Climate Simulations Research Articles

Diving Deeper: Leveraging the Chondrichthyan Fossil Record to Investigate Environmental, Ecological, and Biological Change

The extensive chondrichthyan fossil record spans 400+ million years and has a global distribution. Paleontological studies provide a foundation of description and taxonomy to support deeper forays into ecology and evolution considering geographic, morphologic, and functional changes through time with nonanalog species and climate states. Although chondrichthyan teeth are most studied, analyses of dermal denticle metrics and soft tissue imprints are increasing. Recent methodological advances in morphology and geochemistry are elucidating fine-scale details, whereas large datasets and ecological modeling are broadening taxonomic, temporal, and geographic perspectives. The combination of ecological metrics and modeling with environmental reconstruction and climate simulations is opening new horizons to explore form and function, demographic dynamics, and food web structure in ancient marine ecosystems. Ultimately, the traits and taxa that endured or perished during the many catastrophic upheaval events in Earth's history contribute to conservation paleobiology, which is a much-needed perspective for extant chondrichthyans. ▪ The longevity and abundance of the chondrichthyan fossil record elucidates facets of ecological, evolutionary, and environmental histories. ▪ Though lacking postcranial, mineralized skeletons, dental enameloid and dermal denticles exquisitely preserve morphology and geochemistry. ▪ Technical advances in imaging, geochemistry, and modeling clarify the linkages between form and function with respect to physiology, diet, and environment. ▪ Conservation efforts can benefit from the temporal and spatial perspective of chondrichthyan persistence through past global change events.

Impacts of Climate Change on Arctic Winter Cyclones

AbstractWe simulated Arctic climate using a high‐resolution implementation of WRF driven by HadGEM‐ES2 climate model outputs, following IPCC5 warming scenarios RCP 2.6, RCP 4.5 and RCP 8.5. The downscaled results indicate that, by the end‐of‐century, there are no significant changes in the average minimum central pressures or total number of winter Arctic cyclones. However, there are significant changes in the spatial patterns. For example, the frequency and vorticity of cyclones tend to increase over the western Arctic. Due to the poleward movement of the polar frontal zone and the increased low‐level tropospheric baroclinicity, more cyclones are expected to form within the Arctic Basin and migrate into the western‐central Arctic. We expect about 39% more cyclone tracks forming and dying in the Arctic Basin under RCP8.5, compared to present climate. On the other hand, with the reduced baroclinicity in the entire troposphere, there is a reduced genesis, frequency, and vorticity of cyclones over the Atlantic Arctic. Moreover, the depth of cyclones shows a robust decrease over the Arctic Basin, suggesting weakened eddy kinetic energy. With increasing greenhouse gases, the changes in cyclone vorticities and their depths tend to be stronger. In addition, the high resolution Polar WRF results demonstrate that changes in cyclone track density and intensities consistently become more pronounced with increasing radiative forcing.

Aerosol Direct Radiative Effects From Extreme Fire Events in Australia, California and Siberia Occurring in 2019–2020

AbstractThis study aims at investigating the biomass burning aerosols (BBA) from 2019 to 2020 extreme wildfires in California, Australia and Siberia, in terms of aerosol characteristics and direct radiative effect. This study is based on the comparison between global climate simulations (ARPEGE‐Climat) and reference aerosol data sets (reanalyzes, ground‐based observations and satellite data). First, our results demonstrate the need to constrain the injection heights in the model in order to realistically represent extinction vertical profiles observed during fire events, both in the troposphere and in the lower stratosphere due to the contribution of pyro‐convection. Without specific vertical emission profiles for fires, the ARPEGE‐Climat simulations fail in representing aerosol extinction vertical profiles. For each region studied, the modeled aerosol optical depth (AOD) is extremely high (above 3 at 550 nm). An important long‐range transport of BBA emitted in Australia and California is shown, with high AOD further from sources. These extremely dense plumes significantly perturb the surface incident solar radiation and exert a large direct (surface) shortwave radiative effect up to −13, −29 and −17 W on monthly average over Australia (January 2020), California (September 2020) and Siberia (August 2019), respectively. A noteworthy positive BBA direct radiative effect (warming) is found at the top of the atmosphere, when dense and strongly absorbing smoke plumes are advected over cloudy oceanic regions, characterized by high surface albedo. This absorption leads to an increase of the solar heating rate up to 0.3 K with possible implications on the atmospheric temperature and dynamics.

