational comparison that accounts for the observational filter. We assess the representation of stratospheric GWs in three high-resolution (3-5 km horizontal resolution) global free-running simulations (ICON, IFS and GEOS), for the period 20 January-29 February 2020, against AIRS satellite observations.Time-mean wave amplitudes are systematically lower in the models than observations, consistent with previous studies. GW occurrence rates are higher in all models than the observations, dominated by low amplitude waves in the models. During the first 10 d spatial patterns of GW occurrence rate, amplitudes and momentum flux agree across the models and observations but subsequently they diverge. Agreement is more consistent in the Northern Hemisphere (where orographic waves dominate) than in the Southern Hemisphere (where convective waves dominate).These results benchmark the current state of high-resolution modelling and demonstrate that whilst there are strengths in models' ability to capture the morphology of GWs (particularly orographically generated waves), there is room for improvement in modelling amplitudes, occurrence rates and zonal-mean flux magnitudes globally, with the largest discrepancies in the tropical convective regions.

Satellite observations of the atmosphere are often extremely noisy due to both hardware limitations and the inherent complexity of retrieving and making measurements of the atmosphere. Gravity waves, which are low amplitude signals present in the atmosphere, are hard to resolve in this data due to their relatively low amplitude and small spatial extent. As a result, noise becomes a limiting factor when trying to identify and characterise them in real observed data.Current methods to address this problem often lean upon smoothing approaches; however, such approaches suppress small scale signals and reduce measured amplitude and momentum fluxes significantly. This impedes the process in developing the next generation of models where these waves must be resolved accurately.A novel supervised machine learning approach is introduced which is able to accurately remove small scale noise features from nadir observations of gravity waves. This model was trained on synthetic observations derived from high resolution DYAMOND model runs. This is then applied to 22 years of NASA AIRS data and 12 years of MetOp IASI data and used to produce a new gravity wave climatology to better access small amplitude gravity waves.

Atmospheric gravity waves (GWs) are one of the most important drivers of the circulation of the middle and upper atmosphere. Usually generated in the lower atmosphere and propagating upwards through the atmospheric layers, the aggregated forcing of these waves drives circulations in the middle atmosphere that are far from that expected under radiative equilibrium. Circulations in the mesosphere and lower thermosphere (MLT) and above, especially in polar regions, have shown extreme sensitivity to GW parameterisations in recent high-top modelling simulations and can exhibit significant and limiting biases compared to observations. This uncertainty in the role of GW dynamics between models has made predictions of how these high-altitude circulations are expected to respond to a changing climate very challenging. This is confounded by a relative scarcity of global observations of GW activity in the middle and upper atmosphere with which to understand these connections over climate timescales. Since the early 2000s, satellite and ground-based instrumentation has provided an unprecedented observational view of middle atmospheric dynamics and composition, especially for the study of GWs. However, due to different instrument capabilities and limited hardware lifetimes, examining long term trends of GW properties observationally has been challenging due to the need to re-establish baselines. Here we examine results from some of the longest known single-instrument records of GW activity in the middle and upper atmosphere spanning more than two decades. We explore changes in GW amplitudes, wavelengths and directional momentum flux in the stratosphere from a 22-year climatology derived from global 3-D satellite observations from the AIRS/Aqua, the longest single-instrument climatology of this type. We also explore changes in wind, temperature and large-scale GW activity in the polar MLT from nearly 20 years of single-station meteor wind radar observations in the Arctic and Antarctic. We compare these trends to equivalent analysis of other long-term satellite GW datasets and resolved GW activity in ERA5 stratospheric reanalysis. Finally, we discuss limitations and best practise for considering observed trends in GW observations, such as how changes in circulation can affect GW propagation and their apparent sensitivity to satellite remote sensing techniques.

