Evaluation of Northern Hemisphere natural climate variability in multiple temperature reconstructions and global climate model simulations

2003 ◽  
Vol 37 (1-2) ◽  
pp. 19-32 ◽  
Author(s):  
J.L. Bell ◽  
L.C. Sloan ◽  
J. Revenaugh ◽  
P.B. Duffy
Keyword(s):  
Climate Variability ◽  
Northern Hemisphere ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Natural Climate Variability ◽  
Model Simulations ◽  
Temperature Reconstructions ◽  
Climate Model Simulations ◽  
Natural Climate

scholarly journals Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations

2014 ◽  
Vol 119 (13) ◽  
pp. 8169-8188 ◽  
Author(s):  
Paul Glantz ◽  
Adam Bourassa ◽  
Andreas Herber ◽  
Trond Iversen ◽  
Johannes Karlsson ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
The Arctic ◽  
Model Simulations ◽  
Climate Model Simulations

scholarly journals Elevation-dependent warming in global climate model simulations at high spatial resolution

2018 ◽  
Vol 52 (5-6) ◽  
pp. 2685-2702 ◽  
Author(s):  
Elisa Palazzi ◽  
Luca Mortarini ◽  
Silvia Terzago ◽  
Jost von Hardenberg
Keyword(s):  
Spatial Resolution ◽  
Climate Model ◽  
High Spatial Resolution ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Simulations ◽  
Climate Model Simulations

scholarly journals A vertically resolved, global, gap-free ozone database for assessing or constraining global climate model simulations

2012 ◽  
Vol 5 (2) ◽  
pp. 999-1033 ◽  
Author(s):  
G. E. Bodeker ◽  
B. Hassler ◽  
P. J. Young ◽  
R. W. Portmann
Keyword(s):  
Regression Model ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Initial Guess ◽  
Model Fit ◽  
Total Column Ozone ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Vertical Level

Abstract. High vertical resolution ozone measurements from eight different satellite-based instruments have been merged with data from the global ozonesonde network to calculate monthly mean ozone values in 5° latitude zones. These "Tier 0" ozone number densities and ozone mixing ratios are provided on 70 altitude levels (1 to 70 km) and on 70 pressure levels spaced ~1 km apart (878.4 hPa to 0.046 hPa). The Tier 0 data are sparse and do not cover the entire globe or altitude range. To provide a gap-free database, a least squares regression model is fitted to the Tier 0 data and then evaluated globally. The regression model fit coefficients are expanded in Legendre polynomials to account for latitudinal structure, and in Fourier series to account for seasonality. Regression model fit coefficient patterns, which are two dimensional fields indexed by latitude and month of the year, from the N-th vertical level serve as an initial guess for the fit at the N+1th vertical level. The initial guess field for the first fit level (20 km/58.2 hPa) was derived by applying the regression model to total column ozone fields. Perturbations away from the initial guess are captured through the Legendre and Fourier expansions. By applying a single fit at each level, and using the approach of allowing the regression fits to change only slightly from one level to the next, the regression is less sensitive to measurement anomalies at individual stations or to individual satellite-based instruments. Particular attention is paid to ensuring that the low ozone abundances in the polar regions are captured. By summing different combinations of contributions from different regression model basis functions, four different "Tier 1" databases have been compiled for different intended uses. This database is suitable for assessing ozone fields from chemistry-climate model simulations or for providing the ozone boundary conditions for global climate model simulations that do not treat stratospheric chemistry interactively.

scholarly journals Uncertainty of Hydrological Model Components in Climate Change Studies over Two Nordic Quebec Catchments

2018 ◽  
Vol 19 (1) ◽  
pp. 27-46 ◽  
Author(s):  
Magali Troin ◽  
Richard Arsenault ◽  
Jean-Luc Martel ◽  
François Brissette
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Hydrological Model ◽  
Climate Model ◽  
Global Climate Model ◽  
Substantial Contribution ◽  
Climate Change Signal ◽  
Natural Climate Variability ◽  
Degree Day ◽  
Natural Climate

Abstract Projected climate change effects on hydrology are investigated for the 2041–60 horizon under the A2 emission scenarios using a multimodel approach over two snowmelt-dominated catchments in Canada. An ensemble of 105 members was obtained by combining seven snow models (SMs), five potential evapotranspiration (PET) methods, and three hydrological model (HM) structures. The study was performed using high-resolution simulations from the Canadian Regional Climate Model (CRCM–15 km) driven by two members of the third-generation Canadian Coupled Global Climate Model (CGCM3). This study aims to compare various combinations of SM–PET–HM in terms of their ability to simulate streamflows under the current climate and to evaluate how they affect the assessment of the climate change–induced hydrological impacts at the catchment scale. The variability of streamflow response caused by the use of different SMs (degree-day versus degree-day/energy balance), PET methods (temperature-based versus radiation-based methods), and HM structures is evaluated, as well as the uncertainty due to the natural climate variability (CRCM intermember variability). The hydroclimatic simulations cover 1961–90 in the present period and 2041–60 in the future period. The ensemble spread of the climate change signal on streamflow is large and varies with catchments. Using the variance decomposition on three hydrologic indicators, the HM structure was found to make the most substantial contribution to uncertainty, followed by the choice of the PET methods or natural climate variability, depending on the hydrologic indicator and the catchment. Snow models played a minor, almost negligible role in the assessment of the climate change impacts on streamflow for the study catchments.

Assessment of the CMIP5 global climate model simulations of the western tropical Pacific climate system and comparison to CMIP3

2014 ◽  
Vol 34 (12) ◽  
pp. 3382-3399 ◽  
Author(s):  
Michael R. Grose ◽  
Jaclyn N. Brown ◽  
Sugata Narsey ◽  
Josephine R. Brown ◽  
Bradley F. Murphy ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Tropical Pacific ◽  
Climate System ◽  
Model Simulations ◽  
Western Tropical Pacific ◽  
Climate Model Simulations
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