scholarly journals Evaluation of Historical CMIP5 GCM Simulation Results Based on Detected Atmospheric Teleconnections

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 723 ◽  
Author(s):  
Erzsébet Kristóf ◽  
Zoltán Barcza ◽  
Roland Hollós ◽  
Judit Bartholy ◽  
Rita Pongrácz
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Evaluation Method ◽  
Polynomial Regression ◽  
Diversity Index ◽  
Regional Climate ◽  
Coupled Model ◽  
General Circulation Models ◽  
Teleconnection Patterns ◽  
Atmospheric Teleconnections

Atmospheric teleconnections are characteristic to the climate system and exert major impacts on the global and regional climate. Accurate representation of teleconnections by general circulation models (GCMs) is indispensable given their fundamental role in the large scale circulation patterns. In this study a statistical method is introduced to evaluate historical GCM outputs of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with respect to teleconnection patterns. The introduced method is based on the calculation of correlations between gridded time series of the 500 hPa geopotential height fields in the Northern Hemisphere. GCMs are quantified by a simple diversity index. Additionally, potential action centers of the teleconnection patterns are identified on which the local polynomial regression model is fitted. Diversity fields and regression curves obtained from the GCMs are compared against the NCEP/NCAR Reanalysis 1 and the ERA-20C reanalysis datasets. The introduced method is objective, reproducible, and reduces the number of arbitrary decisions during the analysis. We conclude that major teleconnection patterns are positioned in the GCMs and in the reanalysis datasets similarly, however, spatial differences in their intensities can be severe in some cases that could hamper the applicability of the GCM results for some regions. Based on the evaluation method, best-performing GCMs can be clearly distinguished. Evaluation of the GCMs based on the introduced method might help the modeling community to choose GCMs that are the most applicable for impact studies and for regional downscaling exercises.

scholarly journals Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1

2019 ◽  
Vol 12 (8) ◽  
pp. 3725-3743 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
Coupled Model ◽  
General Circulation Models

Abstract. We present multi-seasonal simulations representative of present-day and future environments using the global Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select 10 simulation years with varying phases of El Niño–Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analyzed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most Northern Hemisphere basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemisphere phenomena, and, more generally, the utility of MPAS-A for studying climate change at spatial scales generally unachievable in GCMs.

scholarly journals CMIP5 temperature biases and 21st century warming around the Antarctic coast

2016 ◽  
Vol 57 (73) ◽  
pp. 69-78 ◽  
Author(s):  
Christopher M. Little ◽  
Nathan M. Urban
Keyword(s):  
Mass Balance ◽  
21St Century ◽  
General Circulation ◽  
Large Scale ◽  
Ice Sheet ◽  
Coupled Model ◽  
General Circulation Models ◽  
Ensemble Mean ◽  
Rcp 8.5 ◽  
Ice Sheet Mass Balance

ABSTRACTProjections of ice-sheet mass balance require regional ocean warming projections derived from atmosphere-ocean general circulation models (AOGCMs). However, the coarse resolution of AOGCMs: (1) may lead to systematic or AOGCM-specific biases and (2) makes it difficult to identify relevant water masses. Here, we employ a large-scale metric of Antarctic Shelf Bottom Water (ASBW) to investigate circum-Antarctic temperature biases and warming projections in 19 different Coupled Model Intercomparison Project Phase 5 (CMIP5) AOGCMs forced with two different ‘representative concentration pathways’ (RCPs). For high-emissions RCP 8.5, the ensemble mean 21st century ASBW warming is 0.66, 0.74 and 0.58°C for the Amundsen, Ross and Weddell Seas (AS, RS and WS), respectively. RCP 2.6 ensemble mean projections are substantially lower: 0.21, 0.26, and 0.19°C. All distributions of regional ASBW warming are positively skewed; for RCP 8.5, four AOGCMs project warming of greater than 1.8°C in the RS. Across the ensemble, there is a strong, RCP-independent, correlation between WS and RS warming. AS warming is more closely linked to warming in the Southern Ocean. We discuss possible physical mechanisms underlying the spatial patterns of warming and highlight implications of these results on strategies for forcing ice-sheet mass balance projections.

