Climate Model Intercomparison Project Phase Research Articles

A storyline view of the projected role of remote drivers on summer air stagnation in Europe and the United States

Storylines of atmospheric circulation change, or physically self-consistent narratives of plausible future events, have recently been proposed as a non-probabilistic means to represent uncertainties in climate change projections. Here, we apply the storyline approach to 21st century projections of summer air stagnation over Europe and the United States. We use a Climate Model Intercomparison Project Phase 6 (CMIP6) ensemble to generate stagnation storylines based on the forced response of three remote drivers of the Northern Hemisphere mid-latitude atmospheric circulation: North Atlantic warming, North Pacific warming, and tropical versus Arctic warming. Under a high radiative forcing scenario (SSP5-8.5), models consistently project increases in stagnation over Europe and the U.S., but the magnitude and spatial distribution of changes vary substantially across CMIP6 ensemble members, suggesting that future projections are not well-constrained when using the ensemble mean alone. We find that the diversity of projected stagnation changes depends on the forced response of remote drivers in individual models. This is especially true in Europe, where differences of ∼2 summer stagnant days per degree of global warming are found amongst the different storyline combinations. For example, the greatest projected increase in stagnation for most European regions leads to the smallest increase in stagnation for southwestern Europe; i.e. limited North Atlantic warming combined with near-equitable tropical and Arctic warming. In the U.S., only the atmosphere over the northern Rocky Mountain states demonstrates comparable stagnation projection uncertainty, due to opposite influences of remote drivers on the meteorological conditions that lead to stagnation.

Climate change projections and trends simulated from the CMIP5 models for the Lake Tana sub-basin, the Upper Blue Nile (Abay) River Basin, Ethiopia

Climate change is mainly refers to the long-term fluctuations in the weather parameters of a large area with statistical significance. Earth's climate change is either due to natural variability or human activity, in combination. The Lake Tana basin has been studied to project future climate change using the Statistical DownSclaing Model (SDSM). The SDSM was used to downscale both temperature and precipitation from Canadian Earth System Model version 2 (CanESM2) Global Climate Models (GCMs) for Bahir Dar, Dangila, Debre Tabor and Gonder synoptic weather stations. The Manna Kendall non-parametric test was then used to examine both the baseline and projected precipitation and temperature trends. The historical or baseline data for downscaling purpose was obtained from National Meteorological Agency, Ethiopia (NMA) while large-scale predictor variables were obtained under Climate Model Intercomparison Project Phase 5 (CMIP5). Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 radiative forcing scenarios have been derived from the CanESM2 model. The performance of SDSM have been validated by using various statistical methods, such as RMSE, NSE, R and R2. The SDSM results are not reliablefor projecting the precipitation as compared to maximum and minimum temperatures. These findings indicated that maximum temperature tend to increase from 1.38 °C to 3.59 °C under RCP4.5 radiative forcing scenario by the year 2080s, while minimum temperature is projected to increase up to 5.92 °C under RCP8.5 by the end of the 21st century in the Lake Tana sub-basin. On the other hand, precipitation projection did not show consistent pattern over the basin. For instance, precipitation is projected to increase up to 255 mm in the northern and central parts of the basin, however, but relatively lower result (up to 200 mm) from the RCP8.5 radiative forcing scenarios by year 2080s. By considering Mann-Kendal trend test, the baseline and projected mean annual maximum and minimum temperatures show increasing trend, while baseline rainfall shows increasing trend, but projected rainfall shows a decreasing trend at Dangila and Debre Tabor stations. Whereas, an increasing trend noticed at Bahir Dar and Gonder stations. Therefore, basin or watershed scale climate change adaptation and mitigation strategies have be developed to minimize the negative impacts of climate change.

