Hydrological droughts in the southern Andes (40–45°S) from an ensemble experiment using CMIP5 and CMIP6 models

AbstractThe decrease in freshwater input to the coastal system of the Southern Andes (40–45°S) during the last decades has altered the physicochemical characteristics of the coastal water column, causing significant environmental, social and economic consequences. Considering these impacts, the objectives were to analyze historical severe droughts and their climate drivers, and to evaluate the hydrological impacts of climate change in the intermediate future (2040–2070). Hydrological modelling was performed in the Puelo River basin (41°S) using the Water Evaluation and Planning (WEAP) model. The hydrological response and its uncertainty were compared using different combinations of CMIP projects (n = 2), climate models (n = 5), scenarios (n = 3) and univariate statistical downscaling methods (n = 3). The 90 scenarios projected increases in the duration, hydrological deficit and frequency of severe droughts of varying duration (1 to 6 months). The three downscaling methodologies converged to similar results, with no significant differences between them. In contrast, the hydroclimatic projections obtained with the CMIP6 and CMIP5 models found significant climatic (greater trends in summer and autumn) and hydrological (longer droughts) differences. It is recommended that future climate impact assessments adapt the new simulations as more CMIP6 models become available.

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Storylines of UK drought based on the 2010-2012 event

10.5194/egusphere-egu21-1544 ◽

2021 ◽

Author(s):

Wilson Chan ◽

Theodore Shepherd ◽

Katie Smith ◽

Geoff Darch ◽

Nigel Arnell

Keyword(s):

Climate Change ◽

Stress Test ◽

Economic Consequences ◽

Drought Characteristics ◽

Singular Event ◽

Climate Change Model ◽

The Uk ◽

Event Based ◽

Hydrological Droughts ◽

Impacts Of Climate Change

Spatially extensive multi-year hydrological droughts threaten water resources availability and incur significant environmental and socio-economic consequences. Given the impacts of climate change, the UK is expected to remain vulnerable to future multi-year droughts. Existing approaches to quantify hydrological impacts of climate change are often scenario-driven and may miss out plausible outcomes with significant impacts. Event-based storyline approaches aim to quantify &#8220;storylines&#8221; of how a singular event with significant impacts could hypothetically have unfolded in alternative ways from plausible changes to its causal factors under present and future climate. This study uses the 2010-2012 UK drought, the most recent period of severe hydrological drought, as a basis, to create counterfactual storylines based on changes to 1) precondition severity, 2) temporal drought sequence and 3) climate change. Model simulations are performed using the GR4J hydrological model and drought characteristics for each counterfactual storyline is calculated using the Standardized Streamflow Index at multiple accumulation periods.The storylines show that maximum intensity, mean deficit and duration of the 2010-2012 drought were highly conditioned by its meteorological preconditions. Recovery time from progressively drier preconditions reflect both spatial variation in drought characteristics and the influence of physical catchment characteristics, particularly hydrogeology, in the propagation of multi-year droughts. Plausible storylines of an additional dry year with dry winter conditions repeated before the observed drought or replacing the observed dramatic drought termination confirm the vulnerability of UK catchments to a &#8220;three dry winter&#8221; scenario. Application of the UKCP18 projections at four global warming levels explore the impacts of the drought in a warmer world. Drought conditions of the storylines could have matched and exceeded that experienced in past severe droughts, especially for southern catchments. The construction of storylines based on observed events can complement existing methods to stress test UK catchments against plausible unrealized droughts.