ENSO teleconnections in an ensemble of CORDEX-CORE regional simulations

2021 ◽  
Author(s):  
Abraham Torres-Alavez ◽  
Fred Kucharski ◽  
Erika Coppola ◽  
Lorena Castro
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Permutation Test ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
Regional Climate ◽  
General Circulation Models ◽  
Boreal Winter ◽  
Climate Change Research ◽  
Teleconnection Patterns

<p>Using high-spatial-resolution regional simulations from the global program, Coordinated Regional Climate Downscaling Experiment-Coordinated Output for Regional Evaluations (CORDEX-CORE), we examine the capability of regional climate models (RCMs) to represent the El Niño–Southern Oscillation (ENSO) precipitation and surface air temperature teleconnections during boreal winter (December-February). This study uses CORDEX-CORE simulations for the period 1975-2004 with two RCMs, the RegCM4 and REMO, driven by three General Circulation Models (GCMs) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5). The RCM simulations were run at a 25-km grid spacing over Africa, Central and North America, South Asia and South America.</p><p>The teleconnection patterns are calculated in the reanalysis data (observations), and these results are compared to those of the ensemble and individual simulations of both the GCM and RCM. Linear regression is used to calculate the teleconnection patterns and a permutation test is applied to calculate the statistical significance of the regression coefficients. Results show that overall, the ENSO signal from the GCMs is preserved in the ensemble and the individual RCM simulations over most of the regions analyzed. These reproduced most of the observed regional responses to ENSO forcing and showing teleconnection signals statistically significant at the 95% level. Furthermore, in some cases, the ensemble and individual simulations of RCMs improve the spatial pattern and the amplitude of the ENSO precipitation response of the GCMs, particularly over southern Africa, the Arabian-Asian region, and the region composed of Mexico and the southern United States. These results show the potential value of the GCM-RCM downscaling systems not only in the context of climate change research but also for seasonal to annual prediction.</p>

Robust Late 21st Century Shift in the Regional Monsoons in RegCM-CORDEX Simulations

2020 ◽  
Author(s):  
Moetasim Ashfaq ◽  
Tereza Cavazos ◽  
Michelle Reboita ◽  
José Abraham Torres-Alavez ◽  
Eun-Soon Im ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Lower Boundary ◽  
Coupled Model ◽  
General Circulation Models ◽  
Monsoon Onset ◽  
Historical Period ◽  
Monsoon Period

<p>We use an unprecedented ensemble of regional climate model (RCM) projections over seven regional CORDEX domains to provide, for the first time, an RCM-based global view of monsoon changes at various levels of increased greenhouse gas (GHG) forcing. All regional simulations are conducted using RegCM4 at a 25km horizontal grid spacing using lateral and lower boundary forcing from three General Circulation Models (GCMs), which are part of the fifth phase of the Coupled Model Inter-comparison Project (CMIP5). Each simulation covers the period from 1970 through 2100 under two Representative Concentration Pathways (RCP2.6 and RCP8.5). Regional climate simulations exhibit high fidelity in capturing key characteristics of precipitation and atmospheric dynamics across monsoon regions in the historical period. In the future period, regional monsoons exhibit a spatially robust delay in the monsoon onset, an increase in seasonality, and a reduction in the rainy season length at higher levels of radiative forcing. All regions with substantial delays in the monsoon onset exhibit a decrease in pre-monsoon precipitation, indicating a strong connection between pre-monsoon drying and a shift in the monsoon onset. The weakening of latent heat driven atmospheric warming during the pre-monsoon period delays the overturning of atmospheric subsidence in the monsoon regions, which defers their transitioning into deep convective states. Monsoon changes under the RCP2.6 scenario are mostly within the baseline variability. </p>

scholarly journals Assessment of the performance of CMIP5 and CORDEX-SA models over the drought-prone Bundelkhand region, India

2020 ◽  
Vol 11 (S1) ◽  
pp. 133-144 ◽  
Author(s):  
Ankur Vishwakarma ◽  
Mahendra Kumar Choudhary ◽  
Mrityunjay Singh Chauhan
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Central India ◽  
General Circulation Models ◽  
Coefficient Of Determination ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Study Region ◽  
Daily Precipitation Data

