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vary from year to year ( Guo and Dirmeyer 2013 ) depending on the pattern of the climatology of soil moisture and the fluctuation of its anomalies. These results raise questions. Have the interactions between land and atmosphere on intraseasonal to interannual time scales changed since preindustrial times when atmospheric composition, aerosol loading, and global vegetation cover were different? More importantly, will land–atmosphere interactions change in the future? Phase 5 of the Coupled Model
vary from year to year ( Guo and Dirmeyer 2013 ) depending on the pattern of the climatology of soil moisture and the fluctuation of its anomalies. These results raise questions. Have the interactions between land and atmosphere on intraseasonal to interannual time scales changed since preindustrial times when atmospheric composition, aerosol loading, and global vegetation cover were different? More importantly, will land–atmosphere interactions change in the future? Phase 5 of the Coupled Model
evaporation on the variabilities of simulated soil wetness and climate. J. Climate, 1, 523–547. Delworth , T. L. , and S. Manabe , 1989 : The influence of soil wetness on near-surface atmospheric variability. J. Climate, 2, 1447–1462. Dirmeyer , P. A. , Y. Jin , B. Singh , and X. Yan , 2013 : Trends in land–atmosphere interactions from CMIP5 simulations . J. Hydrometeor. , 14 , 829 – 849 . Douville , H. , J.-F. Royer , J. Polcher , P. Cox , N. Gedney , D. B
evaporation on the variabilities of simulated soil wetness and climate. J. Climate, 1, 523–547. Delworth , T. L. , and S. Manabe , 1989 : The influence of soil wetness on near-surface atmospheric variability. J. Climate, 2, 1447–1462. Dirmeyer , P. A. , Y. Jin , B. Singh , and X. Yan , 2013 : Trends in land–atmosphere interactions from CMIP5 simulations . J. Hydrometeor. , 14 , 829 – 849 . Douville , H. , J.-F. Royer , J. Polcher , P. Cox , N. Gedney , D. B
interdecadal Pacific oscillation (IPO), the Pacific decadal oscillation (PDO), and the Atlantic multidecadal oscillation (AMO; Robinson et al. 2002 ; Kunkel et al. 2006 ; Wang et al. 2009 ; Meehl et al. 2012a ; Weaver 2013 ), other studies have highlighted the role of regional-scale hydrologic processes and land–atmosphere interaction (e.g., Pan et al. 2004 ; Liang et al. 2006 ; Misra et al. 2012 ). The most common feature of these studies is investigating the temperature trends for a fixed time
interdecadal Pacific oscillation (IPO), the Pacific decadal oscillation (PDO), and the Atlantic multidecadal oscillation (AMO; Robinson et al. 2002 ; Kunkel et al. 2006 ; Wang et al. 2009 ; Meehl et al. 2012a ; Weaver 2013 ), other studies have highlighted the role of regional-scale hydrologic processes and land–atmosphere interaction (e.g., Pan et al. 2004 ; Liang et al. 2006 ; Misra et al. 2012 ). The most common feature of these studies is investigating the temperature trends for a fixed time
–sea interaction or coupling between the atmosphere and ocean amplifies the errors in the atmospheric feedbacks. By comparing the HSM and the LSM in the quantification of the skill scores over the tropical Pacific (see Fig. 8 ), it is found that the simulated feedbacks in the AMIP experiments are generally better than the historical experiments. Although the representations of the feedbacks in the HSM AMIP runs are very close to those in the LSM AMIP runs, they are very different in their corresponding
–sea interaction or coupling between the atmosphere and ocean amplifies the errors in the atmospheric feedbacks. By comparing the HSM and the LSM in the quantification of the skill scores over the tropical Pacific (see Fig. 8 ), it is found that the simulated feedbacks in the AMIP experiments are generally better than the historical experiments. Although the representations of the feedbacks in the HSM AMIP runs are very close to those in the LSM AMIP runs, they are very different in their corresponding
, coupled with NEMO, medium-resolution IPSL-CM5B-LR IPSL Coupled Model, version 5 MPI-ESM-LR Max Planck Institute (MPI) Earth System Model, low resolution MPI-ESM-P MPI Earth System Model MRI-CGCM3 Meteorological Research Institute Coupled General Circulation Model, version 3 NorESM1-M Norwegian Earth System Model, intermediate resolution REFERENCES Bates , S. C. , 2008 : Coupled ocean–atmosphere interaction and variability in the tropical Atlantic Ocean with and without an annual cycle . J. Climate
, coupled with NEMO, medium-resolution IPSL-CM5B-LR IPSL Coupled Model, version 5 MPI-ESM-LR Max Planck Institute (MPI) Earth System Model, low resolution MPI-ESM-P MPI Earth System Model MRI-CGCM3 Meteorological Research Institute Coupled General Circulation Model, version 3 NorESM1-M Norwegian Earth System Model, intermediate resolution REFERENCES Bates , S. C. , 2008 : Coupled ocean–atmosphere interaction and variability in the tropical Atlantic Ocean with and without an annual cycle . J. Climate
