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Atmospheric models forced with observed sea surface temperatures (SSTs) suggest a trend toward a more-stabilizing cloud feedback in recent decades, partly due to the surface cooling trend in the eastern Pacific (EP) and the warming trend in the western Pacific (WP). Here, we show model evidence that the low-cloud feedback has contributions from both forced and unforced feedback components and that its time variation arises in large part through changes in the relative importance of the two over time, rather than through variations in forced or unforced feedbacks themselves. Initial-condition large ensembles (LEs) suggest that the SST patterns are dominated by unforced variations for 30-yr windows ending prior to the 1980s. In general, unforced SSTs are representative of an ENSO-like pattern, which corresponds to weak low-level stability in the tropics and less-stabilizing low-cloud feedback. Since the 1980s, the forced signals have become stronger, outweighing the unforced signals for the 30-yr windows ending after the 2010s. Forced SSTs are characterized by relatively uniform warming with an enhancement in the WP, corresponding to a more-stabilizing low-cloud feedback in most cases. The time-evolving SST pattern due to this increasing importance of forced signals is the dominant contributor to the recent stabilizing shift of low-cloud feedback in the LEs. Using single-forcing LEs, we further find that if only greenhouse gases evolve with time, the transition to the domination of forced signals occurs 10–20 years earlier compared to the LEs with full forcings, which can be understood through the compensating effect between aerosols and greenhouse gases. [ABSTRACT FROM AUTHOR]

The weak temperature gradients in the tropical free troposphere due to the vanishing Coriolis force near the equator lead to a strong dynamical coupling over the entire tropics. Using theory and a suite of targeted model experiments, we show that the weak temperature gradients further weaken under global warming. We show that the temperature gradient is set by the circulation strength, with a weaker circulation being associated with weaker gradients. Thus, the known scaling difference between atmospheric radiative cooling and static stability that leads to a slowdown of the circulation under warming also leads to a weakening of the temperature gradients in the tropical free troposphere. The impact from the weakening circulation on the weakening of temperature gradients is shown to dominate over the impact of masked CO2 forcing and the El Niño–like tropical Pacific warming pattern in model projections. Key to the result is the nonlinear zonal momentum advection term. Using the well-known Matsuno–Gill model with the correct scaling of heating and static stability may give the correct sign of the response in the temperature gradients, but inaccurate scaling, due to the linear momentum damping in that model. The robust scaling of the magnitude of the tropical quasi-stationary structure with temperature opens possibilities for theoretical advances on questions of societal relevance, ranging from changes in tropical cloudiness to heat stress under climate change. [ABSTRACT FROM AUTHOR]

ABSTRACT The Coupled Model Inter‐comparison Project phase 6 (CMIP6) provides a suite of general circulation models (GCMs) and Socioeconomic Shared Pathways (SSPs) primarily for continental‐scale climate assessments. However, adapting these models for sub‐national assessments, particularly in countries with varied geography like Ecuador, and for complex variables such as precipitation, introduces challenges, including uncertainties in selecting appropriate GCMs and SSPs. To address these issues, we adopt a biogeographical approach that integrates regional climatic variations. Our analysis explores 26 GCMs, four SSP scenarios and four 20‐year time frames from WorldClim to evaluate discrepancies between the GCM precipitation projections, historical data and national climate projections across five Ecuadorian bioregions. This approach enabled us to sort the GCMs by annual precipitation medians, classify their monthly precipitation using Dynamic Time Warping (DTW) clustering, and develop ensembles highlighting both the largest and average precipitation anomalies within and beyond the bioregions. Among the 26 models examined, 16 projected an increase in annual precipitation in Ecuador, especially during the wet seasons, with the BCC‐CSM2‐MR model showing peak values, notably in the Choco region and eastern Amazon basin. Conversely, 10 models, with CMCC‐ESM2 showing the largest decreases, projected reduced precipitation across almost all Ecuadorian territories, except the Choco region. The largest reductions were in the Amazon basin, raising concerns about reduced precipitation. Discrepancies, primarily in the Andes and Galapagos bioregions, reveal the challenges posed by their complex topography and insular environments. While the GCMs captured spatial patterns of ENSO, our research was constrained to 20‐year averages, making direct comparison with historical records infeasible, highlighting the need for further research with shorter time frames and finer spatial resolutions. The variability in precipitation was linked to geographical factors, GCM configurations and unexpected SSP outcomes. Therefore, selecting GCMs and climatic indices tailored to specific bioregions is recommended for effective climate change impact assessments. [ABSTRACT FROM AUTHOR]

The southern Great Plains experience fluctuating precipitation extremes that significantly impact agriculture and water management. Despite ongoing efforts to enhance forecast accuracy, the underlying causes of these climatic phenomena remain inadequately understood. This study elucidates the relative influence of the tropical Pacific and Atlantic basins on April–May–June precipitation variability in this region. Our partial ocean assimilation experiments using the Community Earth System Model unveil the prominent role of interbasin interaction, with the Pacific and Atlantic contributing approximately 70% and 30%, respectively, to these interbasin contrasts. Our statistical analyses suggest that these tropical interbasin contrasts could serve as a more reliable indicator for late-spring precipitation anomalies than El Niño–Southern Oscillation. The conclusions are reinforced by analyses of seven climate forecasting systems within the North American Multi-Model Ensemble, offering an optimistic outlook for enhancing real-time forecasting of late-spring precipitation in the southern plains. However, the current predictive skills of the interbasin contrasts across the prediction systems are hindered by the lower predictability of the tropical Atlantic Ocean, pointing to the need for future research to refine climate prediction models further. Significance Statement: Agriculture and infrastructure in the southern plains face challenges from severe late-spring precipitation extremes. Traditional predictors like El Niño–Southern Oscillation (ENSO) lose effectiveness during the critical spring-to-summer transition, creating a forecasting gap. This study introduces the concept of tropical interbasin interactions, known to enhance seasonal predictability for late-spring precipitation in the southern plains. Novel climate model experiments highlight contributions from the tropical Pacific and Atlantic, offering a promising predictability that potentially surpasses the limitations of ENSO-based predictions. These outcomes hold the potential for developing operational forecasts of late-spring precipitation anomalies in the southern plains, enabling proactive risk management. [ABSTRACT FROM AUTHOR]

High clouds play an important role in climate variations by shading the sun and contributing to the greenhouse effect. It has been suggested that these variations are strongly controlled by atmospheric circulations; however, the relationship between high clouds and circulations in global simulations has been confirmed only for a limited number of general circulation models (GCMs). Increasing our understanding of this relationship requires a more complete dataset of state-of-the-art GCMs. This study quantifies the relationship between high clouds and circulations by spatial and temporal correlation using data from 28 atmospheric GCMs along with a global nonhydrostatic model, a new-type of GCM, and reveals a robust and strong relationship in most models. This study also finds that the sensitivity, which is defined as the slope of the relationship between high clouds and mass fluxes of circulations, is highly model-dependent. This suggests that a similar change of circulations does not guarantee that of high clouds, which could be one reason for the complexity in projecting high-cloud changes due to warming. Moreover, this study confirms in both observation and models that the relationship with circulations is stronger for medium-thickness and thick high clouds than for thin clouds. Furthermore, the relationship between high clouds and circulations is more convincing in near-equatorial regions between 15°S–15°N, the ascending branch of the Hadley circulation, where deep convection is especially active. [ABSTRACT FROM AUTHOR]

