Atmosphere-ocean General Circulation Model Research Articles

Modeling water availability under climate change scenarios: a systemic approach in the metropolitan area in Morelos, México

The research investigates integrated water management with complex socio-environmental interactions in worsening climate change scenarios. The proposed methodology involves the integration of Atmosphere–Ocean General Circulation Models (AOGCM) with Water Evaluation and Planning models (WEAP) to ensure water availability in the future. Two Shared Socioeconomic Pathways (SSP) integrate environmental, socioeconomic, and political elements under climate change scenarios with greater rainfall variability, extreme droughts, and floods in the metropolitan area of Morelos, located in the Center of México. Water availability in this region, along with population growth, industrialization, service activities, and agriculture, depends on forest conservation in the Ravines System of Northwest Morelos (RSNM). Public policy lacks interdisciplinary socio-environmental development, which prioritizes unsustainable economic growth overexploiting aquifers and polluting rivers. Official data from national and state governments do not reflect water conditions, and aquifer statistics date back decades. The majority of the analyzed models predict a delay in the monsoon, higher temperatures, extreme climate events, depletion of groundwater, and severe water scarcity during the hot months, rendering them unable to meet the increasing demand. This research provides valuable insights into the complex socioeconomic dynamics of a region with future water scarcity, which could be useful for similar conditions in the Global South.

Impact of biomass burning aerosols (BBA) on the tropical African climate in an ocean–atmosphere–aerosol coupled climate model

Abstract. The impact of biomass burning aerosols (BBA) emitted in central Africa on the tropical African climate is studied using the ocean–atmosphere global climate model CNRM-CM, including prognostic aerosols. The direct BBA forcing, cloud feedbacks (semi-direct effects), effects on surface solar radiation, atmospheric dynamics and precipitation are analysed for the 1990–2014 period. During the June–July–August (JJA) season, the CNRM-CM simulations reveal a BBA semi-direct effect exerted on low-level clouds with an increase in the cloud fraction of ∼5 %–10 % over a large part of the tropical ocean. The positive effect of BBA radiative effects on low-level clouds is found to be mainly due to the sea surface temperature response (decrease of ∼0.5 K) associated with solar heating at 700 hPa, which increases the lower-tropospheric stability. Over land, results also indicate a positive effect of BBA on the low-cloud fraction, especially for the coastal regions of Gabon and Angola, with a potentially enhanced impact in these coupled simulations that integrates the response (cooling) of the sea surface temperature (SST). In addition to the BBA radiative effect on SST, the ocean–atmosphere coupled simulations highlight that the oceanic temperature response is noticeable (about −0.2 to −0.4 K) down to ∼80 m depth in JJA between the African coast and 10° W. In parallel to low-level clouds, reductions of ∼5 %–10 % are obtained for mid-level clouds over central Africa, mainly due to BBA-induced surface cooling and lower-tropospheric heating inhibiting convection. In terms of cloud optical properties, the BBA radiative effects induced an increase in the optical depth of about ∼2–3 over the ocean south of the Equator. The result of the BBA direct effect and feedback on tropical clouds modulates the surface solar radiation over the whole of tropical Africa. The strongest surface dimming is over central Africa (∼-30 W m−2), leading to a large reduction in the continental surface temperature (by ∼1 to 2 K), but the solar radiation at the oceanic surface is also affected up to the Brazilian coast. With respect to the hydrological cycle, the CNRM-CM simulations show a negative effect on precipitation over the western African coast, with a decrease of ∼1 to 2 mm d−1. This study also highlights a persistent impact of BBA radiative effects on low-level clouds (increase in cloud fraction, liquid water content and optical depth) during the September–October–November (SON) period, mainly explained by a residual cooling of sea surface temperature over most of the tropical ocean. In SON, the effect on precipitation is mainly simulated over the Gulf of Guinea, with a reduction of ∼1 mm d−1. As for JJA, the analysis clearly highlights the important role of the slow response of the ocean in SON and confirms the need to use coupled modelling platforms to study the impact of BBA on the tropical African climate.

