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Peter A. G. Watson and Lesley J. Gray

Abstract

The stratospheric polar vortex is weaker in the easterly phase of the quasi-biennial oscillation (QBO-E) than in the westerly phase (QBO-W), but the mechanism behind the QBO's influence is not well understood. The composite difference of the atmospheric state between QBO-E and QBO-W is found to closely resemble the structure of the northern annular mode, the leading empirical orthogonal function of stratospheric variability, including its wave components. Studies of dynamical systems indicate that many different forcings could give rise to this response, and therefore this composite difference does not provide much information about the forcing mechanism. It is argued that the full transient response of a system to an applied forcing is likely to be much more informative about the dynamics of the forcing mechanism, especially the response on time scales shorter than the dynamical time scale, which is about a week for vortex variability. It is shown that the transient response of the vortex to forcing by the QBO in a general circulation model is consistent with the proposed mechanism of Holton and Tan, indicating that this mechanism has a role in the QBO modulation of vortex strength, in contrast to the conclusions of several recent studies. This novel approach of examining the transient response to a forcing on short time scales may be useful in various other outstanding problems.

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Peter A. G. Watson, H. M. Christensen, and T. N. Palmer

Abstract

Important questions concerning parameterization of tropical convection are how should subgrid-scale variability be represented and which large-scale variables should be used in the parameterizations? Here the statistics of observational data in Darwin, Australia, are compared with those of short-term forecasts of convection made by the European Centre for Medium-Range Weather Forecasts Integrated Forecast System. The forecasts use multiplicative-noise stochastic physics (MNSP) that has led to many improvements in weather forecast skill. However, doubts have recently been raised about whether MNSP is consistent with observations of tropical convection. It is shown that the model can reproduce the variability of convection intensity for a given large-scale state, both with and without MNSP. Therefore MNSP is not inconsistent with observations, and much of the modeled variability arises from nonlinearity of the deterministic part of the convection scheme. It is also shown that the model can reproduce the lack of correlation between convection intensity and large-scale CAPE and an entraining CAPE, even though the convection parameterization assumes that deep convection is more intense when the vertical temperature profile is more unstable, with entrainment taken into account. Relationships between convection and large-scale convective inhibition and vertical velocity are also correctly captured.

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Daniel M. Mitchell, Scott M. Osprey, Lesley J. Gray, Neal Butchart, Steven C. Hardiman, Andrew J. Charlton-Perez, and Peter Watson
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Emma J. D. Boland, Emily Shuckburgh, Peter H. Haynes, James R. Ledwell, Marie-José Messias, and Andrew J. Watson

Abstract

The use of a measure to diagnose submesoscale isopycnal diffusivity by determining the best match between observations of a tracer and simulations with varying small-scale diffusivities is tested. Specifically, the robustness of a “roughness” measure to discriminate between tracer fields experiencing different submesoscale isopycnal diffusivities and advected by scaled altimetric velocity fields is investigated. This measure is used to compare numerical simulations of the tracer released at a depth of about 1.5 km in the Pacific sector of the Southern Ocean during the Diapycnal and Isopycnal Mixing Experiment in the Southern Ocean (DIMES) field campaign with observations of the tracer taken on DIMES cruises. The authors find that simulations with an isopycnal diffusivity of ~20 m2 s−1 best match observations in the Pacific sector of the Antarctic Circumpolar Current (ACC), rising to ~20–50 m2 s−1 through Drake Passage, representing submesoscale processes and any mesoscale processes unresolved by the advecting altimetry fields. The roughness measure is demonstrated to be a statistically robust way to estimate a small-scale diffusivity when measurements are relatively sparse in space and time, although it does not work if there are too few measurements overall. The planning of tracer measurements during a cruise in order to maximize the robustness of the roughness measure is also considered. It is found that the robustness is increased if the spatial resolution of tracer measurements is increased with the time since tracer release.

