scholarly journals Global trends in extreme precipitation: climate models vs. observations

2014 ◽  
Vol 11 (10) ◽  
pp. 11369-11393 ◽  
Author(s):  
B. Asadieh ◽  
N. Y. Krakauer
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Daily Precipitation ◽  
Average Rate ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Annual Maximum ◽  
Rate Of Increase

Abstract. Precipitation events are expected to become substantially more intense under global warming, but few global comparisons of observations and climate model simulations are available to constrain predictions of future changes in precipitation extremes. We present a systematic global-scale comparison of changes in historical (1901–2010) annual-maximum daily precipitation between station observations (compiled in HadEX2) and the suite of global climate models contributing to the fifth phase of the Coupled Model Inter-comparison Project (CMIP5). We use both parametric and non-parametric methods to quantify the strength of trends in extreme precipitation in observations and models, taking care to spatially and temporally sample them in comparable ways. We find that both observations and models show generally increasing trends in extreme precipitation since 1901 with largest changes in deep tropics, although annual-maximum daily precipitation has increased faster in the observations than in most of the CMIP5 models. Global average of observational annual-maximum daily precipitation has increased about 5.73 mm over the last 110 years or 8.5% in relative terms and has increased by approximately 10% per K of global warming since 1901, which is larger than the average of climate models with 8.3% K−1. The average rate of increase in extreme precipitation per K of warming in models and observations is higher than the rate of increase in atmospheric water vapor content per K of warming expected from the Clausius–Clapeyron equation. We expect our findings to help inform assessments of precipitation-related hazards such as flooding, droughts and storms.

scholarly journals Global trends in extreme precipitation: climate models versus observations

2015 ◽  
Vol 19 (2) ◽  
pp. 877-891 ◽  
Author(s):  
B. Asadieh ◽  
N. Y. Krakauer
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Daily Precipitation ◽  
Average Rate ◽  
Global Scale ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Annual Maximum ◽  
Rate Of Increase

Abstract. Precipitation events are expected to become substantially more intense under global warming, but few global comparisons of observations and climate model simulations are available to constrain predictions of future changes in precipitation extremes. We present a systematic global-scale comparison of changes in historical (1901–2010) annual-maximum daily precipitation between station observations (compiled in HadEX2) and the suite of global climate models contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We use both parametric and non-parametric methods to quantify the strength of trends in extreme precipitation in observations and models, taking care to sample them spatially and temporally in comparable ways. We find that both observations and models show generally increasing trends in extreme precipitation since 1901, with the largest changes in the deep tropics. Annual-maximum daily precipitation (Rx1day) has increased faster in the observations than in most of the CMIP5 models. On a global scale, the observational annual-maximum daily precipitation has increased by an average of 5.73 mm over the last 110 years, or 8.5% in relative terms. This corresponds to an increase of 10% K−1 in global warming since 1901, which is larger than the average of climate models, with 8.3% K−1. The average rate of increase in extreme precipitation per K of warming in both models and observations is higher than the rate of increase in atmospheric water vapor content per K of warming expected from the Clausius–Clapeyron equation. We expect our findings to help inform assessments of precipitation-related hazards such as flooding, droughts and storms.

scholarly journals Fidelity of the Observational/Reanalysis Datasets and Global Climate Models in Representation of Extreme Precipitation in East China

2018 ◽  
Vol 32 (1) ◽  
pp. 195-212 ◽  
Author(s):  
Sicheng He ◽  
Jing Yang ◽  
Qing Bao ◽  
Lei Wang ◽  
Bin Wang
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Yangtze River Basin ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Global Ocean ◽  
East China ◽  
Cmip5 Models

AbstractRealistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM) simulations. This work assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean–Atmospheric Land System Model–Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations’ rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days. The TRMM observation displays similar rainfall intensity–frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models. Higher-resolution models tend to have better performance, and physical parameterization may be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation of moisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models’ simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation.