Throughout their service life, bridges are exposed to ambient actions and environmental influences such as wind, thermal, and snow loads. Bridge design for environmental actions is currently based on observed, historical climate data. However, the effects of climate change have put these guidelines into question due to the ongoing and projected change in climate conditions. Bridge engineers are adapting current guidelines and design provisions to incorporate climate change. The main challenges encountered in this endeavor are the nonavailability of future climate data in the required format and the ability of bridge engineers to access and use these data as needed. The focus of this study is to investigate the effect of climate change on thermal load. The objective is achieved through the development of a methodology that can be used to model future hourly climate data; these may be input as boundary conditions in a thermal finite-element model to determine the thermal load acting on a bridge. To demonstrate the methodology, future climate conditions are projected for two locations across Canada (Toronto and Whitehorse), whereas the resulting thermal loads acting on the bridge are determined during heat waves, cold waves, and periods of high daily temperature variation. The results show that climate change could lead to a significant increase in the magnitude of thermal loads on bridges. It is also shown that the effects of climate change on the thermal load vary significantly depending on the general circulation model used, the emission scenario, and the location. [ABSTRACT FROM AUTHOR]

In contrast to boreal winter when extratropical seasonal predictions benefit greatly from ENSO-related teleconnections, our understanding of forecast skill and sources of predictability in summer is limited. Based on 40 years of hindcasts of the Canadian Seasonal to Interannual Prediction System, version 3 (CanSIPSv3), this study shows that predictions for the Northern Hemisphere summer surface air temperature are skillful more than 6 months in advance in several midlatitude regions, including eastern Europe–Middle East, central Siberia–Mongolia–North China, and the western United States. These midlatitude regions of statistically significant predictive skill appear to be connected to each other through an upper-tropospheric circumglobal wave train. Although a large part of the forecast skill for the surface air temperature and 500-hPa geopotential height is attributable to the linear trend associated with global warming, there is significant long-lead seasonal forecast skill related to interannual variability. Two additional idealized hindcast experiments are performed to help shed light on sources of the long-lead forecast skill using one of the CanSIPSv3 models and its uncoupled version. It is found that tropical ENSO-related sea surface temperature (SST) anomalies contribute to the forecast skill in the western United States, while land surface conditions in winter, including snow cover and soil moisture, in the Siberian and western U.S. regions have a delayed or long-lasting impact on the atmosphere, which leads to summer forecast skill in these regions. This implies that improving land surface initial conditions and model representation of land surface processes is crucial for the further development of a seasonal forecasting system. Significance Statement: Useful seasonal predictions in the boreal summer midlatitude regions are of great value. In this study, we show that predictions for the boreal summer season are skillful more than 6 months in advance in several midlatitude regions, including eastern Europe–Middle East, central Siberia–Mongolia–North China, and the western United States. The forecast skill in these regions is associated with a circumglobal teleconnection atmospheric circulation pattern. Sources of the long-lead forecast skill include the global warming–related trend and anomalies in the ocean and land surface initial conditions. It is found that the wintertime snow cover and soil moisture in the Siberian and western U.S. regions have a delayed or long-lasting impact on the atmosphere, which leads to summer forecast skill. [ABSTRACT FROM AUTHOR]

Atmospheric general circulation models (AGCMs) and coupled general circulation models (CGCMs) in the High Resolution Model Intercomparison Project (HighResMIP) were evaluated on their ability to simulate tropical cyclone (TC) activity in the western North Pacific (WNP) over its annual cycle. Specifically, we examined these models' ability to simulate the south–north migration of the mean TC genesis location. The results revealed that both types of models realistically captured TC numbers and the south–north migration of TC genesis locations associated with the meridional migration of the WNP subtropical high ridge in response to the annual cycle. However, TC numbers decreased less rapidly in the AGCMs than in both the CGCMs and observed data during the monsoon retreat period (after September). This bias was probably attributed to a low-tropospheric cyclonic anomaly over the Philippine Sea in response to La Niña–like sea surface temperature (SST) differences between the AGCMs and the CGCMs. Because of these differences, the TC genesis frequency in the AGCMs over the Philippine Sea was overestimated. The cyclonic anomaly occurred when the northeasterly trade wind arose and was maintained through wind–evaporation–SST feedback. In future climate (2021–50), the main changes occurred during the monsoon retreat period. A more rapid decrease in TC numbers shown in AGCMs was likely attributed to the decrease (increase) of low-level vorticity (vertical wind shear) modulated by enhanced WNP subtropical high and subsidence anomalies. Conversely, a cyclonic circulation and ascending anomalies projected by CGCMs were identified off-equator, which favored TC genesis location shifting northward. Significance Statement: Model performance and future changes in the annual cycle of tropical cyclone (TC) activity in the western North Pacific are investigated. We found that high-resolution uncoupled and coupled models realistically captured the TC numbers and meridional migration of TC genesis locations associated with the meridional migration of subtropical high ridge. However, TC numbers decreased more gradually in the uncoupled models than in the coupled models after September. This lower skill may stem from differences between the uncoupled and coupled models in simulating a cyclonic anomaly over the Philippine Sea in response to the La Niña–like sea surface temperature difference. In future climate (2021–50), TC numbers are significantly projected to decrease more rapidly during the monsoon retreat period in uncoupled models. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) have been widely used to project how species respond to future climate changes as forecasted by global climate models (GCMs). While uncertainties in GCMs specific to the Tibetan Plateau have been acknowledged, their impacts on species distribution modeling needs to be explored. Here, we employed ten algorithms to evaluate the uncertainties of SDMs across four GCMs (ACCESS-CM2, CMCC-ESM2, MPI-ESM1-2-HR, and UKESM1-0-LL) under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) at two time stages. We selected two endemic species of the Tibetan Plateau, Gentiana yunnanensis and G. siphonantha, distributed in the Hengduan Mountain regions of the southeast plateau and northeast plateau regions, respectively, as case studies. Under the two SSPs and two time periods, there are significant differences in the distribution areas of G. yunnanensis predicted by different GCMs, with some showing increases and others showing decreases. In contrast, the distribution range trends for G. siphonantha predicted by different GCMs are consistent, initially increasing and then decreasing. The CMCC-ESM2 model predicted the largest increase in the distribution range of G. yunnanensis, while the UKESM1-0-LL model predicted the greatest decrease in the distribution range of G. siphonantha. Our findings highlight that the four selected GCMs still lead to some variations in the final outcome despite the existence of similar trends. We recommend employing the average values from the four selected GCMs to simulate species potential distribution under future climate change scenarios to mitigate uncertainties among GCMs. [ABSTRACT FROM AUTHOR]

Geospatial climate change projections are critical for assessing climate change impacts and adaptations across a wide range of disciplines. Here we present monthly-based grids of climate change projections at a 2-km resolution covering Canada and the United States. These data products are based on outputs from the 6th Coupled Model Intercomparison Project (CMIP6) and include projections for 13 General Circulation Models (GCMs), three Shared Socio-economic Pathways (SSP1 2.6, SSP2 4.5, and SSP5 8.5), four 30-year time periods (2011–2040, 2021–2050, 2041–2070, and 2071–2100), and a suite of climate variables, including monthly maximum and minimum temperature, precipitation, climate moisture index, and various bioclimatic summaries. The products employ a delta downscaling method, which combines historical normal values at climate stations with broad-scale change projections (or deltas) from GCMs, followed by spatial interpolation using ANUSPLIN. Various quality control efforts, described herein, were undertaken to ensure that the final products provided reasonable estimates of future climate.