An appraisal of seasonal precipitation dynamics over the North‐West Himalayan region under future warming scenarios

ABSTRACTIn the context of widely reported climate change over the mountainous region, the present work addresses the notable changes in the seasonal precipitation dynamics over the NWH region under two different future warming scenarios [socioeconomic pathway 245 (SSP245) and socio economic pathway 585 (SSP585)]. Using three coupled climate models which participated in the Climate Model Inter‐comparison Project Phase 6 (CMIP6), we focus on the alterations of the spatio‐temporal pattern of solid and liquid precipitation in respective seasons under future warming (2066–2100) scenarios with respect to the historical time period (1981–2014). Intercomparative validation of the CMIP6 data sets has been carried out against the GPCP and ERA‐5 reanalysis datasets where the multimodel mean (MMM) product has performed well (r value = 0.63) compared with the individual model outputs in the historical scenario for last 35 years (1981–2014). Therefore, MMM has been used for analysis. Statistically robust K–S test suggests a remarkable variation in the cumulative distribution of the precipitation across the NWH region at 95% confidence level in both of the future warming scenarios as compared with the historical time period. Furthermore, significant increase in the JJAS rainfall (~25–30%) and decrease in the DJF snowfall (~20–25%) has been observed for ssp585 scenario whereas no significant results are noted under ssp245 scenario. Remarkable variations in the surface temperature distribution, large scale wind circulation pattern and mesoscale hydrometeorological balance under the warmest scenario (SSP585) elucidate the reason behind the noteworthy changes in the precipitation dynamics reflected from the normalized precipitation index (NPI) and changes in annual cycle and therefore illustrates the possibility of more extreme precipitation years in future. The overall investigation reflects the possible effect of climate change over the NWH region pertaining to the dynamics of the South West Monsoon and Western Disturbances.

Southern Ocean polynyas in CMIP6 models

Abstract. Polynyas facilitate air–sea fluxes, impacting climate-relevant properties such as sea ice formation and deep water production. Despite their importance, polynyas have been poorly represented in past generations of climate models. Here we present a method to track the presence, frequency and spatial distribution of polynyas in the Southern Ocean in 27 models participating in the Climate Model Intercomparison Project Phase 6 (CMIP6) and two satellite-based sea ice products. Only half of the 27 models form open-water polynyas (OWPs), and most underestimate their area. As in satellite observations, three models show episodes of high OWP activity separated by decades of no OWP, while other models unrealistically create OWPs nearly every year. In contrast, the coastal polynya area is overestimated in most models, with the least accurate representations occurring in the models with the coarsest horizontal resolution. We show that the presence or absence of OWPs is linked to changes in the regional hydrography, specifically the linkages between polynya activity with deep water convection and/or the shoaling of the upper water column thermocline. Models with an accurate Antarctic Circumpolar Current transport and wind stress curl have too frequent OWPs. Biases in polynya representation continue to exist in climate models, which has an impact on the regional ocean circulation and ventilation that should be addressed. However, emerging iceberg discharge schemes, more adequate vertical grid type or overflow parameterisation are anticipated to improve polynya representations and associated climate prediction in the future.

The Convective‐To‐Total Precipitation Ratio and the “Drizzling” Bias in Climate Models

AbstractOverestimation of precipitation frequency and duration while underestimating intensity, that is, the “drizzling” bias, has been a long‐standing problem of global climate models. Here we explore this issue from the perspective of precipitation partitioning. We found that most models in the Climate Model Intercomparison Project Phase 5 (CMIP5) have high convective‐to‐total precipitation (PC/PR) ratios in low latitudes. Convective precipitation has higher frequency and longer duration but lower intensity than non‐convective precipitation in many models. As a result, the high PC/PR ratio contributes to the “drizzling” bias over low latitudes. The PC/PR ratio and associated “drizzling” bias increase as model resolution coarsens from 0.5° to 2.0°, but the resolution's effect weakens as the grid spacing increases from 2.0° to 3.0°. Some of the CMIP6 models show reduced “drizzling” bias associated with decreased PC/PR ratio. Thus, more reasonable precipitation partitioning, along with finer model resolution should alleviate the “drizzling” bias within current climate models.

Identifying the sources of uncertainty in climate model simulations of solar radiation modification with the G6sulfur and G6solar Geoengineering Model Intercomparison Project (GeoMIP) simulations