The mesosphere and lower thermosphere (MLT) plays a critical role in linking the middle and upper atmosphere. However, many General Circulation Models do not model the MLT and those that do remain poorly constrained. We use long-term meteor radar observations (2005-2021) from Rothera (67 degrees S, 68 degrees W) on the Antarctic Peninsula to evaluate the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (WACCM-X) and investigate interannual variability. We find some significant differences between WACCM-X and observations. In particular, at upper heights, observations reveal eastwards wintertime (April-September) winds, whereas the model predicts westwards winds. In summer (October-March), the observed winds are northwards but predictions are southwards. Both the model and observations reveal significant interannual variability. We characterize the trend and the correlation between the winds and key phenomena: (a) the 11-year solar cycle, (b) El Nino Southern Oscillation, (c) Quasi-Biennial Oscillation and (d) Southern Annular Mode using a linear regression method. Observations of the zonal wind show significant changes with time. The summertime westwards wind near 80 km is weakening by up to 4-5 ms-1 per decade, whilst the eastward wintertime winds around 85-95 km are strengthening at by around 7 ms-1 per decade. We find that at some times of year there are significant correlations between the phenomena and the observed/modeled winds. The significance of this work lies in quantifying the biases in a leading General Circulation Model and demonstrating notable interannual variability in both modeled and observed winds. The mesosphere and lower thermosphere (MLT), at heights of 80-100 km is an important region for the coupling of the middle and upper atmosphere. We carry out a study of the winds above Rothera (Antarctic Peninsula) for the years 2005-2021. We use observations from a meteor radar which measures winds at heights of 80-100 km and compare with the eXtended version of the Whole Atmosphere Community Climate Model (WACCM-X), a leading general circulation model. We find that although most of the seasonal cycle in the winds is captured well, WACCM-X exhibits biases in the winds at upper heights. In wintertime, the zonal winds are westwards whereas in observations they are eastward. In summertime WACCM-X model meridional winds at 90-100 km are southwards but observations northwards. The observed and modeled winds also display significant interannual variability. We characterize the trends of the winds and the correlation with various drivers (the 11-year solar cycle, El Nino Southern Oscillation, the Quasi-Biennial Oscillation and the Southern Annular Mode), using a multi-linear regression method. The study uses a uniquely long data set of Antarctic MLT winds to test and further develop general circulation models and quantifies the relationship between these winds and drivers such as the solar cycle. We characterize the variability of monthly mean winds in the mesosphere and lower thermosphere (MLT) over 17 years at Rothera using meteor radar observations and the eXtended version of the Whole Atmosphere Community Climate Model (WACCM-X) WACCM-X displays biases in the wintertime winds in the upper MLT. Observed winds are eastwards whilst WACCM-X winds are westwards Significant variability, trends and intermittent correlations with the solar cycle, Quasi-Biennial Oscillation and Southern Annular Mode are found in the observed and modeled winds

During winter, the latitude belt at 60S is one of the most intense hotspots of stratospheric gravity wave (GW) activity. However, producing accurate representations of GW dynamics in this region in numerical models has proved exceptionally challenging. One reason for this is that questions remain regarding the relative contributions of different orographic and non-orographic sources of GWs here.We use 3-D satellite GW observations from the Atmospheric InfraRed Sounder (AIRS) from winter 2012 in combination with the Gravity-wave Regional Or Global Ray Tracer (GROGRAT) to backwards ray trace GWs to their sources. We trace over 14.2 million rays, which allows us to investigate GW propagation and to produce systematic estimates of the relative contribution of orographic and non-orographic sources to the total observed stratospheric GW momentum flux in this region.We find that in winter 56% of momentum flux (MF) traces back to the ocean and 44% to land, despite land representing less than a quarter of the region’s area. This demonstrates that, while orographic sources contribute much more momentum flux per unit area, the large spatial extent of non-orographic sources leads to a higher overall contribution. The small islands of Kerguelen and South Georgia specifically contribute up to 1.6% and 0.7% of average monthly stratospheric MF, and the intermittency of these sources suggests that their short-timescale contribution is even higher. These results provide the important insights needed to significantly advance our knowledge of the atmospheric momentum budget in the Southern polar region.