A deep winter mixed layer forms north of the Antarctic Circumpolar Current (ACC) in the Indo-Pacific sectors, while the mixed layer depth (MLD) is shallow in the Atlantic. Using observations and a global atmospheric model, this study investigates the contribution of surface buoyancy flux and background stratification to interbasin MLD variations. The surface heat flux is decomposed into broad-scale and frontal-scale variations. At the broad scale, the meandering ACC path is accompanied by a zonal wavenumber-1 structure of sea surface temperature (SST) with a warmer Pacific than the Atlantic; under the prevailing westerly winds, this temperature contrast results in larger surface heat loss facilitating deeper MLD in the Indo-Pacific sectors than in the Atlantic. In the Indian sector, the intense ACC fronts strengthen surface heat loss compared to the Pacific. The surface freshwater flux pattern largely follows that of evaporation and reinforces the heat flux pattern, especially in the southeast Pacific. A diagnostic relationship is introduced to highlight the role of ACC's sloping isopycnals in setting a weak submixed layer stratification north of ACC. This weak stratification varies in magnitude across basins. In the Atlantic and western Indian Oceans where the ACC is at a low latitude (∼45°S), solar heating, intrusions of subtropical gyres, and energetic mesoscale eddies together maintain relatively strong stratification. In the southeast Pacific, in comparison, the ACC reaches the southernmost latitude (56°S), far away from the subtropical front. This creates weaker stratification, allowing deep mixed layers to form, aided by surface buoyancy loss. [ABSTRACT FROM AUTHOR]

Modeling studies which abruptly increase atmospheric CO2 concentration evidence a rapid reduction or collapse of the Atlantic Meridional Overturning Circulation (AMOC) from its present state of strong overturning circulation into one characterized by a nearly absent deep ocean overturning in the Atlantic and a reduced northward heat transport. Similar transitions are frequently discussed in the context of both present and past global climate changes. Far less discussed, however, is the eventual recovery of the circulation and the establishment of a new equilibrium state, which may occur, or not, many millennia following the initial collapse. Here, we use the Community Earth System Model (CESM1) and a range of abrupt CO2 forcing scenarios (0.5xCO2, and 2xCO2 up to 16xCO2) to evaluate the timescales, and the factors influencing these timescales, in the AMOC's slow evolution to equilibrium. This takes ~ 2000 years for 2xCO2, but over 10,000 years for 8xCO2 in the model. We focus on the interplay between upper- and deep-ocean temperature and salinity, and Arctic sea ice, to diagnose the mechanisms of AMOC recovery and its transition towards equilibrium. We show that the freshening of the Arctic and Subpolar region can delay or possibly halt AMOC recovery. Critically, even after radiative balance is reached at the top of the atmosphere, ocean temperature and salinity keep evolving for thousands of years, affecting the AMOC. These results highlight the long timescales needed for ocean adjustment to radiative forcing, and also shed light on AMOC characteristics in past climates with atmospheric CO2 concentrations markedly different from the present day. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) exhibits nonlinearity in its amplitude and impacts. This study investigates the dependence of summertime synoptic-scale disturbance (SSD) intensity over the tropical western North Pacific (TWNP) on the ENSO amplitude. A tendency of nonlinearity exists in the observed response of the TWNP SSD intensity to the amplitude of tropical central-eastern Pacific (CEP) sea surface temperature (SST) anomalies in boreal summer. Numerical experiments are conducted with an atmospheric general circulation model with linearly varying tropical CEP SST anomalies imposed to illustrate the nonlinearity exclusively induced by changes in the ENSO amplitude. A linear increase in the amplitude of El Niño–like SST anomalies results in a nonlinear enhancement of SSD intensity over the TWNP, manifested as the increase in SSD intensity at a rate larger than expected by linear response with an eastward shift. This is attributed to the nonlinear intensification of anomalous ascent over the TWNP induced by tropical convection response to positive tropical CEP SST anomalies and the nonlinear effect of anomalous convection on the synoptic-scale activity. In contrast, as La Niña–like SST anomalies increase linearly, the SSD intensity over the TWNP decreases at a rate slower than expected from a linear response and even reaches saturation with little longitudinal shift. Due to the thermodynamic control on the occurrence of deep convection in the tropics, enhanced negative SST anomalies do not induce additional changes in anomalous descent over the tropical CEP. Thus, the TWNP SSD intensity no longer decreases with further increase in tropical CEP cold SST anomalies. Significance Statement: Synoptic-scale disturbances (SSDs) over the tropical western North Pacific (TWNP) play an important role in weather and climate over East and Southeast Asia. Impacts of those SSDs are contingent on their intensity. El Niño–Southern Oscillation (ENSO) has substantial impacts on weather and climate worldwide, including the SSDs over the TWNP. ENSO displays a diversity in amplitude, spatial pattern, and temporal evolution. The present study investigates the response of the TWNP SSD intensity to varying ENSO amplitude during boreal summer and reveals a distinctive nonlinear response of the TWNP SSD intensity to the amplitude of El Niño and La Niña, which has important implication for understanding the impacts of ENSO on climate over the TWNP and Asia. [ABSTRACT FROM AUTHOR]

Stratospheric ozone, and its response to anthropogenic forcings, provides an important pathway for the coupling between atmospheric composition and climate. In addition to stratospheric ozone's radiative impacts, recent studies have shown that changes in the ozone layer due to 4xCO2 have a considerable impact on the Northern Hemisphere (NH) tropospheric circulation, inducing an equatorward shift of the North Atlantic jet during boreal winter. Using simulations produced with the NASA Goddard Institute for Space Studies (GISS) high-top climate model (E2.2), we show that this equatorward shift of the Atlantic jet can induce a more rapid weakening of the Atlantic meridional overturning circulation (AMOC). The weaker AMOC, in turn, results in an eastward acceleration and poleward shift of the Atlantic and Pacific jets, respectively, on longer time scales. As such, coupled feedbacks from both stratospheric ozone and the AMOC result in a two-time-scale response of the NH midlatitude jet to abrupt 4xCO2 forcing: a "fast" response (5–20 years) during which it shifts equatorward and a "total" response (∼100–150 years) during which the jet accelerates and shifts poleward. The latter is driven by a weakening of the AMOC that develops in response to weaker surface zonal winds that result in reduced heat fluxes out of the subpolar gyre and reduced North Atlantic Deep Water formation. Our results suggest that stratospheric ozone changes in the lower stratosphere can have a surprisingly powerful effect on the AMOC, independent of other aspects of climate change. [ABSTRACT FROM AUTHOR]

