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Summer cooling is one of the most direct consequences of explosive volcanic eruptions that can affect ecosystems and human societies. Recent studies revealed a multiyear cooling impact on hemispheric and global summer temperatures after tropical eruptions, yet the volcanic responses appear to vary on regional scales. Here, we revisit volcano-induced summer cooling in eastern Canada and northern and central Europe by applying superposed epoch analysis on CMIP6-PMIP4 simulations and millennial temperature reconstructions based on tree-ring density. We then examine potential causes modulating region-specific volcanic impact. While confirming that, on average, tropical eruptions over the last millennium have induced a longer cooling (>4 yr) than eruptions from extratropical Northern Hemisphere in all three North Atlantic regions, we show that the peak magnitude of cooling is stronger in eastern Canada. We also find that the detected volcanic temperature anomalies can be strongly affected by the selection and number of volcanic events and nonvolcanic signals embedded in the climate time series. This study highlights the risks of using highly noisy proxy records to investigate volcanic impacts, especially in regions with strong unforced climate variability. The CMIP6-PMIP4 simulations generally agree with the three reconstructions on the average response to tropical eruptions, but their performance is poorer regarding the production of significant cooling after extratropical eruptions. Our results further suggest that the particular sensitivity to tropical eruptions in eastern Canada is likely related to increased sea ice surrounding Quebec–Labrador associated with the positive Arctic Oscillation and North Atlantic Oscillation formed during the first posteruption winter. [ABSTRACT FROM AUTHOR]

Projecting precipitation changes is essential for researchers to understand climate change impacts on hydrological cycle. This study projected future precipitation over the Hanjiang River Basin (HRB) based on the multimodel ensemble (ME) of six global climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). An ME method using the fusion of four machine learning (ML) algorithms (random forest [RF], K‐nearest neighbors [KNN], extra tree [ET], and gradient boosting decision tree [GBDT]) was proposed in this study. The future precipitation changes were investigated during 2023–2042 (Near‐term), 2043–2062 (Mid‐term), and 2081–2100 (Long‐term) periods, with reference to the base period 1995–2014, under three integrated scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5) of the Shared Socioeconomic Pathways (SSPs) and the representative concentration pathways (RCPs). The results show that: (1) the proposed ME method performs better than the ME mean and individual ML algorithms, with a correlation coefficient value reaching 0.88 and Taylor skill score reaching 0.764. (2) The precipitation under SSP5‐8.5 has the largest upward trend with the annual precipitation variation range of −9.27% to 112.84% from 2023 to 2100, followed by SSP2‐4.5 with −30.48% to 44.67%, and the smallest under SSP1‐2.6 with −37.19% to 37.78%, which show a significant trend of humidification over the HRB in the future. (3) The precipitation changes over the HRB are projected to increase over time, with the largest in the Long‐term, followed by Mid‐term, and the smallest in the Near‐term. (4) The northeastern parts of the HRB are projected to experience a large precipitation in the future, and the southeastern parts are smaller. (5) Uncertainties in the projected precipitation over the HRB still exist, which can be reduced by ME. The findings obtained in this study have important implications for hydrological policymakers to make adaptive strategies to reduce the risks of climate change. [ABSTRACT FROM AUTHOR]

Selection of suitable general circulation models (GCMs) increases the reliability in the assessment of the impact of climate change. In a recent study, we introduced the concepts of complex networks for evaluating the performance of GCMs in simulating rainfall using clustering coefficient, which quantifies the tendency of a network to cluster. However, since networks have different properties, it is important to use any additional measure to verify the consistency in the outcomes for more reliable interpretations and conclusions. To this end, in the present study, we employ the shortest path length to evaluate the performance and ranking of GCMs for rainfall simulation. The shortest path length quantifies the efficiency of a network in transmitting information between the nodes in the network. It is generally a better measure, as its calculation involves every pair of nodes in the entire network, rather than only the nodes that are in 'clusters' with a given node of interest. We evaluate the ability of 49 GCMs from the Coupled Model Intercomparison Project phase 6 (CMIP6) to simulate the monthly rainfall in India for the period 1961–2014. We consider each grid, of the 288 grids of 1° × 1° spatial resolution across India, as a network. For each network, we treat the higher-dimensional vectors reconstructed from the scalar rainfall time series as the nodes and the connections between the vectors as the links. We determine the optimum dimension for reconstruction using the false nearest neighbor method. We consider two cases for the evaluation of GCMs: (1) Case 1—whole-year rainfall (January-December); and (2) Case 2—summer monsoon rainfall (June–September). For each grid, we rank the 49 GCMs based on the difference in the average shortest path length between the observed rainfall network and the GCM-simulated rainfall network. For each of Case 1 and Case 2, we employ the group decision-making (GDM) methodology to rank the GCMs for the entire study area, considering all the 288 grids. We then use the comprehensive rating metric (RM) value to combine the ranks obtained for the GCMs for Case 1 and Case 2 and to identify the final ranking of the GCMs. For the whole-year rainfall, the models CMCC-ESM2, NorCPM1, GFDL-ESM4, CMCC-CM2-SR5, and CESM2-WACCM, in order, occupy the top five positions. For the summer monsoon rainfall, the models CESM2-FV2, E3SM-1-1-ECA, CMCC-ESM2, EC-Earth3-Veg-LR and CMCC-CM2-HR4, in order, are the top five. The results from the RM values suggest that the models CMCC-ESM2, CESM2-WACCM, CMCC-CM2-HR4, E3SM-1-1-ECA, and BCC-ESM1 are, in order, the five best-performing models. We find that the ranks obtained for the GCMs based on the shortest path length analysis are in reasonably good agreement and consistent with those obtained using clustering coefficient, especially for the whole-year rainfall. [ABSTRACT FROM AUTHOR]

This study investigates the transient evolution of tropical Pacific sea surface temperature (SST) responses to a constant northern high-latitude solar heating in fully coupled CESM 1.2. The study identifies two stages through multiple ensemble runs. 1) In the first 3 years, a hemispherically asymmetric pattern emerges, caused by air–sea interactions associated with the anomalous cross-equatorial Hadley cell. The northern tropics experience warming that is blocked north of the equator by the intertropical convergence zone. The southeast Pacific cooling reaches the equatorial region and is amplified by the equatorial Ekman divergence. 2) Within a decade, the equatorial cooling is replaced by warming in the eastern equatorial basin. The anomalous warming that appears faster than the time scales of the oceanic ventilation is attributed to anomalous meridional heat convergence and weakening of the northern subtropical cell. Our findings highlight the influence of ocean dynamics on the temporal and spatial evolution of tropical SST response to hemispherically asymmetric heating. The initial cooling caused by Ekman divergence delays the arrival of slow warming, while initial wind and temperature anomalies set the stage for the weakening of the subtropical cell. The results have important implications for understanding the evolution of tropical SST patterns in observational records and future climate change simulations, as they show strong interhemispheric temperature asymmetry in the extratropics. [ABSTRACT FROM AUTHOR]

The potential role of the New England seamount chain (NESC) on the Gulf Stream pathway and variability has been long recognized, and the series of numerical experiments presented in this paper further emphasize the importance of properly resolving the NESC when modeling the Gulf Stream. The NESC has a strong impact on the Gulf Stream pathway and variability, as demonstrated by comparison experiments with and without the NESC. With the NESC removed from the model bathymetry, the Gulf Stream remains a stable coherent jet much farther east than in the experiment with the NESC. The NESC is the leading factor destabilizing the Gulf Stream and, when it is not properly resolved by the model's grid, its impact on the Gulf Stream's pathway and variability is surprisingly large. A high-resolution bathymetry, which better resolves the New England seamounts (i.e., narrower and rising higher in the water column), leads to a tighter Gulf Stream mean path that better agrees with the observed path and a sea surface height variability distribution that is in excellent agreement with the observations. [ABSTRACT FROM AUTHOR]

