scholarly journals Seasonal prediction of high-resolution temperature at 2-m height over Mongolia during boreal winter using both coupled general circulation model and artificial neural network

2018 ◽  
Vol 38 (14) ◽  
pp. 5418-5429 ◽  
Author(s):  
Gerelchuluun Bayasgalan ◽  
Joong-Bae Ahn
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
High Resolution ◽  
General Circulation Model ◽  
General Circulation ◽  
Circulation Model ◽  
Seasonal Prediction ◽  
Boreal Winter ◽  
Coupled General Circulation Model ◽  
Artificial Neural

scholarly journals Effects of Tropical Cyclones on Ocean Heat Transport in a High-Resolution Coupled General Circulation Model

2011 ◽  
Vol 24 (16) ◽  
pp. 4368-4384 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Alessio Bellucci ◽  
Antonella Sanna ◽  
Pier Giuseppe Fogli ◽  
...  
Keyword(s):  
Twentieth Century ◽  
High Resolution ◽  
Heat Transport ◽  
Tropical Cyclones ◽  
General Circulation Model ◽  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Ocean Heat Transport ◽  
Coupled General Circulation Model

Abstract In this paper the interplay between tropical cyclones (TCs) and the Northern Hemispheric ocean heat transport (OHT) is investigated. In particular, results from a numerical simulation of the twentieth-century and twenty-first-century climates, following the Intergovernmental Panel on Climate Change (IPCC) twentieth-century run (20C3M) and A1B scenario protocols, respectively, have been analyzed. The numerical simulations have been performed using a state-of-the-art global atmosphere–ocean–sea ice coupled general circulation model (CGCM) with relatively high-resolution (T159) in the atmosphere. The CGCM skill in reproducing a realistic TC climatology has been assessed by comparing the model results from the simulation of the twentieth century with available observations. The model simulates tropical cyclone–like vortices with many features similar to the observed TCs. Specifically, the simulated TCs exhibit realistic structure, geographical distribution, and interannual variability, indicating that the model is able to capture the basic mechanisms linking the TC activity with the large-scale circulation. The cooling of the surface ocean observed in correspondence of the TCs is well simulated by the model. TC activity is shown to significantly increase the poleward OHT out of the tropics and decrease the poleward OHT from the deep tropics on short time scales. This effect, investigated by looking at the 100 most intense Northern Hemisphere TCs, is strongly correlated with the TC-induced momentum flux at the ocean surface, where the winds associated with the TCs significantly weaken (strengthen) the trade winds in the 5°–18°N (18°–30°N) latitude belt. However, the induced perturbation does not impact the yearly averaged OHT. The frequency and intensity of the TCs appear to be substantially stationary through the entire 1950–2069 simulated period, as does the effect of the TCs on the OHT.

scholarly journals Projection of Temperature and Precipitation using Multiple Linear Regression and Artificial Neural Network as a Downscaling Methodology for Upper Bhima Basin

2020 ◽  
Vol 9 (3) ◽  
pp. 1-8
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
General Circulation ◽  
Circulation Model ◽  
Small Scale ◽  
Climate Parameters ◽  
Temperature And Precipitation ◽  
Artificial Neural

Study of Climate change effect on water resources is very important for its effective management. Projection of temperature and precipitation can be performed by using General Circulation Model (GCM) outputs. GCM can make the projections of climate parameters with different emission scenarios at coarser scale. However hydrological models require climate parameters at smaller scale Downscaling technique is used for obtaining small scale climate variables from large scale variables of GCM outputs. In this study downscaling has been carried out by using Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) techniques. Performance of MLR and ANN models has been evaluated considering Coefficient of determination value (R2 ). It has been observed that ANN performs better against MLR Model, showed the results that rainfall distribution pattern is varied, in monsoon season rainfall decreases while it increases in post monsoon period. Due to its good evaluation performance such techniques can be applicable for downscaling purpose.

scholarly journals MIROC4h^|^mdash;A New High-Resolution Atmosphere-Ocean Coupled General Circulation Model

2012 ◽  
Vol 90 (3) ◽  
pp. 325-359 ◽  
Author(s):  
Takashi T. SAKAMOTO ◽  
Yoshiki KOMURO ◽  
Teruyuki NISHIMURA ◽  
Masayoshi ISHII ◽  
Hiroaki TATEBE ◽  
...  
Keyword(s):  
High Resolution ◽  
General Circulation Model ◽  
General Circulation ◽  
Circulation Model ◽  
Coupled General Circulation Model

scholarly journals Effect of AMOC collapse on ENSO in a high resolution general circulation model

2017 ◽  
Vol 50 (7-8) ◽  
pp. 2537-2552 ◽  
Author(s):  
Mark S. Williamson ◽  
Mat Collins ◽  
Sybren S. Drijfhout ◽  
Ron Kahana ◽  
Jennifer V. Mecking ◽  
...  
Keyword(s):  
High Resolution ◽  
General Circulation Model ◽  
General Circulation ◽  
Circulation Model
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