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Spatio-temporal consistent bias pattern detection on MIROC5 andFGOALS-g2

10.5194/gmd-2019-107 ◽

2019 ◽

Author(s):

Bo Cao ◽

Ying Zhao ◽

Ziheng Zhou

Keyword(s):

Climate Models ◽

Climate Model ◽

Model Performance ◽

Climate System ◽

Cmip5 Models ◽

Seasonal Characteristics ◽

Double Itcz ◽

Model Improvement ◽

Spatio Temporal ◽

Impacts Of Climate Change

Abstract. Building climate models is a typical means of studying the dynamics of the climate system and assessing the impacts of climate change. However, model-related biases are common in existing climate models, such as the double ITCZ bias in most CMIP5 models. Recent studies suggest that biases showing distinct spatio-temporal characteristics may involve different mechanisms and sources in climate models. More dedicated studies on bias patterns is important not only for improving model performance, but also for helping modelers to better understand the climate system. In this paper, we focus on detecting spatio-temporal consistent bias patterns from climate model outputs. A spatio-temporal pattern is a bias pattern that is present in contiguous space with significant and coherent biases in continuous time periods. These patterns are ideal for revealing regional and seasonal characteristics of biases and worth further investigation by modelers. Due to the high computation cost, most of the existing analysis methods can only detect bias patterns that are either spatial consistent or temporal consistent, but not both at the same time. We proposed a bottom-up algorithm to tackle this problem. The proposed method first detects regions showing significant and consistent biases at each time slot and then merges them iteratively to form bias instances. The resulting bias instances are further clustered into different families to depict corresponding spatio-temporal consistent bias patterns. The experiments on both MIROC5 and FGOALS-g2 precipitation outputs show that the proposed approach can detect some important bias patterns that are consistent with previous studies and can produce other interesting findings. Modelers can adopt the proposed method as an exploratory tool to develop insights for bias correction and model improvement.

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Climate Drift in the CMIP5 Models*

Journal of Climate ◽

10.1175/jcli-d-12-00521.1 ◽

2013 ◽

Vol 26 (21) ◽

pp. 8597-8615 ◽

Cited By ~ 128

Author(s):

Alexander Sen Gupta ◽

Nicolas C. Jourdain ◽

Jaclyn N. Brown ◽

Didier Monselesan

Keyword(s):

Climate Models ◽

Coupled Model ◽

Deep Ocean ◽

Internal Variability ◽

Correction Method ◽

Physical Models ◽

Cmip5 Models ◽

Steric Sea Level ◽

Biogeochemical Models ◽

The Difference

Abstract Climate models often exhibit spurious long-term changes independent of either internal variability or changes to external forcing. Such changes, referred to as model “drift,” may distort the estimate of forced change in transient climate simulations. The importance of drift is examined in comparison to historical trends over recent decades in the Coupled Model Intercomparison Project (CMIP). Comparison based on a selection of metrics suggests a significant overall reduction in the magnitude of drift from phase 3 of CMIP (CMIP3) to phase 5 of CMIP (CMIP5). The direction of both ocean and atmospheric drift is systematically biased in some models introducing statistically significant drift in globally averaged metrics. Nevertheless, for most models globally averaged drift remains weak compared to the associated forced trends and is often smaller than the difference between trends derived from different ensemble members or the error introduced by the aliasing of natural variability. An exception to this is metrics that include the deep ocean (e.g., steric sea level) where drift can dominate in forced simulations. In such circumstances drift must be corrected for using information from concurrent control experiments. Many CMIP5 models now include ocean biogeochemistry. Like physical models, biogeochemical models generally undergo long spinup integrations to minimize drift. Nevertheless, based on a limited subset of models, it is found that drift is an important consideration and must be accounted for. For properties or regions where drift is important, the drift correction method must be carefully considered. The use of a drift estimate based on the full control time series is recommended to minimize the contamination of the drift estimate by internal variability.

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Evaluating temperature extremes in CMIP6 simulations using statistically proper evaluation methods

10.5194/egusphere-egu21-9722 ◽

2021 ◽

Author(s):

Thordis Thorarinsdottir ◽

Jana Sillmann ◽

Marion Haugen ◽

Nadine Gissibl ◽

Marit Sandstad

Keyword(s):

Air Temperature ◽

Model Evaluation ◽

Climate Models ◽

Climate Model ◽

Mean Squared Error ◽

Surface Air Temperature ◽

Cmip5 Models ◽

Model Output ◽

Intergovernmental Panel ◽

Near Surface

Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important&#160;as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.

