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Mimi Stith, Alessandra Giannini, John del Corral, Susana Adamo, and Alex de Sherbinin

). Independent of evidence from remote sensing, climate research had already demonstrated that large-scale drying could be explained by factors external to the region, namely, changes in the surface temperature of the global oceans ( Folland et al. 1986 ), with no need to invoke regional-scale land degradation and its interaction with atmospheric dynamics as originally envisaged. More recent research has confirmed the dominant role of global sea surface temperature patterns in driving the twentieth

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Peter J. Lamb, Diane H. Portis, and Abraham Zangvil

dPW. The daily correlations of SR with P , E − P , MFD, HD, and E are of the same sign but smaller than their monthly counterparts discussed above ( Table 2 ). Most pronounced is the weakening of the SR associations with MFD (+0.78/+0.84 to +0.18), E − P (+0.81/+0.86 to +0.55), and E (−0.64/−0.73 to −0.24). c. Moisture recycling, soil moisture, and wheat and sorghum crops Important new insight into SGP growing season land–atmosphere interactions is added to the above results of traditional

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John G. Dwyer, Michela Biasutti, and Adam H. Sobel

significant at the 95% level. The effect that the amplitude of SST has on the phase of precipitation is reduced by 60% in the aquaplanet simulations and the effect that the phase of SST has on the amplitude of precipitation is reduced by 85%. Insolation still varies throughout the year, and has a phase-locked annual cycle of shortwave absorption in the atmosphere that may account for the remainder of the cross-effects. But when the effects of land and other zonal asymmetries are totally removed, the cross

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Elinor R. Martin and Chris Thorncroft

AEWs in 28 models from the observed SST-forced atmosphere and land-only (AMIP) runs. As the well-known southeast Atlantic warm SST bias is present in CMIP5 simulations ( Richter et al. 2014 ) and impacts the WAM ( Roehrig et al. 2013 ), we examine the AMIP simulations to help establish the impact of SST bias on AEW characteristics. In addition, we examine 28 models from the historical and future projection (RCP8.5) simulations. Output from AMIP models is available from 1979 to 2008 and historical

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Lisa Hannak, Peter Knippertz, Andreas H. Fink, Anke Kniffka, and Gregor Pante

.662 . 10.1002/qj.662 Bao , Q. , and Coauthors , 2013 : The Flexible Global Ocean–Atmosphere–Land System model version: FGOALS-s2 . Adv. Atmos. Sci. , 30 , 561 – 576 , doi: 10.1007/s00376-012-2113-9 . 10.1007/s00376-012-2113-9 Benson , C. , and E. J. Clay , 1998 : The impact of drought on sub-Saharan economies. World Bank Tech. Paper 401, 80 pp. 10.1596/0-8213-4180-4 Biasutti , M. , I. Held , A. Sobel , and A. Giannini , 2008 : SST forcings and Sahel rainfall variability in

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M. Issa Lélé, Lance M. Leslie, and Peter J. Lamb

seasonal cycle of precipitation north of 8°N latitude consists of a single rainy season maximum, which could be brief as three months, from July to September. Other important features occur during the summer, which is the season when the atmosphere–ocean–land surface interactions are strong, and when the Sahelian precipitations are abundant. Figure 4 displays the climatology of moisture flow fields during the summer season months. As the monsoon extends into these boreal summer months, the moisture

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Kerry H. Cook and Edward K. Vizy

clearly not increasing precipitation over the land. The reason is that the flow is divergent, being associated with an anticyclonic circulation system. As seen in Fig. 8b , which shows 800-hPa moisture convergence representing the lower atmosphere, the region over the Indian Ocean with a strong anticyclonic flow anomaly exhibits large-scale divergence. Fig . 8. Differences (21C − 20C) in the 800 hPa ensemble-mean (a) winds (vectors; m s −1 ) and mixing ratio (contours; CI is 2 kg kg −1 ) and (b

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Zewdu T. Segele, Michael B. Richman, Lance M. Leslie, and Peter J. Lamb

potential predictors Guided by Part I , the full three-dimensional state of the regional atmosphere and global SST was represented by a set of potential March predictors of Kiremt (JJAS) rainfall. Raw atmospheric predictors consisted of gridpoint values for 50°N–40°S, 30°W–90°E of geopotential height (Φ), temperature ( T ), horizontal wind ( u , υ ), vertical velocity ( w ), and specific humidity ( q ) at standard pressure levels, and MSLP. To accommodate potential interaction effects between these

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Irenea L. Corporal-Lodangco, Lance M. Leslie, and Peter J. Lamb

. El Niño–Southern Oscillation (ENSO) is a tropical atmosphere–ocean interaction that modifies the thermodynamic and dynamic states that influence the weather and climate system ( Bjerknes 1969 ). Kim et al. (2008) consider it to be the most important planetary-scale phenomenon affecting interannual variations in TC activity in the WNP. The relationship between ENSO and TC activity in the WNP has been explored extensively in previous studies (e.g., Chan 1985 , 2000 ; Dong 1988 ; Lander 1993

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