Abstract

This paper investigates the vertical filtering of parameterized gravity wave pseudomomentum flux in the troposphere–stratosphere version of the Met Office Unified Model. Gravity wave forcing is parameterized using the Warner and McIntyre spectral gravity wave parameterization. The same amount of isotropic pseudomomentum flux per unit mass is launched from the planetary boundary layer at each grid point. The parameterization models the azimuthally dependent Doppler shifting and breaking of the gravity wave spectrum as it is filtered by the background atmosphere. The result is an anisotropic distribution of pseudomomentum flux among azimuthal sectors that varies greatly with altitude and location. This gives an idealized global climatology of nonorographic gravity waves. The filtering effect of the atmosphere in this climatology is diagnosed using the “zonal anisotropy.”

Results show areas where observational measurements could be targeted to find the most prominent features in the gravity wave field. Such areas include, for example, the summer stratosphere where zonal anisotropy is very large and where there is a significant localization in latitude and longitude of patches of high zonal anisotropy. Comparisons are also made with recent observational estimates of gravity wave fluxes and test whether wind filtering of a homogeneous, azimuthally isotropic source is enough to reproduce observed features of the gravity wave field.

Abstract

The prediction skill and errors in surface temperature anomalies in initialized decadal hindcasts from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are assessed using six ocean–atmosphere coupled models initialized every year from 1961 to 2008. The initialized hindcasts show relatively high prediction skill over the regions where external forcing dominates, indicating that a large portion of the prediction skill is due to the long-term trend. After removing the linear trend, high prediction skill is shown near the centers of action of the dominant decadal climate oscillations, such as the Pacific decadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO). Low prediction skill appears over the tropical and eastern North Pacific Ocean where the predicted anomaly patterns associated with the PDO are systematically different in model and observations. By statistically correcting those systematic errors using a stepwise pattern projection method (SPPM) based on the data in an independent training period, the prediction skill of sea surface temperature (SST) is greatly enhanced over the North Pacific Ocean. The SST prediction skill over the North Pacific Ocean after the SPPM error correction is as high as that over the North Atlantic Ocean. In addition, the prediction skill in a single model after correction exceeds the skill of the multimodel ensemble (MME) mean before correction, implying that the MME method is not as effective in addressing systematic errors as the SPPM correction.

Abstract

Recent periods of extreme weather in Europe, such as the cold winter of 2009/10, have caused widespread impacts and were remarkable because of their persistence. It is therefore of great interest to improve the ability to forecast such events. Weather forecasts at midlatitudes generally show low skill beyond 5–10 days, but long-range forecast skill may increase during extended tropospheric blocking episodes or perturbations of the stratospheric polar vortex, which can affect midlatitude weather for several weeks at a time. Here a simple, linear approach is used to identify previously undocumented persistence in northern European summer and winter temperature anomalies in climate model simulations, corroborated by observations and reanalysis data. For instance, temperature anomalies of at least one standard deviation above or below climatology in March were found to be about 20%–120% more likely than normal if the preceding February was anomalous by 0.5–1.5 standard deviations (with the same sign). The corresponding range for April (i.e., persistence over two months) is between 20% and 80%. The persistence is observed irrespective of the data source or driving mechanisms, and the temperature itself is a more skillful predictor of the temperatures one month ahead than the stratospheric polar vortex or the NAO and even than both factors together. The results suggest potential to conditionally improve the skill of long-range forecasts and enhance recent advancements in dynamical seasonal prediction.

Abstract

Models often underestimate blocking in the Atlantic and Pacific basins and this can lead to errors in both weather and climate predictions. Horizontal resolution is often cited as the main culprit for blocking errors due to poorly resolved small-scale variability, the upscale effects of which help to maintain blocks. Although these processes are important for blocking, the authors show that much of the blocking error diagnosed using common methods of analysis and current climate models is directly attributable to the climatological bias of the model. This explains a large proportion of diagnosed blocking error in models used in the recent Intergovernmental Panel for Climate Change report. Furthermore, greatly improved statistics are obtained by diagnosing blocking using climate model data corrected to account for mean model biases. To the extent that mean biases may be corrected in low-resolution models, this suggests that such models may be able to generate greatly improved levels of atmospheric blocking.

