North Atlantic climate model bias influence on multiyear predictability

2018 ◽  
Vol 481 ◽  
pp. 171-176 ◽  
Author(s):  
Y. Wu ◽  
T. Park ◽  
W. Park ◽  
M. Latif
Keyword(s):  
North Atlantic ◽  
Climate Model ◽  
Model Bias ◽  
Climate Model Bias ◽  
North Atlantic Climate

Climate model bias correction for nonstationary conditions

2020 ◽  
Vol 47 (3) ◽  
pp. 326-336
Author(s):  
Mohammad Madani ◽  
Vinod Chilkoti ◽  
Tirupati Bolisetti ◽  
Rajesh Seth
Keyword(s):  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Bias Reduction ◽  
Historical Period ◽  
Monthly Precipitation ◽  
Model Bias ◽  
New Methods ◽  
Climate Model Bias

In most of the climate change impact assessment studies, climate model bias is considered to be stationary between the control and scenario periods. Few methods are found in the literature that addresses the issue of nonstationarity in correcting the bias. To overcome the shortcomings reported in these approaches, three new methods of bias correction (NBC_μ, NBC_σ, and NBC_bs) are presented. The methods are improvised versions of previous techniques relying on distribution mapping. The methods are tested using split sample approach over 50-year historical period for nine climate stations in Ontario, using six regional climate models. The average bias reduction improvement by new methods, in mean daily and monthly precipitation, was found to be 73.9%, 74.3%, and 77.4%, respectively, higher than that obtained by the previous methods (eQM 67.7% and CNCDFm_NP 64.1%). Thus, the methods are found to be more effective in accounting for nonstationarity in the model bias.

Atmospheric composition changes in CMIP6 experiments over the North Atlantic region

2020 ◽  
Author(s):  
Paul Griffiths ◽  
James Keeble ◽  
Fiona O'Connor ◽  
Alexander Archibald ◽  
John Pyle ◽  
...  
Keyword(s):  
North Atlantic ◽  
Radiative Forcing ◽  
Climate Model ◽  
Climate System ◽  
Atmospheric Composition ◽  
North Atlantic Region ◽  
Atlantic Region ◽  
The North ◽  
North Atlantic Climate ◽  
The North Atlantic

<div> <div> <div> <p>A grand challenge in the field of chemistry-climate modelling is understanding the connection between anthropogenic emissions, atmospheric composition and the radiative forcing of trace gases and aerosols.</p> <p>The 6th phase of the Coupled Model Intercomparison Project (CMIP6) includes a number of climate model experiments that can be used for this purpose.  AerChemMIP [Collins et al.2017] focuses on calculating the radiative forcing of gases and aerosol particles over the period 1850 to 2100, and comprises several tiers of experiments designed to attribute the effect of changes in emissions. </p> <p>The UK Earth System Model, UKESM-1, is a novel climate model developed for CMIP6  [Sellar et al., 2019] and is a community research tool for studying past and future climate.  It includes a detailed treatment of tropospheric chemistry, interactive BVOC emissions and extensive stratospheric chemistry.</p> <p>The North Atlantic Climate System is an area of current interest [Robson et al., 2020] and is the focus of the UKRI 'ACSIS' project.  ACSIS brings together scientists from a range of different specialisms to understand complex changes in the North Atlantic climate system.    By understanding how these changes relate to external drivers of climate, such as human activity, or natural variability, ACSIS aims to improve our capability to detect, explain and predict changes in the North Atlantic climate system.</p> <p>We present an analysis of the evolution of atmospheric composition over the period 1950-2015. The work is based on a recent global multi-model evaluation of tropospheric ozone for CMIP6 [Griffiths et al., 2020] , but focuses on changes over the North Atlantic region in UKESM-1.  We draw on CMIP and AerChemMIP simulations to provide an initial survey of the response of this region to changing emissions , focusing on atmospheric composition and attempting attribution from a series of targeted experiments involving perturbed emissions .</p> </div> </div> </div>

Plausible effect of climate model bias on abrupt climate change simulations in Atlantic sector

2011 ◽  
Vol 58 (17-18) ◽  
pp. 1904-1913 ◽  
Author(s):  
Xiuquan Wan ◽  
Ping Chang ◽  
Charles S. Jackson ◽  
Link Ji ◽  
Mingkui Li
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Abrupt Climate Change ◽  
Model Bias ◽  
Atlantic Sector ◽  
Climate Model Bias

scholarly journals Adjusting climate model bias for agricultural impact assessment: How to cut the mustard

2019 ◽  
Vol 13 ◽  
pp. 65-69 ◽  
Author(s):  
S. Galmarini ◽  
A.J. Cannon ◽  
A. Ceglar ◽  
O.B. Christensen ◽  
N. de Noblet-Ducoudré ◽  
...  
Keyword(s):  
Impact Assessment ◽  
Climate Model ◽  
Model Bias ◽  
Climate Model Bias ◽  
Agricultural Impact

scholarly journals Predicting a Decadal Shift in North Atlantic Climate Variability Using the GFDL Forecast System

2014 ◽  
Vol 27 (17) ◽  
pp. 6472-6496 ◽  
Author(s):  
Rym Msadek ◽  
T. L. Delworth ◽  
A. Rosati ◽  
W. Anderson ◽  
G. Vecchi ◽  
...  
Keyword(s):  
North Atlantic ◽  
Climate Model ◽  
Coupled Model ◽  
Climate Impacts ◽  
Meridional Overturning Circulation ◽  
The Arctic ◽  
North Atlantic Current ◽  
Forecast System ◽  
Sea Ice Concentration ◽  
North Atlantic Climate

Abstract Decadal prediction experiments were conducted as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5) using the GFDL Climate Model, version 2.1 (CM2.1) forecast system. The abrupt warming of the North Atlantic Subpolar Gyre (SPG) that was observed in the mid-1990s is considered as a case study to evaluate forecast capabilities and better understand the reasons for the observed changes. Initializing the CM2.1 coupled system produces high skill in retrospectively predicting the mid-1990s shift, which is not captured by the uninitialized forecasts. All the hindcasts initialized in the early 1990s show a warming of the SPG; however, only the ensemble-mean hindcasts initialized in 1995 and 1996 are able to reproduce the observed abrupt warming and the associated decrease and contraction of the SPG. Examination of the physical mechanisms responsible for the successful retrospective predictions indicates that initializing the ocean is key to predicting the mid-1990s warming. The successful initialized forecasts show an increased Atlantic meridional overturning circulation and North Atlantic Current transport, which drive an increased advection of warm saline subtropical waters northward, leading to a westward shift of the subpolar front and, subsequently, a warming and spindown of the SPG. Significant seasonal climate impacts are predicted as the SPG warms, including a reduced sea ice concentration over the Arctic, an enhanced warming over the central United States during summer and fall, and a northward shift of the mean ITCZ. These climate anomalies are similar to those observed during a warm phase of the Atlantic multidecadal oscillation, which is encouraging for future predictions of North Atlantic climate.

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