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Meire L. C. Berbet and Marcos Heil Costa

seasonal variability, with higher values in the dry period (June–November), and lower values in the rainy period (December–May). On the other hand, the pasture albedo presents a stronger variability throughout the year, especially in Ji-Paraná, Rondonia, Brazil ( Fig. 1b ), with albedo values decreasing in the dry season, a consequence of the decrease in the leaf area index in the dry period ( Wright et al. 1996 ). In Fig. 1 , the combined effects of four of the most important sources of variability

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Adam J. Kalkstein, Miloslav Belorid, P. Grady Dixon, Kyu Rang Kim, and Keith A. Bremer

nonlinear and lagged effects of an exposure variable such as temperature on a specific human health outcome. Further, DLNM is effective at controlling for cyclical patterns such as day-of-week and seasonal effects along with long-term trends such as population change and the implementation of suicide prevention efforts, all of which have been highlighted in previous environment–suicide research as having important impacts on suicide rates ( Dixon and Kalkstein 2009 ; Mok et al. 2012 ; Hiltunen et al

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William B. Rossow and Andrew A. Lacis

1204 JOURNAL OF CLIMATE VOLUME 3Global, Seasonal Cloud Variations from Satellite Radiance Measurements. Part II: Cloud Properties and Radiative Effects WILLIAM B. ROSSOW AND ANDREW A. LACISNASA Goddard Space Flight Center, Institute for Space Studies, New York, New York(Manuscript received 14 December 1989, in final form 25 April 1990)ABSTRACT Global, daily, visible

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Renu Joseph and Ning Zeng

–Southern Oscillation (ENSO) on vegetation and the carbon cycle ( Zeng et al. 2005 ; Qian et al. 2008 ). The model consists of the global version of the atmospheric model Quasi-equilibrium Tropical Circulation Model (QTCM) ( Neelin and Zeng 2000 ; Zeng et al. 2000 ), which simulates a reasonable seasonal climate compared to observations in the tropics and midlatitudes. The QTCM is coupled to the simple-land model ( Zeng et al. 2000 ), and a slab mixed layer ocean model with Q-flux to represent the effects of

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Robert B. Scott, Christina L. Holland, and Terrence M. Quinn

skeletons will arise from dating errors, errors in characterization of the Sr/Ca (including both measurement errors and the effects of heterogeneity of the Sr/Ca within the coral skeleton), and errors in the calibration resulting from limitations in the reference instrumental data and/or variations of the calibration on long time scales. We paid particular attention to the latter, which may result from gradual, non-SST influences on Sr/Ca that are dominated by seasonal SST variations but accumulate on

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Natasa Skific, Jennifer A. Francis, and John J. Cassano

the emission of longwave radiation to the surface ( Francis and Hunter 2007 ). Both of these effects constitute positive feedbacks to the system that will augment Arctic warming and the loss of sea ice, permafrost, and low-elevation land ice. Net precipitation in the North Atlantic region is projected to increase substantially (about 18%), but it exhibits a very different seasonal behavior. The largest increase occurs in nonsummer months, with winter accounting for about 44% of the annual

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Sarah J. Arnup and Michael J. Reeder

change in moisture accompanied by a relatively small change in temperature and is another example of an airmass boundary ( Cohen and Kreitzberg 1997 ; Cohen and Schultz 2005 ). In the Australian region, a dryline forms inland from the northern coastlines from the diffuse moisture gradient across the tropical and continental air masses. Despite the prominence of the dryline in the climatology of northern Australia, there have been few investigations of its structure, daily evolution, or seasonal

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Patrick F. Cummins

VOLUME 19 JOURNAL OF PHYSICAL OCEANOGRAPHY NOVEMBER 1989A Quasi-geostrophic Circulation Model of the Northeast Pacific.Part II: Effects of Topography and Seasonal Forcing PATRICK F. CUMMINS*Institute of Ocean Sciences, Sidney, British Columbia, Canada(Manuscript received l0 November 1988, in final form 23 March 1989)ABSTRACT A quasi-geostrophic regional model of the northeast Pacific is used to investigate the

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Lingjing Zhu, Jiming Jin, and Yimin Liu

at a rate of 46.5 mm decade −1 ( Zhu et al. 2019 ). Therefore, the effects of TP lakes and their changes on local and regional climate are worth characterizing and quantifying. Due to their wide distribution and ability to modulate energy and water transfer, TP lakes are likely to affect TP precipitation at diurnal and seasonal scales. TP precipitation is generated mainly by small (<100 km 2 ) and medium (100–10 000 km 2 ) convective systems ( Hirose and Nakamura 2005 ) and characterized by a

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Eleonora M. C. Demaria, Joshua K. Roundy, Sungwook Wi, and Richard N. Palmer

-depth fields, available at 0.25° resolution, were regridded to a common 0.125° grid using a cubic interpolation. The winter snow climatology is characterized by a thick snowpack over high latitudes with little orographic control ( Fig. 1b ), as is the case in the western United States, in New England, and in the Great Lakes region where mean seasonal values reach 50 cm. Figures 1c and 1d show the November–March averaged snow depth for observations and VIC simulations, respectively. VIC-simulated snow

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