Uncertainties both in the initial condition (IC) and surface wind high-frequency perturbations (HFPs) contribute to the prediction spread of El Niño–Southern Oscillation (ENSO), yet the relative roles of the two are hard to separate, mostly due to the nonlinearity in ENSO dynamics. In this study, we conducted two ensemble experiments using the CESM model to analyze the source of ENSO spread arising from the tropical Pacific. The HFPs were precluded using an online low-pass-filtering scheme in one experiment. Results showed that the uncertainty in ENSO prediction depends on both the IC and HFPs. By comparing simulations with and without HFPs, it is found that the predicted ENSO spread decreased in magnitude when HFPs are removed, especially in the first four prediction months. At integration time longer than that, the additional impact of HFPs cannot be detected on top of that of the uncertainty in IC. To the ENSO spread anomaly, we found that it is tightly associated with uncertainty in the sea surface temperature and surface wind in the central-eastern equatorial Pacific at the short integration time, and associated with the HFPs in the western equatorial Pacific at the long integration time. When the HFPs are removed, the precursor of the ENSO spread anomaly at the long lead time emerges in the northeastern tropical Pacific, the area where the Pacific meridional mode originates from. Our results indicate that the uncertainty in ENSO prediction depends primarily on IC, and the HFPs in the western equatorial Pacific play the secondary role. [ABSTRACT FROM AUTHOR]

Earth’s planetary albedo shows a remarkable hemispheric symmetry. We assess to what extent CMIP models symmetrize the hemispheric clear-sky albedo asymmetry and what the role of clouds is for this. Following Voigt et al., we calculate a reference TOA reflected solar radiation considering the masking of clear-sky asymmetry by symmetric cloud contributions. We use the simple radiation model of Donohoe and Battisti to estimate this benchmark and to separate surface, aerosol, and cloud contributions to the compensation of this benchmark. In CERES, tropical clouds enhance the reference asymmetry while extratropical cloud asymmetries balance the reference asymmetry and the additional asymmetry introduced by tropical clouds. CMIP multimodel means show similar results as CERES. Clouds compensate reference asymmetries by 85% (CMIP3), 65% (CMIP5), and 78% (CMIP6) as compared with 98% for CERES. Spatial distributions of hemispheric differences indicate clear improvements across the CMIP phases. Remaining all-sky reflection asymmetries predominantly result from too-small, partly compensating cloud asymmetries: a too-weak enhancement of the reference asymmetry in the tropical Atlantic and eastern Pacific Oceans is accompanied by a too-weak compensation by extratropical clouds. Thus, tropical clouds and extratropical storm track regions are largely responsible for the compensation of hemispheric clear-sky asymmetries in CERES and CMIP, and for remaining biases in the GCMs. An unexpected result is the magnitude of model biases in the clear-sky asymmetries, which potentially condition systematic cloud biases. Experiments testing cloud-controlling factors influencing hemispheric asymmetry could help us to understand what drives hemispheric cloud differences. [ABSTRACT FROM AUTHOR]

Much of Siberia experienced exceptional warmth during the spring of 2020, which followed an unusually warm winter over the same region. Here, we investigate the drivers of the spring warmth from the perspective of atmospheric dynamics and remote influences, focusing on monthly-time-scale features of the event. We find that the warm anomalies were associated with separate quasi-stationary Rossby wave trains emanating from the North Atlantic in April and May. The wave trains are shown to be extreme manifestations of the dominant modes of spring subseasonal meridional wind variability over the Northern Hemisphere. Using a large ensemble of simulations from NASA’s GEOS atmospheric model, in which the model is constrained to remain close to observations over selected regions, we further elucidate the remote drivers of the unusual spring temperatures in Siberia. In both April and May, the wave trains were likely forced from an upstream region including eastern North America and the western North Atlantic. Analysis with a stationary wave model shows that transient vorticity flux forcing over and downwind of the North Atlantic, which is strongly related to storm activity caused by internal variability, is key to generating the wave trains, suggesting limited subseasonal predictability of the Rossby waves and hence the exceptional Siberian warmth. Our observational and model analyses also suggest that anomalous tropical atmospheric heating contributed to the unusual warmth in Siberia through a teleconnection involving upper-troposphere dynamics and the mean meridional circulation. This tropical–extratropical teleconnection offers a possible physical mechanism by which anthropogenic climate change influenced the extreme Siberian warmth. [ABSTRACT FROM AUTHOR]

The virtual temperature used to model moisture-modified tropospheric dynamics is generalized to include a new thermospheric component. The resulting hybrid virtual potential temperature (HVPT) transitions seamlessly with height, from moist virtual potential temperature (MVPT) in the troposphere, to potential temperature in the stratosphere and mesosphere, to thermospheric virtual potential temperature thereafter. For numerical weather prediction (NWP) models looking to extend into the thermosphere, but still heavily invested in retaining MVPT-based dynamical cores for tropospheric prediction, upgrading to HVPT allows the core to capture critical new aspects of variable composition thermospheric dynamics, while leaving the original MVPT-based tropospheric equations and numerics essentially untouched. In this way, HVPT augmentation can both simplify and streamline extension into the thermosphere at little computational cost beyond the inevitable need for more vertical layers and somewhat smaller time steps. To demonstrate, we upgrade the MVPT-based dynamical core of the Navy global NWP model to HVPT, then test its performance in forecasting analytical globally balanced states containing hot or rapidly heated thermospheres and height-varying gas constants. These tests confirm that HVPT augmentation offers an efficient and effective means of extending MVPT-based NWP models into the thermosphere to accelerate development of future ground-to-space NWP models supporting space weather applications. The related issues of variable gravitational acceleration and shallow-atmosphere approximations are also briefly discussed. [ABSTRACT FROM AUTHOR]

AbstractLand-use and land-cover change (LULCC) is one of the most important forcings affecting climate in the past century. This study evaluates the global and regional LULCC impacts in 1950–2015 by employing an annually updated LULCC map in a coupled land–atmosphere–ocean model. The difference between LULCC and control experiments shows an overall land surface temperature (LST) increase by 0.48 K in the LULCC regions and a widespread LST decrease by 0.18 K outside the LULCC regions. A decomposed temperature metric (DTM) is applied to quantify the relative contribution of surface processes to temperature changes. Furthermore, while precipitation in the LULCC areas is reduced in agreement with declined evaporation, LULCC causes a southward displacement of the intertropical convergence zone (ITCZ) with a narrowing by 0.5°, leading to a tripole anomalous precipitation pattern over the warm pool. The DTM shows that the temperature response in LULCC regions results from the competing effect between increased albedo (cooling) and reduced evaporation (warming). The reduced evaporation indicates less atmospheric latent heat release in convective processes and thus a drier and cooler troposphere, resulting in a reduction in surface cooling outside the LULCC regions. The southward shift of the ITCZ implies a northward cross-equatorial energy transport anomaly in response to reduced latent/sensible heat of the atmosphere in the Northern Hemisphere, where LULCC is more intensive. Tropospheric cooling results in the equatorward shift of the upper-tropospheric westerly jet in both hemispheres, which, in turn, leads to an equatorward narrowing of the Hadley circulation and ITCZ.

Paleoclimate proxy evidence suggests that the Atlantic meridional overturning circulation (AMOC) was about 1000 m shallower at the Last Glacial Maximum (LGM) compared to the present. Yet it remains unresolved what caused this glacial shoaling of the AMOC, and many climate models instead simulate a deeper AMOC under LGM forcing. While some studies suggest that Southern Ocean surface buoyancy forcing controls the AMOC depth, others have suggested alternatively that North Atlantic surface forcing or interior diabatic mixing plays the dominant role. To investigate the key processes that set the AMOC depth, here we carry out a number of MITgcm ocean-only simulations with surface forcing fields specified from the simulation results of three coupled climate models that span much of the range of glacial AMOC depth changes in phase 3 of the Paleoclimate Model Intercomparison Project (PMIP3). We find that the MITgcm simulations successfully reproduce the changes in AMOC depth between glacial and modern conditions simulated in these three PMIP3 models. By varying the restoring time scale in the surface forcing, we show that the AMOC depth is more strongly constrained by the surface density field than the surface buoyancy flux field. Based on these results, we propose a mechanism by which the surface density fields in the high latitudes of both hemispheres are connected to the AMOC depth. We illustrate the mechanism using MITgcm simulations with idealized surface forcing perturbations as well as an idealized conceptual geometric model. These results suggest that the AMOC depth is largely determined by the surface density fields in both the North Atlantic and the Southern Ocean.