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 Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Open Field ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Current Model ◽  
Global Climate Models ◽  
The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

Regionally Varying Assessments of Upper-Level Tropical Width in Reanalyses and CMIP5 Models Using a Tropopause Break Metric

2020 ◽  
Vol 33 (14) ◽  
pp. 5885-5903 ◽  
Author(s):  
Elinor R. Martin ◽  
Cameron R. Homeyer ◽  
Roarke A. McKinzie ◽  
Kevin M. McCarthy ◽  
Tao Xian
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
The Past ◽  
East Pacific ◽  
Change Climate ◽  
Upper Level ◽  
The Tropics

AbstractChanges in tropical width can have important consequences in sectors including ecosystems, agriculture, and health. Observations suggest tropical expansion over the past 30 years although studies have not agreed on the magnitude of this change. Climate model projections have also indicated an expansion and show similar uncertainty in its magnitude. This study utilizes an objective, longitudinally varying, tropopause break method to define the extent of the tropics at upper levels. The location of the tropopause break is associated with enhanced stratosphere–troposphere exchange and thus its structure influences the chemical composition of the stratosphere. The method shows regional variations in the width of the upper-level tropics in the past and future. Four modern reanalyses show significant contraction of the tropics over the eastern Pacific between 1981 and 2015, and slight but significant expansion in other regions. The east Pacific narrowing contributes to zonal mean narrowing, contradicting prior work, and is attributed to the use of monthly and zonal mean data in prior studies. Six global climate models perform well in representing the climatological location of the tropical boundary. Future projections show a spread in the width trend (from ~0.5° decade−1 of narrowing to ~0.4° decade−1 of widening), with a narrowing projected across the east Pacific and Northern Hemisphere Americas. This study illustrates that this objective tropopause break method that uses instantaneous data and does not require zonal averaging is appropriate for identifying upper-level tropical width trends and the break location is connected with local and regional changes in precipitation.

scholarly journals Saharan Heat Low Biases in CMIP5 Models

2017 ◽  
Vol 30 (8) ◽  
pp. 2867-2884 ◽  
Author(s):  
Ross D. Dixon ◽  
Anne Sophie Daloz ◽  
Daniel J. Vimont ◽  
Michela Biasutti
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
West African Monsoon ◽  
West African ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
African Climate ◽  
Heat Low

Representing the West African monsoon (WAM) is a major challenge in climate modeling because of the complex interaction between local and large-scale mechanisms. This study focuses on the representation of a key aspect of West African climate, namely the Saharan heat low (SHL), in 22 global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel dataset. Comparison of the CMIP5 simulations with reanalyses shows large biases in the strength and location of the mean SHL. CMIP5 models tend to develop weaker climatological heat lows than the reanalyses and place them too far southwest. Models that place the climatological heat low farther to the north produce more mean precipitation across the Sahel, while models that place the heat low farther to the east produce stronger African easterly wave (AEW) activity. These mean-state biases are seen in model ensembles with both coupled and fixed sea surface temperatures (SSTs). The importance of SSTs on West African climate variability is well documented, but this research suggests SSTs are secondary to atmospheric biases for understanding the climatological SHL bias. SHL biases are correlated across the models to local radiative terms, large-scale tropical precipitation, and large-scale pressure and wind across the Atlantic, suggesting that local mechanisms that control the SHL may be connected to climate model biases at a much larger scale.

scholarly journals The representation of Northern Hemisphere blocking in current global climate models

2020 ◽  
Author(s):  
Reinhard Schiemann ◽  
Panos Athanasiadis ◽  
David Barriopedro ◽  
Francisco Doblas-Reyes ◽  
Katja Lohmann ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Development ◽  
Reanalysis Data ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
The Pacific ◽  
Intercomparison Project ◽  
Blocking Index

Abstract. Global Climate Models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations, and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and in winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 32 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 19 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 km to 20 km grid spacing, in the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer, and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.

scholarly journals Northern Hemisphere blocking simulation in current climate models: evaluating progress from the Climate Model Intercomparison Project Phase 5 to 6 and sensitivity to resolution

2020 ◽  
Vol 1 (1) ◽  
pp. 277-292 ◽  
Author(s):  
Reinhard Schiemann ◽  
Panos Athanasiadis ◽  
David Barriopedro ◽  
Francisco Doblas-Reyes ◽  
Katja Lohmann ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Development ◽  
Global Climate Models ◽  
Assessment Model ◽  
Climate Simulation ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract. Global climate models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA – PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and during winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 33 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 18 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 to 20 km grid spacing, in most of the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.