<p>Gravity waves have a variety of different sources including wind flow over mountains, convection and jet stream instabilities. Yet when working with observations of gravity waves we can only make informed guesses of their sources. In this work we use GROGRAT to backwards ray trace stratospheric observations of gravity waves globally to learn more about their origins.</p> <p>We use observations of temperatures at 40km altitude observed by the AIRS (Atmospheric InfraRed Sounder) instrument on NASA’s Aqua satellite. From these observations we extract temperature perturbations and use the 3D Stockwell transform to derive gravity wave properties such as momentum flux, horizontal wavelength, vertical wavelength. These gravity waves are then backwards ray traced through the ERA5 atmosphere. The significance in this work lies in the volume: we ray trace 21 years (2002-2022) of AIRS data globally, representing by far the largest such observational dataset ever reverse ray-traced.</p> <p>By investigating the lowest traceable altitude of these rays, we can attribute the gravity waves to their sources (orographic gravity waves will originate near the surface whilst convective waves will have a higher origin). We can also investigate the horizontal propagation of orographic gravity waves from specific mountain ranges and how this changes seasonally. This work aims to answer the question: “Where do gravity waves observed by AIRS come from?”</p>

. The mesosphere and lower thermosphere (MLT), at heights of 80-100 km, is critical in the coupling of the middle and upper atmosphere and controls the momentum and energy transfer between these two regions. However, despite its importance, many General Circulation Models (GCMs) do not extend upwards into the MLT and those that do remain poorly constrained. In this study, we use a long-term meteor radar wind dataset from Rothera (67°S, 68°W) on the Antarctic Peninsula to test the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (WACCM-X). This radar has 5 an interferometer to determine meteor heights and has been running since 2005. This unique combination yields a dataset ideally suited to investigate interannual variability. We find that although some characteristic features in monthly median winds are represented well in WACCM-X, the model exhibits significant biases. In particular, the observations reveal a ∼ 10 ms − 1 eastward wind at heights of 85-100 km in Antarctic winter, whereas the model predicts winds of the same magnitude but of opposite direction. We propose that this bias exists because WACCM-X is missing eastward momentum forcing in the MLT 10 from the breaking of secondary gravity waves. the observations significant in We the of particular key external phenomena the in this region. These phenomena are; i) variations in Solar activity, ii) the El Niño Southern Oscillation (ENSO), iii) the Quasi-Biennial Oscillation (QBO) and iv) the Southern Annular Mode (SAM). We use a linear regression method to investigate how the observed and modelled winds, and modelled gravity wave 15 tendencies in the Antarctic MLT vary in relation to the indices that quantify these phenomena. We find that there are some times of year and some height ranges at which there are significant correlations between the indices and the observed/modelled winds. In particular, in summer, there is a strong positive correlation in the modelled and observed zonal winds with the 11-year Solar cycle of magnitude up to 9 ms − 1 per 70 Solar flux units. However, there appears to be little significant influence of the ENSO on the winds observed by the radar although WACCM-X zonal winds display a 20 negative correlation throughout January-February and a positive correlation during March-May. Results from the QBO indices are varied and we find differing correlations in the model and observations. Finally, we find a positive correlation between observed summertime zonal winds and the SAM which has a magnitude of 9 ms − 1 per 2.5 hPa change in the SAM index. However, in WACCM-X zonal winds the summertime response is negative and around 10 ms − 1 per 2.5 hPa. The significance of this work lies in our quantifying the biases in a leading GCM and demonstrating there is significant interannual variability 25 in both modelled and observed winds, some of which are consistent with the proposal of external forcing. In this work we present the first long-term study (i.e. spanning over a Solar cycle) of the interannual variability of Antarctic winds from a meteor radar equipped with height resolving capabilities and compare these observations to the predictions of WACCM-X. Long-term Antarctic MLT winds have been explored in the past by radars without height resolving Portnyagin and Merzlyakov et al. (2009). Whilst some of these studies span a longer time period than that considered here, the MLT winds have strong variation with height which could not be addressed. Other long-term work has 65 used observations from MF radars Baumgaertner 2005; Dowdy 2007; Iimura et al., 2011; Portnyagin al., Merzlyakov 2009). However, MF radars have known and significant biases in winds measured at heights above 90 km 2004; Jacobi 2009; 2017). Here we investigate data recorded from 2005-2020 by the Rothera meteor radar and build upon work done earlier by Sandford et al. who reported first results from this radar and compared to winds in Esrange (68°N, 21°E). Cullens et al. also inspires the basis for this study wherein they used 70 WACCM to explore the influence of the 11-year Solar cycle on atmospheric winds globally. They found that in the southern hemisphere there are statistically significant changes in gravity wave drag and associated winds that are likely due to the Solar cycle. Our goal here is to determine the interannual variability found in this long radar dataset and compare the winds to the WACCM-X model. We use a linear regression method to explore the relationship between both observed and modelled MLT winds and modelled gravity wave tendencies with four particular potential external phenomena, namely, i) the Solar cycle, ii) 75 the ENSO, iii) the QBO and iv) zonal the is the zonal winds no significant in of the the model’s stratospheric polar vortex altering the critical level filtering of study was proposed and by TMG, NM, CW, SE, CC, PN. Data analysis was led by PN with radar hourly winds supplied by NH. Model data was processed by CC. Manuscript and all figures prepared by PN. Scientific interpretation led by PN and contributed to by all authors

