Understanding future increases in precipitation extremes in global land monsoon regions

2021 ◽  
pp. 1-38
Keyword(s):  
Climate Models ◽  
Daily Precipitation ◽  
Coupled Model ◽  
Social Benefit ◽  
Precipitation Extremes ◽  
Historical Period ◽  
Dynamic Scaling ◽  
Continuous Increase ◽  
Global Land ◽  
Thermodynamics And Dynamics

Abstract This study investigates future changes in daily precipitation extremes and the involved physics over the global land monsoon (GM) region using climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The daily precipitation extreme is identified by the cutoff scale, measuring the extreme tail of the precipitation distribution. Compared to the historical period, multi-model results reveal a continuous increase in precipitation extremes under four scenarios, with a progressively higher fraction of precipitation exceeding the historical cutoff scale when moving into the future. The rise of the cutoff-scale by the end of the century is reduced by 57.8% in the moderate emission scenario relative to the highest scenario, underscoring the social benefit in reducing emissions. The cutoff scale sensitivity, defined by the increasing rates of the cutoff scale over the GM region to the global mean surface temperature increase, is nearly independent of the projected periods and emission scenarios, roughly 8.0% K−1 by averaging all periods and scenarios. To understand the cause of the changes, we applied a physical scaling diagnostic to decompose them into thermodynamic and dynamic contributions. We find that thermodynamics and dynamics have comparable contributions to the intensified precipitation extremes in the GM region. Changes in thermodynamic scaling contribute to a spatially uniform increase pattern, while changes in dynamic scaling dominate the regional differences in the increased precipitation extremes. Furthermore, the large inter-model spread of the projection is primarily attributed to variations of dynamic scaling among models.

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.

Investigating the seasonal response of precipitation extremes to global warming using observations and large-ensembles of coupled climate models

2020 ◽  
Author(s):  
Andrew Williams ◽  
Paul O'Gorman
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Precipitation Extremes ◽  
Cmip5 Models ◽  
Historical Period ◽  
Societal Relevance ◽  
Coupled Climate Models

<p>Changes in extreme precipitation are amongst the most impactful consequences of global warming, with potential effects ranging from increased flood risk and landslides to crop failures and impacts on ecosystems. Thus, understanding historical and future changes in extreme precipitation is not only important from a scientific perspective, but also has direct societal relevance.</p><p>However, while most current research has focused on annual precipitation extremes and their response to warming, it has recently been noted that climate model projections show a distinct seasonality to future changes in extreme precipitation. In particular, CMIP5 models suggest that over Northern Hemisphere (NH) land the summer response is weaker than the winter response in terms of percentage changes.</p><p>Here we investigate changes in seasonal precipitation extremes using observations and simulations with coupled climate models. First, we analyse observed trends from the Hadley Centre’s global climate extremes dataset (HadEX2) to investigate to what extent there is already a difference between summer and winter trends over NH land. Second, we use 40 ensemble members from the CESM Large Ensemble to characterize the role played by internal variability in trends over the historical period. Lastly, we use CMIP5 simulations to explore the possibility of a link between the seasonality of changes in precipitation extremes and decreases in surface relative humidity over land.</p>

scholarly journals FROGs: a daily 1° × 1° gridded precipitation database ofrain gauge, satellite and reanalysis products

2019 ◽  
Author(s):  
Rémy Roca ◽  
Lisa V. Alexander ◽  
Gerald Potter ◽  
Margot Bador ◽  
Rômulo Jucá ◽  
...  
Keyword(s):  
South America ◽  
Daily Precipitation ◽  
Precipitation Extremes ◽  
Careful Selection ◽  
Large Ensemble ◽  
Rain Gauges ◽  
Large Spread ◽  
Global Land ◽  
Selection Of

Abstract. We introduce the Frequent Rainfall Observations on GridS (FROGS) database (Roca et al., 2019). It is composed of gridded daily precipitation products on a common 1° × 1° grid to ease intercomparison and assessment exercises. The database includes satellite, ground–based and reanalysis products. As most of the satellite products rely on rain gauges for calibration, unadjusted versions of satellite products are also provided where available. Each product is provided over its length of record and up to 2017 if available. Quasi-global, quasi-global land only, ocean only as well as tropical only and regional products (over continental Africa and South America) are included. All products are provided on a common netCDF format that is compliant with CF and AAC standards. Preliminary investigations of this large ensemble indicate that while a lot of features appear robust across the products, the characterization of precipitation extremes exhibit a large spread calling for careful selection of the products used for scientific applications. All datasets are freely available via an ftp server and identified thanks to the DOI: https://doi.org/10.14768/06337394-73A9-407C-9997-0E380DAC5598.

scholarly journals Future precipitation changes in three key sub-regions of East Asia: the roles of thermodynamics and dynamics