Raindrop evaporation is an important sub-cloud process that modifies rainfall amount and rainwater isotope values. Earlier studies have shown that various general circulation models (GCMs) do not incorporate this process properly during the simulation of water isotope ratios (oxygen and hydrogen). Our recent study has demonstrated that an inadequate estimation of this process for the Indian Summer Monsoon (ISM) results in significant biases (model-observed values) in the simulation of various GCMs on a monthly scale. However, a quantitative estimation was lacking. The magnitude of raindrop evaporation depends upon ambient humidity and temperature, which vary considerably during the ISM. Consequently, the isotope biases would also vary over various time scales. The present study aims to investigate the magnitude of the monthly scale variation in raindrop evaporation in the simulations and its causal connection with the corresponding variation in isotope biases. Towards this, we compare an 11-year-long (1997–2007) dataset of rain isotope ratios (both oxygen and hydrogen) from an Indian station, Kozhikode (Kerala), obtained under the Global Network of Isotopes in Precipitation (GNIP) programme of the International Atomic Energy Agency (IAEA) with the corresponding outputs of two isotope-enabled nudged GCMs—ISOGSM and LMDZ4. The raindrop evaporation fractions are estimated for 44 ISM months (June–September) of the study period using the Stewart (1975) formalism. Using a simple condensation–accretion model based on equilibrium fractionation from vapour, obtained from two adopted vapour isotope profiles, we estimate the liquid water isotope ratios at the cloud base. Considering this water as the initial rain, the raindrop evaporation fractions are estimated using the observed oxygen and hydrogen isotope ratios of Kozhikode surface rain samples. The estimated fractions show strong positive correlations with the isotope biases (R2 = 0.60 and 0.66). This suggests that lower estimates of raindrop evaporation could be responsible for the rain isotope biases in these two GCMs. [ABSTRACT FROM AUTHOR]

The Indo-Pacific Ocean appears exponentially stratified between 1- and 3-km depth with a decay scale on the order of 1 km. In his celebrated paper "Abyssal recipes," W. Munk proposed a theoretical explanation of these observations by suggesting a pointwise buoyancy balance between the upwelling of cold water and the downward diffusion of heat. Assuming a constant upwelling velocity w and turbulent diffusivity κ, the model yields an exponential stratification whose decay scale is consistent with observations if κ ∼ 10−4 m2 s−1. Over time, much effort has been made to reconcile Munk's ideas with evidence of vertical variability in κ, but comparably little emphasis has been placed on the even stronger evidence that w decays toward the surface. In particular, the basin-averaged w nearly vanishes at 1-km depth in the Indo-Pacific. In light of this evidence, we consider a variable-coefficient, basin-averaged analog of Munk's budget, which we verify against a hierarchy of numerical models ranging from an idealized basin-and-channel configuration to a coarse global ocean simulation. Study of the budget reveals that the decay of basin-averaged w requires a concurrent decay in basin-averaged κ to produce an exponential-like stratification. As such, the frequently cited value of 10−4 m2 s−1 is representative only of the bottom of the middepths, whereas κ must be much smaller above. The decay of mixing in the vertical is as important to the stratification as its magnitude. Significance Statement: Using a combination of theory and numerical simulations, it is argued that the observed magnitude and shape of the global ocean stratification and overturning circulation appear to demand that turbulent mixing increases quasi-exponentially toward the ocean bottom. Climate models must therefore prescribe such a vertical profile of turbulent mixing in order to properly represent the heat and carbon uptake accomplished by the global overturning circulation on centennial and longer time scales. [ABSTRACT FROM AUTHOR]

Motivation: Climate 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 Contained: Spatio‐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 Grain: Global landmasses, at 1° × 1°. Time Period and Grain: Last 5 Myr at 1000 year resolution. Major Taxa and Level of Measurement: Not applicable. Software Format: Tab‐delimited text files and accompanying R code to derive bioclimatic variables. [ABSTRACT FROM AUTHOR]

The frequency of large-scale anomalous precipitation events over China has increased during 1961–2018. However, it remains challenging to understand the mechanisms associated with these anomalous events showing different spatial patterns. Here, we applied an autoencoder technique to identify large-scale anomalous precipitation events for both observations and model simulations, which were then classified into several patterns through a self-organizing map method. The synoptic behavior and atmospheric circulation background of different anomalous patterns were also analyzed using simultaneous composite analyses. Results show that occurrences of different anomalous precipitation patterns have increased significantly, except those centered in North China, Northeast China, and the Yangtze River basin. The anomalous precipitation patterns manifest various intraseasonal distributions, which are linked to zonal oscillations of the western North Pacific subtropical high (WNPSH) and meridional displacements of East Asia westerly jet (EAJ). Accompanied by the westward movement of WNPSH, anticyclonic systems transport warm moist air from the Indian Ocean and the South China Sea to converge with the cold air caused by anomalous cyclones over the northwest flank of the WNPSH, leading to large-scale anomalous precipitation in these regions. Besides WNPSH, the northward and southward displacements of EAJ also favor the occurrence of anomalous precipitation events in northern and southern China, respectively. Our study also illustrates that the occurrence frequency of anomalous precipitation events is projected to increase remarkably under the Shared Socioeconomic Pathway 5–8.5 (SSP585) scenario by rates of twofold to fourfold. [ABSTRACT FROM AUTHOR]

This work assesses the contribution of assimilating AMSU-A satellite-based radiance measurements to a global data assimilation system based on an atmospheric general circulation model and the local ensemble transform Kalman filter (LETKF). The radiance measurements were from three channels that are sensitive to the upper troposphere and lower stratosphere. The contribution of these measurements, or AMSU-A observation impact, was estimated both through ensemble-based forecast sensitivity to observations (EFSO) and observing system experiments (OSEs). Two streams of data-denial experiments for the AMSU-A observations were performed for about one month during winter in each hemisphere. The OSEs quantified the accumulated observation impact by cycling (repeating) data denials: including AMSU-A observations reduced the total observation impact for all observations of each data assimilation cycle. In contrast, EFSO estimated AMSU-A to increase the total observation impact. The opposing effects were attributed to the accumulated observation impact in the OSEs; the accumulation could stabilize the data assimilation cycles. In both experiments, the accumulated observation impact of AMSU-A was strongest in the upper troposphere, particularly in the austral midlatitudes where westerly jets exist and observations of other types are sparse. EFSO also assessed AMSU-A to have the most beneficial observation impact in similar locations. The AMSU-A observation impact tended to accumulate just downstream of where EFSO estimated the beneficial observation impact signals. The accumulated AMSU-A observation impact was tied to dynamic processes in the upper-tropospheric and general stratospheric circulation. Therefore, EFSO helps estimate the beneficial distributions of AMSU-A accumulated observation impact by considering their dynamical propagation. [ABSTRACT FROM AUTHOR]

Climate change is linked with change in precipitation, evapotranspiration, and other climatological parameters, and therefore the runoff of a river basin will be affected. The Gomati River basin is the largest in Tripura. The increased settlement in the Gomati River basin and climate change may threaten the natural flow patterns that enable its diversity. This study assesses the impact of climate change on total flow from a catchment in northeast India (the Gomati River catchment). For this assessment, the Group Method of Data Handling (GMDH) model was used to simulate the rainfall–runoff relationship in the catchment with respect to the observed data during 2008–2009. The statistically downscaled outputs of the Hadley Centre Global Environment Model version 2 (HadGEM2-ES) general circulation model scenario was used to assess the impacts of climate change on the Gomati River basin. Future projections were developed for the 2030s, 2040s, and 2050s. The results of this study may contribute to the development of adaptive strategies and future policies for the sustainable management of water resources in northeast Tripura. [ABSTRACT FROM AUTHOR]

