Surface impacts of the Quasi Biennial Oscillation

Teleconnections between the Quasi Biennial Oscillation (QBO) and the Northern Hemisphere zonally averaged zonal winds, mean sea level pressure (mslp) and tropical precipitation are explored. The standard approach that defines the QBO using the equatorial zonal winds at a single pressure level is compared with the empirical orthogonal function approach that characterizes the vertical profile of the equatorial winds. Results are interpreted in terms of three potential routes of influence, referred to as the tropical, subtropical and polar routes. A novel technique is introduced to separate responses via the polar route that are associated with the stratospheric polar vortex, from the other two routes. A previously reported mslp response in January, with a pattern that resembles the positive phase of the North Atlantic Oscillation under QBO westerly conditions, is confirmed and found to be primarily associated with a QBO modulation of the stratospheric polar vortex. This mid-winter response is relatively insensitive to the exact height of the maximum QBO westerlies and a maximum positive response occurs with westerlies over a relatively deep range between 10 and 70hPa. Two additional mslp responses are reported, in early winter (December) and late winter (February/March). In contrast to the January response the early and late winter responses show maximum sensitivity to the QBO winds at  ∼ 20 and  ∼ 70hPa respectively, but are relatively insensitive to the QBO winds in between ( ∼ 50hPa). The late winter response is centred over the North Pacific and is associated with QBO influence from the lowermost stratosphere at tropical/subtropical latitudes in the Pacific sector. The early winter response consists of anomalies over both the North Pacific and Europe, but the mechanism for this response is unclear. Increased precipitation occurs over the tropical western Pacific under westerly QBO conditions, particularly during boreal summer, with maximum sensitivity to the QBO winds at 70hPa. The band of precipitation across the Pacific associated with the Inter-tropical Convergence Zone (ITCZ) shifts southward under QBO westerly conditions. The empirical orthogonal function (EOF)-based analysis suggests that this ITCZ precipitation response may be particularly sensitive to the vertical wind shear in the vicinity of 70hPa and hence the tropical tropopause temperatures

An unexpected disruption of the atmospheric quasi-biennial oscillation

This is the author accepted manuscript. The final version is available from AAAS via the DOI in this recordWe thank the European Centre for Medium-Range Weather Forecasts for providing ERA-Interim and Operational Analysis data (www.ecmwf.int/en/forecasts) and the Freie Universität Berlin for providing radiosonde data (www.geo.fu-berlin.de/en/met/ag/strat/produkte/qbo). The CMIP5 data was obtained from the British Atmospheric Data Centre (browse.ceda.ac.uk/browse/badc/cmip5). A summary of data used in the study is listed in table S1.One of the most repeatable phenomena seen in the atmosphere, the quasi-biennial oscillation (QBO) between prevailing eastward and westward wind jets in the equatorial stratosphere (approximately 16 to 50 kilometers altitude), was unexpectedly disrupted in February 2016. An unprecedented westward jet formed within the eastward phase in the lower stratosphere and cannot be accounted for by the standard QBO paradigm based on vertical momentum transport. Instead, the primary cause was waves transporting momentum from the Northern Hemisphere. Seasonal forecasts did not predict the disruption, but analogous QBO disruptions are seen very occasionally in some climate simulations. A return to more typical QBO behavior within the next year is forecast, although the possibility of more frequent occurrences of similar disruptions is projected for a warming climate.S.M.O. was supported by UK Natural Environment Research Council grants NE/M005828/1 and NE/P006779/1. A.A.S., J.R.K., and N.B. were supported by the Joint UK Business, Energy and Industrial Strategy/Defra Met Office Hadley Centre Climate Programme (GA01101). A.A.S. and J.R.K. were additionally supported by the EU Seventh Framework Programme SPECS (Seasonal-to-decadal climate Prediction for the improvement of European Climate Services) project

