A5032407680- Climate variability and models
- Atmospheric and Environmental Gas Dynamics
- Meteorological Phenomena and Simulations
- Climate Change Policy and Economics
- Scientific Computing and Data Management
- Geophysics and Gravity Measurements
- Geological Studies and Exploration
- Climate Change and Health Impacts
- Research Data Management Practices
- COVID-19 impact on air quality
- Climate change impacts on agriculture
- Hydrology and Watershed Management Studies
- Air Quality and Health Impacts
- Geochemistry and Geologic Mapping
Environment and Climate Change Canada
2018-2024
Climate Centre
2024
University of Victoria
2018
Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within Coupled phase 6 (CMIP6). This paper presents a range its outcomes by synthesizing results from participating global coupled Earth system models. We limit our scope to analysis strictly geophysical outcomes: mainly averages spatial patterns change for surface air temperature precipitation. also compare CMIP6...
Abstract. The World Climate Research Programme (WCRP)'s Working Group on Modelling (WGCM) Infrastructure Panel (WIP) was formed in 2014 response to the explosive growth size and complexity of Coupled Model Intercomparison Projects (CMIPs) between CMIP3 (2005–2006) CMIP5 (2011–2012). This article presents WIP recommendations for global data infrastructure needed support CMIP design, future growth, evolution. Developed close coordination with those who build run existing (the Earth System Grid...
Abstract Many nations responded to the corona virus disease‐2019 (COVID‐19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO 2 , greenhouse gases ozone aerosol precursors. We present initial results from a coordinated Intercomparison, CovidMIP, Earth system model simulations which assess impact on climate these reductions. 12 models performed multiple initial‐condition ensembles produce over 300 spanning both condition...
Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the primary future climate projections within Coupled Phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from participating global coupled Earth system models for concentration driven simulations. We limit our scope to analysis strictly geophysical outcomes: mainly averages spatial patterns change surface air temperature precipitation. also compare CMIP6 CMIP5 results,...
Abstract. The World Climate Research Programme (WCRP)'s Working Group on Modeling (WGCM) Infrastructure Panel (WIP) was formed in 2014 response to the explosive growth size and complexity of Coupled Model Intercomparison Projects (CMIPs) between CMIP3 (2005-06) CMIP5 (2011-12). This article presents WIP recommendations for global data infrastructure needed support CMIP design, future evolution. Developed close coordination with those who build run existing (the Earth System Grid Federation),...
A novel runtime empirical bias correction (EBC) has recently been developed and applied to enhance the Canadian Center for Climate Modelling Analysis' (CCCma) global earth system model CanESM, demonstrating significant improvements in future climate projections, particularly under strong change scenarios. The application of EBC CanESM provides enhanced driving data dynamical downscaling through regional models (RCMs). This project aims assess impact improved on two RCMs, namely CanRCM5 CRCM5...
All Earth System Models (ESMs) have climatological biases relative to the observed historical climate. The quality of a model and, more importantly, accuracy its predictions are often associated with magnitude and properties biases. For than decade, new strategies been developed empirically reduce such in components ESMs during their execution. present study considers cyclostationary class empirical runtime bias corrections climate model, referred here as ERBCs. Such ERBCs state independent...
Abstract All Earth System Models (ESMs) have climatological biases relative to the observed historical climate. The quality of a model and, more importantly, accuracy its predictions are often associated with magnitude and properties biases. For than decade, new strategies been developed empirically reduce such in components ESMs during their execution. present study considers cyclostationary class empirical runtime bias corrections climate model, referred here as (ERBCs). Such ERBCs state...