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EL NINO EFFECTS ON THE ARCTIC STRATOSPHERE ACCORDING TO CMIP5 MODELS AND REANALYSIS

Meteorologiya i Gidrologiya ◽

10.52002/0130-2906-2021-6-5-23 ◽

2021 ◽

pp. 5-23

Author(s):

M. A. Kolennikova ◽

◽

P. N. Vargin ◽

D. Yu. Gushchina ◽

◽

...

Keyword(s):

El Niño ◽

Climate Models ◽

El Nino ◽

Reanalysis Data ◽

The Arctic ◽

Cmip5 Models ◽

Composite Analysis ◽

Central Pacific ◽

Coupled Climate Models

The response of the Arctic stratosphere to El Nio is studied with account of its Eastern and Central Pacific types for the period of 1950-2005. The study is based on the regression and composite analysis using the simulations with six CMIP5 coupled climate models and reanalysis data.

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Smallholder Farmers’ Vulnerability to Impact of Climate Change in Central Bhutan

International Journal of Environment and Climate Change ◽

10.9734/ijecc/2020/v10i1230305 ◽

2020 ◽

pp. 286-299

Author(s):

Pema Rinzin ◽

Thubten Sonam ◽

Sangay Tshering ◽

Purna Prasad Chapagai

Keyword(s):

Climate Change ◽

Adaptive Capacity ◽

Smallholder Farmers ◽

Composite Index ◽

Climate Impact ◽

Food Component ◽

Central Regions ◽

Framework Approach ◽

Context Specific ◽

Impacts Of Climate Change

Climate change carries immense threat to the livelihood and food security of smallholder farmers in Bhutan and it is therefore crucial to enhance their adaptive capacity. However, building resiliency to climate impact require information on vulnerability of the system of interest. Therefore, this study assessed smallholder farmers’ vulnerability to impacts of climate change and variability in central regions (Bumthang and Trongsa) of Bhutan. Data was collected from 247 randomly selected households by administering a pre-tested survey questionnaire. Data was analyzed using composite index approach (LVI) and IPCC framework approach (LVI-IPCC). The LVI analysis revealed that Bumthang was more vulnerable in terms of Socio-demographic profile (0.55), social networks (0.45), health (0.31) and natural disasters and climate variability (0.47) compared to Trongsa. Whereas, Trongsa was more vulnerable in terms of livelihood strategies (0.31) and water (0.13). Vulnerability score on the food component was same for both the districts (0.27). Overall, Bumthang was more vulnerable compared to Trongsa on both LVI (Bumthang: 0.36, Trongsa: 0.34) and LVI-IPCC (Bumthang: 0.24, Trongsa: 0.13) analysis. The findings could be used for designing micro-level context specific interventions to enhance smallholder farmers’ adaptive capacity to impacts of climate change in central Bhutan.

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Reduced global warming from CMIP6 projections when weighting models by performance and independence

Earth System Dynamics ◽

10.5194/esd-11-995-2020 ◽

2020 ◽

Vol 11 (4) ◽

pp. 995-1012

Author(s):

Lukas Brunner ◽

Angeline G. Pendergrass ◽

Flavio Lehner ◽

Anna L. Merrifield ◽

Ruth Lorenz ◽

...