Increasing contribution of the atmospheric vertical motion to precipitation in a warming climate

Global warming already influences precipitation, with more intense precipitation in many locations. Although the ‘wet-get-wetter, dry-get-drier’ tendency in mean precipitation holds in many locations, the situations for precipitation extremes are more complex, due to changes in dynamic and thermodynamic influences on atmospheric moisture distributions. Here, we build a dynamically interactive atmospheric moisture model for the present (2006–2025) and the future climate (2081–2100), using outputs from coupled ocean-atmosphere general circulation models. We find that the dynamic process of vertical advection of moisture dominates the same-day precipitation, while the smaller impact of the thermodynamic process provides available moisture for several days. As climate warms, we find that the dynamical-induced precipitation more completely exhausts the vertically-integrated moisture and the distribution of the dynamic process’s impact on precipitation exhibits a greater spread in the warmer future. The dynamical process is primarily responsible for more extreme heavy precipitation as climate warms, at all latitudes.

Distinct response of Asian summer monsoon circulation and precipitation to orbital forcing during six Heinrich events

Climatic fingerprint of Heinrich (H) events was characterized by widespread megadroughts over the Asian summer monsoon (ASM) region accompanied by systemic weakening of the ASM. However, recent studies of hydroclimate proxies suggest huge spatial discrepancies in precipitation over the ASM region during some H events, characterized by increased precipitation in the Yangtze River Valley contrasting with the prevalent megadroughts across the whole ASM region. The mechanism responsible for the spatial discrepancies in precipitation and the relationship between local precipitation and the ASM intensity remain elusive. In this study, we investigate the response of the ASM circulation and precipitation to orbital forcing during six H events based on simulations with a coupled atmosphere-ocean general circulation model. The results show that changes in insolation alone can induce spatial discrepancies in precipitation over the ASM region during the H events. During the H1, 3, 4, 5, 6 events, the amplification of the land-sea pressure contrast in response to a positive interhemispheric insolation gradient (30°N-30°S) during boreal summer intensifies moisture transport from the adjacent oceans to the ASM region. The ensuing moisture divergence, combined with anomalous downdrafts, results in decreased precipitation in the South Asian Summer Monsoon (SASM) region, but converse scenario for the East Asian Summer Monsoon (EASM) region. During the H2 event, the increased precipitation across the Yangtze River Valley sharply contrasts the widespread drought over the ASM region, attributing to an anticyclone anomaly over the subtropical Western North Pacific and a cyclone anomaly over Japan and Korea. Moisture budget analysis shows that the dynamic effect, especially the vertical term, rather than the thermodynamic effect, is the dominant control of precipitation changes over the ASM region. Our results also suggest that despite the synchronous variation in the strength of the EASM and SASM in response to orbital forcing, the EASM should not be regarded as an eastward and northward extension of the SASM. Furthermore, our model simulates a weak correlation between the monsoon intensity and precipitation in the SASM region in response to orbital forcing, calling for caution in employing precipitation to reconstruct SASM intensity on orbital time scale.

Spatially Heterogeneous Responses of Planktonic Foraminiferal Assemblages Over 700,000 Years of Climate Change

ABSTRACTAimTo determine the degree to which assemblages of planktonic foraminifera track thermal conditions.LocationThe world's oceans.Time PeriodThe last 700,000 years of glacial–interglacial cycles.Major Taxa StudiedPlanktonic foraminifera.MethodsWe investigate assemblage dynamics in planktonic foraminifera in response to temperature changes using a global dataset of Quaternary planktonic foraminifera, together with a coupled Atmosphere–Ocean General Circulation Model (AOGCM) at 8000‐year resolution. We use ‘thermal deviance’ to assess assemblage responses to climate change, defined as the difference between the temperature at a given location and the bio‐indicated temperature (i.e., the abundance‐weighted average of estimated temperature optima for the species present).ResultsAssemblages generally tracked annual mean temperature changes through compositional turnover, but thermal deviances are evident under certain conditions. The coldest‐adapted species persisted in polar regions during warming but were not joined by additional immigrants, resulting in minimal assemblage turnover. The warmest‐adapted species persisted in equatorial regions during cooling with similarly minimal assemblage change. Assemblages at mid‐latitudes mostly tracked temperature cooling and warming.Main ConclusionsPlanktonic foraminiferal assemblages were generally able to track or endure temperature changes: as climate warmed or cooled, bio‐indicated temperature also became warmer or cooler, although to a variable degree. At polar sites under warming and at equatorial sites under cooling, the change in bio‐indicated temperature was less than, or even opposite to, what would be expected from estimated environmental change. Nevertheless, all studied species persisted across the study interval, regardless of thermal deviance—a result that highlights the resilience and inertia of planktonic foraminifera on an assemblage level to the last 700,000 years of climate change.