We assess the representation of mesoscale stirring in a suite of models against an estimate derived from microstructure data collected during the North Atlantic Tracer Release Experiment (NATRE). We draw heavily from the approximate temperature variance budget framework of Ferrari and Polzin. This framework assumes two sources of temperature variance away from boundaries: first, the vertical stirring of the large-scale mean vertical gradient by small-scale turbulence; and second, the lateral stirring of large-scale mean along-isopycnal gradients by mesoscale eddies. Temperature variance so produced is transformed and on average transferred down scales for ultimate dissipation at the microscale at a rate χ estimated using microstructure observations. Ocean models represent these pathways by a vertical mixing parameterization, and an along-isopycnal lateral mixing parameterization (if needed). We assess the rate of variance production by the latter as a residual from the NATRE dataset and compare against the parameterized representations in a suite of model simulations. We find that variance production due to lateral stirring in a Parallel Ocean Program version 2 (POP2) 1/10° simulation agrees well, to within the estimated error bars, with that inferred from the NATRE estimate. A POP2 1° simulation and the Estimating the Circulation and Climate of the Ocean Version 4 release 4 (ECCOV4r4) simulation appear to dissipate an order of magnitude too much variance by applying a lateral diffusivity, when compared to the NATRE estimate, particularly below 1250 m. The ECCOV4r4-adjusted lateral diffusivities are elevated where the microstructure suggests elevated χ sourced from mesoscale stirring. Such elevated values are absent in other diffusivity estimates suggesting the possibility of compensating errors and caution in interpreting ECCOV4r4's adjusted lateral diffusivities. Significance Statement: We look at whether microstructure turbulence observations can provide a useful metric for judging the fidelity of representation of mesoscale stirring in a suite of models. We focus on the region of the North Atlantic Tracer Release Experiment (NATRE), the site of a major ocean turbulence observation campaign, and use an approximate variance budget framework for the region with observational estimates from Ferrari and Polzin (2005). The approach provides a novel framework to evaluate the approximate representation of mesoscale stirring in a variety of models. [ABSTRACT FROM AUTHOR]

The impacts of climate change increasingly show themselves in many forms in our everyday lives such as heatwaves and droughts. Drought is one of the critical events today for increasing drought frequency. This study focuses on meteorological drought because it directly affects other drought types. Hence, this study focuses on how the future drought conditions will vary under climate change effects in the Mediterranean basin (Turkey). In doing so, this study utilizes precipitation data from three General Circulation Models (GCMs) and three Regional Circulation Models (RCMs). The GCMs are CNRM-CM6, GFDL-CM4, and MPI-ESM1, while the RCMs are (RCA4)-CNRM-CM5, (Reg CM4)-GFDL-ESM2M, and (RCA4)-MPI-ESM-MR. Mitigating biases of the climate models, this study utilizes four statistical downscaling methods (SD), linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), and distribution mapping (DM). Here, the study has two purposes. The main aim of the paper here is to compare the performance of SD methods in improving the representation of observed climate variables in climate models. In addition, the study shows how different methods will affect the spatial drought distribution in the area under the SSP2 4.5 and SSP5 8.5 scenarios. Consequently, the study uses the standardized precipitation index (SPI) and Z-score index (ZSI) to quantify future drought conditions and reaches the following results. The study reveals that mild drought conditions are prevalent in the basin for future periods, and drought indices go down to − 0.55. The study also shows that different SD methods affect the results obtained by each climate model diversely. For example, while the LS method causes the most drought conditions on the results based on CNRM-CM5 and CNRM-CM6, the DM method has a similar impact on outcomes based on GFDL-CM4 and GFDL-ESM2M and causes the most drought conditions. [ABSTRACT FROM AUTHOR]

Subseasonal-to-seasonal (S2S) precipitation prediction in boreal spring and summer months, which contains a significant number of high-signal events, is scientifically challenging and prediction skill has remained poor for years. Tibetan Plateau (TP) spring observed surface temperatures show a lag correlation with summer precipitation in several remote regions, but current global land-atmosphere coupled models are unable to represent this behavior due to significant errors in producing observed TP surface temperatures. To address these issues, the Global Energy and Water Exchanges (GEWEX) program launched the "Impact of Initialized Land Temperature and Snowpack on Subseasonal-to-Seasonal Prediction"(LS4P) initiative as a community effort to test the impact of land temperature in high-mountain regions on S2S prediction by climate models: more than 40 institutions worldwide are participating in this project. After using an innovative new land state initialization approach based on observed surface 2-m temperature over the TP in the LS4P experiment, results from a multimodel ensemble provide evidence for a causal relationship in the observed association between the Plateau spring land temperature and summer precipitation over several regions across the world through teleconnections. The influence is underscored by an out-of-phase oscillation between the TP and Rocky Mountain surface temperatures. This study reveals for the first time that high-mountain land temperature could be a substantial source of S2S precipitation predictability, and its effect is probably as large as ocean surface temperature over global "hotspot"regions identified here; the ensemble means in some "hotspots"produce more than 40% of the observed anomalies. This LS4P approach should stimulate more follow-on explorations.

Climate change research uses an ensemble of general circulation model runs (GCMs-runs) to predict future climate under uncertainties. To reduce computational costs, this study selects representative GCM-runs (RGCM-runs) for Western North America (WNA) based on their performance in replicating historical climate conditions from 1981 to 2005 and projecting future changes from 1981–2010 to 2071–2100. This evaluation is conducted under two representative concentration pathways (RCPs) scenarios, RCP4.5 and RCP8.5, from the Coupled Model Intercomparison Project 5. By using an envelope-based selection technique and a multi-objective distance-based approach, we identify four RGCM-runs per RCP representing diverse climatic conditions, including wet-warm, wet-cold, dry-warm, and dry-cold. Compared to the full-set, these selected runs show a decreased mean absolute error (MAE) between the reference and RGCM-runs concerning the monthly average mean air temperature (T̄) and precipitation (P̄). For RCP4.5, T̄ MAE is 0.45 (vs. 0.58 in the full-set) and P̄ MAE is 0.31 (vs. 0.42). For RCP8.5, T̄ MAE is 0.51 (vs. 0.75) and P̄ MAE is 0.25 (vs. 0.36). The lower MAE values in the RGCM-run set indicate closer alignment between predicted and reference values, making the RGCM-run suitable for climate impact assessments in the region. HIGHLIGHTS Pioneered a multistep framework for representative general circulation model run (RGCM-run) selection in Western North America, considering computing limitations and ensuring diverse climatic scenarios.; Compared temperature and precipitation variability under RCP4.5 and RCP8.5, aiding decision-making in the context of climate change.; Demonstrated substantial reduction in mean absolute error for vital climatic variables using selected RGCM-runs, reducing uncertainty.;