Compared to the canonical eastern Pacific El Niño, the understanding and ability to predict the central Pacific (CP)-type event still need further improvement. In this study, the principal component analysis-based particle swarm optimization algorithm (PPSO) is applied in Geophysical Fluid Dynamics Laboratory Climate Model version 2p1 (GFDL CM2p1) to obtain the optimal precursors (OPRs) for CP El Niño events, based on the conditional nonlinear optimal perturbation (CNOP) method. For this, three normal years with neither El Niño nor La Niña events, i.e., three cases, are chosen as the reference states. The obtained OPRs for these cases exhibit a consistent positive sea surface temperature (SST) perturbation distribution in the subtropical North Pacific (208-408N, 1758E-1408W), which is further proven to be crucial for the evolution of CP El Niño based on the Northern and Southern Hemisphere significance test results. Mechanically, these positive SST perturbations are enhanced and reach the equatorial Pacific via wind-evaporation-SST (WES) feedback to evolve into a CP El Niño at the end of the year. The nonlinear approach is adopted to investigate the predictability of CP El Niño events and can shed some light on future studies. [ABSTRACT FROM AUTHOR]

A new set of CMIP6 data downscaled using the localized constructed analogs (LOCA) statistical method has been produced, covering central Mexico through southern Canada at 6-km resolution. Output from 27 CMIP6 Earth system models is included, with up to 10 ensemble members per model and 3 SSPs (245, 370, and 585). Improvements from the previous CMIP5 downscaled data result in higher daily precipitation extremes, which have significant societal and economic implications. The improvements are accomplished by using a precipitation training dataset that better represents daily extremes and by implementing an ensemble bias correction that allows a more realistic representation of extreme high daily precipitation values in models with numerous ensemble members. Over southern Canada and the CONUS exclusive of Arizona (AZ) and New Mexico (NM), seasonal increases in daily precipitation extremes are largest in winter (∼25% in SSP370). Over Mexico, AZ, and NM, seasonal increases are largest in autumn (∼15%). Summer is the outlier season, with low model agreement except in New England and little changes in 5-yr return values, but substantial increases in the CONUS and Canada in the 500-yr return value. One-in-100-yr historical daily precipitation events become substantially more frequent in the future, as often as once in 30–40 years in the southeastern United States and Pacific Northwest by the end of the century under SSP 370. Impacts of the higher precipitation extremes in the LOCA version 2 downscaled CMIP6 product relative to the LOCA downscaled CMIP5 product, even for similar anthropogenic emissions, may need to be considered by end-users. [ABSTRACT FROM AUTHOR]

Objective: This research aimed to identify variations in areas with agroecological potential for Moringa oleifera Lam. (Moringa) cultivation, derived from the effects of climate change to the near horizon of 2039 in the state of Veracruz, Mexico. Design/methodology/approach: The future scenario considered the current agroecological potential in the State and the general circulation model (GCM) HADGEM2-ES for the RCP8.5 scenario projected to the near future, 2039, with five categories: Very High, High, Medium, Low, and Very Low potential. Results: An area with a Very High category of 1,057,415 hectares (ha) was identified, which corresponds to an expansion of 4.9% with respect to the current size. It was determined that climate change favors the cultivation of Moringa in three areas of the state. The most significant variation with an increase in the Very High category (115.58%) was identified in southern Veracruz, followed by the central area (110.17%). The greatest decrease (-4.53%) occurred in the north of the state. Limitations on study/implications: Only the regions with Very High potential were identified, without considering those with High, Medium, Low, and Very Low agroecological potential. Findings/conclusions: The projections under climate change conditions to the horizon of 2039 highlight the expansion of regions with Very High potential for cultivating the species in 19% of the Veracruz territory. [ABSTRACT FROM AUTHOR]

The study of climate and its change had traditionally been descriptive and regionally oriented and regarded as a minor branch of meteorology. With advances in computing technology, however, climate studies gradually moved towards highly mathematical endeavors. By the mid-1970s, climate research became dominated by dynamical meteorologists, atmospheric physicists, and physical oceanographers armed with complex numerical modeling as a principal methodology. The observational studies of climate, as well as simple climate modeling studies focusing on climate sensitivity and feedback processes, continued to play an essential role in raising the issue of climate change -- both natural and anthropogenic -- in the 1960s and early 1970s. On the other hand, many meteorologists firmly believed that climate and its change could only be properly studied using numerical models of the large-scale atmospheric circulation -- i.e., general circulation models (GCMs). This tendency was particularly strong in Britain. From early on, the British Meteorological Office devoted much of its climate research efforts to developing GCMs. This paper traces the history of GCM developments at the British Meteorological Office from the 1950s to the mid-1970s and also explores how particular styles of scientific practice, disciplinary traditions, institutional cultures, and broader political environments shaped these developments. [ABSTRACT FROM AUTHOR]

Tropical cyclone intensification processes are explored in six high-resolution climate models. The analysis framework employs process-oriented diagnostics that focus on how convection, moisture, clouds, and related processes are coupled. These diagnostics include budgets of column moist static energy and the spatial variance of column moist static energy, where the column integral is performed between fixed pressure levels. The latter allows for the quantification of the different feedback processes responsible for the amplification of moist static energy anomalies associated with the organization of convection and cyclone spinup, including surface flux feedbacks and cloud-radiative feedbacks. Tropical cyclones (TCs) are tracked in the climate model simulations and the analysis is applied along the individual tracks and composited over many TCs. Two methods of compositing are employed: a composite over all TC snapshots in a given intensity range, and a composite over all TC snapshots at the same stage in the TC life cycle (same time relative to the time of lifetime maximum intensity for each storm). The radiative feedback contributes to TC development in all models, especially in storms of weaker intensity or earlier stages of development. Notably, the surface flux feedback is stronger in models that simulate more intense TCs. This indicates that the representation of the interaction between spatially varying surface fluxes and the developing TC is responsible for at least part of the intermodel spread in TC simulation.

ABSTRACT The objective of this study was to analyze the influence of climate change on the flow duration curves of five small rural catchments in the Amazon, as well as the hydroelectric power duration curves of micro hydroelectric power plants (MHPs) which can be implemented in the respective hydroelectric sites. The scenarios used were RCP 4.5 and RCP 8.5, defined during the 5th IPCC Report; these are the main optimistic and realistic greenhouse gas emission scenarios in the future. They projected on the flow duration curves of the small catchments under study and, consequently, on the hydroelectric power duration curves. Future precipitation was obtained via the PROJETA platform. For the simulation of flow duration curves, a rainfall-runoff model was used. The determination of the power duration curves was considered with the observed and simulated flow duration curves and with design parameters available in the literature. Based on the simulations, the reduction of high duration flows (minimum flows) was verified for the future scenarios studied, mainly for RCP 8.5, reflecting directly in the reduction of the hydro energetic potential of the analyzed rural catchments.