Climatic Effects of Ocean Salinity on M Dwarf Exoplanets

Ocean salinity is known to dramatically affect the climates of Earth-like planets orbiting Sun-like stars, with high salinity leading to less ice and higher surface temperature. However, how ocean composition impacts climate under different conditions, such as around different types of stars or at different positions within the habitable zone, has not been investigated. We used ROCKE-3D, an ocean-atmosphere general circulation model, to simulate how planetary climate responds to ocean salinities for planets with G-star versus M dwarf hosts at several stellar fluxes. We find that increasing ocean salinity from 20 to 100 g kg−1 in our model results in nonlinear ice reduction and warming on G-star planets, sometimes causing abrupt transitions to different climate states. Conversely, sea ice on M dwarf planets responds more gradually and linearly to increasing salinity. Moreover, reductions in sea ice on M dwarf planets are not accompanied by significant surface warming as on G-star planets. High salinity can modestly bolster the resilience of M dwarf planets against snowball glaciation and allow these planets to retain surface liquid water further from their host star, but the effects are muted compared to G-star planets that experience snowball bifurcation and climate hysteresis due to the ice-albedo feedback.

Diagnosing drivers of tropical precipitation biases in coupled climate model simulations

In this study, we analyse the large-scale biases in tropical precipitation climatology of two different types of coupled ocean–atmosphere general circulation models (GCMs): the coupled model intercomparison project (CMIP) models and ICON-Sapphire, a global storm-resolving model. We employ the simple globally resolved energy balance (GREB) diagnostic precipitation model to evaluate four drivers of the precipitation biases in the simulations: surface specific humidity, surface relative humidity, tropospheric mean and variability in the vertical motion. The tropical precipitation biases in the CMIP and ICON-Sapphire simulations are surprisingly similar in their patterns and also in the elements forcing them. The results of our analysis using the GREB model show that the precipitation biases result from both biases in the sensitivity to the four forcing fields and biases in the simulated forcing fields themselves. The most significant bias for both, the CMIP and ICON-Sapphire simulations, is a too high sensitivity to the mean vertical circulation (ωmean\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\omega }_{\ ext{mean}}$$\\end{document}) and bias in the ωmean\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\omega }_{\ ext{mean}}$$\\end{document} climatology itself. This also holds for specific long-standing biases, such as the double intertropical convergence zone problem. Meanwhile, biases in the climatology of specific and relative humidity play only a minor role but contribute to an overall small increase in precipitation in CMIP models that may be related to the “drizzling” bias. These results can give insights to the modelling community regarding model development, and illustrate that the GREB diagnostic precipitation model applied is a good tool for evaluating the drivers of large-scale tropical precipitation.

Assessment of CMIP6 models performance in simulation precipitation and temperature over Iran and surrounding regions.

This study investigates the performance of CMIP6 models in reproducing historical temperature and precipitation data for Iran and neighboring countries (Afghanistan, Pakistan, Turkmenistan, Azerbaijan, Armenia, Turkey, and Iraq) from 1980 to 2014. Reanalysis data from the ECMWF database (ERA5) for temperature and precipitation were utilized as a reference for the period 1980-2014. Additionally, ten Atmosphere-Ocean General Circulation Models (AOGCMs) from CMIP6 were employed to simulate temperature and precipitation data for the study region based on the IPCC Sixth Assessment Report databases. The Kling-Gupta Efficiency (KGE) index was used to evaluate the accuracy of CMIP6 models in replicating daily temperature and precipitation. The results indicate that different CMIP6 models exhibit varying degrees of accuracy in simulating historical temperatures and precipitation, depending on the month and the country. For instance, the IPSL-CM6A-LR model demonstrated the best annual performance in estimating temperature in Azerbaijan (KGE = 0.5), while the HadGEM3-GC31-LL model showed the lowest annual performance in Pakistan (KGE = -1.4). Interestingly, the models were found to be more accurate in simulating temperatures during warm months compared to cold ones. Furthermore, the accuracy of different models in estimating annual precipitation varied significantly, ranging from -0.64 (MRI-EMS2-0 model in Afghanistan) to 0.05 (CMCC-ESM2 model in Armenia). Similar to temperature, the study found that models were generally more accurate in simulating precipitation during cold months compared to warm ones.

