Process-based model evaluation and projections over southern Africa from Coordinated Regional Climate Downscaling Experiment and Coupled Model Intercomparison Project Phase 5 models

2018 ◽  
Vol 38 (11) ◽  
pp. 4251-4261 ◽  
Author(s):  
Izidine Pinto ◽  
Chris Jack ◽  
Bruce Hewitson
Keyword(s):  
Southern Africa ◽  
Model Evaluation ◽  
Regional Climate ◽  
Coupled Model ◽  
Model Intercomparison ◽  
Intercomparison Project ◽  
Climate Downscaling

scholarly journals The Dynamics and Variability Model Intercomparison Project (DynVarMIP) for CMIP6: assessing the stratosphere–troposphere system

2016 ◽  
Vol 9 (9) ◽  
pp. 3413-3425 ◽  
Author(s):  
Edwin P. Gerber ◽  
Elisa Manzini
Keyword(s):  
Climate Models ◽  
Energy Transport ◽  
Regional Climate ◽  
Coupled Model ◽  
Model Intercomparison ◽  
Dynamical Processes ◽  
Surface Climate ◽  
Intercomparison Project ◽  
The Impact ◽  
Variability Model

Abstract. Diagnostics of atmospheric momentum and energy transport are needed to investigate the origin of circulation biases in climate models and to understand the atmospheric response to natural and anthropogenic forcing. Model biases in atmospheric dynamics are one of the factors that increase uncertainty in projections of regional climate, precipitation and extreme events. Here we define requirements for diagnosing the atmospheric circulation and variability across temporal scales and for evaluating the transport of mass, momentum and energy by dynamical processes in the context of the Coupled Model Intercomparison Project Phase 6 (CMIP6). These diagnostics target the assessments of both resolved and parameterized dynamical processes in climate models, a novelty for CMIP, and are particularly vital for assessing the impact of the stratosphere on surface climate change.

Precipitation biases over southern Africa: examining the role of the Angola Low.

2020 ◽  
Author(s):  
Maria Chara Karypidou ◽  
Eleni Katragkou
Keyword(s):  
Southern Africa ◽  
Structural Model ◽  
Regional Climate ◽  
Potential Temperature ◽  
Coupled Model ◽  
Relative Vorticity ◽  
Specific Humidity ◽  
Wet Season ◽  
Pressure System ◽  
Intercomparison Project

<p>One of the main features controlling precipitation over southern Africa during the wet season is the Angola Low (AL) pressure system that appears as a heat low during October and November and as a tropical low during the climatological mean of December, January and February. The literature provides evidence that wet biases over southern Africa in the Coupled Model Intercomparison Project Phase 5 ensemble (CMIP5) are associated with a strongly simulated AL. In the current work, we examine the degree to which this observation holds for the CORDEX-Africa (Coordinated Regional Climate Downscaling Experiment - Africa) ensemble, using evaluation experiments forced with ERA-Interim at a spatial resolution of 0.44<sup>o</sup>. The analysis is performed using daily values for months October to March for the period 1990-2008. We characterize the precipitation bias over southern Africa using 10 satellite and gridded precipitation products. For the identification of the AL we use potential temperature at 850 hPa, specific humidity at 850 hPa and relative vorticity at 850 and 500 hPa. Our results highlight the fact that process-based evaluation of climate simulations are key in understanding structural model deficiencies. </p>

scholarly journals Using Co-Behavior Analysis to Interrogate the Performance of CMIP5 GCMs over Southern Africa

2020 ◽  
Vol 33 (7) ◽  
pp. 2891-2905
Author(s):  
Kwesi A. Quagraine ◽  
Bruce Hewitson ◽  
Christopher Jack ◽  
Piotr Wolski ◽  
Izidine Pinto ◽  
...  
Keyword(s):  
Climate Variability ◽  
Southern Africa ◽  
Large Scale ◽  
Regional Climate ◽  
Temperature Response ◽  
Coupled Model ◽  
Strong Response ◽  
Drought Pattern ◽  
Intercomparison Project ◽  
Research Analysis