State of the climate in 2018

In 2018, the dominant greenhouse gases released into Earth’s atmosphere—carbon dioxide, methane, and nitrous oxide—continued their increase. The annual global average carbon dioxide concentration at Earth’s surface was 407.4 ± 0.1 ppm, the highest in the modern instrumental record and in ice core records dating back 800 000 years. Combined, greenhouse gases and several halogenated gases contribute just over 3 W m−2 to radiative forcing and represent a nearly 43% increase since 1990. Carbon dioxide is responsible for about 65% of this radiative forcing. With a weak La Niña in early 2018 transitioning to a weak El Niño by the year’s end, the global surface (land and ocean) temperature was the fourth highest on record, with only 2015 through 2017 being warmer. Several European countries reported record high annual temperatures. There were also more high, and fewer low, temperature extremes than in nearly all of the 68-year extremes record. Madagascar recorded a record daily temperature of 40.5°C in Morondava in March, while South Korea set its record high of 41.0°C in August in Hongcheon. Nawabshah, Pakistan, recorded its highest temperature of 50.2°C, which may be a new daily world record for April. Globally, the annual lower troposphere temperature was third to seventh highest, depending on the dataset analyzed. The lower stratospheric temperature was approximately fifth lowest. The 2018 Arctic land surface temperature was 1.2°C above the 1981–2010 average, tying for third highest in the 118-year record, following 2016 and 2017. June’s Arctic snow cover extent was almost half of what it was 35 years ago. Across Greenland, however, regional summer temperatures were generally below or near average. Additionally, a satellite survey of 47 glaciers in Greenland indicated a net increase in area for the first time since records began in 1999. Increasing permafrost temperatures were reported at most observation sites in the Arctic, with the overall increase of 0.1°–0.2°C between 2017 and 2018 being comparable to the highest rate of warming ever observed in the region. On 17 March, Arctic sea ice extent marked the second smallest annual maximum in the 38-year record, larger than only 2017. The minimum extent in 2018 was reached on 19 September and again on 23 September, tying 2008 and 2010 for the sixth lowest extent on record. The 23 September date tied 1997 as the latest sea ice minimum date on record. First-year ice now dominates the ice cover, comprising 77% of the March 2018 ice pack compared to 55% during the 1980s. Because thinner, younger ice is more vulnerable to melting out in summer, this shift in sea ice age has contributed to the decreasing trend in minimum ice extent. Regionally, Bering Sea ice extent was at record lows for almost the entire 2017/18 ice season. For the Antarctic continent as a whole, 2018 was warmer than average. On the highest points of the Antarctic Plateau, the automatic weather station Relay (74°S) broke or tied six monthly temperature records throughout the year, with August breaking its record by nearly 8°C. However, cool conditions in the western Bellingshausen Sea and Amundsen Sea sector contributed to a low melt season overall for 2017/18. High SSTs contributed to low summer sea ice extent in the Ross and Weddell Seas in 2018, underpinning the second lowest Antarctic summer minimum sea ice extent on record. Despite conducive conditions for its formation, the ozone hole at its maximum extent in September was near the 2000–18 mean, likely due to an ongoing slow decline in stratospheric chlorine monoxide concentration. Across the oceans, globally averaged SST decreased slightly since the record El Niño year of 2016 but was still far above the climatological mean. On average, SST is increasing at a rate of 0.10° ± 0.01°C decade−1 since 1950. The warming appeared largest in the tropical Indian Ocean and smallest in the North Pacific. The deeper ocean continues to warm year after year. For the seventh consecutive year, global annual mean sea level became the highest in the 26-year record, rising to 81 mm above the 1993 average. As anticipated in a warming climate, the hydrological cycle over the ocean is accelerating: dry regions are becoming drier and wet regions rainier. Closer to the equator, 95 named tropical storms were observed during 2018, well above the 1981–2010 average of 82. Eleven tropical cyclones reached Saffir–Simpson scale Category 5 intensity. North Atlantic Major Hurricane Michael’s landfall intensity of 140 kt was the fourth strongest for any continental U.S. hurricane landfall in the 168-year record. Michael caused more than 30 fatalities and $25 billion (U.S. dollars) in damages. In the western North Pacific, Super Typhoon Mangkhut led to 160 fatalities and$6 billion (U.S. dollars) in damages across the Philippines, Hong Kong, Macau, mainland China, Guam, and the Northern Mariana Islands. Tropical Storm Son-Tinh was responsible for 170 fatalities in Vietnam and Laos. Nearly all the islands of Micronesia experienced at least moderate impacts from various tropical cyclones. Across land, many areas around the globe received copious precipitation, notable at different time scales. Rodrigues and Réunion Island near southern Africa each reported their third wettest year on record. In Hawaii, 1262 mm precipitation at Waipā Gardens (Kauai) on 14–15 April set a new U.S. record for 24-h precipitation. In Brazil, the city of Belo Horizonte received nearly 75 mm of rain in just 20 minutes, nearly half its monthly average. Globally, fire activity during 2018 was the lowest since the start of the record in 1997, with a combined burned area of about 500 million hectares. This reinforced the long-term downward trend in fire emissions driven by changes in land use in frequently burning savannas. However, wildfires burned 3.5 million hectares across the United States, well above the 2000–10 average of 2.7 million hectares. Combined, U.S. wildfire damages for the 2017 and 2018 wildfire seasons exceeded $40 billion (U.S. dollars)