When quadrupling the atmospheric CO2 concentration in relation to preindustrial levels, most global climate models show an initially strong net radiative feedback that significantly reduces the energy imbalance during the first two decades after the quadrupling. Afterward, the net radiative feedback weakens, needing more surface warming than before to reduce the remaining energy imbalance. Such weakening radiative feedback has its origin in the tropical oceanic stratiform cloud cover, linked to an evolving spatial warming pattern. In the classic linearized energy balance framework, such variation is represented by an additional term in the planetary budget equation. This additional term is usually interpreted as an ad hoc emulation of the cloud feedback change, leaving unexplained the relationship between this term and the spatial warming pattern. I use a simple nonlinearized energy balance framework to justify that there is a physical interpretation of this term: the evolution of the spatial pattern of warming is explained by changes in the ocean's circulation and energy uptake. Therefore, the global effective thermal capacity of the system also changes, leading to the additional term. In reality, the clouds respond to what occurs in the ocean, changing their radiative effect. In the equation, the term is now a concrete representation of the ocean's role. Additionally, I derive for the first time an explicit mathematical expression of the net radiative feedback and its temporal evolution in the linearized energy balance framework. This mathematical expression supports the new proposed interpretation. As a corollary, it justifies the 20-yr time scale used to study the variation of the net radiative feedback. Significance Statement: Linearized energy balance models have helped the study of Earth's radiative response. However, the present linear models are at the edge of usefulness to get more insights. In this work, I justify that part of the nonlinearity in the radiative response can be explained without peculiar atmospheric radiative feedback mechanisms or a nonlinearity in the radiative response. Instead, the concept of an evolving thermal capacity recovers the ocean's role in redistributing the energy, changing the spatial warming pattern, and, finally, altering the atmospheric feedback mechanisms. This work also justifies the time scales used in the field for studying the variation of the net radiative feedback. [ABSTRACT FROM AUTHOR]

Ocean heat content (OHC) is one of the most relevant metrics tracking the current global heating. Therefore, simulated OHC time series are a cornerstone for assessing the scientific performance of Earth system models and global climate models. Here we present a detailed analysis of OHC change in simulations of the historical climate (1850–2014) performed with two pairs of CMIP6 models: U.K. Earth System Model 1 (UKESM1.0) and HadGEM3-GC3.1-LL, and CNRM-ESM2-1 and CNRM-CM6-1. The small number of models enables us to analyze OHC change globally and for individual ocean basins, making use of a novel ensemble of observational products. For the top 700 m of the global ocean, the two CNRM models reproduce the observed OHC change since the 1960s closely. The two U.K. models (UKESM1.0-LL and HadGEM3-GC3.1-LL) compensate a lack of warming in the 0–700 m layer in the 1970s and 1980s with warming below 2000 m. The observed warming between 700 and 2000 m is substantially underestimated by all models. An increased relevance for ocean heat uptake in the Atlantic after 1991—suggested by observations—is picked up by the U.K. models but less so by the CNRM models, probably related to an AMOC strengthening in the U.K. models. The regional ocean heat uptake characteristics differ even though all four models share the same ocean component (NEMO ORCA1). Differences in the simulated global, full-depth OHC time series can be attributed to differences in the model's total effective radiative forcing. [ABSTRACT FROM AUTHOR]

A global–regional-unified nonhydrostatic dynamical core was constructed on the Yin–Yang grid using a semi-implicit semi-Lagrangian solver. Arbitrary coordinate rotation was possible for both global and limited-area models with a multilevel nesting capability. Significant flexibility is available when configuring the model’s horizontal mesh using coordinate rotation. The performance of the dynamical core was assessed using a series of numerical tests in Cartesian and spherical coordinates. The results illustrate the reasonable ability of the piecewise rational method to manage sharp gradient advection and the capability of the dry dynamical core to simulate fine structures in target systems in the Cartesian and spherical configurations. An average convergence rate of 2.43 was confirmed for the dry dynamical core in the balanced flow test. The nested grid improved the fine structure simulation of the baroclinic wave development without affecting wave propagation. The propagating speed of the vortex remained unchanged in the nested grid in the colliding modons test, although the vorticity amplitude decayed more slowly than that in the coarse grid. Proper development of topographic waves was achieved for both large- and small-scale mountains with a clear damping effect in association with the off-center semi-implicit average. A deepened trough in the nesting region, in comparison with that in the parent grid, was simulated in a topographic Rossby wave test. The implementation of coordinate rotation and grid nesting improved the numerical performance when managing atmospheric dynamical problems at relatively low cost. [ABSTRACT FROM AUTHOR]

Land-use and land-cover changes (hereafter simply "land use") alter climates biogeophysically by affecting surface fluxes of energy and water. Yet, near-surface temperature responses to land use across observational versus model-based studies and spatial-temporal scales can be inconsistent. Here we assess the prevalence of the historical land use signal of daily maximum temperatures averaged over the warmest month of the year (tLU) using regularized optimal fingerprinting for detection and attribution. We use observations from the Climatic Research Unit and Berkeley Earth alongside historical simulations with and without land use from phase 6 of the Coupled Model Intercomparison Project to reconstruct an experiment representing the effects of land use on climate. To assess the signal of land use at spatially resolved continental and global scales, we aggregate all input data across reference regions and continents, respectively. At both scales, land use does not comprise a significantly detectable set of forcings for two of four Earth system models and their multimodel mean. Furthermore, using a principal component analysis, we find that tLU is mostly composed of the nonlocal effects of land use rather than its local effects. These findings show that, at scales relevant for climate attribution, uncertainties in Earth system model representations of land use are too high relative to the effects of internal variability to confidently assess land use. [ABSTRACT FROM AUTHOR]

We present four 140-yr wind-wave climate simulations (1961–2100) forced with surface wind speed and sea ice concentration from two CMIP6 GCMs under two different climate scenarios: SSP1–2.6 and SSP5–8.5. A global three-grid system is implemented in WAVEWATCH III to simulate the wave–ice interactions in the Arctic and Antarctic regions. The models perform well in comparison with global satellite altimeter and in situ buoys climatology. The comparison with traditional trend analyses demonstrates the present GCM-forced wave models' ability to reproduce the main historical climate signals. The long-term datasets allow a comprehensive description of the twentieth- and twenty-first-century wave climate and yield statistically robust trends. Analysis of the latest IPCC ocean climatic regions highlights four regions where changes in wave climate are projected to be most significant: the Arctic, the North Pacific, the North Atlantic, and the Southern Ocean. The main driver of offshore wave climate change is the wind, except for the Arctic where the significant sea ice retreat causes a sharp increase in the projected wave heights. Distinct changes in the wave period and the wave direction are found in the Southern Hemisphere, where the poleward shift of the Southern Ocean westerlies causes an increase in the wave period of up to 5% and a counterclockwise change in wave direction of up to 5°. The new CMIP6 forced wave models improve in performance compared to previous CMIP5 forced wave models, and will ultimately contribute to a new CMIP6 wind-wave climate model ensemble, crucial for coastal adaptation strategies and the design of future marine offshore structures and operations. Significance Statement: The purpose of this study is to advance the understanding of ocean wind-wave climate evolution over the twentieth and twenty-first centuries and to effectively communicate the long-term impacts of climate change in diverse wind-wave climatic regions across the globe. The 140-yr continuous model results produced in this work are crucial to studying changes in extreme sea states and investigating the relationship between interdecadal periodic oscillations and long-term climate trends. The dataset produced can be used to gain further insight into the substantial long-term changes of the polar wind-wave climate caused by the rapid decrease of sea ice coverage, and the evolution of the directional changes in the sea states triggered by climate change. [ABSTRACT FROM AUTHOR]

The Indonesian Throughflow (ITF) is projected to slow down under anthropogenic warming. Several mechanisms}some mutually conflicting}have been proposed but the detailed processes causing this slowdown remain unclear. By turning on/off buoyancy and wind forcings globally and in key regions, this study investigates the dynamical adjustments underlying the centennial ITF slowdown in the global oceans and climate models. Our results show that the projected weakened ITF transport in the top 1500 m is dominated by remote anomalous buoyancy forcing in the North Atlantic Ocean. Specifically, surface freshening and warming over the North Atlantic Ocean slow the Atlantic meridional overturning circulation (AMOC), and the resultant dynamic signals propagate through the coastal-equatorial waveguide into the southeastern Indian Ocean and western Pacific Ocean, causing the reduction of ITF transport over a deep layer. In contrast, the anomalous surface buoyancy flux in the Indo-Pacific affects the ocean temperature and salinity in a shallow upper layer, resulting in ITF changes in forms of high baroclinic mode structure with negligible impacts on the net ITF transport. A vertical partitioning index is proposed to distinguish the remote forcing via the AMOC and regional forcing in the Indo-Pacific Ocean, which could be useful for monitoring, attributing, and predicting the changing ITF transport under global warming. [ABSTRACT FROM AUTHOR]