Abstract. We present here results from the Geoengineering Model Intercomparison Project (GeoMIP) simulations for the experiments G6sulfur and G6solar for six Earth system models participating in the Climate Model Intercomparison Project (CMIP) Phase 6. The aim of the experiments is to reduce the warming that results from a high-tier emission scenario (Shared Socioeconomic Pathways SSP5-8.5) to that resulting from a medium-tier emission scenario (SSP2-4.5). These simulations aim to analyze the response of climate models to a reduction in incoming surface radiation as a means to reduce global surface temperatures, and they do so either by simulating a stratospheric sulfate aerosol layer or, in a more idealized way, through a uniform reduction in the solar constant in the model. We find that over the final two decades of this century there are considerable inter-model spreads in the needed injection amounts of sulfate (29 ± 9 Tg-SO2/yr between 2081 and 2100), in the latitudinal distribution of the aerosol cloud and in the stratospheric temperature changes resulting from the added aerosol layer. Even in the simpler G6solar experiment, there is a spread in the needed solar dimming to achieve the same global temperature target (1.91 ± 0.44 %). The analyzed models already show significant differences in the response to the increasing CO2 concentrations for global mean temperatures and global mean precipitation (2.05 K ± 0.42 K and 2.28 ± 0.80 %, respectively, for SSP5-8.5 minus SSP2-4.5 averaged over 2081–2100). With aerosol injection, the differences in how the aerosols spread further change some of the underlying uncertainties, such as the global mean precipitation response (−3.79 ± 0.76 % for G6sulfur compared to −2.07 ± 0.40 % for G6solar against SSP2-4.5 between 2081 and 2100). These differences in the behavior of the aerosols also result in a larger uncertainty in the regional surface temperature response among models in the case of the G6sulfur simulations, suggesting the need to devise various, more specific experiments to single out and resolve particular sources of uncertainty. The spread in the modeled response suggests that a degree of caution is necessary when using these results for assessing specific impacts of geoengineering in various aspects of the Earth system. However, all models agree that compared to a scenario with unmitigated warming, stratospheric aerosol geoengineering has the potential to both globally and locally reduce the increase in surface temperatures.

Probabilistic projections of future warming and climate sensitivity trajectories

Abstract Projections of future global mean surface warming for a given forcing scenario remain uncertain, largely due to uncertainty in the climate sensitivity. The ensemble of Earth system models from the Climate Model Intercomparison Project phase 6 (CMIP6) represents the dominant tools for projecting future global warming. However, the distribution of climate sensitivities within the CMIP6 ensemble is not representative of recent independent probabilistic estimates, and the ensemble contains significant variation in simulated historic surface warming outside agreement with observational datasets. Here, a Bayesian approach is used to infer joint probabilistic projections of future surface warming and climate sensitivity for shared socio-economic pathway (SSP) scenarios. The projections use an efficient climate model ensemble filtered and weighted to encapsulate observational uncertainty in historic warming and ocean heat content anomalies. The probabilistic projection of climate sensitivity produces a best estimate of 2.9°C, and 5th–95th percentile range of 1.5–4.6°C, in line with previous estimates using multiple lines of evidence. The joint projection of surface warming over the period 2030–40 has a 50% or greater probability of exceeding 1.5°C above preindustrial for all SSPs considered: 119, 126, 245, 370 and 585. Average warming by the period 2050–60 has a >50% chance of exceeding 2°C for SSPs 245, 370 and 585. These results imply that global warming is no longer likely to remain under 1.5°C, even with drastic and immediate mitigation, and highlight the importance of urgent action to avoid exceeding 2°C warming.

A perturbed parameter ensemble of HadGEM3-GC3.05 coupled model projections: part 2: global performance and future changes

This paper provides a quantitative assessment of large-scale features in a perturbed parameter ensemble (PPE) of Met Office Unified Model HadGEM-GC3.05 in coupled global historical and future simulations. The main motivation for the simulations is to provide a major component of the UK Climate Projections 2018 (UKCP18), but they will also be used to make worldwide projections and inform future model development. Initially, a 25-member PPE, with 25 different parameter combinations, was simulated. Five members were subsequently dropped because either their simulated climate was unrealistically cool by 1970 or they suffered from numerical instabilities. The remaining 20 members were evaluated after completing the historical phase (1900–2005) against 13 separately selected Climate Model Intercomparison Project Phase 5 (CMIP5) models, and five more members were dropped. The final product is a combined projection system of 15 PPE members and 13 CMIP5 models, which has a number of benefits. In particular, the range of outcomes available from the combined set of 28 is often larger than from either of the two constituent ensembles, thus providing users with a more complete picture of plausible impacts. Here we mainly describe the evaluation process of the 20 PPE members. We evaluate biases in a number of important properties of the global coupled system, including assessment of climatological averages, coupled modes of internal variability and historical and future changes. The parameter combinations yielded plausible yet diverse atmosphere and ocean model behaviours. The range of global temperature changes is narrow, largely driven by use of different CO2 pathways. The range of global warming is seemingly not linked to range of feedbacks estimated from atmosphere-only runs, though we caution that the range of the latter is narrow relative to CMIP5, and therefore this result is not unexpected. This is the second of two papers describing the generation of the PPE for UKCP18 projections. Part 1 (Sexton et al. 2021) describes the selection of 25 parameter combinations of 47 atmosphere and land surface parameters, using a set of cheap atmosphere-only runs at a coarser resolution from nearly 3000 samples of parameter space.

