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 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.

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

<p>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.</p>

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.

The Double-ITCZ Bias in CMIP6 Models

2020 ◽  
Author(s):  
Baijun Tian
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Tropical Precipitation ◽  
Double Itcz ◽  
Intercomparison Project ◽  
Fully Coupled

<p>The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.</p>

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 European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP)

2020 ◽  
Vol 13 (11) ◽  
pp. 5485-5506
Author(s):  
Marie-Estelle Demory ◽  
Ségolène Berthou ◽  
Jesús Fernández ◽  
Silje L. Sørland ◽  
Roman Brogli ◽  
...  
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Daily Precipitation ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Model Intercomparison ◽  
Grid Spacing ◽  
Intercomparison Project ◽  
Horizontal Grid

Abstract. In this study, we evaluate a set of high-resolution (25–50 km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12–50 km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50 km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events. The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12 km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50 km scale.

scholarly journals Characterizing and Understanding Cloud Ice and Radiation Budget Biases in Global Climate Models and Reanalysis

2016 ◽  
Vol 56 ◽  
pp. 13.1-13.20 ◽  
Author(s):  
J.-L. F. Li ◽  
D. E. Waliser ◽  
G. Stephens ◽  
Seungwon Lee
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Model Intercomparison ◽  
Convective Core ◽  
Intercomparison Project ◽  
Annual Means ◽  
Cloud Ice ◽  
Ice Water

Abstract The authors present an observationally based evaluation of the vertically resolved cloud ice water content (CIWC) and vertically integrated cloud ice water path (CIWP) as well as radiative shortwave flux downward at the surface (RSDS), reflected shortwave (RSUT), and radiative longwave flux upward at top of atmosphere (RLUT) of present-day global climate models (GCMs), notably twentieth-century simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), and compare these results to those of the third phase of the Coupled Model Intercomparison Project (CMIP3) and two recent reanalyses. Three different CloudSat and/or Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined ice water products and two methods are used to remove the contribution from the convective core ice mass and/or precipitating cloud hydrometeors with variable sizes and falling speeds so that a robust observational estimate can be obtained for model evaluations. The results show that, for annual mean CIWC and CIWP, there are factors of 2–10 (either over- or underestimate) in the differences between observations and models for a majority of the GCMs and for a number of regions. Most of the GCMs in CMIP3 and CMIP5 significantly underestimate the total ice water mass because models only consider suspended cloud mass, ignoring falling and convective core cloud mass. For the annual means of RSDS, RLUT, and RSUT, a majority of the models have significant regional biases ranging from −30 to 30 W m−2. Based on these biases in the annual means, there is virtually no progress in the simulation fidelity of RSDS, RLUT, and RSUT fluxes from CMIP3 to CMIP5, even though there is about a 50% bias reduction improvement of global annual mean CIWP from CMIP3 to CMIP5. It is concluded that at least a part of these persistent biases stem from the common GCM practice of ignoring the effects of precipitating and/or convective core ice and liquid in their radiation calculations.

scholarly journals Global exposure to flooding from the new CMIP6 climate model projections

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yukiko Hirabayashi ◽  
Masahiro Tanoue ◽  
Orie Sasaki ◽  
Xudong Zhou ◽  
Dai Yamazaki
Keyword(s):  
Spatial Patterns ◽  
Flood Risk ◽  
Climate Models ◽  
Climate Model ◽  
Model Development ◽  
Coupled Model ◽  
Model Intercomparison ◽  
Internal Climate Variability ◽  
Intercomparison Project ◽  
New Generation

AbstractEstimates of future flood risk rely on projections from climate models. The relatively few climate models used to analyze future flood risk cannot easily quantify of their associated uncertainties. In this study, we demonstrated that the projected fluvial flood changes estimated by a new generation of climate models, the collectively known as Coupled Model Intercomparison Project Phase 6 (CMIP6), are similar to those estimated by CMIP5. The spatial patterns of the multi-model median signs of change (+ or −) were also very consistent, implying greater confidence in the projections. The model spread changed little over the course of model development, suggesting irreducibility of the model spread due to internal climate variability, and the consistent projections of models from the same institute suggest the potential to reduce uncertainties caused by model differences. Potential global exposure to flooding is projected to be proportional to the degree of warming, and a greater threat is anticipated as populations increase, demonstrating the need for immediate decisions.

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