Abstract

The IPCC Fifth Assessment Report highlighted large uncertainty in European precipitation changes in the coming century. This paper investigates the sources of intermodel differences using CMIP5 model European precipitation data. The contribution of atmospheric circulation to differences in precipitation trends is investigated by applying cluster analysis to daily mean sea level pressure (MSLP) data. The resulting classification is used to reconstruct monthly precipitation time series, thereby isolating the component of precipitation variability directly related to atmospheric circulation. Reconstructed observed precipitation and reconstructions of simulated historical and projection data are well correlated with the original precipitation series, showing that circulation variability accounts for a substantial fraction of European precipitation variability. Removing the reconstructed precipitation from the original precipitation leaves a residual component related to noncirculation effects (and any small remaining circulation effects). Intermodel spread in residual future European precipitation trends is substantially reduced compared to the spread of the original precipitation trends. Uncertainty in future atmospheric circulation accounts for more than half of the intermodel variance in twenty-first-century precipitation trends for winter months for both northern and southern Europe. Furthermore, a substantial part of this variance is related to different forced dynamical responses in different models and is therefore potentially reducible. These results highlight the importance of understanding future changes in atmospheric dynamics in achieving more robust projections of regional climate change. Finally, the possible dynamical mechanisms that may drive the future differences in regional circulation and precipitation are illustrated by examining simulated teleconnections with tropical precipitation.

Abstract

This study investigates the stratosphere–troposphere coupling associated with the Scandinavian (SCA) pattern in boreal winter. The results indicate that the SCA impacts stratospheric circulation but that its positive and negative phases have different effects. The positive phase of the SCA (SCA⁺) pattern is restricted to the troposphere, but the negative phase (SCA⁻) extends to the upper stratosphere. The asymmetry between phases is also visible in the lead–lag evolution of the stratosphere and troposphere. Prominent stratospheric anomalies are found to be intensified following SCA⁺ events, but prior to SCA⁻ events. Further analysis reveals that the responses are associated with upward propagation of planetary waves, especially wavenumber 1, which is asymmetric between SCA phases. The wave amplitudes in the stratosphere, originating from the troposphere, are enhanced after the SCA⁺ events and before the SCA⁻ events. Furthermore, the anomalous planetary wave activity can be understood through its interference with climatological stationary waves. Constructive wave interference is accompanied by clear upward propagation in the SCA⁺ events, while destructive interference suppresses stratospheric waves in the SCA⁻ events. Our results also reveal that the SCA⁺ events are more likely to be followed by sudden stratospheric warming (SSW) events, because of the deceleration of stratospheric westerlies following the SCA⁺ events.

Abstract

December 2010 was unusual both in the strength of the negative North Atlantic Oscillation (NAO) intense atmospheric blocking and the associated record-breaking low temperatures over much of northern Europe. The negative North Atlantic Oscillation for November–January was predicted in October by 8 out of 11 World Meteorological Organization Global Producing Centres (WMO GPCs) of long-range forecasts. This paper examines whether the unusual strength of the NAO and temperature anomaly signals in early winter 2010 are attributable to slowly varying boundary conditions [El Niño–Southern Oscillation state, North Atlantic sea surface temperature (SST) tripole, Arctic sea ice extent, autumn Eurasian snow cover], and whether these were modeled in the Met Office Global Seasonal Forecasting System version 4 (GloSea4). Results from the real-time forecasts showed that a very robust signal was evident in both the surface pressure fields and temperature fields by the beginning of November. The historical reforecast set (hindcasts), used to calibrate and bias correct the real-time forecast, showed that the seasonal forecast model reproduces at least some of the observed physical mechanisms that drive the NAO. A series of ensembles of atmosphere-only experiments was constructed, using forecast SSTs and ice concentrations from November 2010. Each potential mechanism in turn was systematically isolated and removed, leading to the conclusion that the main mechanism responsible for the successful forecast of December 2010 was anomalous ocean heat content and associated SST anomalies in the North Atlantic.