Abstract The present study evaluates the reliability of the latest generation five best general circulation models (GCMs) under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and their corresponding regional climate models (RCMs) of Coordinated Regional Climate Downscaling Experiment (CORDEX) for the Bundelkhand region in central India. The study is performed on a microscale due to frequent drought events and more climate susceptibility in the study region. Observed daily precipitation data of 35 years (1971–2005) from the Indian Meteorological Department (IMD) have been chosen to check the performance of the models. Bilinear interpolation has been adopted to prepare all the data to obtain them on a common grid platform at a half-degree (0.5° × 0.5°) resolution. The data of the models have been bias-corrected using quantile mapping. Uncertainty of the models has been assessed using Nash–Sutcliffe efficiency (NSE), coefficient of determination (r2) and a modified method known as skill score (SS). The study concluded that the bias-corrected GCMs played a better role than the CORDEX RCMs for the Bundelkhand region. Earth System Model, ESM-2M of the Geophysical Fluid Dynamics Laboratory (GFDL) has shown better accuracy than all the CORDEX RCMs and their driving GCMs for the study region.

scholarly journals Present day bias and future change signal of temperature over China in a series of multi-GCM driven RCM simulations

2019 ◽  
Vol 54 (1-2) ◽  
pp. 1113-1130 ◽  
Author(s):  
Jia Wu ◽  
Xuejie Gao
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
Added Value ◽  
The Tibetan Plateau ◽  
Low Sensitivity ◽  
June July

Abstract Simulation of surface air temperature over China from a set of regional climate model (RCM) climate change experiments are analyzed with the focus on bias and change signal of the RCM and driving general circulation models (GCMs). The set consists of 4 simulations by the RCM of RegCM4 driven by 4 different GCMs for the period of 1979–2099 under the mid-range RCP4.5 (representative concentration pathway) scenario. Results show that for present day conditions, the RCM provides with more spatial details of the distribution and in general reduces the biases of GCM, in particular in DJF (December–January–February) and over areas with complex topography. Bias patterns show some correlation between the RCM and driving GCM in DJF but not in JJA (June–July–August). In JJA, the biases in RCM simulations show similar pattern and low sensitivity to the driving GCM, which can be attributed to the large effect of internal model physics in the season. For change signals, dominant forcings from the driving GCM are evident in the RCM simulations as shown by the magnitude, large scale spatial distribution, as well as interannual variation of the changes. The added value of RCM projection is characterized by the finer spatial detail in sub-regional (river basins) and local scale. In DJF, profound warming over the Tibetan Plateau is simulated by RCM but not GCMs. In general no clear relationships are found between the model bias and change signal, either for the driving GCMs or nested RCM.

Assessing the Representation of Australian Regional Climate Extremes and Their Associated Atmospheric Circulation in Climate Models

2020 ◽  
Vol 33 (4) ◽  
pp. 1227-1245 ◽  
Author(s):  
Carly R. Tozer ◽  
James S. Risbey ◽  
Didier P. Monselesan ◽  
Dougal T. Squire ◽  
Matthew A. Chamberlain ◽  
...  
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Extreme Event ◽  
Wave Train ◽  
Regional Climate ◽  
Climate Extremes ◽  
General Circulation Models ◽  
Dry Spells ◽  
Rainfall Extremes

AbstractWe assess the representation of multiday temperature and rainfall extremes in southeast Australia in three coupled general circulation models (GCMs) of varying resolution. We evaluate the statistics of the modeled extremes in terms of their frequency, duration, and magnitude compared to observations, and the model representation of the midtropospheric circulation (synoptic and large scale) associated with the extremes. We find that the models capture the statistics of observed heatwaves reasonably well, though some models are “too wet” to adequately capture the observed duration of dry spells but not always wet enough to capture the magnitude of extreme wet events. Despite the inability of the models to simulate all extreme event statistics, the process evaluation indicates that the onset and decay of the observed synoptic structures are well simulated in the models, including for wet and dry extremes. We also show that the large-scale wave train structures associated with the observed extremes are reasonably well simulated by the models although their broader onset and decay is not always captured in the models. The results presented here provide some context for, and confidence in, the use of the coupled GCMs in climate prediction and projection studies for regional extremes.