Observations show predictive skill of the minimum sea ice extent (Min SIE) from late winter anomalous offshore ice drift along the Eurasian coastline, leading to local ice thickness anomalies at the onset of the melt season—a signal then amplified by the ice–albedo feedback. We assess whether the observed seasonal predictability of September sea ice extent (Sept SIE) from Fram Strait Ice Area Export (FSIAE; a proxy for Eurasian coastal divergence) is present in global climate model (GCM) large ensembles, namely the CESM2-LE, GISS-E2.1-G, FLOR-LE, CNRM-CM6-1, and CanESM5. All models show distinct periods where winter FSIAE anomalies are negatively correlated with the May sea ice thickness (May SIT) anomalies along the Eurasian coastline, and the following Sept Arctic SIE, as in observations. Counterintuitively, several models show occasional periods where winter FSIAE anomalies are positively correlated with the following Sept SIE anomalies when the mean ice thickness is large, or late in the simulation when the sea ice is thin, and/or when internal variability increases. More important, periods with weak correlation between winter FSIAE and the following Sept SIE dominate, suggesting that summer melt processes generally dominate over late-winter preconditioning and May SIT anomalies. In general, we find that the coupling between the winter FSIAE and ice thickness anomalies along the Eurasian coastline at the onset of the melt season is a ubiquitous feature of GCMs and that the relationship with the following Sept SIE is dependent on the mean Arctic sea ice thickness. [ABSTRACT FROM AUTHOR]

The Last Glacial Maximum (LGM; 26,000–19,000 years before the present) altered the distribution of species worldwide. Its effect is poorly known in tropical regions because the cooling and drought reached during that period are uncertain. Here, I generated hypotheses regarding the possible responses of cloud forest mammals in the Oaxacan Highlands (OH) of Mexico, a region with one of the most extensive cloud forests in the Neotropics. First, I used three General Circulation Models (GCMs: CCSM3, MIROC‐ESM and MPI) to characterize probable climates during the LGM. Then, I used ecological niche models to estimate the current and LGM potential distributions of four cloud forest species. As in other locations, the results show that GCMs are consistent with cooler conditions relative to today; however, the three GCMs estimate precipitation regimes with notable variations in the region. MPI indicates that the LGM could have been even wetter than present. Consequently, the MPI scenario allowed more widespread potential distributions of mammals. The paleodistributions show how mid‐ and lowlands were essential for the long‐term survival of these 'high‐mountain mammals' throughout the last glacial–interglacial cycle. The paleodistributions presented here are precise hypotheses that can be tested based on paleoecological and genetic evidence. [ABSTRACT FROM AUTHOR]

Gravity waves (GWs) are among the key drivers of the meridional overturning circulation in the mesosphere and upper stratosphere. Their representation in climate models suffers from insufficient resolution and limited observational constraints on their parameterizations. This obscures assessments of middle atmospheric circulation changes in a changing climate. This study presents a comprehensive analysis of stratospheric GW activity above and downstream of the Andes from 1 to 15 August 2019, with special focus on GW representation ranging from an unprecedented kilometer-scale global forecast model (1.4 km ECMWF IFS), ground-based Rayleigh lidar (CORAL) observations, modern reanalysis (ERA5), to a coarse-resolution climate model (EMAC). Resolved vertical flux of zonal GW momentum (GWMF) is found to be stronger by a factor of at least 2–2.5 in IFS compared to ERA5. Compared to resolved GWMF in IFS, parameterizations in ERA5 and EMAC continue to inaccurately generate excessive GWMF poleward of 60°S, yielding prominent differences between resolved and parameterized GWMFs. A like-to-like validation of GW profiles in IFS and ERA5 reveals similar wave structures. Still, even at ∼1 km resolution, the resolved waves in IFS are weaker than those observed by lidar. Further, GWMF estimates across datasets reveal that temperature-based proxies, based on midfrequency approximations for linear GWs, overestimate GWMF due to simplifications and uncertainties in GW wavelength estimation from data. Overall, the analysis provides GWMF benchmarks for parameterization validation and calls for three-dimensional GW parameterizations, better upper-boundary treatment, and vertical resolution increases commensurate with increases in horizontal resolution in models, for a more realistic GW analysis. Significance Statement: Gravity wave–induced momentum forcing forms a key component of the middle atmospheric circulation. However, complete knowledge of gravity waves, their atmospheric effects, and their long-term trends are obscured due to limited global observations, and the inability of current climate models to fully resolve them. This study combines a kilometer-scale forecast model, modern reanalysis, and a coarse-resolution climate model to first compare the resolved and parameterized momentum fluxes by gravity waves generated over the Andes, and then evaluate the fluxes using a state-of-the-art ground-based Rayleigh lidar. Our analysis reveals shortcomings in current model parameterizations of gravity waves in the middle atmosphere and highlights the sensitivity of the estimated flux to the formulation used. [ABSTRACT FROM AUTHOR]

The present-day deep ocean global meridional overturning circulation is dominated by the Atlantic meridional overturning circulation (AMOC), with dense water sinking in the high-latitude North Atlantic Ocean. In contrast, deep-water formation in the subarctic North Pacific is inhibited by a strong upper-ocean halocline, which prevents the development of an analogous Pacific meridional overturning circulation (PMOC). Nevertheless, paleoclimate evidence suggests that a PMOC with deep-water formation in the North Pacific was active, for instance, during the warm Pliocene epoch and possibly during the most recent deglaciation. In the present study, we describe a spontaneous activation of the PMOC in a multimillennial abrupt 4 × CO2 experiment using one of the configurations of the Community Earth System Model (CESM1). Soon after the imposed CO2 increase, the model's AMOC collapses and remains in a weakened state for several thousand years. The PMOC emerges after some 2500 years of integration, persists for about 1000 years, reaching nearly 10 Sv (1 Sv ≡ 106 m3 s−1), but eventually declines to about 5 Sv. The PMOC decline follows the AMOC recovery in the model, consistent with an Atlantic–Pacific interbasin seesaw. The PMOC activation relies on two factors: (i) gradual warming and freshening of the North Pacific deep ocean, which reduces ocean vertical stratification on millennial time scales, and (ii) upper-ocean salinity increase in the subarctic North Pacific over several centuries, followed by a rapid erosion of the pycnocline and activation of deep-water formation. Ultimately, our results provide insights on the characteristics of global ocean overturning in warm climates. [ABSTRACT FROM AUTHOR]

Precipitation and near-surface temperature from an ensemble of 36 new state‐of‐the‐art climate models under the Coupled Model Inter‐comparison Project phase 6 (CMIP6) are evaluated over Chile's climate. The analysis is focused on four distinct climatic subregions: Northern Chile, Central Chile, Northern Patagonia, and Southern Patagonia. Over each of the subregions, first, we evaluate the performance of individual global climate models (GCMs) against a suit of precipitation and temperature observation-based gridded datasets over the historical period (1986–2014) and then we analyze the models' projections for the end of the century (2080–2099) for four different shared socioeconomic pathways scenarios (SSP). Although the models are characterized by general wet and warm mean bias, they reproduce realistically the main spatiotemporal climatic variability over different subregions. However, none of the models is best across all subregions for both precipitation and temperature. Moreover, among the best performing models defined based on the Taylor skill score, one finds the so-called "hot models" likely exhibiting an overestimated climate sensitivity, which suggests caution in using these models for accessing future climate change in Chile. We found robust (90% of models agree in the direction of change) projected end-of-the-century reductions in mean annual precipitation for Central Chile (~ − 20 to ~ − 40%) and Northern Patagonia (~ − 10 to ~ − 30%) under scenario SSP585, but changes are strong from scenario SSP245 onwards, where precipitation is reduced by 10–20%. Northern Chile and Southern Patagonia show non-robust changes in precipitation across the models. Yet, future near-surface temperature warming presented high inter-model agreement across subregions, where the greatest increments occurred along the Andes Mountains. Northern Chile displays the strongest increment of up to ~ 6 °C in SSP585, followed by Central Chile (up to ~ 5 °C). Both Northern and Southern Patagonia show a corresponding increment by up to ~ 4 °C. We also briefly discuss about the environmental and socio-economic implications of these future changes for Chile. [ABSTRACT FROM AUTHOR]