African easterly waves (AEWs) exert significant influence on local and downstream high-impact weather including tropical cyclone (TC) genesis over the Atlantic. Accurate representation of AEWs in climate and weather prediction models therefore is necessary for skillful predictions. In this study, we examine simulated AEWs, including their evolution, vertical structure, and linkage to tropical cyclone genesis, in the NASA Goddard Earth Observing System Model, version 5 (GEOS-5) atmospheric global climate model. Identified by the leading empirical orthogonal function mode of time-filtered precipitation, the observed westward propagating AEWs along the southern track over the Atlantic are largely captured in GEOS-5, but with a slower phase speed and significantly weaker amplitude downstream off the West Africa coast. The weak downstream development of AEWs in GEOS-5 is accompanied by much reduced TC genesis over the main development region. Further analyses suggest that the slow westward propagation and weaker AEW amplitude downstream can be ascribed to a weak African easterly jet, while overestimated negative (positive) meridional potential vorticity (PV) gradients appear to the north (south) of 10°N in GEOS-5. The greatly overestimated positive meridional PV gradient to the south of 10°N is expected to generate strong horizontal stretching in the AEW wave pattern in the model, which hinders organization of convection and its feedback to sustain the AEW development. Persistent and vigorous AEW precipitation in the Guinea Highlands of the West Africa coast could also be responsible for reduced westward propagation of AEWs in the model. [ABSTRACT FROM AUTHOR]

The response of trade cumulus clouds to warming remains a major source of uncertainty for climate sensitivity. Recent studies have highlighted the role of the cloud-convection coupling in explaining this spread in future warming estimates. Here, using observations from an instrumented site and an airborne field campaign, together with high-frequency climate model outputs, we show that i) over the course of the daily cycle, a cloud transition is observed from deeper cumuli during nighttime to shallower cumuli during daytime, ii) the cloud evolution that models predict from night to day reflects the strength of cloud sensitivity to convective mass flux and exhibits many similarities with the cloud evolution they predict under global warming, and iii) those models that simulate a realistic cloud transition over the daily cycle tend to predict weak trade cumulus feedback. Our findings thus show that the daily cycle is a particularly relevant testbed, amenable to process studies and anchored by observations, to assess and improve the model representation of cloud-convection coupling and thus make climate projections more reliable. [ABSTRACT FROM AUTHOR]

A vertically resolved moist static energy (MSE) variance budget framework is used to diagnose processes associated with the development of tropical cyclones (TCs) in a general circulation model (GCM) under realistic boundary conditions. Previous studies have shown that interactions between radiation and MSE promote TC development. Here, we examine the vertical contributions of radiation and its interactions with MSE by performing several mechanism-denial experiments in which synoptic-scale radiative interactions are suppressed either in the boundary layer or in the free troposphere. Partly suppressing radiative interactions results in a reduction in global TC frequency. However, the magnitude of reduction and structure of the feedback depend on the intensity and structure of the TCs in these mechanism-denial experiments, indicating that both the magnitude and the vertical location of radiative interactions can impact global TC frequency. Using instantaneous 6-hourly outputs, an explicit computation reveals distinct spatial patterns of the advection term: the vertical component is positive in the mid- to upper troposphere, which reflects an upward transport of MSE by deep convection, whereas the horizontal component is positive in the boundary layer. These results illustrate the impact of the vertical distribution of radiative interactions and vertically varied contribution of the advection term in the development of TCs. [ABSTRACT FROM AUTHOR]

Temperate forests are key to the balance and provision of hydrological and environmental services. Currently, these forests are subject to human alterations as well as to the effects of global change, including warming, variability, deforestation, and forest fires. As a consequence, the hydrological balance has been modified. The present study simulates the effects of climate change and land use change on the hydrological balance of micro-watersheds in Mexico using the hydrological model Water Evaluation and Planning (WEAP). The land use change between 1995 and 2021 was estimated to establish a baseline. Climate scenario SSP585 was projected using three global models, MPI-ESM1-2-LR, HadGEM3-GC31-LL, and CNRM-CM6-1 by the 2081–2100 horizon, along with two scenarios of land use change: one with forest permanence and another with loss of forest cover and increased forest fires. Results indicate that future climatic conditions will modify the hydrological balance at the microbasin level. Even with positive conditions of forest permanence, increases in surface runoff of 124% (CNRM), 35% (HadGEM3), and 13% (MPI) are expected. The projections of coverage loss and fires showed surface runoff increases of 338% (CNRM), 188% (HadGEM3), and 143% (MPI). In the high areas of the microbasins where temperate forest predominates, climatic variations could be contained. If the forest is conserved, surface runoff decreases by −70% (CNRM), −87% (HadGEM3), and −89% (MPI). Likewise, the moisture in the soil increases. In areas with temperate forests, there will be modifications of the hydrological balance mainly due to the increase in evapotranspiration (due to the increase in temperature and precipitation). This will cause a significant decrease in flow and interflow. The alteration of these flows will decrease water availability in soil for infiltration. It is expected that the availability of hydrological and environmental services will be compromised in the entire study area due to climate change. [ABSTRACT FROM AUTHOR]

Previous studies have shown that climate sensitivity, defined as the global mean surface temperature change per unit radiative forcing, is smaller for solar radiative forcing compared to an equivalent CO2 radiative forcing. We investigate the causes for this difference using the NCAR CAM4 model. The contributions to the climate feedback parameter, which is inversely related to climate sensitivity, are estimated for water vapor, lapse rate, Planck, albedo, and cloud feedbacks using the radiative kernel technique. The total feedback estimated for CO2 and solar radiative forcing from our model simulations is −1.23 and −1.45 W m−2 K−1, respectively. We find that the difference in feedback between the two cases is primarily due to differences in lapse rate, water vapor, and cloud feedbacks, which together explain 65% of the difference in total feedback. The rest comes from Planck and albedo feedbacks. The differences in feedbacks arise mainly from differences in the horizontal (meridional) structure of forcing and the consequent warming. Our study provides important insights into the effects of the meridional structure of forcing on climate feedback, which is important for evaluating global climate change from different forcing agents. Significance Statement: An increase in atmospheric CO2 concentration or an increase in incoming solar radiation leads to a rise in the radiative budget and consequent climate warming, which is amplified by the presence of multiple climate feedbacks. These feedbacks, from changes in surface albedo, combined effect of water vapor and the vertical lapse rate of temperature, and changes in clouds, differ between solar and CO2 forcing. Using radiative kernels, this study quantifies these individual feedbacks for an equivalent radiative change caused by an increase in CO2 or incoming solar radiation, showing how the differences arise from differences in the meridional patterns of warming. In agreement with prior studies, these differences can explain the smaller efficacy of solar forcing compared to CO2 forcing. [ABSTRACT FROM AUTHOR]

Global climate models (GCMs) developed by the numerical simulation of physical processes in the atmosphere, ocean, and land are useful tools for climate prediction studies. However, these models involve parameterizations and assumptions for the simulation of complex phenomena, which lead to random and structural errors called biases. So, the GCM outputs need to be bias-corrected with respect to observed data before applying these model outputs for future climate prediction. This study develops a statistical bias correction approach using a four-layer feedforward radial basis neural network – a generalized regression neural network (GRNN) to reduce the biases of the near-surface temperature data in the Indian mainland. The input to the network is the CNRM-CM5 model output gridded data of near-surface temperature for the period 1951–2005, and the target to the model used for bias correcting the input data is the gridded near-surface temperature developed by the Indian Meteorological Department for the same period. Results show that the trained GRNN model can improve the inherent biases of the GCM output with significant accuracy, and a good correlation is seen between the test statistics of observed and bias-corrected data for both the training and testing period. The trained GRNN model developed is then used for bias correction of CNRM-CM5 modelled projected near-surface temperature for 2006–2100 corresponding to the RCP4.5 and RCP8.5 emission scenarios. It is observed that the model can adapt well to the nature of unseen future temperature data and correct the biases of future data, assuming quasi-stationarity of future temperature data for both emission scenarios. The model captures the seasonal variation in near-surface temperature over the Indian mainland, having diverse topography appreciably, and this is evident from the bias-corrected output. HIGHLIGHTS Analysed the performance of the GRNN in correcting the inherent biases of GCM output near-surface temperature (NST) gridded data.; The results show that the method has better accuracy in correcting the biases as compared to the prevalent techniques, considering the diverse topography and seasonal variations in the study area.; The method is also successful in correcting the biases in future NST gridded data with decent accuracy.;