Interpreting the nature of Northern and Southern Annular Mode variability in CMIP5 Models

Characteristic timescales for the Northern Annular Mode (NAM) and Southern Annular Mode (SAM) variability are diagnosed in historical simulations submitted to the Coupled Model Intercomparison Project Phase 5 (CMIP5) and are compared to the European Centre for Medium-Range Weather Forecasts ERA-Interim data. These timescales are calculated from geopotential height anomaly spectra using a recently developed method, where spectra are divided into low-frequency (Lorentzian) and high-frequency (exponential) parts to account for stochastic and chaotic behaviors, respectively. As found for reanalysis data, model spectra at high frequencies are consistent with low-order chaotic behavior, in contrast to an AR1 process at low frequencies. This places the characterization of the annular mode timescales in a more dynamical rather than purely stochastic context. The characteristic high-frequency timescales for the NAM and SAM derived from the model spectra at high frequencies are ∼5 days, independent of season, which is consistent with the timescales of ERA-Interim. In the low-frequency domain, however, models are slightly biased toward too long timescales, but within the error bars, a finding which is consistent with previous studies of CMIP3 models. For the SAM, low-frequency timescales in November, December, January, and February are overestimated in the models compared to ERA-Interim. In some models, the overestimation in the SAM austral summer timescale is partly due to interannual variability, which can inflate these timescales by up to ∼40% in the models but only accounts for about 5% in the ERA-Interim reanalysis

Defining metrics of the Quasi-Biennial Oscillation in global climate models

As the dominant mode of variability in the tropical stratosphere, the Quasi-Biennial Oscillation (QBO) has been subject to extensive research. Though there is a well developed theory of this phenomenon being forced by wave-mean flow interaction, simulating the QBO adequately in global climate models (GCMs) still remains difficult. This paper presents a set of metrics to characterise the QBO using a number of different reanalysis datasets and the FU Berlin radiosonde observation dataset. The same metrics are then calculated from CMIP5 and CCMVal-2 intercomparison project simulations which included a representation of QBO like behaviour to evaluate which aspects of the QBO are well captured by the models and which ones remain a challenge for future model development

Defining metrics of the Quasi-Biennial Oscillation in global climate models

As the dominant mode of variability in the tropical stratosphere, the Quasi-Biennial Oscillation (QBO) has been subject to extensive research. Though there is a well-developed theory of this phenomenon being forced by wave-mean flow interaction, simulating the QBO adequately in global climate models still remains difficult. This paper presents a set of metrics to characterize the morphology of the QBO using a number of different reanalysis datasets and the FU Berlin radiosonde observation dataset. The same metrics are then calculated from Coupled Model Intercomparison Project 5 and Chemistry-Climate Model Validation Activity 2 simulations which included a representation of QBO-like behaviour to evaluate which aspects of the QBO are well captured by the models and which ones remain a challenge for future model development

