A Fully Coupled Model of a Nonlinear Thin Plate

2001 ◽  
pp. 9-22
Author(s):  
Nikolai D. Botkin ◽  
Karl-Heinz Hoffmann
2020 ◽  
Vol 579 ◽  
pp. 411894
Author(s):  
Valerio Apicella ◽  
Carmine Stefano Clemente ◽  
Daniele Davino ◽  
Damiano Leone ◽  
Ciro Visone

2021 ◽  
Author(s):  
Anupam Gupta ◽  
Sudhakar Tallavajhula ◽  
Sachin Mathakari

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 808 ◽  
Author(s):  
Fernando De Sales ◽  
David E. Rother

The study introduces a new atmosphere-land-aquifer coupled model and evaluates terrestrial water storage (TWS) simulations for Southern California between 2007 and 2016. It also examines the relationship between precipitation, groundwater, and soil moisture anomalies for the two primary aquifer systems in the study area, namely the Coastal Basin and the Basin and Range aquifers. Two model designs are introduced, a partially-coupled model forced by reanalysis atmospheric data, and a fully-coupled model, in which the atmospheric conditions were simulated. Both models simulate the temporal variability of TWS anomaly in the study area well (R2 ≥ 0.87, P < 0.01). In general, the partially-coupled model outperformed the fully-coupled model as the latter overestimated precipitation, which compromised soil and aquifer recharge and discharge. Simulations also showed that the drought experienced in the area between 2012 and 2016 caused a decline in TWS, evapotranspiration, and runoff of approximately 24%, 65%, and 11%, and 20%, 72% and 8% over the two aquifer systems, respectively. Results indicate that the models first introduced in this study can be a useful tool to further our understanding of terrestrial water storage variability at regional scales.


2020 ◽  
Author(s):  
Baijun Tian

&lt;p&gt;The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.&lt;/p&gt;


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