An improved empirical quantile mapping approach for bias correction of extreme values in climate model simulations

Abstract Quantifying and correcting biases in modeling simulations is crucial for deriving meaningful findings across various scientific disciplines. Climate model simulations, in particular, often exhibit systemic biases when compared to observations. These biases may persist in future climate simulations, affecting the results of many climate change impact assessment studies. Empirical Quantile Mapping (QM) is a widely used method to correct such biases, mapping quantiles between observed and simulated Cumulative Distribution Functions (CDFs). However, empirical QM faces a fundamental challenge when the CDF of future simulations differs from historical simulations, potentially leading to extreme values falling outside the historical CDF range. To address this issue, our study introduces a novel approach to extrapolate future extreme values for bias correction, preserving the rank order of simulated future extremes. By construction, our approach ensures that bias corrected values are not exaggerated and retain the rank structure of the original simulated data, while preserving climate change signals in the bias corrected outputs. Additionally, our approach includes a technique to adjust the wet-day frequency for precipitation by preserving the ratio of wet-day frequency between observations and historical model simulations.

Climate Change‐Driven Long‐Term Stability Risks of Ubiquitous Moraine Dams in Glacial Lakes on Qinghai‐Tibet Plateau: A Multiphysics Coupling Evolution Perspective

AbstractGlacial lake‐moraine dam systems are widespread in cold alpine environments such as the Qinghai‐Tibet Plateau (QTP). Without climate change, the lake‐dam system exhibits stably dynamic evolution on a hydrological annual cycle. However, climate change may drive subtle alterations in the system's evolution. We developed a fully coupled Thermal‐Hydraulic‐Mechanical simulation platform considering ice‐water phase change, showing robust performance under CMIP6‐derived boundary conditions. Using this platform, we simulated climate warming‐driven multiphysics responses and dam stability evolutions of a homogeneous, simplified conceptual model of the lake‐dam system. We identified critical temperature thresholds for permanently frozen area thawing and abrupt changes in dam stability of this lake‐dam system. Considering the current slope stability situations on the QTP, the SSP 5–8.5 climate warming scenario is conservatively anticipated to pose significant geological safety risks due to potential disaster chains from glacial lake failures. Our study provides insights into profound geological process evolutions driven by climate change.

Simulated winter climate change reveals greater cold than warm temperature tolerance in Chrysolina polita (Coleoptera: Chrysomelidae).

Climate change is expected to lead to rising winter temperatures in temperate zones, coinciding with a decrease in winter snow cover. Insects adapted to winter conditions in the temperate zone might be exposed to changing winter conditions and higher temperature fluctuations, which can affect diapause and mortality. We studied the effects of climate change on Chrysolina polita, a temperate zone species overwintering as an adult in the shallow surface of the soil. We tested the effects of increased and fluctuating temperature on the mortality and body composition of the beetles in a laboratory environment, as well as the effects of snow cover removal on the mortality and body mass in field conditions. We found that in the laboratory study, a 2 °C increase in mean temperature increased mortality and resulted in increased lipid consumption, whereas temperature fluctuation caused desiccation of the beetles but did not affect mortality compared to the control condition. In the field study, the snow removal caused the mean soil temperature to decrease by 3 °C and fluctuate (ranging from -26.4 to 2.5 °C compared to a range of -1.7 to 0.5 °C in the control), yet these differences did not affect beetle mortality or body mass. We conclude that C. polita exhibits greater resistance to cold temperatures than to higher temperatures during diapause. Therefore, the rising temperatures associated with climate change can pose challenges for overwintering.

Rainfall Erosivity Projection in South‐East Australia Using the Improved Regional Climate Simulations