Abstract

The variability of the North Atlantic Oscillation (NAO) is a key aspect of Northern Hemisphere atmospheric circulation and has a profound impact upon the weather of the surrounding landmasses. Recent success with dynamical forecasts predicting the winter NAO at lead times of a few months has the potential to deliver great socioeconomic impacts. Here, a linear regression model is found to provide skillful predictions of the winter NAO based on a limited number of statistical predictors. Identified predictors include El Niño, Arctic sea ice, Atlantic SSTs, and tropical rainfall. These statistical models can show significant skill when used to make out-of-sample forecasts, and the method is extended to produce probabilistic predictions of the winter NAO. The statistical hindcasts can achieve similar levels of skill to state-of-the-art dynamical forecast models, although out-of-sample predictions are less skillful, albeit over a small period. Forecasts over a longer out-of-sample period suggest there is true skill in the statistical models, comparable with that of dynamical forecasting models. They can be used both to help evaluate and to offer insight into the sources of predictability and limitations of dynamical models.

Abstract

It is well known that the stratospheric quasi-biennial oscillation (QBO) is forced by equatorial waves with different horizontal/vertical scales, including Kelvin waves, mixed Rossby–gravity (MRG) waves, inertial gravity waves (GWs), and mesoscale GWs, but the relative contribution of each wave is currently not very clear. Proper representation of these waves is critical to the simulation of the QBO in general circulation models (GCMs). In this study, the vertical resolution in the Beijing Climate Center Atmospheric General Circulation Model (BCC-AGCM) is increased to better represent large-scale waves, and a mesoscale GW parameterization scheme, which is coupled to the convective sources, is implemented to provide unresolved wave forcing of the QBO. Results show that BCC-AGCM can spontaneously generate the QBO with realistic periods, amplitudes, and asymmetric features between westerly and easterly phases. There are significant spatiotemporal variations of parameterized convective GWs, largely contributing to a great degree of variability in the simulated QBO. In the eastward wind shear of the QBO at 20 hPa, forcing provided by resolved waves is 0.1–0.2 m s⁻¹ day⁻¹ and forcing provided by parameterized GWs is ~0.15 m s⁻¹ day⁻¹. On the other hand, westward forcings by resolved waves and parameterized GWs are ~0.1 and 0.4–0.5 m s⁻¹ day⁻¹, respectively. It is inferred that the eastward forcing of the QBO is provided by both Kelvin waves and mesoscale convective GWs, whereas the westward forcing is largely provided by mesoscale GWs. MRG waves barely contribute to the formation of the QBO in the model.

Abstract

Results are presented from two 60-yr integrations of the troposphere–stratosphere configuration of the U.K. Met. Office’s Unified Model. The integrations were set up identically, apart from different initial conditions, which, nonetheless, were both representative of the early 1990s. Radiative heating rates were calculated using the IS92A projected concentrations of the well-mixed greenhouse gases (GHGs) given by the Intergovernmental Panel on Climate Change, but changes in stratospheric ozone and water vapor were not included. Sea surface conditions were taken from a separate coupled ocean–atmosphere experiment. Both integrations reproduced the familiar pattern of tropospheric warming and a stratospheric cooling increasing with height to about −1.4 K per decade at 1 mb. There was good agreement in the trends apart from in the polar upper stratosphere and, to a greater extent, the polar lower-to-middle stratosphere, where there is significant interannual variability during the winter months. Even after decadal smoothing, the trends in the northern winter were still overshadowed by the variability resulting from the planetary wave forcing from the troposphere. In general, the decadal variability of the Northern Hemisphere stratosphere was not a manifestation of a uniform change throughout each winter but, as with other models, there was a change in the frequency of occurrence of sudden stratospheric warmings. Unlike previous studies, the different results from the two simulations confirm the change in frequency of warmings was due to internal atmospheric variability and not the prescribed changes in GHG concentrations or sea surface conditions. In the southern winter stratosphere the flux of wave activity from the troposphere increased, but any additional dynamical heating was more than offset by the extra radiative cooling from the growing total GHG concentration. Consequently the polar vortex became more stable, with the spring breakdown delayed by 1–2 weeks by the 2050s. Polar stratospheric cloud (PSC) amounts inferred from the predicted temperatures increased in both hemispheres, especially in the early winter. In the Southern Hemisphere, the region of PSC formation expanded both upward and equatorward in response to the temperature trend.