<p>The Mesosphere and Lower Thermosphere (MLT), at 80-100 km altitude, is critical in the coupling of the middle and upper atmosphere and determining momentum and energy transfer between these two regions. However, despite its importance, General Circulation Models (GCMs) have only recently been extended to the MLT region and remain poorly constrained.</p><p>We use a long term meteor radar dataset from Rothera on the Antarctic Peninsula to test the eXtended Whole Atmosphere Community Climate Model (WACCM-X). This radar has been running continuously since 2005, resulting in a uniquely long, consistent measure of the winds in the MLT that we can use to investigate long term variability. We find that although some characteristic features are represented well in WACCM-X, the model exhibits considerable biases. In particular, the observations show a ~10m/s eastward wind in Antarctic winter whereas the model predicts winds of the same magnitude but opposite direction. We propose that this difference is due to the lack of secondary gravity wave modelling in WACCM-X.</p><p>We also find interannual variability in both the observations and the model. In order to understand these differences, we further investigate the role of external climate processes in driving the winds in this region. Using a linear regression method, we quantify how the (observed and modelled) winds in the Antarctic MLT respond to Solar activity, the El Nino Southern Oscillation (ENSO), the Quasi-Biennial Oscillation (QBO) and the Southern Annular Mode (SAM). For some indices we find good agreement between the observations and model results while for others we see important differences.</p>

Commercial aviation is both a major economic sector and has significant effects on the climate system via emissions, and is forecast to continue to grow over coming decades. Significant modelling work over the past decade suggests strongly that climate-dynamical processes can affect flight times, but observational quantification of this is limited, particular in the important transatlantic sector. Here, we examine flight record data from the In-service Aircraft for a Global Observing System (IAGOS) to quantify the magnitude of how climate processes affect transatlantic flight times between Europe and North America. Using >14 000 individual flight records covering the period 1994-2019, we specifically apply a combination of data-selection and multilinear regression techniques to quantify the effect of the North Atlantic oscillation (NAO), the quasi-biennial oscillation (QBO), the El Nino-Southern Oscillation (ENSO), the decadal solar cycle, and climate change on trans-Atlantic flight times over this period. We see statistically-significant effects on flight times for all these indices for at least some part of the year, with the magnitude and direction of these effects varying seasonal and by flight direction. These range from the very large, such as changes in flight time of half an hour or more across the NAO cycle for winter flights - to the relatively small, such as changes of just a few minutes across the solar cycle. These results are broadly similar in form to previous modelling studies, but show important quantitative differences with implications for our understanding of how these processes do and will affect aviation in future.