ABSTRACTRainfall erosivity is one of the most dynamic factors in the soil erosion process. The increase in soil erosion caused by high rainfall erosivity, and the subsequent loss of soil nutrients, can lead to reduced food production and ecosystem services. This research program under the New South Wales (NSW) Climate Change Adaptation Strategy, assesses rainfall pattern change, rainfall erosivity and erosion risk across NSW under future climate conditions. Daily rainfall erosivity and erosion risk were modelled by Revised Soil Loss Universal Equation (RUSLE) approach and compared with that driven by observed rainfall data. Future rainfall erosivity and soil erosion risk change were investigated from daily precipitation projection of the updated NSW and Australian Regional Climate Modelling (NARCliM1.5) for two future scenarios, RCP4.5 and RCP8.5, from the historical (1986–2005) to far future (2060–2079) periods. The annual average rainfall erosivity is projected to increase about 8% under RCP 4.5 and further decrease 5% under RCP 8.5 in NSW due to the predicted temperature rises. More frequent heavy rainfall events are projected to occur during summer (December–January–February), and the rainfall from these extreme rainfall events is expected to account for 51% of the total annual rainfall in the far future. NARCliM‐derived results underestimate annual rainfall erosivity compared with observation‐derived erosivity. There are greater instability (root mean squared error [RMSE]: 803.2) and erosivity uncertainty (Bias: 16%~48%) in high rainfall zones. At a monthly scale, dry months (June–July–August) are becoming drier, while wet months (December–January–February) are becoming wetter and more erosive. 67% of NSW is predicted to experience increased rainfall erosivity under RCP4.5, whereas most of NSW will shift to drought and its consequent effects under the high‐end emission scenario (RCP 8.5). To address the dual challenges of excessive wetness in coastal and north‐east NSW and increasing aridity in Western NSW, it is necessary to develop climate change adaptation management strategies based on high‐risk areas and monthly or seasonal conditions. With the emerging launch of NARCliM2.0, we anticipate further improvements of these predictions will be achieved by more accurate models and data at higher spatial and temporal resolutions.

Accounting for transience in the baseline climate state changes the surface climate response attributed to stratospheric aerosol injection

Abstract Stratospheric aerosol injection (SAI) is a proposed means of climate intervention that could halt global temperature rise, though it would imperfectly offset climate change. To estimate this imperfection, it is common to compare the simulated climate under SAI against that of a baseline state at the same global mean temperature without SAI. Here, we combine a recent set of SAI simulations (ARISE-SAI-1.5) in the earth system model UKESM1, with simulations of idealized abrupt and transient warming scenarios, to assess the impact of transient warming through this baseline state on surface climate changes attributed to SAI. We quantify the effect of temperature stabilisation as the expected change in surface climate between a climate state under warming and one in quasi-equilibrium at the same global mean temperature. We estimate that accounting for temperature stabilisation eliminates the land-sea warming ratio change attributed to SAI. However, relative to the hypothetical scenario with lower CO2 concentrations that would achieve a stabilised climate at the same temperature, SAI produces a 69% larger reduction in global precipitation. Accounting for stabilisation can also meaningfully change the spatial pattern of surface temperature response attributable to SAI. We repeat our analysis for the GeoMIP G6sulfur scenario, to show that effects qualitatively consistent with these findings are seen when comparing the SAI state against the faster and slower warming baselines of the SSP5-8.5 and SSP2-4.5 scenarios. The changes in climate state attributable to temperature stabilisation are generally small compared to changes due to warming since pre-industrial. However, these differences can be significant in the context of assessing residual changes under SAI because these residuals are themselves roughly an order of magnitude smaller than the effects of warming. Our findings have implications for the design and assessment of future SAI simulations, and for the attribution of changes in surface climate to SAI.

Northern Hemisphere Atmospheric Blocking in CMIP6 Climate Projections Using a Hybrid Index

Abstract Atmospheric blocking is quantified by a variety of different blocking indices. Here, the index by Davini et al. (DAV12) is modified to a hybrid index by additionally considering the extent of the blocking anticyclone. Applying both indices, the DAV12 and the hybrid index, to the twentieth-century reanalyses, the ERA-20C and the 20CRv3 (hereafter 20CR) ensemble reveals large differences between the reanalyses. The annual blocking frequency increases widespread and significantly in ERA-20C, but only regionally and nonsignificantly in the 20CR ensemble mean. Trend analysis reveals higher reliability of the 20CR ensemble mean than ERA-20C blocking results. Seasonally, the changes in summer blocking are most pronounced and significantly positive around Greenland. The CMIP6-mean historical climate simulation agrees well in magnitude with 20CR during the period 1900–2014, with some underestimation of blocking frequency in the last decades related to inconsistent trends. For a future climate, the average of the CMIP6 models projects a decrease in blocking frequency in major parts of the Northern Hemisphere in summer and in winter. A CMIP6 subset of models which agree best with reanalyses shows a less negative future trend. Because of the mismatch of historical trends, especially in summer, the future projections are uncertain.