How do ocean initial states impact historical and future climate projections in Earth system models? To answer this question, we use the 50-member Canadian Earth System Model (CanESM2) large ensemble, in which individual ensemble members are initialized using a combination of different oceanic initial states and atmospheric microperturbations. We show that global ocean heat content anomalies associated with the different ocean initial states, particularly differences in deep ocean heat content due to ocean drift, persist from initialization at year 1950 through the end of the simulations at year 2100. We also find that these anomalies most readily impact surface climate over the Southern Ocean. Differences in ocean initial states affect Southern Ocean surface climate because persistent deep ocean temperature anomalies upwell along sloping isopycnal surfaces that delineate neighboring branches of the upper and lower cells of the global meridional overturning circulation. As a result, up to a quarter of the ensemble variance in Southern Ocean turbulent heat fluxes, heat uptake, and surface temperature trends can be traced to variance in the ocean initial state, notably deep ocean temperature differences of order 0.1 K due to model drift. Such a discernible impact of varying ocean initial conditions on ensemble variance over the Southern Ocean is evident throughout the full 150 simulation years of the ensemble, even though upper ocean temperature anomalies due to varying ocean initial conditions rapidly dissipate over the first two decades of model integration over much of the rest of the globe. [ABSTRACT FROM AUTHOR]

Air temperature and precipitation outputs from 10 CMIP6 GCMs were input to the Precipitation-Runoff Modeling System hydrologic model to evaluate water and energy responses in three headwater basins to projected climate change over the twenty-first century. The headwater basins (398–801 km2) are located within the Mataura River basin in the South Island of New Zealand. CMIP6 datasets included two emission scenarios [shared socioeconomic pathways (SSPs) SSP2-4.5 and SSP5-8.5]. Half of the 10 GCMs selected in the study have equilibrium climate sensitivity (ECS) values above 4.5°C, which has been considered the upper end of equilibrium climate sensitivity. Modeling results included increased annual air temperature, evapotranspiration, and precipitation by the end of the twenty-first century for both SSP emissions scenarios, both high- and low-ECS GCMs, and all three headwater basins. Monthly precipitation and evapotranspiration totals also increased for all or most months. Monthly streamflow changes generally corresponded with monthly precipitation changes. Snowpack decreased significantly in depth and seasonal duration in all basins. However, streamflow increased for all SSP and ECS groups and basins because increased precipitation was consistently greater than increased evapotranspiration losses. Sources of uncertainty include the GCMs, climate sensitivity, downscaling, bias adjustment, emission scenarios, and the hydrologic model. Simulated hydrologic responses based on climate data from GCMs with ECS values of greater than 4.5°C could be less plausible since previous studies have suggested true ECS ranges from 1.5° to 4.5°C. [ABSTRACT FROM AUTHOR]

Observing system experiments were undertaken within the 4D-Var data assimilation of the Météo-France global numerical weather prediction (NWP) model. A 6-month period was chosen (October 2019–March 2020) where 40 million observations per day were assimilated. The importance of in situ observations provided by aircraft, radiosondes, and surface weather stations, despite their small fractional amount (7%), has been confirmed particularly in the Northern Hemisphere. Moreover, the largest impact over Europe in terms of root-mean-square error (RMSE) scores comes from surface observations. Satellite data play a dominant role over tropical regions and the Southern Hemisphere. Microwave radiances have a more pronounced impact on the long range and on the humidity field than infrared radiances, despite being less numerous (10% versus 80%). Bending angles impact significantly the quality of the upper-troposphere–lower-stratosphere temperature of the tropics and Southern Hemisphere. Atmospheric motion vectors (AMVs) are beneficial in wind forecasts at low and high levels in the tropics and the Southern Hemisphere, but also in the humidity field. Such impacts are only significant during the first 48 h of the forecasts. Scatterometer winds have an impact restricted to low levels that is kept at longer ranges. A comparison with forecast sensitivity–observation impact studies over a 3-month period using the same measure of short-range (24-h) forecast errors reveals that the ranking between the major observing systems is kept between these two ways of measuring observation impact in NWP. From our conclusions, recommendations are provided on possible evolutions of the global observing system for NWP. [ABSTRACT FROM AUTHOR]

The tropical intraseasonal variability in an idealized moist general circulation model (GCM) coupled to a slab ocean is investigated. The model has a simple moist convection scheme and realistic radiative transfer, but no parameterization of cloud processes. In a zonally symmetric aquaplanet state, variability is dominated by westward-propagating Rossby waves. Enforcing zonal asymmetry through the application of a prescribed ocean heat flux in the bottom boundary leads to the development of a slow, eastward propagating mode that bears some of the characteristics of the observed Madden–Julian oscillation (MJO). When the ocean heat flux is made stronger, high-frequency Kelvin waves exist alongside the MJO mode. The strength of the disturbances and the spatial distribution of their precipitation anomalies are sensitive to the strength of intraseasonal sea surface temperature (SST) anomalies. The greatest resemblance to the MJO is observed when shallow slab ocean depths (1 m) are used, but the mode still exists at deeper slabs. Sensitivity experiments to the parameters of the convection scheme suggest that the simulated MJO mode couples to convection in a way that is distinct from both Kelvin and Rossby waves generated by the model. Analysis of the column moist static energy (CMSE) budget of the MJO mode suggests that column radiative heating plays only a weak role in destabilizing the mode relative to the stabilizing contribution of vertical advection. The CMSE budget analysis highlights the importance of the life cycle of horizontal advection for the destabilization and propagation of the MJO. Synergies between the generated MJO mode and linear theories of the MJO are discussed as well. [ABSTRACT FROM AUTHOR]

Lateral mesoscale eddy-induced tracer transport is traditionally represented in coarse-resolution models by the flux–gradient relation. In its most complete form, the relation assumes the eddy tracer flux as a product of the large-scale tracer concentration gradient and an eddy transport coefficient tensor. However, several recent studies reported that the tensor has significant spatiotemporal complexity and is not uniquely defined, that is, it is sensitive to the tracer distributions and to the presence of nondivergent ("rotational") components of the eddy flux. These issues could lead to significant biases in the representation of the eddy-induced transport. Using a high-resolution tracer model of the Gulf Stream region, we examine the diffusive and advective properties of lateral eddy-induced transport of dynamically passive tracers, reevaluate the utility of the flux–gradient relation, and propose an alternative approach based on modeling the local eddy forcing by a combination of diffusion and generalized eddy-induced advection. Mesoscale eddies are defined by a scale-based spatial filtering, which leads to the importance of new eddy-induced terms, including eddy-mean covariances in the eddy fluxes. The results show that the biases in representing these terms are noticeably reduced by the new approach. A series of targeted simulations in the high-resolution model further demonstrates that the approach outperforms the flux–gradient model in reproducing the stirring and dispersing effect of eddies. Our study indicates potential to upgrade the traditional flux–gradient relation for representing the eddy-induced tracer transport. [ABSTRACT FROM AUTHOR]