, compared to the CMIP3 models, in simulating the GPLLJ and the seasonal transitions (see Part I), a result largely attributable to the higher spatial resolution of CMIP5 models, but most models struggle to represent observed teleconnections between precipitation and Atlantic SSTs (see section 6 ). Even so, the transport of moisture transport is not the whole story and local dynamic processes (e.g., Veres and Hu 2013 ), as well as land–atmosphere feedbacks ( Ruiz-Barradas and Nigam 2006 ), are
, compared to the CMIP3 models, in simulating the GPLLJ and the seasonal transitions (see Part I), a result largely attributable to the higher spatial resolution of CMIP5 models, but most models struggle to represent observed teleconnections between precipitation and Atlantic SSTs (see section 6 ). Even so, the transport of moisture transport is not the whole story and local dynamic processes (e.g., Veres and Hu 2013 ), as well as land–atmosphere feedbacks ( Ruiz-Barradas and Nigam 2006 ), are
1. Introduction El Niño–Southern Oscillation (ENSO) is a leading mode of interannual climate variability originating in the tropical Pacific. ENSO teleconnections are a reflection of the strong coupling between the tropical ocean and global atmosphere, and SST anomalies in the equatorial Pacific can have substantial remote effects on climate ( Horel and Wallace 1981 ; Ropelewski and Halpert 1987 ; Trenberth et al. 1998 ; Wallace et al. 1998 ; Dai and Wigley 2000 ). In recent decades
1. Introduction El Niño–Southern Oscillation (ENSO) is a leading mode of interannual climate variability originating in the tropical Pacific. ENSO teleconnections are a reflection of the strong coupling between the tropical ocean and global atmosphere, and SST anomalies in the equatorial Pacific can have substantial remote effects on climate ( Horel and Wallace 1981 ; Ropelewski and Halpert 1987 ; Trenberth et al. 1998 ; Wallace et al. 1998 ; Dai and Wigley 2000 ). In recent decades
cyclone activity over the ENP and the Gulf of Mexico (e.g., Magana et al. 1999 ; Maloney and Hartmann 2000a , b ; Higgins and Shi 2001 ; Lorenz and Hartmann 2006 ; Small et al. 2007 ; Wu et al. 2009 ; Serra et al. 2010 ; Martin and Schumacher 2011 ). By modulating the activity of these climate/weather systems on an intraseasonal time scale, the ISV thus provides a foundation for extended-range prediction of the tropical atmosphere. Two leading ISV modes associated with the ENP ITCZ have been
cyclone activity over the ENP and the Gulf of Mexico (e.g., Magana et al. 1999 ; Maloney and Hartmann 2000a , b ; Higgins and Shi 2001 ; Lorenz and Hartmann 2006 ; Small et al. 2007 ; Wu et al. 2009 ; Serra et al. 2010 ; Martin and Schumacher 2011 ). By modulating the activity of these climate/weather systems on an intraseasonal time scale, the ISV thus provides a foundation for extended-range prediction of the tropical atmosphere. Two leading ISV modes associated with the ENP ITCZ have been
006290 . Arora , V. K. , and Coauthors , 2011 : Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases . Geophys. Res. Lett. , 38 , L05805 , doi:10.1029/2010GL046270 . Bao , Q. , and Coauthors , 2013 : The Flexible Global Ocean-Atmosphere-Land system model, spectral version 2: FGOALS-s2 . Adv. Atmos. Sci. , 30 , 561 – 576 . Barnett , T. P. , 1983 : Interaction of the monsoon and Pacific trade wind system at interannual time scales
006290 . Arora , V. K. , and Coauthors , 2011 : Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases . Geophys. Res. Lett. , 38 , L05805 , doi:10.1029/2010GL046270 . Bao , Q. , and Coauthors , 2013 : The Flexible Global Ocean-Atmosphere-Land system model, spectral version 2: FGOALS-s2 . Adv. Atmos. Sci. , 30 , 561 – 576 . Barnett , T. P. , 1983 : Interaction of the monsoon and Pacific trade wind system at interannual time scales
available their model output. For CMIP the U.S. Department of Energy Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. REFERENCES Bao , Q. , and Coauthors , 2013 : The Flexible Global Ocean-Atmosphere-Land System model, spectral version: FGOALS-s2 . Adv. Atmos. Sci. , 30 , 561 – 576 . Bender , M. A. , T. R. Knutson , R. E. Tuleya
available their model output. For CMIP the U.S. Department of Energy Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. REFERENCES Bao , Q. , and Coauthors , 2013 : The Flexible Global Ocean-Atmosphere-Land System model, spectral version: FGOALS-s2 . Adv. Atmos. Sci. , 30 , 561 – 576 . Bender , M. A. , T. R. Knutson , R. E. Tuleya
