The tenth IMSC, Beijing, China, 2007 - International Meetings on ...

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Extending attribution studies: postage stamps for the world Speaker: Dáithí Stone Dáithí Stone Tyndall Centre, Dept. of Physics, University of Oxford stoned@atm.ox.ac.uk Studies of the detection and attribution of climate change are progressing beyond the question `Have we influenced the climate?' and starting to address the question `How does the current climate differ because of our influence?' <strong>The</strong> subtle but important difference between these two questions means that different assumptions are required when addressing them. Are these assumptions contradictory? This talk will discuss these questions through a comparison of observed continental surface temperature trends with those from a multi-model ensemble of historical simulations including only natural external forcings and an ensemble including both anthropogenic and natural forcings. Consistency of observed winter precipitation trends in northern Europe with regional climate change projections Speaker: Hans von Storch Hans von Storch Institute for Coastal Research, GKSS hvonstorch@web.de Jonas Bhend Institute for Coastal Research, GKSS Often it is claimed that the recent changes in northern European climate are at least partly anthropogenic even though a human influence has not yet been successfully detected. Hence we investigate whether the recent changes are consistent with regional climate change projections.<strong>The</strong>refore, trends in winter (DJF) mean precipitation in northern Europe are compared to human induced changes as predicted by an ensemble of four regional climate model simulations. <strong>The</strong> patterns of recent trends and predicted changes match reasonably well as indicated by pattern correlation and the similarity is very likely not random. However, the model projections severely underestimate the recent change in winter precipitation by 50 to 80\%. That is, the signal-to-noise ratio of the anthropogenic precipitation change is either rather low or the presently used simulations are significantly flawed in their ability to project changes into the future. 47
European trends contain large NAO-related signals, of which a major unknown part may be unrelated to the anthropogenic signal. <strong>The</strong>refore, we also examine the consistency of recent and projected changes after subtracting the NAO signal in both the observations and in the projections. It turns out that even after the removal of the NAO signal, the pattern of trends in the observations are similar to those projected by the models. At the same time, the magnitude of the trends is considerably reduced and closer to the magnitude of the change in the projections. Detection of external influence on trends of atmospheric storminess and northern oceans wave heights Speaker: Xiaolan L. Wang Xiaolan L. Wang Climate Research Division, ASTD, STB, Environment Canada, Toronto, Ontario Xiaolan.Wang@ec.gc.ca Val R. Swail, Francis W. Zwiers, Xuebin Zhang,Yang Feng Climate Research Division, ASTD, STB, Environment Canada, Toronto, Ontario <strong>The</strong> atmospheric storminess (as inferred from geostrophic wind energy) and ocean wave heights have increased in the cold seasons over the past half century in the high-latitudes of the northern hemisphere (especially the northeast North Atlantic in boreal winter), and have decreased in more southerly northern latitudes. This study shows that these trend patterns contain a detectable response to external forcing (i.e., both natural and anthropogenic forcing). <strong>The</strong> signal of external influence is found to be strongest in the winter hemisphere, that is, in the northern hemisphere in January-February-March and in the southern hemisphere in July-August-September. However, the magnitude of the estimated response to the forcing, which was obtained directly from climate models in the case of geostrophic wind energy and indirectly via an empirical downscaling procedure in the case of ocean wave heights, is significantly less than the magnitude of the observed changes in these parameters. Detection of Human Influence on 20th Century Precipitation Trends Speaker: Xuebin Zhang Xuebin Zhang Environment Canada Xuebin.Zhang@ec.gc.ca 48
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1Oth International
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Preface It is truly a great pleasur
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Speaker: Dan Cooley................
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Speaker: Qian Li ..................
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Speaker: Ediang Okuku Archibong....
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Speaker: Yi Wang...................
Page 14 and 15: Climatological Dataset.............