Comparisons Between CMIP5 and CMIP6 Models: Simulations of Climate Indices Influencing Food Security, Infrastructure Resilience, and Human Health in Canada

AbstractThe warming climate can considerably affect socioeconomic activities and environmental health conditions in Canada. Climate models play a key role in evaluating the impact of climate change and developing adaption and mitigation strategies corresponding to Canadian regions. This study compares the behavior of climate models participating in the Climate Model Intercomparison Project Phase 6 (CMIP6) with their CMIP5 predecessors in representing a set of climate indices relevant to Canada’s agricultural productivity, infrastructure resilience, and environmental health. Our results show that although CMIP5 and CMIP6 multi‐model ensemble mean values for the considered indices are almost similar, the behavior of individual CMIP5 and CMIP6 models or even the model pairs of the same modeling center can be different across Canada. Moreover, the CMIP6 models do not necessarily outperform CMIP5 in comparison to NOAA and NCEP reanalysis datasets in simulating the annual mean and coefficient of variation values for the indices during the historical period. The comparisons between models’ simulations also reveal that the envelope of estimated values based on individual CMIP6 models does not cover or overlap with their CMIP5 counterparts or even with other CMIP6 models. Therefore, the CMIP6 models with higher number of simulations do not necessarily provide a larger range of projections over Canadian regions. The divergence between CMIP5 and CMIP6 models’ behavior is more obvious under the 8.5 W/m2 forcing in the long‐term horizon. Overall, the estimated sign, magnitude, and spatial pattern of changes in the climate indices depend on the considered climate model and forcing scenario.

Diversity in the Simulation of Chlorophyll Concentration by CMIP5 Earth System Models over the Indian Ocean

Among many other physical and biogeochemical processes, oceanic upwelling is a major contributor to the primary productivity of oceans. In the present study, sixteen models from the ‘Coupled Climate Model Inter-comparison Project phase 5’ (CMIP5) are assessed for their capability in simulating the Chlorophyll (Chl-a) concentration against satellite observations over the northern Indian Ocean. The sixteen CMIP5 models are categorized into three groups based on their relative skill, Group-A models had the highest skill and captured the phase of the bloom during summer monsoon season whereas the Group-B and Group-C models mostly failed to reproduce the Chl-a concentrations. The observed interannual variations were poorly simulated by all the CMIP5 models. Group-A models showed a negative bias in Chl-a concentration over the northern Arabian Sea and a positive bias in Chl-a simulation off Somalia over the western Indian Ocean. High Chl-a associated with the coastal upwelling along the west coasts of India and Sri Lanka was poorly simulated by CMIP5 models. The study highlights the regional deficiency in CMIP5 climate models in simulating Chl-a and the need for improved coupled physical-biogeochemical models over the tropical Indian Ocean.

Future increases in Arctic lightning and fire risk for permafrost carbon

Lightning is an indicator and a driver of climate change. Here, using satellite observations of lightning flash rate and ERA5 reanalysis, we find that the spatial pattern of summer lightning over northern circumpolar regions exhibits a strong positive relationship with the product of convective available potential energy (CAPE) and precipitation. Applying this relationship to Climate Model Intercomparison Project Phase 5 climate projections for a high-emissions scenario (RCP8.5) shows an increase in CAPE (86 ± 22%) and precipitation (17 ± 2%) in areas underlain by permafrost, causing summer lightning to increase by 112 ± 38% by the end of the century (2081–2100). Future flash rates at the northern treeline are comparable to current levels 480 km to the south in boreal forests. We hypothesize that lightning increases may induce a fire–vegetation feedback whereby more burning in Arctic tundra expedites the northward migration of boreal trees, with the potential to accelerate the positive feedback associated with permafrost soil carbon release. Changes in lightning activity are uncertain under climate change. The authors project that summer lightning in the Arctic is likely to more than double by the end of the century, with implications for lightning-strike tundra wildfires and associated carbon release from permafrost.