scholarly journals Ensemble Projection of Extreme Precipitation Over China Based on Three Dynamical Downscaling Simulations

2021 ◽  
Vol 9 ◽  
Author(s):  
Guangtao Dong ◽  
Ye Xie ◽  
Ya Wang ◽  
Dongli Fan ◽  
Zhan Tian
Keyword(s):  
21St Century ◽  
Extreme Precipitation ◽  
North China ◽  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate Models ◽  
Vapor Flux ◽  
The Future ◽  
Late 21St Century

Based on the outputs of the global climate models (GCMs) HadGEM2-ES, NorESM1-M and MPI-ESM-LR from Coupled Model Intercomparison Project Phase 5 (CMIP5) and the downscaling results with the regional climate model (RCM) REMO, the ability of the climate models to reproduce the extreme precipitation in China during the current period (1986–2005) is evaluated. Then, the future extreme precipitation in the mid (2036–2065) and the late 21st century (2066–2095) is projected under the RCP8.5 scenario. The results show that the RCM simulations have great improvements compared with the GCMs, and the ensemble mean of the RCM results (ensR) outperforms each single RCM simulation. The annual precipitation of the RCM simulations is more consistent with the observation than that of the GCMs, with the overestimation of the peak precipitation reduced, and the ensR further reduces the bias. For the extreme precipitation, the RCM simulations significantly decrease the underestimation of intensity in the GCMs. The RCM simulations and the ensR can greatly improve the simulations of Rx5day and CWD compared with the GCMs, decreasing the wet bias in North China and Northwest China. In the future, the consecutive dry days (CDD) will decrease in the northern arid regions, especially in North China and Northeast China. However, the southern regions will experience longer dry period. Both the amount and the intensity of precipitation will increase in various regions of China. The number of wet days will decrease in the south and increase in the north area. The significantly greater Rx5day and R95t indicate more intensive extreme precipitation in the future, and the intensity in the late 21st century will be stronger than that in the middle. Attribution analysis indicates that the extreme precipitation indices especially the R95t have significant positive temporal and spatial correlations with the water vapor flux.

scholarly journals Sensitivities of Extreme Precipitation to Global Warming Are Lower over Mountains than over Oceans and Plains

2016 ◽  
Vol 29 (13) ◽  
pp. 4779-4791 ◽  
Author(s):  
Xiaoming Shi ◽  
Dale Durran
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Static Stability ◽  
Induced Response ◽  
Model Simulations ◽  
Fractional Rate ◽  
Rate Of Increase ◽  
Climate Model Simulations ◽  
Almost All

Abstract Climate-model simulations predict an intensification of extreme precipitation in almost all areas of the world under global warming. Local variations in the magnitude of this intensification are evident in these simulations, but most previous efforts to understand the factors responsible for the changes in extreme precipitation focused on zonal averages and neglected zonal variations, leading to uncertainties in the understanding and estimation of regional responses. Here the spatial heterogeneity of the warming-induced response of midlatitude extreme precipitation is studied in climate-model simulations with idealized orography on the western margins of otherwise flat continents. It is shown that the sensitivity of extreme precipitation to warming (i.e., its fractional rate of increase in intensity with global-mean surface temperature) is ~3% K−1 lower over the mountains than the oceans and plains. This difference in sensitivity is primarily produced by differences in the dynamics governing vertical ascent over the three regions. In these extreme events, mountain-wave dynamics control the moist ascent over the mountains, and the sensitivity of this ascent to global warming is mainly controlled by changes in upper-level dry static stability and the cross-mountain winds. In contrast, midlatitude cyclone dynamics govern moist ascent over the oceans and plains. Ascending motions in intense midlatitude cyclones are sensitive to the ratio of the moist static stability in their saturated cores to the dry stability in surrounding regions. This ratio decreases in the warmer world, intensifying the maximum vertical velocities while reducing the horizontal extent of the regions of the rising air within the cyclone.

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