AbstractAs established in earlier research, analysis of the combined roles (co-behavior) of multiple climate processes provides useful insights into the drivers of regional climate variability, especially for regions with no singular large-scale circulation control. Here, we extend the previous study in order to examine the performance of eight models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) in representing co-behavior influence on surface expressions over southern Africa. We find that although models broadly simulate observed precipitation responses over southern Africa, they fail to produce statistically strong response signals for an important drought pattern (El Niño co-behaving with positive Antarctic Oscillation during summer) for the region. We also demonstrate that the models show statistically strong temperature response signals to co-behavior that agree well with observed responses over the region. The multimodel ensemble mean although consistent with observations shows a larger spread. By elucidating the performance of models in representing observed co-behavior of climate processes, we are able to evaluate models while establishing important information for understanding of climate variability.

Constraining uncertainty in projected precipitation over land with Causal Discovery

2021 ◽  
Author(s):  
Kevin Debeire ◽  
Veronika Eyring ◽  
Peer Nowack ◽  
Jakob Runge
Keyword(s):  
Time Series ◽  
Model Evaluation ◽  
Climate Model ◽  
Coupled Model ◽  
Causal Discovery ◽  
Model Intercomparison ◽  
Simulated Precipitation ◽  
Intercomparison Project ◽  
Precipitation Changes ◽  
Global Precipitation

<p>The models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) deliver insights on the evolution of the Earth's  climate. The global precipitation changes follow the magnitude of the warming according to a recent study (Tebaldi, Debeire, Eyring et al., 2020) of the CMIP6 ensemble-mean. However, Earth systems models exhibit a large range in simulated precipitation projection over land. In this study, we present a potential approach to constrain the precipitation changes over land globally and regionally. This approach performs a process-oriented model evaluation similar to Nowack et al. study. We evaluate the ability of models to represent atmospheric dynamical interactions by applying Causal Discovery algorithm. We find a relationship between the ability to represent dynamical interactions close to the observations and the projected precipitation changes over land of the model. We show how this relationship can be used to constrain projection of precipitation over land.</p><p> </p><p>References:</p><p>Nowack, P., Runge, J., Eyring, V. et al. Causal networks for climate model evaluation and constrained projections. Nat Commun 11, 1415. https://doi.org/10.1038/s41467-020-15195-y, 2020.</p><p>Runge, J., P. Nowack, M. Kretschmer, S. Flaxman, D. Sejdinovic, Detecting and quantifying causal associations in large nonlinear time series datasets. Sci. Adv. 5, eaau4996, 2019.</p><p>Runge, J, Causal Network Reconstruction from Time Series: From Theoretical Assumptions to Practical Estimation. Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (7): 075310. https://aip.scitation.org/doi/10.1063/1.5025050, 2018.</p><p>Tebaldi, C., Debeire, K., Eyring, V., Fischer, E., Fyfe, J., Friedlingstein, P., Knutti, R., Lowe, J., O'Neill, B., Sanderson, B., van Vuuren, D., Riahi, K., Meinshausen, M., Nicholls, Z., Hurtt, G., Kriegler, E., Lamarque, J.-F., Meehl, G., Moss, R., Bauer, S. E., Boucher, O., Brovkin, V., Golaz, J.-C., Gualdi, S., Guo, H., John, J. G., Kharin, S., Koshiro, T., Ma, L., Olivié, D., Panickal, S., Qiao, F., Rosenbloom, N., Schupfner, M., Seferian, R., Song, Z., Steger, C., Sellar, A., Swart, N., Tachiiri, K., Tatebe, H., Voldoire, A., Volodin, E., Wyser, K., Xin, X., Xinyao, R., Yang, S., Yu, Y., and Ziehn, T.: Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6, Earth Syst. Dynam. Discuss. [preprint], https://doi.org/10.5194/esd-2020-68, in review, 2020.</p>

scholarly journals DynVarMIP: Assessing the Dynamics and Variability of the Stratosphere-Troposphere System