Tropospheric Ozone Assessment Report

Our understanding of the processes that control the burden and budget of tropospheric ozone has changed dramatically over the last 60 years. Models are the key tools used to understand these changes, and these underscore that there are many processes important in controlling the tropospheric ozone budget. In this critical review, we assess our evolving understanding of these processes, both physical and chemical. We review model simulations from the International Global Atmospheric Chemistry Atmospheric Chemistry and Climate Model Intercomparison Project and Chemistry Climate Modelling Initiative to assess the changes in the tropospheric ozone burden and its budget from 1850 to 2010. Analysis of these data indicates that there has been significant growth in the ozone burden from 1850 to 2000 (approximately 43 ± 9%) but smaller growth between 1960 and 2000 (approximately 16 ± 10%) and that the models simulate burdens of ozone well within recent satellite estimates. The Chemistry Climate Modelling Initiative model ozone budgets indicate that the net chemical production of ozone in the troposphere plateaued in the 1990s and has not changed since then inspite of increases in the burden. There has been a shift in net ozone production in the troposphere being greatest in the northern mid and high latitudes to the northern tropics, driven by the regional evolution of precursor emissions. An analysis of the evolution of tropospheric ozone through the 21st century, as simulated by Climate Model Intercomparison Project Phase 5 models, reveals a large source of uncertainty associated with models themselves (i.e., in the way that they simulate the chemical and physical processes that control tropospheric ozone). This structural uncertainty is greatest in the near term (two to three decades), but emissions scenarios dominate uncertainty in the longer term (2050–2100) evolution of tropospheric ozone. This intrinsic model uncertainty prevents robust predictions of near-term changes in the tropospheric ozone burden, and we review how progress can be made to reduce this limitation.

Evaluation of CMIP6 precipitation simulations across different climatic zones: Uncertainty and model intercomparison

This study analyzes the performance of precipitation estimates from historical runs of the CMIP6 (Climate Model Intercomparison Project Phase 6) over the climatic regions of Iran. In order to capture the spatio-temporal precipitation patterns, using a set of evaluation metrics, 12 GCMs (General Circulation Models) are compared to the observation data from the GPCC (Global Precipitation Climatology Centre) at the common 1° spatial resolution for 1950–2014. A comprehensive assessment is performed at different temporal scales including monthly, seasonal and annual. Results indicate that the reliability of precipitation estimates varies significantly across space and time. The CMIP6 models best reproduce the climatological features of precipitation and its spatio-temporal changes over the arid and hyper arid areas of the country. The outputs of the models exhibit less systematic biases in the arid zone. In addition, a strong underestimation is detected throughout the rainiest zone, indicating high uncertainty in wet regions. All models tend to show some level of underestimation in summer months with the lowest rainfall. The findings illustrate substantial inter-model variability over different climatic zones. Each of the CMIP6 models appears to be more suitable in a specific climatic zone. The models that performed reasonably well in the humid zone (CNRM-CM6-1 and MRI-ESM2-0), did not perform well in the hyper arid and arid zones. Similarly, models (HadGEM3-GC31-LL, BCC-CSM2-MR, and CanESM5) that performed well in the arid and hyper arid zones did not perform as well in the humid zone. Results inform what types of models are suitable for different climate zones.

A computationally efficient method for probabilistic local warming projections constrained by history matching and pattern scaling, demonstrated by WASP–LGRTC-1.0