Accurate parameterizations of eddy fluxes across prograde, buoyant shelf and slope currents are crucial to faithful predictions of the heat transfer and water mass transformations in high-latitude ocean environments in ocean climate models. In this work we evaluate several parameterization schemes of eddy buoyancy fluxes in predicting the mean state of prograde current systems using a set of coarse-resolution noneddying simulations, the solutions of which are compared against those of fine-resolution eddy-resolving simulations with nearly identical model configurations. It is found that coarse-resolution simulations employing the energetically constrained GEOMETRIC parameterization can accurately reconstruct the prograde mean flow state, provided that the suppression of eddy buoyancy diffusivity over the continental slope is accounted for. The prognostic subgrid-scale eddy energy budget in the GEOMETRIC parameterization scheme effectively captures the varying trend of the domain-wide eddy energy level in response to environmental changes, even though the energy budget is not specifically designed for a sloping-bottomed ocean. Local errors of the predicted eddy energy are present but do not compromise the predictive skill of the GEOMETRIC parameterization for prograde current systems. This work lays a foundation for improving the representation of prograde current systems in coarse-resolution ocean climate models. Significance Statement: The objective of this study is to evaluate different methods for predicting ocean volume transports caused by ocean mesoscale eddies across continental margins. This is important because these transports play a critical role in exchanges between coastal seas and open oceans, but cannot be resolved or well represented in ocean climate simulations. This study emphasizes the importance of accounting for the influence of sloping seafloors in controlling the eddy transport across the continental slope. This study also highlights the necessity of simultaneously predicting the eddy energy for better representation of the cross-slope eddy transport in ocean climate simulations. [ABSTRACT FROM AUTHOR]

Wind energy plays a pivotal role in the ongoing effort to reduce carbon emissions in the energy sector. With the increasing evidence of climate change, there is a growing concern regarding the planning and operation of wind energy resources. Accurate forecasts are essential to understand the frequency distribution of wind speed data in a given area and, consequently, to estimate energy production. This paper aims to analyze the wind resources under climate change, assess their potential, and create zoning maps for wind energy production in the island of Ireland. For this objective, wind speed data from 31 general circulation models (GCMs) and two climate change scenarios were utilized for both hindcast and forecast periods in 1981–2010 and 2021–2050, respectively. The GCM outputs were first bias-corrected and then post-processed using various (non–)parametric statistical distributions and 3 Copula families. The results indicate an expected decrease in the average wind speed in the region up to ∼ 21 % by 2050, contingent on the climate scenarios under consideration and the target point. Ultimately, this study concludes by presenting wind power density maps specifically to the study region, offering valuable insights for sustainable energy planning.

Species distribution models (SDMs) have been widely used to project how species respond to future climate changes as forecasted by global climate models (GCMs). While uncertainties in GCMs specific to the Tibetan Plateau have been acknowledged, their impacts on species distribution modeling needs to be explored. Here, we employed ten algorithms to evaluate the uncertainties of SDMs across four GCMs (ACCESS-CM2, CMCC-ESM2, MPI-ESM1-2-HR, and UKESM1-0-LL) under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) at two time stages. We selected two endemic species of the Tibetan Plateau, Gentiana yunnanensis and G. siphonantha, distributed in the Hengduan Mountain regions of the southeast plateau and northeast plateau regions, respectively, as case studies. Under the two SSPs and two time periods, there are significant differences in the distribution areas of G. yunnanensis predicted by different GCMs, with some showing increases and others showing decreases. In contrast, the distribution range trends for G. siphonantha predicted by different GCMs are consistent, initially increasing and then decreasing. The CMCC-ESM2 model predicted the largest increase in the distribution range of G. yunnanensis, while the UKESM1-0-LL model predicted the greatest decrease in the distribution range of G. siphonantha. Our findings highlight that the four selected GCMs still lead to some variations in the final outcome despite the existence of similar trends. We recommend employing the average values from the four selected GCMs to simulate species potential distribution under future climate change scenarios to mitigate uncertainties among GCMs.

The atmospheric science community includes both weather and climate scientists. These two groups interact much less than they should, particularly in the United States. The schism is widespread and has persisted for 50 years or more. It is found in academic departments, laboratories, professional societies, and even funding agencies. Mending the schism would promote better, faster science. We sketch the history of the schism and suggest ways to make our community whole. [ABSTRACT FROM AUTHOR]

Projections of precipitation extremes over land are crucial for socioeconomic risk assessments, yet model discrepancies limit their application. Here we use a pattern-filtering technique to identify low-frequency changes in individual members of a multimodel ensemble to assess discrepancies across models in the projected pattern and magnitude of change. Specifically, we apply low-frequency component analysis (LFCA) to the intensity and frequency of daily precipitation extremes over land in 21 CMIP-6 models. LFCA brings modest but statistically significant improvements in the agreement between models in the spatial pattern of projected change, particularly in scenarios with weak greenhouse forcing. Moreover, we show that LFCA facilitates a robust identification of the rates at which increasing precipitation extremes scale with global temperature change within individual ensemble members. While these rates approximately match expectations from the Clausius-Clapeyron relation on average across models, individual models exhibit considerable and significant differences. Monte Carlo simulations indicate that these differences contribute to uncertainty in the magnitude of projected change at least as much as differences in the climate sensitivity. Last, we compare these scaling rates with those identified from observational products, demonstrating that virtually all climate models significantly underestimate the rates at which increases in precipitation extremes have scaled with global temperatures historically. Constraining projections with observations therefore amplifies the projected intensification of precipitation extremes as well as reducing the relative error of their distribution. [ABSTRACT FROM AUTHOR]