Keyword(s):

Climate Change ◽

Retrospective Analysis ◽

Climate Models ◽

Cmip5 Models ◽

Future Climate Change ◽

Historical Period ◽

Climate Change Scenarios ◽

Uncertainty Range ◽

Future Warming ◽

The Mean

Abstract. The sixth Coupled Model Intercomparison Project (CMIP6) constitutes the latest update on expected future climate change based on a new generation of climate models. To extract reliable estimates of future warming and related uncertainties from these models, the spread in their projections is often translated into probabilistic estimates such as the mean and likely range. Here, we use a model weighting approach, which accounts for the models' historical performance based on several diagnostics as well as model interdependence within the CMIP6 ensemble, to calculate constrained distributions of global mean temperature change. We investigate the skill of our approach in a perfect model test, where we use previous-generation CMIP5 models as pseudo-observations in the historical period. The performance of the distribution weighted in the abovementioned manner with respect to matching the pseudo-observations in the future is then evaluated, and we find a mean increase in skill of about 17 % compared with the unweighted distribution. In addition, we show that our independence metric correctly clusters models known to be similar based on a CMIP6 “family tree”, which enables the application of a weighting based on the degree of inter-model dependence. We then apply the weighting approach, based on two observational estimates (the fifth generation of the European Centre for Medium-Range Weather Forecasts Retrospective Analysis – ERA5, and the Modern-Era Retrospective analysis for Research and Applications, version 2 – MERRA-2), to constrain CMIP6 projections under weak (SSP1-2.6) and strong (SSP5-8.5) climate change scenarios (SSP refers to the Shared Socioeconomic Pathways). Our results show a reduction in the projected mean warming for both scenarios because some CMIP6 models with high future warming receive systematically lower performance weights. The mean of end-of-century warming (2081–2100 relative to 1995–2014) for SSP5-8.5 with weighting is 3.7 ∘C, compared with 4.1 ∘C without weighting; the likely (66%) uncertainty range is 3.1 to 4.6 ∘C, which equates to a 13 % decrease in spread. For SSP1-2.6, the weighted end-of-century warming is 1 ∘C (0.7 to 1.4 ∘C), which results in a reduction of −0.1 ∘C in the mean and −24 % in the likely range compared with the unweighted case.

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A Mass and Energy Conservation Analysis of Drift in the CMIP6 Ensemble

10.22541/au.161618917.70147304/v1 ◽

2021 ◽

Author(s):

Damien Irving

Keyword(s):

Climate Models ◽

Heat Content ◽

Moisture Flux ◽

Cmip5 Models ◽

Energy Budgets ◽

Freshwater Flux ◽

Atmospheric Moisture ◽

State Variables ◽

Conservation Of Energy ◽

Ocean Mass

Coupled climate models are prone to ‘drift’ (long-term unforced trends in state variables) due to incomplete spin-up and non-closure of the global mass and energy budgets. Here we assess model drift and the associated conservation of energy, mass and salt in CMIP6 and CMIP5 models. For most models, drift in globally-integrated ocean mass and heat content represents a small but non-negligible fraction of recent historical trends, while drift in atmospheric water vapor is negligible. Model drift tends to be much larger in time-integrated ocean heat and freshwater flux, net top-of-the-atmosphere radiation (netTOA) and moisture flux into the atmosphere (evaporation minus precipitation), indicating a substantial leakage of mass and energy in the simulated climate system. Most models are able to achieve approximate energy budget closure after drift is removed, but ocean mass budget closure eludes a number of models even after de-drifting and none achieve closure of the atmospheric moisture budget. The magnitude of the drift in the CMIP6 ensemble represents an improvement over CMIP5 in some cases (salinity and time-integrated netTOA) but is worse (time-integrated ocean freshwater and atmospheric moisture fluxes) or little changed (ocean heat content, ocean mass and time-integrated ocean heat flux) for others, while closure of the ocean mass and energy budgets after drift removal has improved.