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Daniel M. Mitchell, Scott M. Osprey, Lesley J. Gray, Neal Butchart, Steven C. Hardiman, Andrew J. Charlton-Perez, and Peter Watson

Abstract

With extreme variability of the Arctic polar vortex being a key link for stratosphere–troposphere influences, its evolution into the twenty-first century is important for projections of changing surface climate in response to greenhouse gases. Variability of the stratospheric vortex is examined using a state-of-the-art climate model and a suite of specifically developed vortex diagnostics. The model has a fully coupled ocean and a fully resolved stratosphere. Analysis of the standard stratospheric zonal mean wind diagnostic shows no significant increase over the twenty-first century in the number of major sudden stratospheric warmings (SSWs) from its historical value of 0.7 events per decade, although the monthly distribution of SSWs does vary, with events becoming more evenly dispersed throughout the winter. However, further analyses using geometric-based vortex diagnostics show that the vortex mean state becomes weaker, and the vortex centroid is climatologically more equatorward by up to 2.5°, especially during early winter. The results using these diagnostics not only characterize the vortex structure and evolution but also emphasize the need for vortex-centric diagnostics over zonally averaged measures. Finally, vortex variability is subdivided into wave-1 (displaced) and -2 (split) components, and it is implied that vortex displacement events increase in frequency under climate change, whereas little change is observed in splitting events.

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Cynthia Rosenzweig, William D. Solecki, Lily Parshall, Barry Lynn, Jennifer Cox, Richard Goldberg, Sara Hodges, Stuart Gaffin, Ronald B. Slosberg, Peter Savio, Frank Dunstan, and Mark Watson

This study of New York City, New York's, heat island and its potential mitigation was structured around research questions developed by project stakeholders working with a multidisciplinary team of researchers. Meteorological, remotely-sensed, and spatial data on the urban environment were brought together to understand multiple dimensions of New York City's heat island and the feasibility of mitigation strategies, including urban forestry, green roofs, and high-albedo surfaces. Heat island mitigation was simulated with the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5). Results compare the possible effectiveness of mitigation strategies at reducing urban air temperature in six New York City neighborhoods and for New York City as a whole. Throughout the city, the most effective temperature-reduction strategy is to maximize the amount of vegetation, with a combination of tree planting and green roofs. This lowered simulated citywide surface urban air temperature by 0.4°C on average, and 0.7°C at 1500 Eastern Standard Time (EST), when the greatest temperature reductions tend to occur. Decreases of up to 1.1°C at 1500 EST occurred in some neighborhoods in Manhattan and Brooklyn, where there is more available area for implementing vegetation planting. New York City agencies are using project results to guide ongoing urban greening initiatives, particularly tree-planting programs.

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Keith A. Browning, Alan M. Blyth, Peter A. Clark, Ulrich Corsmeier, Cyril J. Morcrette, Judith L. Agnew, Sue P. Ballard, Dave Bamber, Christian Barthlott, Lindsay J. Bennett, Karl M. Beswick, Mark Bitter, Karen E. Bozier, Barbara J. Brooks, Chris G. Collier, Fay Davies, Bernhard Deny, Mark A. Dixon, Thomas Feuerle, Richard M. Forbes, Catherine Gaffard, Malcolm D. Gray, Rolf Hankers, Tim J. Hewison, Norbert Kalthoff, Samiro Khodayar, Martin Kohler, Christoph Kottmeier, Stephan Kraut, Michael Kunz, Darcy N. Ladd, Humphrey W. Lean, Jürgen Lenfant, Zhihong Li, John Marsham, James McGregor, Stephan D. Mobbs, John Nicol, Emily Norton, Douglas J. Parker, Felicity Perry, Markus Ramatschi, Hugo M. A. Ricketts, Nigel M. Roberts, Andrew Russell, Helmut Schulz, Elizabeth C. Slack, Geraint Vaughan, Joe Waight, David P. Wareing, Robert J. Watson, Ann R. Webb, and Andreas Wieser

The Convective Storm Initiation Project (CSIP) is an international project to understand precisely where, when, and how convective clouds form and develop into showers in the mainly maritime environment of southern England. A major aim of CSIP is to compare the results of the very high resolution Met Office weather forecasting model with detailed observations of the early stages of convective clouds and to use the newly gained understanding to improve the predictions of the model.

A large array of ground-based instruments plus two instrumented aircraft, from the U.K. National Centre for Atmospheric Science (NCAS) and the German Institute for Meteorology and Climate Research (IMK), Karlsruhe, were deployed in southern England, over an area centered on the meteorological radars at Chilbolton, during the summers of 2004 and 2005. In addition to a variety of ground-based remote-sensing instruments, numerous rawinsondes were released at one- to two-hourly intervals from six closely spaced sites. The Met Office weather radar network and Meteosat satellite imagery were used to provide context for the observations made by the instruments deployed during CSIP.

This article presents an overview of the CSIP field campaign and examples from CSIP of the types of convective initiation phenomena that are typical in the United Kingdom. It shows the way in which certain kinds of observational data are able to reveal these phenomena and gives an explanation of how the analyses of data from the field campaign will be used in the development of an improved very high resolution NWP model for operational use.

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