Page 16 and 17: Bridging the gap between simulated
Page 18 and 19: Invited Session: Spatial patterns o
Page 20 and 21: Joint Program on the Science and Po
Page 22 and 23: e to adopt a different calibrated l
Page 24 and 25: those retained, and [iii] performan
Page 26 and 27: A range of existing statistical app
Page 28 and 29: palaeo-environmental data from sout
Page 30 and 31: Whilst it has been noted that such
Page 32 and 33: State Key Laboratory of Numerical M
Page 34 and 35: address new policies for changing c
Page 36 and 37: and show promise for analyzing tren
Page 38 and 39: 1901-2005 with complete data of all
Page 40 and 41: Homogenization of daily meteorologi
Page 42 and 43: as Homogen Data, Gap, Index, Statis
Page 44 and 45: Penalized maximal t-test for detect
Page 46 and 47: Iran,Tehran, Azad university, Resea
Page 48 and 49: We present applications of several
Page 50 and 51: A 50-member ensemble is produced wi
Page 52 and 53: ichard@stats.ucl.ac.uk Nadja Leith
Page 54 and 55: Answering questions about empirical
Page 56 and 57: In a series of climate change impac
Page 58 and 59: climatological annual frequency of
Page 60 and 61: Detection of urban warming in recen
Page 62 and 63: Detection of Human Influence on pan
Page 66 and 67: Francis W. Zwiers, Gabriele C. Hege
Page 68 and 69: 1, In the middle-pattern of El Niñ
Page 70 and 71: convergence zone (ITCZ). Th
Page 72 and 73: stationary waves occur in mid-latit
Page 74 and 75: A multiple surrogate data study of
Page 76 and 77: Linear and non-linear reconstructio
Page 78 and 79: Pseudo-proxy tests of the regulariz
Page 80 and 81: Parallel Sessions:Regional Studies
Page 82 and 83: Iterative Interpolation of Daily Pr
Page 84 and 85: disturbance in the natural ecosyste
Page 86 and 87: Climate Risk Management in North-Ea
Page 88 and 89: Analyzing of synoptic intence showe
Page 90 and 91: chosen since it completely defines
Page 92 and 93: The Roles of Ensem
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Page 96 and 97: Empirical probabilistic seasonal fo
Page 98 and 99: Rajesh J. Department of Atmospheric
Page 100 and 101: Andrew Moore Uni. of California at
Page 102 and 103: Parallel Sessions:Simulation tools
Page 104 and 105: data can ever be generated. In fact
Page 106 and 107: egion can be explained by the rando
Page 108 and 109: on instantaneous time scales, respe
Page 110 and 111: Key words:- principal component reg
Page 112 and 113: een analysed with geostatistical to
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Iberian Peninsula and with the corr
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89% during the 10 days of mid-June,
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The paper examines
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Special AMS Session:Verification of
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Verification of Climate Forecasts (
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the regional climate change is repr
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model has been applied to the serie
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are analyzed. It is shown that thes
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stations in Iran. The</stro
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The study of the U
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Development and analysis of a daily
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Fractal widely exists in nature, an
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Rescue of historical climate data:
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D. Semeradova Institute of Landscap
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Kulkarni Ashwini, Sabade S S and Kr
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The magnitude of t
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Richard E. Chandler University Coll
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convective cloud clusters when they
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1999; Smith et al, 2001; Gibbons, 2
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dmanatsa@buse.ac.zw Wisemen Chingom
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The Relation Betwe
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conditioned on some indices of the
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ari@ludens.elte.hu J. Bartholy Dept
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ainfall as predictand. Additionally
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Impact of ENSO PHASES on Amazonia S
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time lag. Both perturbed analysis a
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Relationship Between Ensemble Mean
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ways were considered. Four zones, f
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- Monthly ratios of synthetic and o
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Total ozone trends are typically st
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Impact of Urban Expansion on Region
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Calibrating and evaluating reanalys
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To explore an optimal climate decis
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