The impact of melt ponds on sea ice albedo has been observed and documented. In general circulation models, ponds are now accounted for through indirect diagnostic treatments ("implicit" schemes) or prognostic melt-pond parameterizations ("explicit" schemes). However, there has been a lack of studies showing the impacts of these schemes on simulated Arctic climate. We focus here on rectifying this using the general circulation model HadGEM3, one of the few models with a detailed explicit pond scheme. We identify the impact of melt ponds on the sea ice and climate, and associated ice–ocean–atmosphere interactions. We run a set of constant forcing simulations for three different periods and show, for the first time, that using mechanistically different pond schemes can lead to very significantly different sea ice and climate states. Under near-future conditions, an implicit scheme never yields an ice-free summer Arctic, while an explicit scheme yields an ice-free Arctic in 35% of years and raises autumn Arctic air temperatures by 5° to 8°C. We find that impacts on climate and sea ice depend on the ice state: under near-future and last-interglacial conditions, the thin sea ice is very sensitive to pond formation and parameterization, whereas during the preindustrial period the thicker sea ice is less sensitive to the pond scheme choice. Both of these two commonly used parameterizations of sea ice albedo yield similar results under preindustrial conditions but in warmer climates lead to very different Arctic sea ice and ocean and atmospheric temperatures. Thus, changes to physical parameterizations in the sea ice model can have large impacts on simulated sea ice, ocean, and atmosphere. Significance Statement: This study investigates the impacts of melt ponds on Arctic sea ice under different climate conditions, using the HadGEM3-GC3.1-LL general circulation model (GCM). Additionally, we study the impact of changing the type of pond scheme used. We find that changing the pond scheme causes large differences to how a GCM simulates Arctic sea ice, the ocean, and the atmosphere, for both near-future and warmer paleoclimate conditions. These large differences have not been found previously, because this is one of the first GCM studies of this type. Our results demonstrate the importance of melt ponds, and their wider impacts on ocean and atmosphere. Furthermore, they suggest that better evaluation of the representation of sea ice processes is vital for the robust projection of future climate change. [ABSTRACT FROM AUTHOR]

The Deep Numerical Analysis for Climate (DNA-Climate) is a pilot project to develop an Earth system model on a kilometer-scale horizontal mesh. The acronym "DNA" is based on the analogies between the hierarchical structures of atmospheric phenomena and living organisms. The multiscale structure of clouds and circulations may be analogous to the multiscale structure of cells and organs organized according to the blueprint, deoxyribonucleic acid (DNA). Whereas global cloud-resolving models (CRMs) can produce better solutions on shorter time scales that are decisively governed by the initial conditions, global climate models (GCMs) may generate reliable solutions on longer time scales that are largely determined to balance energy inputs and outputs. Our challenge is to build a physically valid model that consistently bridges the shorterand longer-time-scale solutions in the intermediate time scales. Research topics of DNA-Climate are configured in consideration of the structural similarity between the climate modeling and the technique of matched asymptotic expansions in mathematics. The central question is whether a single modeling framework using only either global CRM or GCM will work adequately at all time scales of climate, or whether a multiscale modeling framework combining several models, of which each is only valid for limited time scales, will be needed. A multiscale modeling is an attractive framework for advancing climate modeling and would be an intriguing topic to be studied in parallel with global CRMs and GCMs. [ABSTRACT FROM AUTHOR]

Recent analysis of pan-tropical interactions suggests that post-1980 the tropical Indian Ocean's (TIO) influence on the tropical Pacific Ocean (TPO) appears to have subdued, while the tropical Atlantic Ocean's (TAO) influence has become more pronounced. The present study explores whether we can identify and dynamically explain any asymmetries in the pan-tropical connection between the TIO and TPO SSTs in an attempt to explain the recently reported weakening of the TIO influence. To this end, we carry out two idealized atmosphere-only experiments using the ACCESS atmospheric general circulation model where the sign of the decadal TIO SST signal is varied—presenting warm and cool TIO scenarios. We find a relatively strong asymmetric response of TPO precipitation to TIO SST anomalies, where average TPO precipitation shows a strong increase in response to TIO cooling, but a weaker decrease in response to TIO warming. The asymmetry is hypothesized to result from differences in the depth of latent heating over the TIO, which ultimately affects the depth of the remote response over the TPO. Asymmetries also occur in the spatial pattern of the changes in precipitation and surface winds. In the fully coupled system, these asymmetries would be expected to also alter the background state on which ENSO develops, providing a further mechanism by which the TIO influence may vary depending on its phase. [ABSTRACT FROM AUTHOR]

The last few decades have shown evidence of a lengthening dry season in southern Amazonia, which is associated with a delay in the onset of the South American Monsoon System (SAMS). Using a pattern recognition framework of atmospheric circulation patterns (CPs), previous studies have identified specific atmospheric situations related to the onset of the SAMS. Here, we analyze the future changes in the CPs that largely define the main hydro‐climatological states of Tropical South America. We evaluated the CP changes that occurred between two periods: historical (1970–2000) and future (2040–2070), using six General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 6. Future GCM projections show significant spatio‐temporal changes in the CPs associated with the dry season in southern Amazonia during the mid‐21st century. These changes are related to both a late onset of the SAMS and an early demise of the SAMS. Particularly, the CP methodology allowed for a better understanding of the behavior of the southern Amazon dry season under future conditions, showing an increase in the frequency of the CPs typically observed during the dry season. The occurrence of dry days in the Amazon basin during the austral winter of the mid‐21st century increases by 19.4% on average, with respect to the historical period. This methodology also identified a future increase in the frequency of dry CPs, both at the beginning of the dry‐to‐wet transition period (8%) and at the end of the wet‐to‐dry transition season (11%). Plain Language Summary: The southern Amazon has experienced a lengthening of the dry season over the past few decades. This trend has negative impacts on ecological services offered by the Amazon basin, affecting not only the region itself but also the entire planet. This is due to the fact that the Amazon basin plays a critical role in preserving the global hydrological and energy balance. We identify the future changes in the main atmospheric states in South Tropical South America, called atmospheric circulation patterns (CPs). These CPs can be interpreted as an average of each dominant meteorological situation over the region. For this purpose, we evaluated the projected changes occurring in the CPs considering two periods: historical (1970–2000) and future (2040–2070), using six global models. Our results show temporal and spatial variations in the CPs associated with the dry season during the mid‐21st century. These changes are related to both a late dry season ending and an early dry season arrival. For the future period we detect an increase in the frequency of the CPs typically observed during the dry season (19% higher than historical period). This is particularly important in a region already threatened by land use and climate change. Key Points: Circulation Patterns (CPs) provide a new perspective of the lengthening of the dry season in southern AmazoniaGeneral circulation models (GCMs) show significant future changes in the main dry‐to‐wet transitional atmospheric statesGCMs indicate a projected increase in the frequency of CPs typically observed during the Amazon dry season by the mid‐21st century [ABSTRACT FROM AUTHOR]

While GCM horizontal resolution has received the majority of scale improvements in recent years, ample evidence suggests that a model's vertical resolution exerts a strong control on its ability to accurately simulate the physics of the marine boundary layer. Here we show that, regardless of parameter tuning, the ability of a single-column model (SCM) to simulate the subtropical marine boundary layer improves when its vertical resolution is improved. We introduce a novel objective tuning technique to optimize the parameters of an SCM against profiles of temperature and moisture and their turbulent fluxes, horizontal winds, cloud water, and rainwater from large-eddy simulations (LES). We use this method to identify optimal parameters for simulating marine stratocumulus and shallow cumulus. The novel tuning method utilizes an objective performance metric that accounts for the uncertainty in the LES output, including the covariability between model variables. Optimization is performed independently for different vertical grid spacings and value of time step, ranging from coarse scales often used in current global models (120 m, 180 s) to fine scales often used in parameterization development and large-eddy simulations (10 m, 15 s). Uncertainty-weighted disagreement between the SCM and LES decreases by a factor of ∼5 when vertical grid spacing is improved from 120 to 10 m, with time step reductions being of secondary importance. Model performance is shown to converge at a vertical grid spacing of 20 m, with further refinements to 10 m leading to little further improvement. Significance Statement: In successive generations of computer models that simulate Earth's atmosphere, improvements have been mainly accomplished by reducing the horizontal sizes of discretized grid boxes, while the vertical grid spacing has seen comparatively lesser refinements. Here we advocate for additional attention to be paid to the number of vertical layers in these models, especially in the model layers closest to Earth's surface where climatologically important marine stratocumulus and shallow cumulus clouds reside. Our experiments show that the ability of a one-dimensional model to represent physical processes important to these clouds is strongly dependent on the model's vertical grid spacing. [ABSTRACT FROM AUTHOR]

