Search Results

You are looking at 21 - 30 of 35 items for :

  • Decadal variability x
  • CCSM4/CESM1 x
  • All content x
Clear All
Kevin Raeder, Jeffrey L. Anderson, Nancy Collins, Timothy J. Hoar, Jennifer E. Kay, Peter H. Lauritzen, and Robert Pincus

atmosphere are no longer important. Instead, initial conditions for more slowly varying components of the climate system—in particular, the ocean—become the source of most forecast skill. An ocean ensemble data assimilation using the POP2 ocean component of CESM is one method that has been used to produce initial conditions for decadal predictions. Maintaining sufficient variability is one of the key problems in ensemble data assimilation; this leads to the need for inflation as noted in section 2a . If

Full access
William H. Lipscomb, Jeremy G. Fyke, Miren Vizcaíno, William J. Sacks, Jon Wolfe, Mariana Vertenstein, Anthony Craig, Erik Kluzek, and David M. Lawrence

differences (m) by (a) 2005 and (b) 2100 compared to 1850. The negative (blue) color scale saturates strongly; the largest negative differences exceed 400 m in the right panel. b. Future volume change During 2005–50 the rate of sea level rise from GIS mass loss was 1.9 mm decade −1 as a result of a more negative surface mass balance, as shown in Fig. 11a . The SMB declined more sharply after 2050, accompanied by an increase in SMB variability. After 2070 the 20-yr moving average SMB became negative

Full access
Gerald A. Meehl, Warren M. Washington, Julie M. Arblaster, Aixue Hu, Haiyan Teng, Claudia Tebaldi, Benjamin N. Sanderson, Jean-Francois Lamarque, Andrew Conley, Warren G. Strand, and James B. White III

the system, mostly including the upper ocean, comes into equilibrium. The control run branches at this point for the first twentieth-century integration with subsequent branch points for other twentieth-century simulations separated by a few decades at initial states with different values of meridional overturning circulation (MOC) in the Atlantic that span the range of variability of the MOC ( Gent et al. 2011 ). Single-forcing simulations and combinations of single forcings are also run, and

Full access
Keith Oleson

decadal rate of change in the UHI intensity of large U.S. cities between 1951 and 2000 to be 0.05°C. The lack of changes in urban extent and properties in the model explains this discrepancy. These simulations are only an indication of how the UHI changes under static, present-day urban conditions. b. Spatial and seasonal variability in the heat island Table 2 shows the present-day average UHI for the regions illustrated in Fig. 5 compared to climate warming in RCP8.5. As noted by Oleson et al

Full access
Christine A. Shields, David A. Bailey, Gokhan Danabasoglu, Markus Jochum, Jeffrey T. Kiehl, Samuel Levis, and Sungsu Park

: In the south, the momentum is deposited over the continent and does not overly affect the Southern Ocean sea ice; while in the north, the excess momentum is deposited in the center of the Arctic Ocean, leading to substantial cooling and thicker sea ice. However, the benefits of turbulent mountain stress to the overall T31x3 model outweigh the detrimental effects on sea ice, hence TMS is applied by default to this configuration. 6. Climate variability a. ENSO The variability of ENSO on decadal to

Full access
Jenny Lindvall, Gunilla Svensson, and Cecile Hannay

Model . J. Climate , 17 , 930 – 951 . Dunn , A. L. , C. C. Barford , S. C. Wofsy , M. L. Goulden , and B. C. Daube , 2007 : A long-term record of carbon exchange in a boreal black spruce forest: Means, responses to interannual variability, and decadal trends . Global Change Biol. , 13 , 577 – 590 , doi:10.1111/j.1365-2486.2006.01221.x . Eamus , D. , L. B. Hutley , and A. P. O’Grady , 2001 : Daily and seasonal patterns of carbon and water fluxes above a north Australian

Full access
Markus Jochum, Alexandra Jahn, Synte Peacock, David A. Bailey, John T. Fasullo, Jennifer Kay, Samuel Levis, and Bette Otto-Bliesner

. , 2 , 500–504, doi:10.1038/NGEO557 . Saenko , O. A. , E. C. Wiebe , and A. J. Weaver , 2003 : North Atlantic response to the above-normal export of sea ice from the Arctic . J. Geophys. Res. , 108 , 3224 , doi:10.1029/2001JC001166 . Schmittner , A. , and A. J. Weaver , 2001 : Dependence of multiple climate states on ocean mixing parameters . Geophys. Res. Lett. , 28 , 1027 – 1030 . Shaffrey , L. , and R. Sutton , 2006 : Bjerknes compensation and the decadal variability

Full access
Gokhan Danabasoglu, Susan C. Bates, Bruce P. Briegleb, Steven R. Jayne, Markus Jochum, William G. Large, Synte Peacock, and Steve G. Yeager

-scale parameterizations were realized through our collaborations with the university communities that participated in the U.S. Climate Variability and Predictability (CLIVAR) Climate Process Team (CPT) activities. Specifically, the CPTs on gravity current entrainment and eddy–mixed layer interactions resulted in an overflow parameterization ( Danabasoglu et al. 2010 ), a near-surface eddy flux parameterization ( Danabasoglu et al. 2008 ), a prescription for lateral tracer diffusivities that vary in the vertical

Full access
Esther C. Brady, Bette L. Otto-Bliesner, Jennifer E. Kay, and Nan Rosenbloom

overturning circulation in CCSM4 . J. Climate , 25 , 5153 – 5172 . Deser , C. , and Coauthors , 2012 : ENSO and Pacific decadal variability in Community Climate System Model version 4 . J. Climate , 25 , 2622 – 2651 . de Vernal , A. , and C. Hillaire-Marcel , 2000 : Sea-ice cover, sea-surface salinity and halo-/thermocline structure of the northwest North Atlantic: Modern versus full glacial conditions . Quat. Sci. Rev. , 19 , 65 – 85 . Edwards , T. L. , M. Crucifix , and S. P

Full access
J. E. Kay, B. R. Hillman, S. A. Klein, Y. Zhang, B. Medeiros, R. Pincus, A. Gettelman, B. Eaton, J. Boyle, R. Marchand, and T. P. Ackerman

1. Motivation a. Using satellite simulators to evaluate climate model clouds Cloud feedbacks dominate uncertainty in model climate projections (e.g., Cess et al. 1990 ; Bony and Dufresne 2005 ; Williams and Webb 2009 ; Medeiros et al. 2008 ), but the quantification of model cloud biases is often confounded by poor model–observational comparison techniques. In the last decade, data from a number of new cloud-observing satellite platforms have become available. Given this context, the use of

Full access