Closure of tropical seaways favors the climate and vegetation in tropical Africa and South America approaching their present conditions

The tectonically induced closure/constriction of the Central American Seaway (CAS) and Indonesian Seaway (Indo) during the early to mid-Pliocene has been associated with many climatic events, such as the onset of Northern Hemisphere glaciation, the intensification of the Atlantic meridional overturning circulation (AMOC) and Australian aridification. However, studies on how the closure/constriction of tropical seaways affects the tropical climate system are still sparse and not systematic. Previous studies have linked the constriction of Indo to the aridification over East Africa and discussed the role of CAS closure in affecting the moisture supply over South America, but the underlying mechanism and combined effect of both tropical seaways are not well studied. In this study, we evaluate the impacts of tropical seaways' closure/constriction and distinguish the relative roles of CAS and Indo on climate in tropical Africa and South America using the NorESM-L Atmosphere-Ocean General Circulation Model (AOGCM) and a dynamic vegetation model (LPJ-GUESS). Our results show that the closure of the CAS leads mainly to aridification in northeastern Brazil, resulting in an expansion of tropical xerophytic shrubland and savanna in this region. The narrowing of the Indo mainly leads to enhanced aridification in eastern tropical Africa, and reduces the extent of tropical forests in eastern and northern tropical Africa, which is generally consistent with the data. The closure/narrowing of the two tropical seaways results in a superposition of the individual seaway's effect, particularly over northeastern Brazil region, which exhibits enhanced aridification compared to the closure of the individual CAS. The seaways' changes are shown to be pivotal for the evolution of climate and vegetation over East Africa and northeastern South America to contemporary conditions.

A new conceptual model ofglobaloceanheatuptake.

We formulate a new conceptual model, named "MT2", to describe global ocean heat uptake, as simulated by atmosphere-ocean general circulation models (AOGCMs) forced by increasing atmospheric CO2, as a function of global-mean surface temperature change T and the strength of the Atlantic meridional overturning circulation (AMOC, M). MT2 has two routes whereby heat reaches the deep ocean. On the basis of circumstantial evidence, we hypothetically identify these routes as low- and high-latitude. In low latitudes, which dominate the global-mean energy balance, heat uptake is temperature-driven and described by the two-layer model, with global-mean T as the temperature change of the upper layer. In high latitudes, a proportion p (about 14%) of the forcing is taken up along isopycnals, mostly in the Southern Ocean, nearly like a passive tracer, and unrelated to T. Because the proportion p depends linearly on the AMOC strength in the unperturbed climate, we hypothesise that high-latitude heat uptake and the AMOC are both affected by some characteristic of the unperturbed global ocean state, possibly related to stratification. MT2 can explain several relationships among AOGCM projections, some found in this work, others previously reported: Ocean heat uptake efficiency correlates strongly with the AMOC. Global ocean heat uptake is not correlated with the AMOC. Transient climate response (TCR) is anticorrelated with the AMOC. T projected for the late twenty-first century under high-forcing scenarios correlates more strongly with the effective climate sensitivity than with the TCR.

Uncertainties in the Arctic Ocean response to CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document}: a process-based analysis

Using an ensemble of atmosphere–ocean general circulation models (AOGCMs) in an idealized climate change experiment, this study evaluates the contribution of different ocean processes to Arctic Ocean warming. On the AOGCM-mean, the Arctic Ocean warming is greater than the global ocean warming, both in the volume-weighted mean, and at most depths within the upper 2000 m. However, the uncertainty of Arctic Ocean warming is much larger than the uncertainty of global ocean warming. The Arctic warming is greatest a few 100 m below the surface and is dominated by the import of extra heat, which is added to the ocean at lower latitudes and is conveyed to the Arctic mostly by the large-scale barotropic ocean circulation. The change in strength of this circulation in the North Atlantic is relatively small and not correlated with the Arctic Ocean warming. The Arctic Ocean warming is opposed and substantially mitigated by the weakening of the Atlantic meridional overturning circulation (AMOC), though the magnitude of this effect has a large model spread. By reducing the northward transport of heat, the AMOC weakening causes a redistribution of heat from high latitudes to low latitudes. Within the Arctic Ocean, the propagation of heat anomalies is influenced by broadening of cyclonic circulation in the east and weakening of anticyclonic circulation in the west. On the model-mean, the Arctic Ocean warming is most pronounced in the Eurasian Basin, with large spread across the AOGCMs, and accompanied by subsurface cooling by diapycnal mixing and heat redistribution by mesoscale eddies.