2016 ◽  
Author(s):  
Edwin P. Gerber ◽  
Elisa Manzini
Keyword(s):  
Climate Models ◽  
Energy Transport ◽  
Regional Climate ◽  
Coupled Model ◽  
Atmospheric Response ◽  
Model Intercomparison ◽  
Dynamical Processes ◽  
Surface Climate ◽  
Intercomparison Project ◽  
The Impact

Abstract. Diagnostics of atmospheric momentum and energy transport are needed to investigate the origin of circulation biases in climate models and to understand the atmospheric response to natural and anthropogenic forcing. Model biases in atmospheric dynamics are one of the factors that increase uncertainty in projections of regional climate, precipitation, and extreme events. Here we define requirements for diagnosing the atmospheric circulation and variability across temporal scales and for evaluating the transport of mass, momentum and energy by dynamical processes in the context of the Coupled Model Intercomparison Project Phase 6 (CMIP6). These diagnostics target the assessments of both resolved and parameterized dynamical processes in climate models, a novelty for CMIP, and are particularly vital for assessing the impact of the stratosphere on surface climate change.

scholarly journals A Revised View of Australia’s Future Climate

Eos ◽  
2020 ◽  
Vol 101 ◽  
Author(s):  
David Shultz
Keyword(s):  
Regional Climate ◽  
Coupled Model ◽  
Extreme Heat ◽  
Future Climate ◽  
Model Intercomparison ◽  
Extreme Heat Events ◽  
Intercomparison Project ◽  
Heat Events

The most recent generation of models of the Coupled Model Intercomparison Project better captures rainfall drivers, extreme heat events, and other facets of regional climate.

scholarly journals Future Changes in Simulated Evapotranspiration across Continental Africa Based on CMIP6 CNRM-CM6

2021 ◽  
Vol 18 (13) ◽  
pp. 6760
Author(s):  
Isaac Kwesi Nooni ◽  
Daniel Fiifi T. Hagan ◽  
Guojie Wang ◽  
Waheed Ullah ◽  
Jiao Lu ◽  
...  
Keyword(s):  
Extreme Events ◽  
Coupled Model ◽  
Baseline Period ◽  
Model Intercomparison ◽  
Additional Information ◽  
Intercomparison Project ◽  
Key Drivers ◽  
Model Ensembles ◽  
Projected Changes ◽  
Near Future

The main goal of this study was to assess the interannual variations and spatial patterns of projected changes in simulated evapotranspiration (ET) in the 21st century over continental Africa based on the latest Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) provided by the France Centre National de Recherches Météorologiques (CNRM-CM) model in the Sixth Phase of Coupled Model Intercomparison Project (CMIP6) framework. The projected spatial and temporal changes were computed for three time slices: 2020–2039 (near future), 2040–2069 (mid-century), and 2080–2099 (end-of-the-century), relative to the baseline period (1995–2014). The results show that the spatial pattern of the projected ET was not uniform and varied across the climate region and under the SSP-RCPs scenarios. Although the trends varied, they were statistically significant for all SSP-RCPs. The SSP5-8.5 and SSP3-7.0 projected higher ET seasonality than SSP1-2.6 and SSP2-4.5. In general, we suggest the need for modelers and forecasters to pay more attention to changes in the simulated ET and their impact on extreme events. The findings provide useful information for water resources managers to develop specific measures to mitigate extreme events in the regions most affected by possible changes in the region’s climate. However, readers are advised to treat the results with caution as they are based on a single GCM model. Further research on multi-model ensembles (as more models’ outputs become available) and possible key drivers may provide additional information on CMIP6 ET projections in the region.