Cretaceous coastal mountain building and potential impacts on climate change in East Asia.

Crustal thickness and elevation variations control mountain building and climate change at convergent margins. As an archetypal Andean-type convergent margin, eastern Asia preserves voluminous magmas ideal for quantifying these processes and their impacts on climate. Here, we use Sr/Y and Ce/Y proxies to show that the crust experienced alternating thickening and thinning during the Late Mesozoic. We identify a noticeably thickened (50 to 55 kilometers) crust associated with tectonic shortening at 120 to 105 million years, corresponding to a >2500-meter-high coastal mountain range. Using climate simulation with the Community Earth System Model, we demonstrate that the mountain uplift changed Asian atmospheric circulation and precipitation patterns, increased inland aridity (~15%), and prompted the eastward desert expansion, contributing substantially to the arid zonal belt across mid- to low-latitude Asia. These findings-compatible with independent geological, geophysical, and climatic observations-have global implications for broadening our understanding of Earth-system interactions in the Cretaceous greenhouse world.

Droughts in Wind and Solar Power: Assessing Climate Model Simulations for a Net‐Zero Energy Future

AbstractUnderstanding and predicting “droughts” in wind and solar power availability can help the electric grid operator planning and operation toward deep renewable penetration. We assess climate models' ability to simulate these droughts at different horizontal resolutions, ∼100 and ∼25 km, over Western North America and Texas. We find that these power droughts are associated with the high/low pressure systems. The simulated wind and solar power variabilities and their corresponding droughts during historical periods are more sensitive to the model bias than to the model resolution. Future climate simulations reveal varied future change of these droughts across different regions. Although model resolution does not affect the simulation of historical droughts, it does impact the simulated future changes. This suggests that regional response to future warming can vary considerably in high‐ and low‐resolution models. These insights have important implications for adapting power system planning and operations to the changing climate.

Greenland Ice Cores Reveal a South‐To‐North Difference in Holocene Thermal Maximum Timings

AbstractHolocene temperature evolution remains poorly understood. Proxies in the early and mid‐Holocene suggest a Holocene Thermal Maximum (HTM) where temperatures exceed the pre‐industrial, whereas climate models generally simulate monotonic warming. This discrepancy may reflect proxy seasonality biases or errors in climate model internal feedbacks or dynamics. Using seasonally unbiased ice core reconstructions at NEEM, NGRIP, and Greenland Ice Sheet Project 2, we identify a Greenland HTM of ∼2°C above pre‐industrial, in agreement with other Northern Hemisphere proxy reconstructions. The firn‐based reconstructions are verified through borehole thermometry, producing a multi‐core, multi‐proxy reconstruction of Greenland climate from the last glacial to pre‐industrial. HTM timing across Greenland is heterogenous, occurring earlier at high elevations. Total air content measurements suggest a temperature contribution from elevation changes; regional oceanographic conditions, a weakened polar lapse rate, or variable near‐surface inversions may also be important sensitivities. Our reconstructions support climate simulations with dynamic Holocene vegetation, highlighting the importance of vegetation feedbacks.

An Evaluation of Dynamical Downscaling Methods Used to Project Regional Climate Change

AbstractIn the past decade, dynamical downscaling using “pseudo‐global‐warming” (PGW) techniques has been applied frequently to project regional climate change. Such techniques generate signals by adding mean global climate model (GCM)‐simulated climate change signals in temperature, moisture, and circulation to lateral and surface boundary conditions derived from reanalysis. An alternative to PGW is to downscale GCM data directly. This technique should be advantageous, especially for simulation of extremes, since it incorporates the GCM's full spectrum of changing synoptic‐scale dynamics in the regional solution. Here, we test this assumption, by comparing simulations in Europe and Western North America. We find that for warming and changes in temperature extremes, PGW often produces similar results to direct downscaling in both regions. For mean and extreme precipitation changes, PGW generally also performs surprisingly well in many cases. Moisture budget analysis in the Western North America domain reveals why. Large fractions of the downscaled hydroclimate changes arise from mean changes in large‐scale thermodynamics and circulation, that is, increases in temperature, moisture, and winds, included in PGW by design. The one component PGW may have difficulty with is the contribution from changes in synoptic‐scale variability. When this component is large, PGW performance could be degraded. Global analysis of GCM data shows there are regions where it is large or dominant. Hence, our results provide a road map to identify, through GCM analyses, the circumstances when PGW would not be expected to accurately regionalize GCM climate signals.