MIROC6 Large Ensemble (MIROC6-LE): experimental design and initial analyses

Abstract. Single model initial-condition large ensembles (LEs) are a useful approach to understand the roles of forced responses and internal variability in historical and future climate change. Here, we produce one of the largest ensembles thus far using the MIROC6 coupled atmosphere–ocean global climate model (MIROC6-LE). The total experimental period of MIROC6-LE is longer than 76 000 years. MIROC6-LE consists of a long preindustrial control run, 50-member historical simulations, 8 single forcing historical experiments with 10 or 50 members, 5 future scenario experiments with 50 members and 3 single forcing future experiments with 50 members. Here, we describe the experimental design. The output data of most of the experiments are freely available to the public. This dataset would be useful to a wide range of research communities. We also demonstrate some examples of initial analyses. Specifically, we confirm that the linear additivity of the forcing-response relationship holds for the 1850–2020 trends of the annual mean values and extreme indices of surface air temperature and precipitation by analyzing historical fully forced runs and the sum of single forced historical runs. To isolate historical anthropogenic signals of annual mean and extreme temperature for 2000–2020 relative to 1850–1900, ensemble sizes of 4 and 15, respectively, are sufficient in most of the world. Historical anthropogenic signals of annual mean and extreme precipitation are significant with the 50-member ensembles in 76 % and 69 % of the world, respectively. Fourteen members are sufficient to examine differences in changes in annual mean values and extreme indices of temperature and precipitation between the shared socioeconomic pathways (ssp), ssp585 and ssp126, in most of the world. Ensembles larger than 50 members are desirable for investigations of differences in annual mean and extreme precipitation changes between ssp126 and ssp119. Historical and future changes in internal variability, represented by departures from the ensemble mean, are analyzed with a focus on the El Niño/Southern Oscillation (ENSO) and global annual mean temperature and precipitation. An ensemble size of 31 is large enough to detect ENSO intensification from preindustrial conditions to 1951–2000, from 1951–2000 to 2051–2100 in all future experiments, and from low- to high-emission future scenario experiments. The single forcing historical experiments with 27 members can isolate ENSO intensification due to anthropogenic greenhouse gas and aerosol forcings. Future changes in the global mean temperature variability are discernible with 23 members under all future experiments, while 50 members are not sufficient for detecting changes in the global mean precipitation variability in ssp119 and ssp126. We also confirm that these temperature and precipitation variabilities are not precisely analyzed when detrended anomalies from the long-term averages are used due to interannual climate responses to the historical natural forcing, which highlights the importance of large ensembles for assessing internal variability.

Climate Change Assessment Using Atmosphere-Ocean General Circulation Model) AOGCM( and Its Effect on Runoff Using HEC-HMS model

Climate Change Assessment Using Atmosphere-Ocean General Circulation Model) AOGCM( and Its Effect on Runoff Using HEC-HMS model

Comparison between statistical and dynamical downscaling of rainfall over the Gwadar‐Ormara basin, Pakistan

AbstractThis paper evaluated and compared the performance of a statistical downscaling method and a dynamical downscaling method to simulate the spatial–temporal rainfall distribution. Outputs from RegCM4 Regional Climate Model (RCM) and the CanESM2 Atmosphere–Ocean General Circulation Model (AOGCM) were selected for the data scarce Gwadar‐Ormara basin, Pakistan. The evaluation was based on the climatological average and standard deviation for historic (1971–2000) and future (2041–2070) time periods under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. The performance evaluation showed that statistical downscaling is preferred to simulate and project rainfall patterns in the study area. Additionally, the Statistical DownScaling Model (SDSM) showed low R2 values in calibration and validation of the simulations with respect to observed data for the historic period. Overall, SDSM generated satisfactory results in simulating the monthly rainfall cycle of the entire basin. In this study, RegCM4 showed large rainfall errors and missed one rainfall season in the historic period. This study also explored whether the grid‐based rainfall time series of the Asian Precipitation—Highly Resolved Observational Daily Integration Towards Evaluation (APHRODITE) dataset could be used to enlarge and complement the sample of in situ observed rainfall time series. A spatial correlogram was used for observed and APHRODITE rainfall data to assess the consistency between the two data sources, which resulted in rejecting APHRODITE data. For the future time period (2041–2070) under RCPs 4.5 and 8.5 scenarios, rainfall projections did not show significant difference for both downscaling approaches. This may relate to the driving model (CanESM2 AOGCM) and not necessarily suggests poor performance of downscaling; either statistical or dynamical. Hence, the study recommends evaluating a multi‐model ensemble including other GCMs and RCMs for the same area of study.

