scholarly journals Attribution of Extreme Precipitation with Updated Observations and CMIP6 Simulations

2021 ◽  
Vol 34 (3) ◽  
pp. 871-881
Author(s):  
Siyan Dong ◽  
Ying Sun ◽  
Chao Li ◽  
Xuebin Zhang ◽  
Seung-Ki Min ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Coupled Model ◽  
Historical Period ◽  
Anthropogenic Aerosols ◽  
Detection And Attribution ◽  
Attribution Analysis ◽  
Group I ◽  
Annual Total ◽  
Intercomparison Project ◽  
Extreme Indices

AbstractWhile the IPCC Fifth Assessment Working Group I report assessed observed changes in extreme precipitation on the basis of both absolute and percentile-based extreme indices, human influence on extreme precipitation has rarely been evaluated on the basis of percentile-based extreme indices. Here we conduct a formal detection and attribution analysis on changes in four percentile-based precipitation extreme indices. The indices include annual precipitation totals from days with precipitation exceeding the 99th and 95th percentiles of wet-day precipitation in 1961–90 (R99p and R95p) and their contributions to annual total precipitation (R99pTOT and R95pTOT). We compare these indices from a set of newly compiled observations during 1951–2014 with simulations from models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). We show that most land areas with observations experienced increases in these extreme indices with global warming during the historical period 1951–2014. The new CMIP6 models are able to reproduce these overall increases, although with considerable over- or underestimations in some regions. An optimal fingerprinting analysis reveals detectable anthropogenic signals in the observations of these indices averaged over the globe and over most continents. Furthermore, signals of greenhouse gases can be separately detected, taking other forcing into account, over the globe and over Asia in these indices except for R95p. In contrast, signals of anthropogenic aerosols and natural forcings cannot be detected in any of these indices at either global or continental scales.

scholarly journals AerChemMIP: quantifying the effects of chemistry and aerosols in CMIP6

2017 ◽  
Vol 10 (2) ◽  
pp. 585-607 ◽  
Author(s):  
William J. Collins ◽  
Jean-François Lamarque ◽  
Michael Schulz ◽  
Olivier Boucher ◽  
Veronika Eyring ◽  
...  
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Climate Impacts ◽  
Atmospheric Composition ◽  
Historical Period ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract. The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and their climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. Specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.

scholarly journals The 2011 Great Flood in Thailand: Climate Diagnostics and Implications from Climate Change

2015 ◽  
Vol 29 (1) ◽  
pp. 367-379 ◽  
Author(s):  
Parichart Promchote ◽  
S.-Y. Simon Wang ◽  
Paul G. Johnson
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Coupled Model ◽  
Climate Forcing ◽  
High Soil Moisture ◽  
Attribution Analysis ◽  
Flooding Event ◽  
Intercomparison Project ◽  
Chao Phraya River ◽  
Cyclone Frequency

Abstract Severe flooding occurred in Thailand during the 2011 summer season, which resulted in more than 800 deaths and affected 13.6 million people. The unprecedented nature of this flood in the Chao Phraya River basin (CPRB) was examined and compared with historical flood years. Climate diagnostics were conducted to understand the meteorological conditions and climate forcing that led to the magnitude and duration of this flood. Neither the monsoon rainfall nor the tropical cyclone frequency anomalies alone was sufficient to cause the 2011 flooding event. Instead, a series of abnormal conditions collectively contributed to the intensity of the 2011 flood: anomalously high rainfall in the premonsoon season, especially during March; record-high soil moisture content throughout the year; elevated sea level height in the Gulf of Thailand, which constrained drainage; and other water management factors. In the context of climate change, the substantially increased premonsoon rainfall in CPRB after 1980 and the continual sea level rise in the river outlet have both played a role. The rainfall increase is associated with a strengthening of the premonsoon northeasterly winds that come from East Asia. Attribution analysis using phase 5 of the Coupled Model Intercomparison Project historical experiments pointed to anthropogenic greenhouse gases as the main external climate forcing leading to the rainfall increase. Together, these findings suggest increasing odds for potential flooding of similar intensity to that of the 2011 flood.

scholarly journals The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6

2016 ◽  
Vol 9 (10) ◽  
pp. 3685-3697 ◽  
Author(s):  
Nathan P. Gillett ◽  
Hideo Shiogama ◽  
Bernd Funke ◽  
Gabriele Hegerl ◽  
Reto Knutti ◽  
...  
Keyword(s):  
Climate Change ◽  
Experimental Design ◽  
Atmospheric Chemistry ◽  
Stratospheric Ozone ◽  
Future Climate ◽  
Future Climate Change ◽  
Historical Period ◽  
Model Intercomparison ◽  
Detection And Attribution ◽  
Intercomparison Project

Abstract. Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of future climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.

scholarly journals Compiled records of carbon isotopes in atmospheric CO<sub>2</sub> for historical simulations in CMIP6