2021 ◽  
Author(s):  
Jiao Li ◽  
Yang Zhao ◽  
Deliang Chen ◽  
Yanzhen Kang ◽  
Hui Wang
Keyword(s):  
East Asia ◽  
Climate Models ◽  
Coupled Model ◽  
Summer Precipitation ◽  
Tropical Region ◽  
Dynamic Component ◽  
Dynamic Components ◽  
Thermodynamics And Dynamics ◽  
Precipitation Changes

AbstractPrevious studies have projected an increase in future summer precipitation across East Asia (EA). This study investigates the relative contributions of thermodynamic and dynamic components to future precipitation changes in three key sub-regions of EA where the maximum centers of the historical precipitation are located (the tropical region, East China, and the Japan and Korea sector), and analyzes the causes of the changes in thermodynamic and dynamic components. Outputs from 30 climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) are used. From these, the five best-performing models for historical summer precipitation climatology for EA are selected. The future summer precipitations in the three sub-regions over the near- to mid-term (2020–2069) and the long-term (2070–2095) are then examined using the multi-model ensemble mean of the five models selected (MMM05). The projections were driven by four combined scenarios of the Shared Socioeconomic Pathways (SSPs) and forcing levels of the Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The results show that long-term precipitations under SSP5-8.5 are greater than those under the other scenarios across all sub-regions. After the 2070s under SSP5-8.5, a marked precipitation intensification is identified in all three sub-regions, but with different rates of increase. The projected precipitation increase is primarily attributed to the thermodynamic component, while the dynamic component related to circulation changes is relatively weak. Further analysis indicates that the pattern of the thermodynamic component in the three sub-regions is dominated by the climatological upward motion, mediated by an increase in moisture.

scholarly journals Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?

2015 ◽  
Vol 28 (17) ◽  
pp. 6938-6959 ◽  
Author(s):  
Alex J. Cannon ◽  
Stephen R. Sobie ◽  
Trevor Q. Murdock
Keyword(s):  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Precipitation Extremes ◽  
Extreme Value Analysis ◽  
Quantile Mapping ◽  
Value Analysis

Abstract Quantile mapping bias correction algorithms are commonly used to correct systematic distributional biases in precipitation outputs from climate models. Although they are effective at removing historical biases relative to observations, it has been found that quantile mapping can artificially corrupt future model-projected trends. Previous studies on the modification of precipitation trends by quantile mapping have focused on mean quantities, with less attention paid to extremes. This article investigates the extent to which quantile mapping algorithms modify global climate model (GCM) trends in mean precipitation and precipitation extremes indices. First, a bias correction algorithm, quantile delta mapping (QDM), that explicitly preserves relative changes in precipitation quantiles is presented. QDM is compared on synthetic data with detrended quantile mapping (DQM), which is designed to preserve trends in the mean, and with standard quantile mapping (QM). Next, methods are applied to phase 5 of the Coupled Model Intercomparison Project (CMIP5) daily precipitation projections over Canada. Performance is assessed based on precipitation extremes indices and results from a generalized extreme value analysis applied to annual precipitation maxima. QM can inflate the magnitude of relative trends in precipitation extremes with respect to the raw GCM, often substantially, as compared to DQM and especially QDM. The degree of corruption in the GCM trends by QM is particularly large for changes in long period return values. By the 2080s, relative changes in excess of +500% with respect to historical conditions are noted at some locations for 20-yr return values, with maximum changes by DQM and QDM nearing +240% and +140%, respectively, whereas raw GCM changes are never projected to exceed +120%.

Climate change in the tropical Atlantic

2020 ◽  
Author(s):  
Noel Keenlyside ◽  
Lander Crespo ◽  
Shunya Koseki ◽  
Lea Svendsen ◽  
Ingo Richter
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Coupled Model ◽  
Historical Period ◽  
Tropical Atlantic ◽  
Gulf Of Guinea ◽  
Coupled Models ◽  
Model Biases ◽  
Warming Pattern

<p>The tropical Atlantic SST have warmed by about 1 degree over the historical period, with greatest warming in the east, along the African coast and in the Gulf of Guinea. Experiments performed from the Coupled Model Intercomparison Projects (CMIP) indicate that models fail to reproduce this warming pattern, instead showing a rather uniform warming. Future projections with these models also tend to show rather uniform warming. In constrast. results from anomaly coupled models indicate that model biases impact the ability of climate models to simulate warming patterns in the tropical Atlantic. Here we investigate the role of model biases on climate change in the tropical Atlantic in the CMIP experiments. In addition, we have analyzed impacts of global warming on tropical Atlantic climate variability, and we assess the sensitive of the results are to model biases.</p>

scholarly journals Global climate shift in 1970s causes a significant worldwide increase in precipitation extremes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Subharthi Sarkar ◽  
Rajib Maity
Keyword(s):  
Daily Precipitation ◽  
Global Climate ◽  
Precipitation Extremes ◽  
Annual Maximum ◽  
Arctic Amplification ◽  
Land Area ◽  
Global Land ◽  
Spatial Redistribution ◽  
Heat And Moisture Transport ◽  
Heat And Moisture