Role of the tropical Indian Ocean in orbitally induced mid-Holocene precipitation variation in northwest China

Investigating long-term natural precipitation variability in Northwest China is crucial for our understanding of the recent wetting trend in this region. This study explores the mechanisms of precipitation variations in Northwest China during the mid-Holocene (MH) using the Community Earth System Model (CESM). We emphasize the role of ocean feedbacks in the response of precipitation changes in the summer half-year (April–September; the rainy season of Northwest China) to orbital forcing, via comparing simulation results from the single atmosphere general circulation model (AGCM) and fully coupled atmosphere–ocean general circulation model (AOGCM) of the CESM. The AOGCM simulations reveal a decrease of precipitation in Northwest China during the MH compared to the pre-Industrial (PI) era, matching well with proxy records. The drier MH is reproduced by the AGCM with orbital forcing when the tropical Indian Ocean cooling is taken into account. The tropical Indian Ocean cooling is affected by the decrease of spring insolation, contrasting to Eurasian warming caused by the increase of summer insolation during the MH. The tropical Indian Ocean cooling contributes to a reduction of the upper-level westerlies to the south of the westerly jet axis and hence a northward shift of the westerly jet during the MH relative to the PI, via amplifying the decrease of meridional thermal gradient from the tropical Indian Ocean to northern Eurasia and weakening the strength of the South Asian high. The northward migration of the westerly jet benefits anomalous downward motion and ultimately weakens precipitation in Northwest China during the MH. Therefore, the tropical Indian Ocean plays an important role in orbital forcing of MH precipitation variations in Northwest China. We further infer that abnormal warming of the tropical Indian Ocean is probably a key factor for the recent wetting trend in Northwest China.

Climate Response to Atlantic Meridional Energy Transport Variations

Abstract The climate responses to Atlantic meridional overturning circulation (AMOC) fluctuations are investigated in a hierarchy of sensitivity experiments. We modify the baroclinic component of the North Atlantic Ocean currents online in an atmosphere–ocean general circulation model to reproduce typical AMOC multidecadal variability found in a preindustrial control simulation in the same model. An analogous experiment is also conducted using a slab-ocean experiment. The responses to a strong AMOC include a widespread warming in the Northern Hemisphere and a northward shift of the intertropical convergence zone over the Atlantic Ocean. The driving mechanism of climate responses is then investigated with the changes in the energy flows in the ocean and atmosphere. The large-scale atmospheric changes in the tropics are organized by an anomalous cross-equatorial Hadley circulation transporting energy southward and moisture and heat northward. Changes in the Indo-Pacific Ocean circulation and heat transport, driven by the wind stress associated with the abnormal Hadley cell, damp the atmospheric responses. The lack of Indo-Pacific transport and ocean heat storage leads to amplified atmospheric changes in the slab-ocean experiments, which are further amplified by a positive feedback due to the interhemispheric antisymmetric changes in low cloud cover.

PALEO‐PGEM‐Series: A spatial time series of the global climate over the last 5 million years (Plio‐Pleistocene)

AbstractMotivationClimate change plays an important role in the generation and maintenance of biodiversity by driving processes such as diversification and range shifts. As a result, biodiversity patterns are often found to carry the imprints of palaeoclimatic changes. However, we still know little about the spatial and temporal variation in climate over the scale of millennia affecting eco‐evolutionary dynamics, mostly because of the scarcity of user‐friendly and freely available spatio‐temporal palaeoclimate series at such temporal scales. Here, we address this gap by presenting PALEO‐PGEM‐Series, a global spatio‐temporal dataset of the last 5 Myr, with 1 kyr resolution, spatially downscaled from emulations performed with the intermediate‐complexity atmosphere–ocean general circulation model PALEO‐PGEM. PALEO‐PGEM‐Series holds the potential to advance our understanding of the mechanisms behind the strong relationship between biodiversity and climate, a pressing need given projected biodiversity responses to anthropogenic climatic change.Main Types of Variables ContainedSpatio‐temporal series of monthly temperature and precipitation and 17 derived bioclimatic variables over the Pliocene–Pleistocene, along with standard error estimates from multiple runs of the emulator.Spatial Location and GrainGlobal landmasses, at 1° × 1°.Time Period and GrainLast 5 Myr at 1000 year resolution.Major Taxa and Level of MeasurementNot applicable.Software FormatTab‐delimited text files and accompanying R code to derive bioclimatic variables.