2017 ◽  
Author(s):  
Heather Graven ◽  
Colin E. Allison ◽  
David M. Etheridge ◽  
Samuel Hammer ◽  
Ralph F. Keeling ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Carbon Isotopes ◽  
Coupled Model ◽  
Atmospheric Co2 ◽  
Historical Period ◽  
Terrestrial Biosphere ◽  
Climate Simulations ◽  
Intercomparison Project ◽  
Natural Carbon ◽  
Carbon Cycle Modelling

Abstract. The isotopic composition of carbon (Δ14C and δ13C) in atmospheric CO2 and in oceanic and terrestrial carbon reservoirs is influenced by anthropogenic emissions and by natural carbon exchanges, which can respond to and drive changes in climate. Simulations of 14C and 13C in the ocean and terrestrial components of Earth System Models (ESMs) present opportunities for model evaluation and for investigation of carbon cycling, including anthropogenic CO2 emissions and uptake. The use of carbon isotopes in novel evaluation of the ESMs' component ocean and terrestrial biosphere models and in new analyses of historical changes may improve predictions of future changes in the carbon cycle and climate system. We compile existing data to produce records of Δ14C and δ13C in atmospheric CO2 for the historical period 1850–2015. The primary motivation for this compilation is to provide the atmospheric boundary condition for historical simulations in the Coupled Model Intercomparison Project 6 (CMIP6) for models simulating carbon isotopes in their ocean or terrestrial biosphere models. The data may also be useful for other carbon cycle modelling activities.

scholarly journals AerChemMIP: Quantifying the effects of chemistry and aerosols in CMIP6

2016 ◽  
Author(s):  
William J. Collins ◽  
Jean-François Lamarque ◽  
Michael Schulz ◽  
Olivier Boucher ◽  
Veronika Eyring ◽  
...  
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Climate Impacts ◽  
Anthropogenic Emissions ◽  
Historical Period ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract. The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically-reactive gases. These are specifically near-term climate forcers (NTCFs: tropospheric ozone and aerosols, and their precursors), methane, nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions: 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How will future policies (on climate, air quality and land use) affect these species and their climate impacts? 3. Can the uncertainties associated with anthropogenic emissions be quantified? 4. Can climate feedbacks occurring through changes in natural emissions be quantified? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and chemistry to be quantified. Specific diagnostics are requested as part of the CMIP6 data request to evaluate the performance of the models, and to understand any differences in behaviour between them.

Simulation of Northeast U.S. Extreme Precipitation and Its Associated Circulation by CMIP5 Models

2020 ◽  
Vol 33 (22) ◽  
pp. 9817-9834
Author(s):  
Laurie Agel ◽  
Mathew Barlow ◽  
Joseph Polonia ◽  
David Coe
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Coupled Model ◽  
Precipitation Intensity ◽  
Cmip5 Models ◽  
Seasonal Cycles ◽  
Precipitation Frequency ◽  
Circulation Patterns ◽  
Intercomparison Project ◽  
Approximate Magnitude

AbstractHistorical simulations from 14 models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to reproduce observed precipitation in the northeastern United States and its associated circulation, with particular emphasis on extreme (top 1%) precipitation. The models are compared to observations in terms of the spatial variations of extreme precipitation, seasonal cycles of precipitation and extreme precipitation frequency and intensity, and extreme precipitation circulation regimes. The circulation regimes are identified using k-means clustering of 500-hPa geopotential heights on extreme precipitation days, in both observations and in the models. While all models capture an observed northwest-to-southeast gradient of precipitation intensity (reflected in the top 1% threshold), there are substantial differences from observations in the magnitude of the gradient. These differences tend to be more substantial for lower-resolution models. However, regardless of resolution, and despite a bias toward too-frequent precipitation, many of the models capture the seasonality of observed daily precipitation intensity, and the approximate magnitude and seasonality of observed extreme precipitation intensity. Many of the simulated extreme precipitation circulation patterns are visually similar to the set of observed patterns. However, the location and magnitude of specific troughs and ridges within the patterns, as well as the seasonality of the patterns, may differ substantially from the observed corresponding patterns. A series of metrics is developed based on the observed regional characteristics to facilitate comparison between models.

scholarly journals Compiled records of carbon isotopes in atmospheric CO<sub>2</sub> for historical simulations in CMIP6

2017 ◽  
Vol 10 (12) ◽  
pp. 4405-4417 ◽  
Author(s):  
Heather Graven ◽  
Colin E. Allison ◽  
David M. Etheridge ◽  
Samuel Hammer ◽  
Ralph F. Keeling ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Carbon Isotopes ◽  
Coupled Model ◽  
Atmospheric Co2 ◽  
Historical Period ◽  
Terrestrial Biosphere ◽  
Climate Simulations ◽  
Intercomparison Project ◽  
Natural Carbon ◽  
Carbon Cycle Modelling

