human | Q5 |
P496 | ORCID iD | 0000-0002-6656-4437 |
P106 | occupation | researcher | Q1650915 |
Q57726670 | A PDRMIP Multimodel Study on the Impacts of Regional Aerosol Forcings on Global and Regional Precipitation |
Q58061130 | Analysis of present day and future OH and methane lifetime in the ACCMIP simulations |
Q114112828 | Arctic Amplification Response to Individual Climate Drivers |
Q58384479 | Attribution of historical ozone forcing to anthropogenic emissions |
Q57914879 | CMIP5 historical simulations (1850-2012) with GISS ModelE2 |
Q63951581 | Comparison of Effective Radiative Forcing Calculations Using Multiple Methods, Drivers, and Models |
Q57914876 | Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive |
Q114106910 | Coupling interactive fire with atmospheric composition and climate in the UK Earth System Model |
Q63488930 | Drivers of Precipitation Change: An Energetic Understanding |
Q57726676 | Dynamical response of Mediterranean precipitation to greenhouse gases and aerosols |
Q89559918 | Efficacy of Climate Forcings in PDRMIP Models |
Q34448747 | El Niño and health risks from landscape fire emissions in Southeast Asia |
Q111983720 | Extreme wet and dry conditions affected differently by greenhouse gases and aerosols |
Q57402947 | Fast and slow precipitation responses to individual climate forcers: A PDRMIP multimodel study |
Q63488923 | Increased water vapour lifetime due to global warming |
Q118118321 | Local and remote climate impacts of future African aerosol emissions |
Q58074777 | Mediterranean Precipitation Response to Greenhouse Gases and Aerosols |
Q36004990 | Ozone and carbon monoxide budgets over the Eastern Mediterranean. |
Q57726699 | PDRMIP: A Precipitation Driver and Response Model Intercomparison Project—Protocol and Preliminary Results |
Q57589174 | Pre-industrial to end 21st century projections of tropospheric ozone from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) |
Q111692714 | Predicting global patterns of long-term climate change from short-term simulations using machine learning |
Q58061125 | Preindustrial to present-day changes in tropospheric hydroxyl radical and methane lifetime from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) |
Q58074758 | Quantifying the Importance of Rapid Adjustments for Global Precipitation Changes |
Q57564840 | Radiative forcing in the ACCMIP historical and future climate simulations |
Q56837394 | Rapid Adjustments Cause Weak Surface Temperature Response to Increased Black Carbon Concentrations |
Q58079386 | Regional and global climate response to anthropogenic SO 2 emissions from China in three climate models |
Q57879282 | Regional and global temperature response to anthropogenic SO2 emissions from China in three climate models |
Q111983636 | Scientific data from precipitation driver response model intercomparison project |
Q54946925 | Sensible heat has significantly affected the global hydrological cycle over the historical period. |
Q111692746 | Supplementary material to "Regional and global climate response to anthropogenic SO2 emissions from China in three climate models" |
Q106622130 | Supplementary material to "The Global Methane Budget 2000–2017" |
Q58061134 | The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): overview and description of models, simulations and climate diagnostics |
Q106622086 | The Global Methane Budget 2000–2017 |
Q106622144 | The Global Methane Budget 2000–2017 |
Q111983652 | The effect of rapid adjustments to halocarbons and N2O on radiative forcing |
Q57160507 | The global methane budget 2000–2012 |
Q112782730 | The importance of antecedent vegetation and drought conditions as global drivers of burnt area |
Q57017467 | Three decades of global methane sources and sinks |
Q56286589 | Tropospheric ozone changes, radiative forcing and attribution to emissions in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) |
Q58074761 | Understanding Rapid Adjustments to Diverse Forcing Agents |
Q58062086 | Using machine learning to build temperature-based ozone parameterizations for climate sensitivity simulations |
Q57160488 | Variability and quasi-decadal changes in the methane budget over the period 2000–2012 |
Q111983749 | Water vapour adjustments and responses differ between climate drivers |