scholarly journals Atmospheric and Surface Contributions to Planetary Albedo

2011 ◽  
Vol 24 (16) ◽  
pp. 4402-4418 ◽  
Author(s):  
Aaron Donohoe ◽  
David S. Battisti
Keyword(s):  
Surface Albedo ◽  
Coupled Model ◽  
Small Contribution ◽  
Model Intercomparison ◽  
Radiation Model ◽  
Phase 3 ◽  
Surface Reflection ◽  
Global Average ◽  
Intercomparison Project ◽  
Planetary Albedo

Abstract The planetary albedo is partitioned into a component due to atmospheric reflection and a component due to surface reflection by using shortwave fluxes at the surface and top of the atmosphere in conjunction with a simple radiation model. The vast majority of the observed global average planetary albedo (88%) is due to atmospheric reflection. Surface reflection makes a relatively small contribution to planetary albedo because the atmosphere attenuates the surface contribution to planetary albedo by a factor of approximately 3. The global average planetary albedo in the ensemble average of phase 3 of the Coupled Model Intercomparison Project (CMIP3) preindustrial simulations is also primarily (87%) due to atmospheric albedo. The intermodel spread in planetary albedo is relatively large and is found to be predominantly a consequence of intermodel differences in atmospheric albedo, with surface processes playing a much smaller role despite significant intermodel differences in surface albedo. The CMIP3 models show a decrease in planetary albedo under a doubling of carbon dioxide—also primarily due to changes in atmospheric reflection (which explains more than 90% of the intermodel spread). All models show a decrease in planetary albedo due to the lowered surface albedo associated with a contraction of the cryosphere in a warmer world, but this effect is small compared to the spread in planetary albedo due to model differences in the change in clouds.

scholarly journals Atlantic Meridional Overturning Circulation (AMOC) in CMIP5 Models: RCP and Historical Simulations

2013 ◽  
Vol 26 (18) ◽  
pp. 7187-7197 ◽  
Author(s):  
Wei Cheng ◽  
John C. H. Chiang ◽  
Dongxiao Zhang
Keyword(s):  
North Atlantic ◽  
Coupled Model ◽  
Meridional Overturning Circulation ◽  
First Century ◽  
Model Intercomparison ◽  
The North ◽  
Intercomparison Project ◽  
Meridional Overturning ◽  
The North Atlantic ◽  
Twenty First Century

Abstract The Atlantic meridional overturning circulation (AMOC) simulated by 10 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) for the historical (1850–2005) and future climate is examined. The historical simulations of the AMOC mean state are more closely matched to observations than those of phase 3 of the Coupled Model Intercomparison Project (CMIP3). Similarly to CMIP3, all models predict a weakening of the AMOC in the twenty-first century, though the degree of weakening varies considerably among the models. Under the representative concentration pathway 4.5 (RCP4.5) scenario, the weakening by year 2100 is 5%–40% of the individual model's historical mean state; under RCP8.5, the weakening increases to 15%–60% over the same period. RCP4.5 leads to the stabilization of the AMOC in the second half of the twenty-first century and a slower (then weakening rate) but steady recovery thereafter, while RCP8.5 gives rise to a continuous weakening of the AMOC throughout the twenty-first century. In the CMIP5 historical simulations, all but one model exhibit a weak downward trend [ranging from −0.1 to −1.8 Sverdrup (Sv) century−1; 1 Sv ≡ 106 m3 s−1] over the twentieth century. Additionally, the multimodel ensemble–mean AMOC exhibits multidecadal variability with a ~60-yr periodicity and a peak-to-peak amplitude of ~1 Sv; all individual models project consistently onto this multidecadal mode. This multidecadal variability is significantly correlated with similar variations in the net surface shortwave radiative flux in the North Atlantic and with surface freshwater flux variations in the subpolar latitudes. Potential drivers for the twentieth-century multimodel AMOC variability, including external climate forcing and the North Atlantic Oscillation (NAO), and the implication of these results on the North Atlantic SST variability are discussed.

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