Abstract. The isotopic composition of carbon (Δ14C and δ13C) in atmospheric CO2 and in oceanic and terrestrial carbon reservoirs is influenced by anthropogenic emissions and by natural carbon exchanges, which can respond to and drive changes in climate. Simulations of 14C and 13C in the ocean and terrestrial components of Earth system models (ESMs) present opportunities for model evaluation and for investigation of carbon cycling, including anthropogenic CO2 emissions and uptake. The use of carbon isotopes in novel evaluation of the ESMs' component ocean and terrestrial biosphere models and in new analyses of historical changes may improve predictions of future changes in the carbon cycle and climate system. We compile existing data to produce records of Δ14C and δ13C in atmospheric CO2 for the historical period 1850–2015. The primary motivation for this compilation is to provide the atmospheric boundary condition for historical simulations in the Coupled Model Intercomparison Project 6 (CMIP6) for models simulating carbon isotopes in the ocean or terrestrial biosphere. The data may also be useful for other carbon cycle modelling activities.

scholarly journals Future Changes in Mean and Extreme Monsoon Precipitation in the Middle and Lower Yangtze River Basin, China, in the CMIP5 Models

2016 ◽  
Vol 17 (11) ◽  
pp. 2785-2797 ◽  
Author(s):  
Yanjuan Wu ◽  
Shuang-Ye Wu ◽  
Jiahong Wen ◽  
Felipe Tagle ◽  
Ming Xu ◽  
...  
Keyword(s):  
River Basin ◽  
Extreme Precipitation ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Eastern China ◽  
Model Performance ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Intercomparison Project ◽  
Lower Yangtze

Abstract In this study, the potential future changes of mean and extreme precipitation in the middle and lower Yangtze River basin (MLYRB), eastern China, are assessed using the models of phase 5 of the Coupled Model Intercomparison Project (CMIP5). Historical model simulations are first compared with observations in order to evaluate model performance. In general, the models simulate the precipitation mean and frequency better than the precipitation intensity and extremes, but still have difficulty capturing precipitation patterns over complex terrains. They tend to overestimate precipitation mean, frequency, and intensity while underestimating the extremes. After correcting for model biases, the spatial variation of mean precipitation projected by the multimodel ensemble mean (MME) is improved, so the MME after the bias correction is used to project changes for the years 2021–50 and 2071–2100 relative to 1971–2000 under two emission scenarios: RCP4.5 and RCP8.5. Results show that with global warming, precipitation will become less frequent but more intense over the MLYRB. Relative changes in extremes generally exceed those in mean precipitation. Moreover, increased precipitation extremes are also expected even in places where mean precipitation is projected to decrease in 2021–50. The overall increase in extreme precipitation could potentially lead to more frequent floods in this already flood-prone region.

scholarly journals Attribution of the Observed Spring Snowpack Decline in British Columbia to Anthropogenic Climate Change

2017 ◽  
Vol 30 (11) ◽  
pp. 4113-4130 ◽  
Author(s):  
Mohammad Reza Najafi ◽  
Francis Zwiers ◽  
Nathan Gillett
Keyword(s):  
British Columbia ◽  
General Circulation ◽  
Snow Water Equivalent ◽  
Low Frequency ◽  
Coupled Model ◽  
General Circulation Models ◽  
Hydrologic Model ◽  
Infiltration Capacity ◽  
Detection And Attribution ◽  
Attribution Analysis

Abstract A detection and attribution analysis on the multidecadal trend in snow water equivalent (SWE) has been conducted in four river basins located in British Columbia (BC). Monthly output from a suite of 10 general circulation models (GCMs) that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) is used, including 40 climate simulations with anthropogenic and natural forcing combined (ALL), 40 simulations with natural forcing alone (NAT), and approximately 4200 yr of preindustrial control simulations (CTL). This output was downscaled to ° spatial resolution and daily temporal resolution to drive the Variable Infiltration Capacity hydrologic model (VIC). Observed (manual snow survey) and VIC-reconstructed SWE, which exhibit declines across BC, are projected onto the multimodel ensemble means of the VIC-simulated SWE based on the responses to different forcings using an optimal fingerprinting approach. Results of the detection and attribution analysis shows that these declines are attributable to the anthropogenic forcing, which is dominated by the effect of increases in greenhouse gas concentration, and that they are not caused by natural forcing due to volcanic activity and solar variability combined. Anthropogenic influence is detected in three of the four basins (Fraser, Columbia, and Campbell Rivers) based on the VIC-reconstructed SWE, and in all basins based on the manual snow survey records. The simulations underestimate the observed snowpack trends in the Columbia River basin, which has the highest mean elevation. Attribution is supported by the detection of human influence on the cold-season temperatures that drive the snowpack reductions. These results are robust to the use of different observed datasets and to the treatment of low-frequency variability effects.

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