Abstract. Climate projections are made using a hierarchy of models of different complexities and computational efficiencies. While the most complex climate models contain the most detailed representations of many physical processes within the climate system, both parameter space exploration and integrated assessment modelling require the increased computational efficiency of reduced-complexity models. This study presents a computationally efficient method for generating probabilistic projections of local warming across the globe, using a pattern-scaling approach derived from the Climate Model Intercomparison Project phase 5 (CMIP5) ensemble, that can be coupled to any efficient model ensemble simulation of global mean surface warming. While the method can project local warming for arbitrary future scenarios, using it for scenarios with peak global mean warming ≤2 ∘C is problematic due to the large uncertainties involved. First, global mean warming is projected using a 103-member ensemble of history-matched simulations with an example reduced complexity Earth system model: the Warming Acidification and Sea-level Projector (WASP). The ensemble projection of global mean warming from this WASP ensemble is then converted into local warming projections using a pattern-scaling analysis from the CMIP5 archive, considering both the mean and uncertainty of the local to global ratio of temperature change (LGRTC) spatial patterns from the CMIP5 ensemble for high-end and mitigated scenarios. The LGRTC spatial pattern is assessed for scenario dependence in the CMIP5 ensemble using RCP2.6, RCP4.5 and RCP8.5, and spatial domains are identified where the pattern scaling is useful across a variety of arbitrary scenarios. The computational efficiency of our WASP–LGRTC model approach makes it ideal for future incorporation into an integrated assessment model framework or efficient assessment of multiple scenarios. We utilise an emergent relationship between warming and future cumulative carbon emitted in our simulations to present an approximation tool making local warming projections from total future carbon emitted.

The effects of anthropogenic and volcanic aerosols and greenhouse gases on twentieth century Sahel precipitation

There is little scientific consensus on the importance of external climate forcings—including anthropogenic aerosols, volcanic aerosols, and greenhouse gases (GHG)—relative to each other and to internal variability in dictating past and future Sahel rainfall. We address this query by relating a 3-tiered multi-model mean (MMM) over the Climate Model Intercomparison Project phase 5 “twentieth century” and pre-Industrial control simulations to observations. The comparison of single-forcing and historical simulations highlights the importance of anthropogenic and volcanic aerosols over GHG in generating forced Sahel rainfall variability in models. However, the forced MMM only accounts for a small fraction of observed variance. A residual consistency test shows that simulated internal variability cannot explain the residual observed multidecadal variability, and points to model deficiency in simulating multidecadal variability in the forced response, internal variability, or both.

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

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.

FIO‐ESM Version 2.0: Model Description and Evaluation

AbstractThe First Institute of Oceanography Earth System Model (FIO‐ESM) version 2.0 was developed and participated in the Climate Model Intercomparison Project phase 6 (CMIP6). In comparison with FIO‐ESM v1.0, all component models of FIO‐ESM v2.0 are updated, and their resolutions are fined. In addition to the non‐breaking surface wave‐induced mixing (Bv), which has also been included in FIO‐ESM v1.0, there are three more distinctive physical processes in FIO‐ESM v2.0, including the effect of surface wave Stokes drifts on air–sea momentum and heat fluxes, the effect of wave‐induced sea spray on air–sea heat fluxes and the effect of sea surface temperature (SST) diurnal cycle on air–sea heat and gas fluxes. The FIO‐ESM v2.0 has conducted the CMIP6 Diagnostic, Evaluation, and Characterization of Klima (DECK) and historical experiments. The historical simulation of FIO‐ESM v2.0 for 1850–2014 is evaluated, including the surface air temperature (SAT), precipitation, SST, Atlantic Meridional Overturning Circulation (AMOC), El Niño‐Southern Oscillation (ENSO), and so forth. The climate changes with respect to SAT and SST global warming and decreasing AMOC are well reproduced by FIO‐ESM v2.0. The correlation coefficient of the global annual mean SAT anomaly can reach 0.92 with observations. In particular, the large warm SST bias at the east coast of tropical Pacific from FIO‐ESM v1.0, which is a common challenge for all climate models, is dramatically reduced in FIO‐ESM v2.0 and the ENSO period within the range of 2–7 years is well reproduced with the largest variation of SST anomalies occurring in boreal winter, which is consistent with observations.

Analyses of rainfall extremes in East Africa based on observations from rain gauges and climate change simulations by CORDEX RCMs

