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, 23 , 1815 – 1836 , https://doi.org/10.1175/2009JCLI3188.1 . 10.1175/2009JCLI3188.1 Wang , H. L. , S. Schubert , R. Koster , Y. G. Ham , and M. Suarez , 2014 : On the role of SST forcing in the 2011 and 2012 extreme U.S. Heat and drought: A study in contrasts . J. Hydrometeor. , 15 , 1255 – 1273 , https://doi.org/10.1175/JHM-D-13-069.1 . 10.1175/JHM-D-13-069.1 Yanai , M. , S. Esbensen , and J. H. Chu , 1973 : Determination of bulk properties of tropical cloud clusters
, 23 , 1815 – 1836 , https://doi.org/10.1175/2009JCLI3188.1 . 10.1175/2009JCLI3188.1 Wang , H. L. , S. Schubert , R. Koster , Y. G. Ham , and M. Suarez , 2014 : On the role of SST forcing in the 2011 and 2012 extreme U.S. Heat and drought: A study in contrasts . J. Hydrometeor. , 15 , 1255 – 1273 , https://doi.org/10.1175/JHM-D-13-069.1 . 10.1175/JHM-D-13-069.1 Yanai , M. , S. Esbensen , and J. H. Chu , 1973 : Determination of bulk properties of tropical cloud clusters
interference of dense plant canopy and limitations in the depth of detection within the soil column ( Entekhabi et al. 2014 ), as well as sensor limitations (especially before the use of L-band radiometers). Likewise, the fidelity of LSM simulations may be undermined by model errors (e.g., model structure error, model parameter error), forcing data uncertainties and limited usage of ground-based observations for model calibration and validation ( Xia et al. 2014 ). Thus, efforts that aim to improve large
interference of dense plant canopy and limitations in the depth of detection within the soil column ( Entekhabi et al. 2014 ), as well as sensor limitations (especially before the use of L-band radiometers). Likewise, the fidelity of LSM simulations may be undermined by model errors (e.g., model structure error, model parameter error), forcing data uncertainties and limited usage of ground-based observations for model calibration and validation ( Xia et al. 2014 ). Thus, efforts that aim to improve large
. 2016 ; Dirmeyer and Halder 2016 , 2017 ; Dirmeyer et al. 2018b ; Halder et al. 2018 ). Model fidelity in representing coupled land–atmosphere processes is also necessary, including proper simulation of variability, covariability, sensitivity, and critical transitions in the chain of processes linking land surface states to surface fluxes, near-surface atmospheric states, boundary layer characteristics, cloud formation, and precipitation ( Dirmeyer and Halder 2017 ; Santanello et al. 2018
. 2016 ; Dirmeyer and Halder 2016 , 2017 ; Dirmeyer et al. 2018b ; Halder et al. 2018 ). Model fidelity in representing coupled land–atmosphere processes is also necessary, including proper simulation of variability, covariability, sensitivity, and critical transitions in the chain of processes linking land surface states to surface fluxes, near-surface atmospheric states, boundary layer characteristics, cloud formation, and precipitation ( Dirmeyer and Halder 2017 ; Santanello et al. 2018