Defining metrics of the Quasi-Biennial Oscillation in global climate models

As the dominant mode of variability in the tropical stratosphere, the Quasi-Biennial Oscillation (QBO) has been subject to extensive research. Though there is a well developed theory of this phenomenon being forced by wave-mean flow interaction, simulating the QBO adequately in global climate models (GCMs) still remains difficult. This paper presents a set of metrics to characterise the QBO using a number of different reanalysis datasets and the FU Berlin radiosonde observation dataset. The same metrics are then calculated from CMIP5 and CCMVal-2 intercomparison project simulations which included a representation of QBO like behaviour to evaluate which aspects of the QBO are well captured by the models and which ones remain a challenge for future model development

Defining metrics of the Quasi-Biennial Oscillation in global climate models

As the dominant mode of variability in the tropical stratosphere, the Quasi-Biennial Oscillation (QBO) has been subject to extensive research. Though there is a well-developed theory of this phenomenon being forced by wave-mean flow interaction, simulating the QBO adequately in global climate models still remains difficult. This paper presents a set of metrics to characterize the morphology of the QBO using a number of different reanalysis datasets and the FU Berlin radiosonde observation dataset. The same metrics are then calculated from Coupled Model Intercomparison Project 5 and Chemistry-Climate Model Validation Activity 2 simulations which included a representation of QBO-like behaviour to evaluate which aspects of the QBO are well captured by the models and which ones remain a challenge for future model development

Defining metrics of the Quasi-Biennial Oscillation in global climate models

As the dominant mode of variability in the tropical stratosphere, the Quasi-Biennial Oscillation (QBO) has been subject to extensive research. Though there is a well developed theory of this phenomenon being forced by wave-mean flow interaction, simulating the QBO adequately in global climate models (GCMs) still remains difficult. This paper presents a set of metrics to characterise the QBO using a number of different reanalysis datasets and the FU Berlin radiosonde observation dataset. The same metrics are then calculated from CMIP5 and CCMVal-2 intercomparison project simulations which included a representation of QBO like behaviour to evaluate which aspects of the QBO are well captured by the models and which ones remain a challenge for future model development

Observed and Simulated Teleconnections Between the Stratospheric Quasi‐Biennial Oscillation and Northern Hemisphere Winter Atmospheric Circulation

This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland. The Quasi-Biennial Oscillation (QBO) is the dominant mode of interannual variability in the tropical stratosphere, with easterly and westerly zonal wind regimes alternating over a period of about 28 months. It appears to influence the Northern Hemisphere winter stratospheric polar vortex and atmospheric circulation near the Earth's surface. However, the short observational record makes unequivocal identification of these surface connections challenging. To overcome this, we use a multicentury control simulation of a climate model with a realistic, spontaneously generated QBO to examine teleconnections with extratropical winter surface pressure patterns. Using a 30-hPa index of the QBO, we demonstrate that the observed teleconnection with the Arctic Oscillation (AO) is likely to be real, and a teleconnection with the North Atlantic Oscillation (NAO) is probable, but not certain. Simulated QBO-AO teleconnections are robust, but appear weaker than in observations. Despite this, inconsistency with the observational record cannot be formally demonstrated. To assess the robustness of our results, we use an alternative measure of the QBO, which selects QBO phases with westerly or easterly winds extending over a wider range of altitudes than phases selected by the single-level index. We find increased strength and significance for both the AO and NAO responses, and better reproduction of the observed surface teleconnection patterns. Further, this QBO metric reveals that the simulated AO response is indeed likely to be weaker than observed. We conclude that the QBO can potentially provide another source of skill for Northern Hemisphere winter prediction, if its surface teleconnections can be accurately simulated