How well are hazards associated with derechos reproduced in regional climate simulations?

Abstract. A 15-member ensemble of convection-permitting regional simulations of the fast-moving and destructive derecho of 29–30 June 2012 that impacted the northeastern urban corridor of the USA is presented. This event generated 1100 reports of damaging winds, generated significant wind gusts over an extensive area of up to 500 000 km2, caused several fatalities, and resulted in widespread loss of electrical power. Extreme events such as this are increasingly being used within pseudo-global-warming experiments to examine the sensitivity of historical, societally important events to global climate non-stationarity and how they may evolve as a result of changing thermodynamic and dynamic contexts. As such it is important to examine the fidelity with which such events are described in hindcast experiments. The regional simulations presented herein are performed using the Weather Research and Forecasting (WRF) model. The resulting ensemble is used to explore simulation fidelity relative to observations for wind gust magnitudes, spatial scales of convection (as is manifest in high composite reflectivity, cREF), and both rainfall and hail production as a function of model configuration (microphysics parameterization, lateral boundary conditions (LBCs), start date, use of nudging, compiler choice, damping, and number of vertical levels). We also examine the degree to which each ensemble member differs with respect to key mesoscale drivers of convective systems (e.g., convective available potential energy and vertical wind shear) and critical manifestations of deep convection, e.g., vertical velocities, cold-pool generation, and how those properties relate to the correct characterization of the associated atmospheric hazards (wind gusts and hail). Use of a double-moment, seven-class scheme with number concentrations for all species (including hail and graupel) results in the greatest fidelity of model-simulated wind gusts and convective structure to the observations of this event. All ensemble members, however, fail to capture the intensity of the event in terms of the spatial extent of convection and the production of high near-surface wind gusts. We further show very high sensitivity to the LBCs employed and specifically that simulation fidelity is higher for simulations nested within ERA-Interim compared to ERA5. Excess convective available potential energy (CAPE) in all ensemble members after the derecho passage leads to excess production of convective cells, wind gusts, cREF > 40 dBZ, and precipitation during a frontal passage on the subsequent day. This event proved very challenging to forecast in real time and to reproduce in the 15-member hindcast simulation ensemble presented here. Future work could examine if simulations with other initial and lateral boundary conditions can achieve greater fidelity.

A pause in the weakening of the Atlantic meridional overturning circulation since the early 2010s

The current state-of-the-art climate models when combined together suggest that the anthropogenic weakening of the Atlantic Meridional Overturning Circulation (AMOC) has already begun since the mid-1980s. However, continuous direct observational records during the past two decades have shown remarkable resilience of the AMOC. To shed light on this apparent contradiction, here we attempt to attribute the interdecadal variation of the historical AMOC to the anthropogenic and natural signals, by analyzing multiple climate and surface-forced ocean model simulations together with direct observational data. Our analysis suggests that an extensive weakening of the AMOC occurred in the 2000s, as evident from the surface-forced ocean model simulations, and was primarily driven by anthropogenic forcing and possibly augmented by natural variability. However, since the early 2010s, the natural component of the AMOC has greatly strengthened due to the development of a strong positive North Atlantic Oscillation. The enhanced natural AMOC signal in turn acted to oppose the anthropogenic weakening signal, leading to a near stalling of the AMOC weakening. Further analysis suggests that the tug-of-war between the natural and anthropogenic signals will likely continue in the next several years.

Bioclimatic indicators dataset for the orographically complex Canary Islands archipelago

The Canary Islands are an archipelago of significant natural value, with a large variety of endemic species living in them, making essential the study of the effects of climate change. This research is based on the use of dynamic techniques of climatic regionalisation to obtain climate projections that contribute to the conservation of ecosystems in the Canary Islands. In this work, climate projections derived from WRF simulations with a spatial resolution of 3 km were used to obtain a novel dataset of 53 bioclimatic indicators, called BICI–ULL (Bioclimatic Indicators in the Canary Islands, University of La Laguna). The regional climate simulations were driven by three CMIP5 models (GFDL–ESM2M, IPSL–CM5A–MR, and MIROC–ESM) over three periods (1980–2009, 2030–2059, 2070–2099) and two emission scenarios (representative concentration pathway 4.5 and 8.5), to obtain, among others, the standard climatic variables used to generate the bioclimatic indicators: temperature, precipitation, solar radiation, humidity and wind speed.