This study derived twelve Extreme Rainfall Indices (ERIs) such as the Maximum Dry Spell (MDS) and Maximum Wet Spell (MWS) from daily rainfall observed over the period 1961–1990 at nine locations across East Africa. Capacity of six CO-ordinated Regional Climate Downscaling EXperiment (CORDEX) Africa Regional Climate Models (RCMs) driven by twenty six Climate Model Intercomparison Project phase 5 (CMIP5) General Circulation Models (GCMs) to reproduce the observed ERIs with respect to long-term mean and trends was evaluated. Four RCMs and their five driving GCMs were further analyzed with respect to ERIs. Ensemble means of the RCMs' biases in simulating trends in several ERIs were of magnitudes above 50%. On average, biases in reproducing long-term mean were smaller than those for trends in ERIs. The difference between the performances of RCMs and GCMs depended on the selected RCM–GCM pair. The ensemble means of the RCMs reproduced observed ERIs better than the individual RCMs corroborating that the use of multi-model ensembles can boost credibility of climate change simulations and projections. The RCMs performed better than their driving GCMs in reproducing MDS. The biases of both the RCMs and GCMs were smaller in reproducing the MWS than MDS. Nonetheless, in reproducing observed MWS, the ensemble mean of RCMs' biases was slightly larger than that of the driving GCMs indicating possible adding up of the uncertainties from the GCMs and RCMs. Suggested RCMs' improvements regarding aerosol impacts on rainfall include adding missing constituents (like nitrate), and refining the crudely represented components. RCMs also require high resolution description (in both space and time) of land use types, land surface covers and characteristics as well as landscape heterogeneity. The GCMs to be used as the initial and lateral boundary conditions for the RCMs require improvement in their representation of key dynamical and thermodynamical feedbacks in the Tropical Indian Ocean.

Rainfall pattern over the North-West Himalayan region: historical time period vs. future warming scenarios

Events like melting glaciers, rising sea level, and changing weather patterns are being observed across the globe due to widely reported global warming. The monsoon season rainfall in the North-Western Himalayan region (NWH) becomes more uncertain as there is considerable variation between the duration of the monsoon season and the amount of rainfall during the season. The NWH region receives substantial amount of rainfall and witness various disasters during the monsoon season. In this context, the present study deals with the analysis of the rainfall patterns under various future warming scenarios (2076–2100), namely representative concentration pathway scenario 4.5 (RCP 4.5) and RCP 8.5 (RCP 8.5) with respect to the reference historical time period (1976–2000) during the principal monsoon season (i.e. 1st June to 30th September) of two Indian states (Uttarakhand and Himachal Pradesh) of the NWH region. To serve this purpose, six attributes are defined as follows; start date of the rainy season (SRS), date of the 50% of the seasonal total rainfall (HRS), end date of the rainy season (ERS), length of the rainy season (LRS), 1 day maximum intensity (MRS) and the day corresponding to the maximum rainfall intensity (MDRS). These attributes are estimated for both historical time period and various future warming scenarios based on the archives of five coupled climate models which participated in the Climate Model Inter-comparison Project Phase 5 (CMIP5). Considering huge inter-model variations amongst the CMIP5 models, results are presented here based on the multi-model mean (MME). Characteristics of various attributes of rainfall during the historical time period are compared with that of the two future warming scenarios viz.; RCP 4.5 and RCP 8.5 by means of statistical techniques. There is a possibility of early SRS, delayed ERS and extended LRS along with intense MRS under different future warming scenarios over Himachal Pradesh (HP) as compared with the historical time period; however, results are significant only for 1 day maximum rainfall under RCP 8.5. Similarly, over the Uttarakhand (UK) region, changes in the rainfall pattern are noted under two future warming scenarios viz.; RCP 4.5 and RCP 8.5 as compared with the historical time period; nonetheless, significant changes are noted in MRS and MDRS only under RCP 8.5. It is anticipated that both of the NWH states of HP and UK would experience enhanced MRS under the warmest future warming scenario (i.e. RCP 8.5). Based on the present analysis, intense rainfall events are expected which could act as an initiator for various meteorological hazards over the NWH region in future.

Implementation of the CMIP6 Forcing Data in the IPSL‐CM6A‐LR Model

AbstractThe implementation of boundary conditions is a key aspect of climate simulations. We describe here how the Climate Model Intercomparison Project Phase 6 (CMIP6) forcing data sets have been processed and implemented in Version 6 of the Institut Pierre‐Simon Laplace (IPSL) climate model (IPSL‐CM6A‐LR) as used for CMIP6. Details peculiar to some of the Model Intercomparison Projects are also described. IPSL‐CM6A‐LR is run without interactive chemistry; thus, tropospheric and stratospheric aerosols as well as ozone have to be prescribed. We improved the aerosol interpolation procedure and highlight a new methodology to adjust the ozone vertical profile in a way that is consistent with the model dynamical state at the time step level. The corresponding instantaneous and effective radiative forcings have been estimated and are being presented where possible.