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A statistical examination of the effects of stratospheric sulphate geoengineering on tropical storm genesis

10.5194/acp-2018-142 ◽

2018 ◽

Cited By ~ 1

Author(s):

Qin Wang ◽

John C. Moore ◽

Duoying Ji

Keyword(s):

Relative Humidity ◽

Wind Shear ◽

Climate Models ◽

Climate Model ◽

Vertical Wind Shear ◽

Stratospheric Aerosol ◽

Vertical Wind ◽

Radiative Heating ◽

Cmip5 Models ◽

The North

Abstract. The thermodynamics of the ocean and atmosphere partly determine variability in tropical cyclone (TC) number and intensity and are readily accessible from climate model output, but a complete description of TC variability requires much more dynamical data than climate models can provide at present. Genesis potential index (GPI) and ventilation index (VI) are combinations of potential intensity, vertical wind shear, relative humidity, midlevel entropy deficit, and absolute vorticity that can quantify both thermodynamic and dynamic forcing of TC activity under different climate states. Here we use six CMIP5 models that have run the RCP4.5 experiment and the Geoengineering Model Intercomparison Project (GeoMIP) stratospheric aerosol injection G4 experiment, to calculate the two TC indices over the 2020 to 2069 period across the 6 ocean basins that generate tropical cyclones. Globally, GPI under G4 is lower than under RCP4.5, though both have a slight increasing trend. Spatial patterns in the effectiveness of geoengineering show reductions in TC in the North Atlantic basin, and Northern Indian Ocean in all models except NorESM1-M. In the North Pacific, most models also show relative reductions under G4. Most models project potential intensity and relative humidity to be the dominant variables affecting genesis potential. Changes in vertical wind shear are significant, but both it and vorticity exhibit relatively small changes with large variation across both models and ocean basins. We find that tropopause temperature is not a useful addition to sea surface temperature in projecting TC genesis, despite radiative heating of the stratosphere due to the aerosol injection, and heating of the upper troposphere affecting static stability and potential intensity. Thus, simplified statistical methods that quantify the thermodynamic state of the major genesis basins may reasonably be used to examine stratospheric aerosol geoengineering impacts on TC activity.

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The response of the ozone layer under abrupt 4xCO2 in CMIP6

10.5194/egusphere-egu21-15283 ◽

2021 ◽

Author(s):

Gabriel Chiodo ◽

William T. Ball ◽

Peer Nowack ◽

Clara Orbe ◽

James Keeble ◽

...

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Stratospheric Ozone ◽

Ozone Layer ◽

Cmip5 Models ◽

Radiative Efficiency ◽

Tropospheric Circulation ◽

Column Ozone ◽

The Relationship

Previous studies indicate a possible role of stratospheric ozone chemistry feedbacks in the climate response to 4xCO2, either via a reduction in equilibrium climate sensitivity (ECS) or via changes in the tropospheric circulation (Nowack et al., 2015; Chiodo and Polvani, 2017). However, these effects are subject to uncertainty. Part of the uncertainty may stem from the dependency of the feedback on the pattern of the ozone response, as the radiative efficiency of ozone largely depends on its vertical distribution (Lacis et al., 1990). Here, an analysis is presented of the ozone layer response to 4xCO2 in chemistry&#8211;climate models (CCMs) which participated to CMIP inter-comparisons. In a previous study using CMIP5 models, it has been shown that under 4xCO2, ozone decreases in the tropical lower stratosphere, and increases over the high latitudes and throughout the upper stratosphere (Chiodo et al., 2018). It was also found that a substantial portion of the spread in the tropical column ozone is tied to inter-model spread in tropical upwelling, which is in turn tied to ECS. Here, we revisit this connection using 4xCO2 data from CMIP6, thereby exploiting the larger number of CCMs available than in CMIP5. In addition, we explore the linearity of the ozone response, by complementing the analysis with simulations using lower CO2 forcing levels (2xCO2). We show that the pattern of the ozone response is similar to CMIP5. In some models (e.g. WACCM), we find larger ozone responses in CMIP6 than in CMIP5, partly because of the larger ECS and thus larger upwelling response in the tropical pipe. In this presentation, we will discuss the relationship between radiative forcing, transport and ozone, as well as further implications for CMIP6 models.

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