scholarly journals Precipitation and Moisture in Four Leading CMIP5 Models: Biases across Large-Scale Circulation Regimes and Their Attribution to Dynamic and Thermodynamic Factors

2018 ◽  
Vol 31 (13) ◽  
pp. 5089-5106 ◽  
Author(s):  
Mengmiao Yang ◽  
Guang J. Zhang ◽  
De-Zheng Sun
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Coupled Model ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Frequency Of Occurrence ◽  
Upward Motion ◽  
Large Scale Circulation ◽  
Intercomparison Project ◽  
Strong Upward Motion

As key variables in general circulation models, precipitation and moisture in four leading models from CMIP5 (phase 5 of the Coupled Model Intercomparison Project) are analyzed, with a focus on four tropical oceanic regions. It is found that precipitation in these models is overestimated in most areas. However, moisture bias has large intermodel differences. The model biases in precipitation and moisture are further examined in conjunction with large-scale circulation by regime-sorting analysis. Results show that all models consistently overestimate the frequency of occurrence of strong upward motion regimes and peak descending regimes of 500-hPa vertical velocity [Formula: see text]. In a given [Formula: see text] regime, models produce too much precipitation compared to observation and reanalysis. But for moisture, their biases differ from model to model and also from level to level. Furthermore, error causes are revealed through decomposing contribution biases into dynamic and thermodynamic components. For precipitation, the contribution errors in strong upward motion regimes are attributed to the overly frequent [Formula: see text]. In the weak upward motion regime, the biases in the dependence of precipitation on [Formula: see text] and the [Formula: see text] probability density function (PDF) make comparable contributions, but often of opposite signs. On the other hand, the biases in column-integrated water vapor contribution are mainly due to errors in the frequency of occurrence of [Formula: see text], while thermodynamic components contribute little. These findings suggest that errors in the frequency of [Formula: see text] occurrence are a significant cause of biases in the precipitation and moisture simulation.

scholarly journals Madden–Julian Oscillation Pacific Teleconnections: The Impact of the Basic State and MJO Representation in General Circulation Models

2017 ◽  
Vol 30 (12) ◽  
pp. 4567-4587 ◽  
Author(s):  
Stephanie A. Henderson ◽  
Eric D. Maloney ◽  
Seok-Woo Son
Keyword(s):  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
Teleconnection Pattern ◽  
Madden Julian Oscillation ◽  
Horizontal Structure ◽  
Teleconnection Patterns ◽  
Subtropical Jet ◽  
The Pacific ◽  
The Impact

Teleconnection patterns associated with the Madden–Julian oscillation (MJO) significantly alter extratropical circulations, impacting weather and climate phenomena such as blocking, monsoons, the North Atlantic Oscillation, and the Pacific–North American pattern. However, the MJO has been extremely difficult to simulate in many general circulation models (GCMs), and many GCMs contain large biases in the background flow, presenting challenges to the simulation of MJO teleconnection patterns and associated extratropical impacts. In this study, the database from phase 5 of the Coupled Model Intercomparison Project (CMIP5) is used to assess the impact of model MJO and basic state quality on MJO teleconnection pattern quality, and a simple dry linear baroclinic model is employed to understand the results. Even in GCMs assessed to have good MJOs, large biases in the MJO teleconnection patterns are produced as a result of errors in the zonal extent of the Pacific subtropical jet. The horizontal structure of Indo-Pacific MJO heating in good MJO models is found to have modest impacts on the teleconnection pattern skill, in agreement with previous studies that have demonstrated little sensitivity to the location of tropical heating near the subtropical jet. However, MJO heating east of the date line can alter the teleconnection pathways over North America. Results show that GCMs with poor basic states can have equally low skill in reproducing the MJO teleconnection patterns as GCMs with poor MJO quality, suggesting that both the basic state and the MJO must be well represented in order to reproduce the correct teleconnection patterns.

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

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