Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models. Part I: Convective Signals
By Jialin Lin, G. Kiladis, B. Mapes, K. Weickmann, K. Sperber, Wuyin Lin, M. Wheeler, S. Schubert, A. D. Del Genio, Leo Donner and 6 more. 2006
796 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/0139579b5e2a7e2fd496e976fa85a7f2f1cbf457
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Citations in the corpus
- MJO prediction in the NCEP Climate Forecast System version 2 (2014, methodology): “…difference is that we only use the forecast from the previous 90 initial days to define the interannual anomaly, unlike the definition used in Lin et al. (2008) and Rashid et al. (2010) who used a mixture of observations before the initial time and forecast before the target day because of…”
- Predictability of the Madden–Julian Oscillation in the Intraseasonal Variability Hindcast Experiment (ISVHE)* (2014, background): “Pastmultimodel assessments ofmodel performance for theMJO (e.g., Slingo et al. 1996; Lin et al. 2006; Kim et al. 2009; Zhang et al. 2013) have indicated that inadequacies in cumulus parameterization schemes (e.g., Maloney and Hartmann 2001; Liu et al. 2005; Vitart et al. 2007), coarse vertical…”
- Tropospheric water vapor, convection, and climate (2010, background): “Section 7 summarizes where the field stands and notes some future directions that seem promising.”
- Role of the Boundary Layer Moisture Asymmetry in Causing the Eastward Propagation of the Madden-Julian Oscillation* (2012, background): “It is found that heating-induced free-atmospheric wave dynamics account for 75%–90% of the total PBL convergence, while the warm SST anomaly induced by air–sea interaction contributes 10%–25% of the total PBL convergence.”
- A Comparison of Dynamical and Statistical Predictions of Weekly Tropical Cyclone Activity in the Southern Hemisphere (2010, background): “…intraseasonal prediction of TCs is likely to be largely dependent on the success of the model to predict MJO events and their impact on model TCs. Slingo et al. (1996) and Lin et al. (2006) have shown that general circulation models (GCMs) often have difficulty to adequately represent MJO events.”
- Observational Evidence for Relationships between the Degree of Aggregation of Deep Convection, Water Vapor, Surface Fluxes, and Radiation (2012, background): “…scales: at the 50–300-km scale (grid-box sizes), the mesoscale organization of convection is not represented in current convection parameterizations and the largescale (explicitly resolved) organization of convection, such as the MJO, is still poorly simulated in many GCMs (Lin et al. 2006).”