Ecohydrological Response of a Tropical Peatland to Rainfall Changes Driven by Intertropical Convergence Zone Variability

ABSTRACTAimTropical peatlands are globally significant carbon stores, increasingly threatened by human activities and climate change. However, their ecohydrological responses to shifting water availability remain poorly understood. In this study, we investigate the connections between climate change, hydrology and vegetation dynamics in a coastal tropical peatland in Panama, aiming to understand the effects of future drying on peatland dynamics.LocationBocas del Toro, Panama (9°22′54″N, 82°21′59″W).TaxonAngiosperms.MethodsHigh‐resolution multiproxy palaeoecological data, including pollen and plant macrofossils (vegetation), testate amoebae (water‐table depth) and physical peat properties, are used to explore the relationships between climate change, hydrology and vegetation in a coastal tropical peatland over the past 700 years. Downscaled climate simulations are integrated with this process‐based understanding to project the likely future responses of this coastal peatland to climate change.ResultsWe identify a clear connection between precipitation variability, driven by shifts in the Intertropical Convergence Zone and water‐table dynamics, which subsequently influence changes in the peatland vegetation mosaic. Historical drier periods are marked by the expansion of shrub communities into the open peatland plain.Main ConclusionsPalaeoecological studies incorporating climate and hydrological proxies are essential for understanding both recent and future ecohydrological dynamics of tropical peatlands. Our findings suggest that in response to future climate change, water tables will lower and shrub communities will expand due to rising temperatures and reduced precipitation. Additionally, future sea‐level rise, combined with declining rainfall, may result in seawater intrusion and significant vegetation shifts in coastal tropical peatlands.

A global Data Assimilation of Moisture Patterns from 21 000–0 BP (DAMP-21ka) using lake level proxy records

Abstract. Global hydroclimate significantly differed from modern climate during the mid-Holocene (6 ka) and Last Glacial Maximum (21 ka). Consequently, both periods have been described as either a partial or reverse analogue for current climate change. To reconstruct past hydroclimate, an offline paleoclimate data assimilation methodology is applied to a dataset of 216 lake status records which provide relative estimates of water level change. The proxy observations are integrated with the climate dynamics of two transient simulations (TraCE-21ka and HadCM3) using a multivariate proxy system model (PSM) which estimates relative lake status from available climate simulation variables. The resulting DAMP-21ka (Data Assimilation of Moisture Patterns 21 000–0 BP) reanalysis reconstructs annual lake status and precipitation values at 500-year resolution and represents the first application of the methodology to global hydroclimate on timescales spanning the Holocene and longer. Validation using Pearson's correlation coefficients indicates that the reconstruction (0.24) is more skillful, on average, than model simulations (0.09), particularly in portions of North America and east Africa, where data density is high and proxy–model disagreement is prominent during the Holocene. Results of the PSM and assimilation are used to evaluate climatic controls on lake status, spatiotemporal patterns of moisture variability, and proxy–model disagreement. During the mid-Holocene, wetter conditions are reconstructed for northern and eastern Africa, Asia, and southern Australia, but in contrast to the model prior, negative anomalies are observed in North America, resulting in drier-than-modern conditions throughout the Northern Hemisphere midlatitudes. Proxy–model disagreement in western North America may reflect a bias in model simulations to stronger sea level pressure gradients in the North Pacific during the mid-Holocene. The data assimilation framework is able to reconcile these differences by integrating the constraints of proxy observations with the dynamics of the model prior to produce a more robust estimation of hydroclimate variability during the past 21 000 years.

Cross-Seasonal Effect on Tropical Pacific Precipitation: Implication of South Pacific Quadrupole Simulation in CMIP6

