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Curt Covey
,
Peter J. Gleckler
,
Charles Doutriaux
,
Dean N. Williams
,
Aiguo Dai
,
John Fasullo
,
Kevin Trenberth
, and
Alexis Berg

-look metrics. 3. Guidelines for metrics Figure 1 presents the diurnal harmonic amplitude and phase from the observations. Since warm seasons have similar dynamics, Fig. 1 combines Northern Hemisphere July and Southern Hemisphere January in both maps. The resulting discontinuity at the equator is small. (Corresponding cold season maps provide little additional information because coherent diurnal variation outside the tropics is small; cf. Figs. S2–S5 in the supplemental material.) The diurnal

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D. R. Jackett
,
T. J. McDougall
,
M. H. England
, and
A. C. Hirst

comparison of sea level rise estimates made from an ocean running with today’s climate with others made from transient fully coupled climate experiments in which the surface forcing is different. Maps of the spatial pattern of sea level rise can be made from the output of coupled GCMs using a simple inverse method. It is shown that the solution obtained using this inverse method is more accurate than the solution obtained by using a simpler technique for finding the spatial map of pressure at a certain

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Xinhua Cheng
and
Timothy J. Dunkerton

relatively small number of spatial patterns that account for large fractions of variance of thefield. Similar analysis techniques such as canonical correlation analysis (CCA) and singular value decomposition (SVD) analysis that identify pairs of spatial patterns from two data fields are also becoming popular.Singular value decomposition, in general, is a basic matrix operation in linear algebra, whereas the SVD analysis discussed in the present study refers to the technique that isolates pairs of spatial

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Louis St. Laurent
and
Harper Simmons

reviewed current knowledge of the diffusivity of turbulence diffusivities throughout the oceans. Estimates of this parameter come from several sources, including direct measurements, parameterizations of oceanic finestructure, and indirect estimates based on algebraic and statistical inversions of hydrography. While each of these methods require assumptions with potential limitations, results are generally consistent among water mass–based comparisons. Diffusivities in the ventilated waters of the

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Richard E. Chandler
,
Clair R. Barnes
, and
Chris M. Brierley

this based on a purely visual inspection. Moreover, it is hard to identify any systematic and detailed spatial structure from the maps. This creates difficulties for several potential users of the ensemble. Consider, for example, a regional climate modeler who sees EuroCORDEX as an opportunity to explore the simulation of summer temperatures by different RCMs. Apart from the apparent cool biases noted above, Fig. 1 does not obviously provide useful information to support such a comparison

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Pavel Ya Groisman
,
Raymond S. Bradley
, and
Bomin Sun

observational data for the past several decades and then testing the GCMs’ output behavior against nature. Only those that pass this comparison are capable of delivering correct answers in experiments with external forcing, and this (we hope) will narrow the present uncertainty in climate change studies. In this paper, we focus on one of the major trouble spots, cloudiness, and its interaction within the climatic system where parameterizations are still not well determined. We will consider overall cloud

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Hisashi Nakamura
,
Takuya Izumi
, and
Takeaki Sampe

anomaly field for any variable based on the reanalyses was constructed as the simple algebraic mean of the two 31-day running mean anomaly fields, one for the mid-January and the other for mid-February. 3. Interannual variability in the storm track and monsoon activities Our main analysis domain is limited within the Far East and the NW Pacific (20°–60°N, 100°E–180°), where both the northwesterly monsoonal flow ( υ * T *) and storm track activity ( υ h T h ) in the lower troposphere are particularly

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Dan G. Blumberg
and
Ronald Greeley

3248JOURNAL OF CLIMATEVOLUME 9A Comparison of General Circulation Mode]l Predictions to Sand Drift and Dune Orientations DAN G. BLUMBERGRemote Sensing Laboratory, Institute for Desert Research, Arizona State University, Tempe, Arizona RONALD GREELEY Department of Geology, Arizona State University, Tempe, ArizonaDepartment of Geography and Environmental Development, Ben-Gurion University of the Negev, Beer-Shera, Israel (Manuscript

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Edwin P. Gerber
and
Geoffrey K. Vallis

important for the surface pressure than zonal winds ( North et al. 1982b ) so that comparison of models P 1 and P 2 to the atmosphere is more tenuous; the result may be the product of canceling errors. Also, the reanalysis winds and pressure EOFs appear to decay exponentially with wavenumber. The differences in the relative importance of EOFs between model M and P 2 is a result of low order algebraic decay. With exponential decay, the top EOFs of both pressure and winds can explain the same

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Cecilia Peralta-Ferriz
,
James H. Morison
,
John M. Wallace
,
Jennifer A. Bonin
, and
Jinlun Zhang

with the IB-corrected records from tide gauges, we removed the global-mean SLP from GRACE for consistency with the tide gauges. Figure 3 shows the time series comparisons between GRACE OBP and in situ records for five locations: the North Pole, Fram Strait, averaged tide gauge records in the Kara Sea, averaged tide gauge records in the Laptev Sea, and the Canadian Arctic at Alert Station ( Fig. 3 ). We averaged the records from the tide gauges located in the Laptev and Kara Seas (see map in Fig

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