Climate change poses a first-order threat to human civilisation and governments across the world, their agencies and big and small corporations have announced climate emergencies and made commitments towards net zero emissions across a range of target dates. Regulators have tasked financial institutions in the insurance and banking sectors to expose their existing portfolios and lending practices to scrutiny as to resilience levels, preparedness and knowledge base relating to property risk level impacts from existing and emerging climate-driven property perils. The scope of these investigations has mobilised a range of consultancies and emerging climate service providers (CSPs) to support regulatory oversight and provide modelling input relative to expertise in a range of environmental issues driven by climate change. The combination of global emission scenarios and general circulation models (GCMs) with existing expertise in modelling real-world problems such as flooding, coastal erosion, storm and subsidence has produced forward-facing forecasts across the natural physical and societal risks. The regulatory results at portfolio levels have necessitated financial institutions scenario planning down to property address levels to assess overall scale of impacts and the possible provisioning requirements against multiple probabilities over decadal horizons out to 2100. These high-level assessments will in the next few years feed directly into valuation and property investigation for origination loans and the cash buyer. CSPs will inevitably seek to monetise a return on their investment in modelling for financial institutions and their unique exposure to portfolio-level provisioning as consultants to these organisations reporting to the regulator. How this data at a property level is interpreted spatially and temporally will be a unique new challenge for chartered surveyors and other property professionals within lending institutions and within the conveyancing sector. This paper looks at the development of portfolio-level climate change reporting, the scientific basis for decisioning and the real risks of assuming that scenario precision produces accurate climate outcomes at the property level. A range of evolving rule sets are proposed for lenders, valuation specialists and conveyancers to ensure reporting is fit for intended purpose. [ABSTRACT FROM AUTHOR]

July-September rainfall is a key component of Ethiopia's annual rainfall and is a source of rainfall variability throughout inland Greater Horn of Africa. In this study we investigate the relative influences of the Mascarene (MH) and South Atlantic (AH) highs on July-September rainfall in a covarying region of the Greater Horn of Africa using CHIRPS observed rainfall and the ERA5 reanalysis. We show that a mixed metric using the circulation at 850 hPa of these two subtropical anticyclones (AH-MH), is better correlated with rainfall than individual high circulations. Variations in remote circulation are translated by changes in Central African westerlies and Turkana Jet wind speeds. We apply the AH-MH mixed metric to the CMIP5 and CMIP6 ensembles and show that it is a good indicator of mean July-September rainfall across both ensembles. Biases in circulation are shown to be related to the Hadley circulation in CMIP5 atmosphere-only simulations, while causes of biases in CMIP6 are more varied. Coupled model biases are related to southern ocean warm biases in CMIP5 and western Indian Ocean warm biases in CMIP6. CMIP6 shows an improved relationship between rainfall and Turkana Jet winds and Central African westerlies across the ensemble. [ABSTRACT FROM AUTHOR]

Climate is one of the most important elements affecting the distribution of species, and it is expected that the distribution of species will be widely influenced by climate change. In plants, edaphic factors also play a special role along with climate in determining the distribution range. The current study aimed to predict the future distribution of the Persian manna (Astragalus adscendens), an endemic perennial shrub in Zagros Mountains of Western Iran. For this purpose, two sets of static (i.e. edaphic and physiographic) and dynamic (i.e. climatic) data and an ensemble approach were used to develop two edaphic-physiographic and climatic models. Current and future suitability maps are representative of the climatic and the edaphic-physiographic niches of A. Adscendens that were obtained based on climatic suitable areas filtered by edaphic-physiographic model. The filtered map has less suitable habitats compared to the climatic model. Three dynamic variables (mean temperature of wettest quarter, temperature seasonality, temperature annual range) and two static variables (altitude and volumetric fraction of coarse fragments) were identified as the most important factors in determining the habitat of A. Adscendens. The importance of altitude was greater than latitude in maintaining or losing suitable habitats under different climate change scenarios, suggesting that the species will not have range expansion or northward shift due to no significant shift in latitude and longitude. Results revealed a sharp decline in the suitable habitats in such that 67% and 91% of the current habitat may be lost by the year 2050 and 2070, respectively. Area reduction was more extreme in future scenarios with the higher level of CO2 emission. Range contraction of A. Adscendens will increases the risk of extinction. This study provides insights into the response of mountain plants, especially range restricted species, to climate change, revealing major dimensions of plant niche. Therefore, developing habitat management and conservation plans to preserve the predicted habitats of such species are required to preserve the predicted sustainable habitats. [ABSTRACT FROM AUTHOR]

Historical simulations and projections of climate extremes indices of precipitation and temperature were analysed over South America until the end of the 21st century through 31 general circulation models (GCMs) under four Representative Concentration Pathways. Simulations were compared with reanalysis data, and a Bayesian inference method was used to assess the uncertainties involved in the multi‐model climate projections. Regarding the precipitation extremes indices, the GCMs' simulations reasonably approached the reanalysis data, but with heterogeneous biases, both in sign and in the location of the highest values. The temperature extremes indices presented the smallest biases when compared to precipitation. Projections show a gradual growth of precipitation extremes events as the analysed radiative forcing scenario increases, both in magnitude and extent, over a large part of South America. Projections also indicate a decrease in cold days and nights and an increase in warm days and nights, more pronounced in the equatorial region. Bayesian inference method smoothed changes in precipitation extremes events, both in magnitude and extent, compared to the simple GCMs' ensemble mean. There was no considerable variation in the temperature indices when applying the Bayesian inference. Finally, the probability density functions resulted in a predominance of multimodal and wide curves for the precipitation indices, showing great uncertainties in the GCMs' results, differently from those for the temperature indices, where the GCMs presented good agreement represented through unimodal and narrow curves. [ABSTRACT FROM AUTHOR]

This study evaluates the simulation of the seasonal cycle of water isotopic composition over Tibetan Plateau regions (TP) from six isotope‐enabled general circulation models (GCMs) participating in the second Phase of Stable Water Isotope Intercomparison Group. For both meteorological factors (precipitation rate and wind field) and isotopic composition, GCMs generally agree with reanalysis data and in‐situ observations, but there is a significant spread across models and the isotopic seasonality is systematically underestimated. In the southern TP, the precipitation isotopic composition is more depleted in summer than in winter, and the amplitude of the simulated isotopic seasonal variations is primarily driven by the amplitude of the simulated upstream precipitation. In contrast, in the northern TP, the precipitation isotopic composition is more depleted in winter than in summer, and the amplitude of the simulated seasonal variability of isotopes is mainly driven by the simulated strength of the zonal wind. We conclude that the skill of a GCM to simulate the seasonal cycle in the isotopic composition depends mainly on the skill of the GCM to simulate the Indian summer monsoon precipitation and the westerlies. The same causes contributing to the underestimated seasonality at present‐day may also contribute to the underestimated δ18O change at the mid‐Holocene. Plain Language Summary: The stable isotopic composition of water is determined by the relative abundances of heavier to lighter isotopologues. Isotope‐enabled general circulation models (GCMs) simulate water isotope composition considering several physical processes operating in the hydrologic cycle. Therefore, a comparison between observed and simulated values provides a better understanding of the processes constraining the isotope values. However, the simulated water isotopic composition is sensitive to various physical processes and parameterization schemes. In this study, we investigate how the model biases in the representation of atmospheric processes affect the simulation of isotopic composition over the Tibetan Plateau (TP). We compare the simulated isotopic composition in precipitation and water vapor to in‐situ and satellite measurements. Our analysis indicates that most GCMs underestimate the seasonality of the isotopic composition in the precipitation and vapor. In the southern TP, the spread of upstream precipitation is an important factor controlling the inter‐model spread in isotopic seasonality. In the northern TP, the westerlies majorly control isotope biases. Key Points: Models systematically underestimate the precipitation isotopic seasonality both in the southern and northern TPThe inter‐model spread of precipitation isotopic seasonality in the southern TP is driven by the spread of upstream precipitationThe westerlies dominate the inter‐model spread of precipitation isotopic seasonality in the northern TP [ABSTRACT FROM AUTHOR]