Abstract The tropical Pacific convergence zone plays a crucial role in the global climate system. Previous research studies emphasized the cross-seasonal influence of the South Pacific quadrupole (SPQ) mode on the tropical Pacific climate. This study assesses the relationship between austral summer SPQ and austral winter tropical precipitation in phase 6 of the Coupled Model Intercomparison Project (CMIP6) models. The analysis emphasizes the historical experiments conducted within this time frame, spanning from 1979 to 2014. Our findings reveal that the SPQ is accurately represented in all CMIP6 models, but the connection between SPQ and precipitation is inadequately simulated in most models. To investigate the reasons behind these intermodel differences in reproducing SPQ-related processes, we categorize models into two groups. The comparisons demonstrate that the fidelity of model simulations in replicating the SPQ–tropical precipitation relationship hinges significantly on their capacity to reproduce the positive wind–evaporation–sea surface temperature (WES; SST) feedback over both the southwestern Pacific (25°–10°S; 150°E–160°W) and the southeastern Pacific (30°–10°S; 140°–80°W). This positive WES feedback propagates the SPQ signal into the tropics, intensifying the meridional gradient of SST anomaly in the tropical western-central Pacific, which consequently amplifies convection and rainfall in that area. In the group of models that failed to simulate this relationship accurately, the weakened WES feedback can be traced back to biases in wind speed and its variation. Furthermore, this WES feedback establishes a connection between SPQ and El Niño–Southern Oscillation (ENSO). A better rendition of the SPQ–tropical rainfall connection tends to result in a better simulation of the onset of SPQ-related ENSO events. As a result, this study advances our comprehension of extratropical impacts on the tropics, with the potential to enhance the accuracy of tropical climate simulation and prediction. Significance Statement Tropical rainfall plays an important role in the global climate system. Beyond the well-known influence of El Niño–Southern Oscillation (ENSO) on the tropical rainfall, the sea surface temperature (SST) anomaly in the South Pacific has a cross-seasonal impact on the precipitation over the tropical Pacific via air–sea coupled processes. Such SST anomaly pattern shows a quadrupole structure in the extratropical South Pacific, known as the South Pacific quadrupole (SPQ) mode. However, the relationship between SPQ and tropical precipitation remains poorly simulated in most state-of-the-art climate models. One primary reason for this gap between observed and simulated relationships is the underestimation of wind speed and its variation over the south tropical Pacific in these models. This limitation undermines their ability to accurately represent the air–sea interactions that drive tropical precipitation patterns, leading to inaccuracies in simulations. Our study aims to bridge this knowledge gap by enhancing our understanding of the extratropical effects on the tropical Pacific. By exploring the mechanisms underlying the SPQ–precipitation connection, we expect to improve the simulation and prediction capabilities of tropical climate models, thereby enhancing our ability to forecast and adapt to future climatic changes.

Estimating the burden of temperature-related low birthweight attributable to anthropogenic climate change in low-income and middle-income countries: a retrospective, multicentre, epidemiological study.

Pregnant individuals are particularly susceptible to non-optimal temperatures due to their physiological status. Moreover, pregnancy is a crucial period for programming fetal health. Quantifying the impact of non-optimal temperature exposure and the contribution of anthropogenic climate change is crucial for mitigating and adapting to climate-related health risks. However, this has not been thoroughly studied in pregnant individuals in low-income and middle-income countries (LMICs). Using data from 511 449 births across 31 LMICs from 1990 to 2018, we linked climate simulations (with and without anthropogenic forcing) to spatiotemporally resolved temperature data and birthweight records. We assessed the association between heat and cold exposure (ie, >90th and <10th percentile of temperature by region) during pregnancy and birthweight across different regions. We then used temperature simulations from both historically forced and natural-only forced climate models to estimate changes in exposure due to anthropogenic climate change and to quantify the burden of temperature-related low birthweight (ie, a birthweight <2500 g) attributable to anthropogenic climate change. Heat exposure during pregnancy, compared with the optimal temperature range, was associated with an increased risk of low birthweight in several regions: southern Asia (odds ratio 1·41, 95% CI 1·34-1·48), western Africa (1·12, 1·02-1·24), and eastern Africa (1·40, 1·27-1·55). Cold exposure increased the risk of low birthweight in central Africa (1·31, 1·10-1·56), southern Africa (1·18, 1·02-1·36), and eastern Africa (1·14, 1·02-1·26). Anthropogenic climate change contributed to approximately 59·2% (95% CI 16·6-94·3), 89·0% (51·0-100·0), and 77·3% (27·0-100·0) of heat-related low birthweight cases in southern Asia, western Africa, and eastern Africa, respectively. Conversely, in regions where cold exposure was predominant, anthropogenic climate change reduced the burden of low birthweight. Our study provides quantitative estimates of the contribution of anthropogenic climate change to the low birthweight burden in LMICs. These findings can inform strategies for climate mitigation and adaptation in LMICs and help reduce global health inequalities. National Natural Science Foundation of China.