AbstractThe shift in climate regimes around 1970s caused an overall enhancement of precipitation extremes across the globe with a specific spatial distribution pattern. We used gridded observational-reanalysis precipitation dataset and two important extreme precipitation measures, namely Annual Maximum Daily Precipitation (AMDP) and Probable Maximum Precipitation (PMP). AMDP is reported to increase for almost two-third of the global land area. The variability of AMDP is found to increase more than its mean that eventually results in increased PMP almost worldwide, less near equator and maximum around mid-latitudes. Continent-wise, such increase in AMDP and PMP is true for all continents except some parts of Africa. The zone-wise analysis (dividing the globe into nine precipitation zones) reveals that zones of ‘moderate precipitation’ and ‘moderate seasonality’ exhibit the maximum increases in PMP. Recent increased in pole-ward heat and moisture transport as a result of Arctic Amplification may be associated with such spatial redistribution of precipitation extremes in the northern hemisphere.

scholarly journals Historically-based run-time bias corrections substantially improve model projections of 100 years of future climate change

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Gerhard Krinner ◽  
Viatcheslav Kharin ◽  
Romain Roehrig ◽  
John Scinocca ◽  
Francis Codron
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Coupled Model ◽  
Atmospheric Model ◽  
Climate Impact ◽  
Future Climate ◽  
Future Climate Change ◽  
Historical Period ◽  
Underlying Assumption ◽  
Bias Corrections

Abstract Climate models and/or their output are usually bias-corrected for climate impact studies. The underlying assumption of these corrections is that climate biases are essentially stationary between historical and future climate states. Under very strong climate change, the validity of this assumption is uncertain, so the practical benefit of bias corrections remains an open question. Here, this issue is addressed in the context of bias correcting the climate models themselves. Employing the ARPEGE, LMDZ and CanAM4 atmospheric models, we undertook experiments in which one centre’s atmospheric model takes another centre’s coupled model as observations during the historical period, to define the bias correction, and as the reference under future projections of strong climate change, to evaluate its impact. This allows testing of the stationarity assumption directly from the historical through future periods for three different models. These experiments provide evidence for the validity of the new bias-corrected model approach. In particular, temperature, wind and pressure biases are reduced by 40–60% and, with few exceptions, more than 50% of the improvement obtained over the historical period is on average preserved after 100 years of strong climate change. Below 3 °C global average surface temperature increase, these corrections globally retain 80% of their benefit.

scholarly journals Intensification of the Western North Pacific Anticyclone Response to the Short Decaying El Niño Event due to Greenhouse Warming

2016 ◽  
Vol 29 (10) ◽  
pp. 3607-3627 ◽  
Author(s):  
Wei Chen ◽  
June-Yi Lee ◽  
Kyung-Ja Ha ◽  
Kyung-Sook Yun ◽  
Riyu Lu
Keyword(s):  
Global Warming ◽  
El Niño ◽  
North Pacific ◽  
Western North Pacific ◽  
Climate Models ◽  
El Nino ◽  
Coupled Model ◽  
Precipitation Anomaly ◽  
Historical Period ◽  
Central Pacific

Abstract Two types of El Niño evolution have been identified in terms of the lengths of their decaying phases: the first type is a short decaying El Niño that terminates in the following summer after the mature phase, and the second type is a long decaying one that persists until the subsequent winter. The responses of the western North Pacific anticyclone (WNPAC) anomaly to the two types of evolution are remarkably different. Using experiments from phase 5 of the Coupled Model Intercomparison Project (CMIP5), this study investigates how well climate models reproduce the two types of El Niño evolution and their impacts on the WNPAC in the historical period (1950–2005) and how they will change in the future under anthropogenic global warming. To reduce uncertainty in future projection, the nine best models are selected based on their performance in simulating El Niño evolution. In the historical run, the nine best models’ multimodel ensemble (B9MME) well reproduces the enhanced (weakened) WNPAC that is associated with the short (long) decaying El Niño. The comparison between results of the historical run for 1950–2005 and the representative concentration pathway 4.5 run for 2050–99 reveals that individual models and the B9MME tend to project no significant changes in the two types of El Niño evolution for the latter half of the twenty-first century. However, the WNPAC response to the short decaying El Niño is considerably intensified, being associated with the enhanced negative precipitation anomaly response over the equatorial central Pacific. This enhancement is attributable to the robust increase in mean and interannual variability of precipitation over the equatorial central Pacific under global warming.

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.

Sign in / Sign up

Export Citation Format

Share Document