[HTML][HTML] Hybrid forecasting: blending climate predictions with AI models

LJ Slater, L Arnal, MA Boucher… - Hydrology and earth …, 2023 - hess.copernicus.org
Hybrid hydroclimatic forecasting systems employ data-driven (statistical or machine
learning) methods to harness and integrate a broad variety of predictions from dynamical …

Future global climate: scenario-based projections and near-term information

JY Lee, J Marotzke, G Bala, L Cao, S Corti… - Climate change 2021 …, 2021 - cambridge.org
This chapter assesses simulations of future global climate change, spanning time horizons
from the near term (2021–2040), mid-term (2041–2060), and long term (2081–2100) out to …

[HTML][HTML] Global carbon budget 2023

P Friedlingstein, M O'sullivan, MW Jones… - Earth System …, 2023 - essd.copernicus.org
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their
redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate …

Framing, Context, and Methods (Chapter 1)

D Chen, M Rojas, BH Samset, K Cobb… - 2021 - pure.iiasa.ac.at
Working Group I (WGI) of the Intergovernmental Panel on Climate Change (IPCC) assesses
the current evidence on the physical science of climate change, evaluating knowledge …

The Meteorological Research Institute Earth System Model version 2.0, MRI-ESM2. 0: Description and basic evaluation of the physical component

S Yukimoto, H Kawai, T Koshiro, N Oshima… - Journal of the …, 2019 - jstage.jst.go.jp
Abstract The new Meteorological Research Institute Earth System Model version 2.0 (MRI-
ESM2. 0) has been developed based on previous models, MRI-CGCM3 and MRI-ESM1 …

[HTML][HTML] Hybrid forecasting: using statistics and machine learning to integrate predictions from dynamical models

L Slater, L Arnal, MA Boucher… - Hydrology and Earth …, 2022 - hess.copernicus.org
Hybrid hydroclimatic forecasting systems employ data-driven (statistical or machine
learning) methods to harness and integrate a broad variety of predictions from dynamical …

[HTML][HTML] The Polar Amplification Model Intercomparison Project (PAMIP) contribution to CMIP6: investigating the causes and consequences of polar amplification

DM Smith, JA Screen, C Deser, J Cohen… - Geoscientific Model …, 2019 - gmd.copernicus.org
Polar amplification–the phenomenon where external radiative forcing produces a larger
change in surface temperature at high latitudes than the global average–is a key aspect of …

Assessment of precipitation extremes in India during the 21st century under SSP1-1.9 mitigation scenarios of CMIP6 GCMs

V Gupta, V Singh, MK Jain - Journal of Hydrology, 2020 - Elsevier
This study used a 30-year observed (1985–2014) precipitation, and the latest Coupled
Model Intercomparison Phase 6 (CMIP6) Shared Socioeconomic Pathways (SSPs) based …

[HTML][HTML] NorCPM1 and its contribution to CMIP6 DCPP

I Bethke, Y Wang, F Counillon… - Geoscientific Model …, 2021 - gmd.copernicus.org
Abstract The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research
tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It …

Improved decadal predictions of North Atlantic subpolar gyre SST in CMIP6

LF Borchert, MB Menary, D Swingedouw… - Geophysical …, 2021 - Wiley Online Library
Due to its wide‐ranging impacts, predicting decadal variations of sea surface temperature
(SST) in the subpolar North Atlantic remains a key goal of climate science. Here, we …