Results 61 to 70 of about 29,437 (300)

Causal networks for climate model evaluation and constrained projections [PDF]

, 2020
Global climate models are central tools for understanding past and future climate change. The assessment of model skill, in turn, can benefit from modern data science approaches. Here we apply causal discovery algorithms to sea level pressure data from a
Eyring, Veronika, Haigh, Joanna D., Nowack, Peer, Runge, Jakob   +3 more
core   +2 more sources

qhgogogo/CMIP6-carbonflux:

, 2021
codes for the CMIP6 cabron fluxes ...
openaire   +1 more source

Insights from CMIP6 for Australia's future climate [PDF]

Earth's Future, 2020
Abstract Outputs from new state‐of‐the‐art climate models under the Coupled Model Inter‐comparison Project phase 6 (CMIP6) promise improvement and enhancement of climate change projections information for Australia. Here we focus on three key aspects of CMIP6: what is new in these models, how the available CMIP6 models evaluate ...
M. R. Grose, S. Narsey, F. P. Delage, A. J. Dowdy, M. Bador, G. Boschat, C. Chung, J. B. Kajtar, S. Rauniyar, M. B. Freund, K. Lyu, H. Rashid, X. Zhang, S. Wales, C. Trenham, N. J. Holbrook, T. Cowan, L. Alexander, J. M. Arblaster, S. Power   +19 more
openaire   +3 more sources

Climate Simulation and Future Scenario Projection for the Zoige Ecological Region by CMIP6 High-Resolution Models

Gaoyuan qixiang
As a unique alpine peat swamp wetland situated on the Tibetan Plateau， climate change in the Zoige ecological region not only impacts its own fragile ecological environment， but also exerts influence over the climate dynamics of the upper reaches of the ...
Qin HU, Dongmei QI, Changyan ZHOU, Xianhong MENG, Yaqiong LÜ, Xianyu YANG   +5 more
doaj   +1 more source

Predicting rainfall response to climate change and uncertainty analysis: Introducing a novel downscaling CMIP6 models technique based on the stacking ensemble machine learning

Journal of Water and Climate Change, 2023
This study proposes a novel downscaling technique based on stacking ensemble machine learning (SEML) to predict rainfall under climate change. The SEML consists of two levels.
Mahdi Valikhan Anaraki, Mojtaba Kadkhodazadeh, Amirreza Morshed-Bozorgdel, Saeed Farzin   +3 more
doaj   +1 more source

Preindustrial Control Simulations With HadGEM3‐GC3.1 for CMIP6 [PDF]

Journal of Advances in Modeling Earth Systems, 2018
AbstractPreindustrial control simulations with the third Hadley Centre Global Environmental Model, run in the Global Coupled configuration 3.1 of the Met Office Unified Model (HadGEM3‐GC3.1) are presented at two resolutions. These are N216ORCA025, which has a horizontal resolution of 60 km in the atmosphere and 0.25° in the ocean, and N96ORCA1, which ...
Matthew Menary, Till Kuhlbrodt, Jeff Ridley, Martin B. Andrews, Oscar Dimdore‐Miles, Julie Deshayes, Rosie Eade, Lesley J. Gray, Sarah Ineson, Emmanuel Mignot, Christopher D. Roberts, Jon Robson, Richard Wood, Prince Xavier   +13 more
openalex   +7 more sources

Historical tropospheric and stratospheric ozone radiative forcing using the CMIP6 database [PDF]

, 2018
We calculate ozone radiative forcing (RF) and stratospheric temperature adjustments for the period 1850-2014 using the newly availableCMIP6 ozone dataset.
Checa-Garcia, Ramiro, Hegglin, Michaela I., Kinnison, Douglas, Plummer, David A., Shine, Keith P.   +4 more
core   +3 more sources

Assessing future changes in flood frequencies under CMIP6 climate projections using SWAT modeling: a case study of Bitlis Creek, Turkey

Journal of Water and Climate Change
Climate change is altering flood risk globally, with local variations prompting the necessity for regional assessments to guide the planning and management of water-related infrastructures.
Emrah Yalcin
doaj   +1 more source

Gridded Emissions for CMIP6 [PDF]

, 2019
Abstract. Spatially distributed anthropogenic and open burning emissions are fundamental data needed by Earth system models. We describe the methods used for generating gridded data sets produced for use by the modelling community, particularly for the Coupled Model Inter-comparison Project Phase 6.
Leyang Feng, Steve J Smith, Caleb Braun, Monica Crippa, Matthew J. Gidden, Rachel Hoesly, Zbigniew Klimont, Margreet van Marle, Maarten van den Berg, Guido R. van der Werf   +9 more
openaire   +1 more source

Climate Change Agricultural Comparative Advantage and the US Trade Balance

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Current science indicates that warming and elevated atmospheric CO2 will have ambiguous results for crop productivity depending on crop type and geographic location, whereas increased heat stress makes livestock and human labor less productive.
Elizabeth A. Fraysse, Thomas W. Hertel, Roman Keeney   +2 more
wiley   +1 more source