Evaluating uncertainty in climate change impacts on peak discharge and flood volume in the Qaran Talar watershed, Iran

Abstract This study evaluates the effects of climate change (CC) on runoff properties over the case study of the Qaran Talar watershed located in Iran. To consider the two main sources of uncertainty, i.e., Greenhouse Gases emission (GHG) scenarios and outputs of Atmosphere-Ocean General Circulation Models (AOGCMs), a daily rainfall time series was generated for two future periods (2021-2050 and 2070-2099) at three risk levels of 0.1, 0.25 and 0.50. 22 AOGCMs outputs following two emission scenarios (RCP4.5 and RCP8.5) were used. The results showed that the uncertainty of climate change scenarios was primarily owing to the uncertainty of GCMs outputs. Regarding the 2021-2050 period, under both emission scenarios, the increases in peak discharge and flood volume (FV) were estimated to reach 70, 50, and 30% at three risk levels of 0.1, 0.25 and 0.50, respectively, compared to the recent past period. As the current century draws to a close, the difference between the results of the two emission scenarios becomes apparent so that in the far-future period (2070-2099), the RCP8.5 scenario estimates and FV more than the RCP4.5 scenario does. Additionally, it was found that the uncertainty caused by AOGCMs was more than that by GHG emission scenarios.

Bias Correction and Statistical Modeling of Variable Oceanic Forcing of Greenland Outlet Glaciers

AbstractVariability in oceanic conditions directly impacts ice loss from marine outlet glaciers in Greenland, influencing the ice sheet mass balance. Oceanic conditions are available from Atmosphere‐Ocean Global Climate Model (AOGCM) output, but these models require extensive computational resources and lack the fine resolution needed to simulate ocean dynamics on the Greenland continental shelf and close to glacier marine termini. Here, we develop a statistical approach to generate ocean forcing for ice sheet model simulations, which incorporates natural spatiotemporal variability and anthropogenic changes. Starting from raw AOGCM ocean heat content, we apply: (a) a bias‐correction using ocean reanalysis, (b) an extrapolation accounting for on‐shelf ocean dynamics, and (c) stochastic time series models to generate realizations of natural variability. The bias‐correction reduces model errors by ∼25% when compared to independent in‐situ measurements. The bias‐corrected time series are subsequently extrapolated to fjord mouth locations using relations constrained from available high‐resolution regional ocean model results. The stochastic time series models reproduce the spatial correlation, characteristic timescales, and the amplitude of natural variability of bias‐corrected AOGCMs, but at negligible computational expense. We demonstrate the efficiency of this method by generating >6,000 time series of ocean forcing for >200 Greenland marine‐terminating glacier locations until 2100. As our method is computationally efficient and adaptable to any ocean model output and reanalysis product, it provides flexibility in exploring sensitivity to ocean conditions in Greenland ice sheet model simulations. We provide the output and workflow in an open‐source repository, and discuss advantages and future developments for our method.

North Atlantic Oscillation impact on the Atlantic Meridional Overturning Circulation shaped by the mean state

Accurate representation of the Atlantic Meridional Overturning Circulation (AMOC) in global climate models is crucial for reliable future climate predictions and projections. In this study, we used 42 coupled atmosphere–ocean global climate models to analyze low-frequency variability of the AMOC driven by the North Atlantic Oscillation (NAO). Our results showed that the influence of the simulated NAO on the AMOC differs significantly between the models. We showed that the large intermodel diversity originates from the diverse oceanic mean state, especially over the subpolar North Atlantic (SPNA), where deep water formation of the AMOC occurs. For some models, the climatological sea ice extent covers a wide area of the SPNA and restrains efficient air–sea interactions, making the AMOC less sensitive to the NAO. In the models without the sea-ice-covered SPNA, the upper-ocean mean stratification critically affects the relationship between the NAO and AMOC by regulating the AMOC sensitivity to surface buoyancy forcing. Our results pinpoint the oceanic mean state as an aspect of climate model simulations that must be improved for an accurate understanding of the AMOC.