The solar tides of the mesosphere and lower thermosphere (MLT) show great variability on time scales of days to years, with significant variability at interannual time scales. However, the nature and causes of this variability remain poorly understood. Here, we present measurements made over the interval 2005–2020 of the interannual variability of the 12‐hr tide as measured at heights of 80–100 km by a meteor radar over Rothera (68°S, 68°W). We use a linear regression analysis to investigate correlations between the 12‐hr tidal amplitudes and several climate indices, specifically the solar cycle (as measured by F10.7 solar flux), El Niño Southern Oscillation (ENSO), the Quasi‐Biennial Oscillation (QBO) at 10 and 30 hPa and the Southern Annular Mode (SAM). Our observations reveal that the 12‐hr tide has a large amplitude and a clearly defined seasonal cycle with monthly mean values as large as 35 m s −1 . We observe substantial interannual variability, with monthly mean 12‐hr tidal amplitudes at 95 km exhibiting a two standard‐deviation range (2 σ ) in spring of 13.4 m s −1 , 11.2 m s −1 in summer, 18.6 m s −1 in autumn, and 7.0 m s −1 in winter. We find that F10.7, QBO10, QBO30, and SAM all have significant correlations to the 12‐hr tidal amplitudes at the 95% level, with a linear trend also present. Whereas we detect very minimal correlation with ENSO. These results suggest that variations in F10.7, the QBO and SAM may contribute significantly to the interannual variability of 12‐hr tidal amplitudes in the Antarctic MLT.

The wind field in the mesosphere and lower thermosphere (MLT), at heights between 80 and 100 km, is dominated by the global scale oscillations of the atmospheric tides. The tides are crucial to the dynamics of the middle and upper atmosphere and hence to understanding the coupling between the lower atmosphere and space. The tides are known to show considerable variability on timescales of days to years, with significant variability at interannual timescales. However, the nature and causes of this variability remain poorly understood. Here, we present measurements made over the interval 2005 to 2020 of the interannual variability of the 12-hour tide as measured at heights of 80 – 100 km by a meteor radar over the British Antarctic Survey base at Rothera (68°S, 68°W). We use a linear regression analysis to investigate correlations between the 12-hour tidal amplitudes and several climate indices, specifically the solar cycle (as measured by F10.7 solar flux), El Niño Southern Oscillation (ENSO), the Quasi-Biennial Oscillation (QBO) at 10 hPa and 30 hPa, the Southern Annular Mode (SAM) and time. Our observations reveal that the 12-hour tide has a large amplitude and a clearly defined seasonal cycle with monthly mean values as large as 35 ms-1. We observe substantial interannual variability with monthly mean tidal amplitudes at 95 km exhibiting an interdecile range in spring of 17.2 ms-1, 12.6 ms-1 in summer, 23.6 ms-1 in autumn and 9.0 ms-1 in winter. We find that F10.7, QBO10, QBO30, SAM and time all have significant correlations at the 95% level, whereas we detect very minimal correlation with ENSO. For example, there is a significant negative correlation between F10.7 solar flux and tidal amplitudes in summer, implying an increase in solar flux is related to a decrease in monthly mean tidal amplitudes in the MLT. These results suggest that the amplitude of the polar 12-hour tide is modulated by the solar cycle, QBO and SAM.

The Mesosphere and Lower Thermosphere (MLT), at 80-100 km altitude, is critical in the coupling of the middle and upper atmosphere and determining momentum and energy transfer between these two regions. However, despite its importance, General Circulation Models (GCMs) have only recently been extended to the MLT region and remain poorly constrained. We use a long term meteor radar dataset from Rothera on the Antarctic Peninsula to test the eXtended Whole Atmosphere Community Climate Model (WACCM-X). This radar has been running continuously since 2005, resulting in a uniquely long, consistent measure of the winds in the MLT that we can use to investigate long term variability. We find that although some characteristic features are represented well in WACCM-X, the model exhibits considerable biases. In particular, the observations show a ~10m/s eastward wind in Antarctic winter whereas the model predicts winds of the same magnitude but opposite direction. We propose that this difference is due to the lack of secondary gravity wave modelling in WACCM-X. We also find interannual variability in both the observations and the model. In order to understand these differences, we further investigate the role of external climate processes in driving the winds in this region. Using a linear regression method, we quantify how the (observed and modelled) winds in the Antarctic MLT respond to Solar activity, the El Nino Southern Oscillation (ENSO), the Quasi-Biennial Oscillation (QBO) and the Southern Annular Mode (SAM). For some indices we find good agreement between the observations and model results while for others we see important differences.