Climate model (CM) statistical downscaling requires quality and quantity modifications of the CM's outputs to increase further modeling accuracy. In this respect, multi-resolution wavelet transform (WT) was employed to determine the hidden resolutions of climate signals and eliminate bias in a CM. The results revealed that the newly developed discrete wavelet transform (DWT)-based bias correction method can outperform the quantile mapping (QM) method. In this study, wavelet coherence analysis was utilized to assess the high common powers and the multi-scale correlation between the predictors and predictand as a function of time and frequency. Thereafter, to rate the most contributing predictors based on potential periodicity, the average variance was calculated, which is named the Scaled Average (SA) measure. Consequently, WT along with Artificial Neural Network (ANN) were applied for bias correction and identifying the dominant predictors for statistical downscaling. The CAN-ESM5 data of Canadian climate models and INM-CM5 data of Russian climate models over two climatic areas of Iran with semi-arid (Tabriz) and humid (Rasht) weather were applied. The projection of future precipitation revealed that Tabriz will experience a 3.4–6.1% decrease in precipitation, while Rasht's precipitation will decrease by 1.5–2.5%. These findings underscore the importance of refining CM data and employing advanced techniques to assess the potential impacts of climate change on regional precipitation patterns. [ABSTRACT FROM AUTHOR]

The aim of this research is to predict the effects of future climate change on cotton yield in Birjand region. In this research, the BCM2 general circulation model under two release scenarios B1 and A1B in three periods (2025 to 2050, 2050 to 2075, and 2075 to 2100) was examined to predict future climate conditions and to generate daily climate parameters of the LARS-WG microscale model. Daily climate data obtained from LARS-WG output were used as inputs for DSSAT model (crop simulation model) to simulate cotton growth under future climate. The selection and preparation of a suitable plot of land for the implementation of the project was done in the beginning of October 2018. The intended experimental design was factorial split plots. The DSSAT model provided acceptable results for cotton yield and phenological stages, and this success was confirmed when the values simulated by the model were compared with the data collected from the field experiments. The maximum NRMSE is related to HW simulation, which is calculated as 9.7%. The value of this index for simulating the phenology stages is much lower and its value is reduced to 1.5%. The results of this research show that the DSSAT model can be a promising tool for predicting yield, leaf area, nitrogen accumulation, phenology and biomass of different cotton cultivars and other crops grown in the region. It seems that this study is useful and appropriate for farmers and their making decisions. The results of the simulations showed that due to future climate change and increase in temperature and carbon dioxide concentration in Birjand city, cotton yield will increase. On average, under all scenarios, the average yield of cotton will increase by 15% in the period of 2025 to 2050, by 15.44% in the period of 2050 to 2075 and by 18.15% in the period of 2075 to 2100. The simulation has shown that climate change increased cotton yield (from 14.73 to 18.53 percent) and reduced the length of the cotton growing season. The main reason for the increase in cotton yield can be attributed to the increase in carbon dioxide concentration. [ABSTRACT FROM AUTHOR]

Quantifying climate change impact on water resources systems at regional or catchment scales is important in water resources planning and management. General circulation models (GCMs) represent our main source of knowledge about future climate change. However, several key limitations restrict the direct use of GCM simulations for water resource assessments. In particular, the presence of systematic bias and the need for its correction is an essential pre-processing step that improves the quality of GCM simulations, making climate change impact assessments more robust and believable. What exactly is systematic bias? Can systematic bias be quantified if the model is asynchronous with observations or other model simulations? Should model bias be sub-categorized to focus on individual attributes of interest or aggregated to focus on lower moments alone? How would one address bias in multiple attributes without making the correction model complex? How could one be confident that corrected simulations for the yet-to-be-seen future bear a closer resemblance to the truth? How can one meaningfully extrapolate correction to multiple dimensions, without being impacted by the ‘Curse of Dimensionality’? These are some of the questions we attempt to address in the paper. HIGHLIGHTS Importance of procedures for correcting systematic biases is discussed.; Extensive literature is presented on bias correction and its use.; The importance of correcting specific attributes for water resources applications is illustrated.; Challenges in formulating a bias correction alternative are highlighted.; Added information on how correcting these biases is critical before any dynamical or statistical downscaling application.;

This study investigates the impacts of climate change on water availability in the Idamalayar basin, Kerala. Soil and Water Assessment Tool (SWAT), Hydrologic Engineering Centre – Hydrologic Modelling System (HEC-HMS), and bias-corrected climate change data were used to simulate future streamflows. The performances of SWAT and HEC-HMS were assessed using four statistical indices (R2, Nash–Sutcliffe efficiency, percentage bias, and RSR). SWAT slightly outperformed HEC-HMS. The CMIP6 general circulation models (GCMs) were selected using PROMETHEE-2. The variations in climate variables and streamflows were studied for three future periods, i.e., near-future (2031–2040), mid-future (2051–2060), and far-future (2071–2080) under three shared socio-economic pathway (SSP) scenarios (SSP126, SSP245, and SSP585). The projections of GCMs show different patterns in variation of precipitation. Generally, there is a slight increase in annual precipitation. However, there was a notable decline in peak in July. An additional peak was often seen in October. The maximum and minimum temperatures showed a decreasing trend. The average annual streamflow reduction under SSP126 was approximately 25.63, 27.92, and 26.24% in the near, mid, and far future, respectively. Under SSP245, the average decrease was 30.71, 16.06, and 19.06% for the near, mid and far future, respectively. For SSP585, there was 12.73% increase in the far-future period. HIGHLIGHTS Water availability in the Idamalayar catchment is studied using five CMIP6 GCMs under three SSP scenarios, for three future periods.; Different GCMs project the variation in water availability differently.; Generally, there is a decrease in the streamflow except in the far-future period under SSP585.; The variation in streamflow calls for better management practices.;

This report is based on a monograph the author prepared for the World Meteorological Organization in Geneva, Switzerland. [ABSTRACT FROM AUTHOR]

With the development of advanced data assimilation and computing techniques, many modern global reanalysis datasets aim to resolve the atmospheric mesoscale spectrum. However, large uncertainties remain with respect to the representation of mesoscale motions in these reanalysis datasets, for which a clear understanding is lacking. The aforementioned challenges have served as a strong motivation to reveal and quantify their mesoscale differences. This study presents the first comprehensive global intercomparison of the tropospheric and stratospheric mesoscale kinetic energy and its spectra over two selected periods of summer and winter events among six leading high-resolution atmospheric reanalysis products: European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), China Meteorological Administration Reanalysis, Modern-Era Retrospective Analysis for Research and Applications version 2, National Centers for Environmental Prediction's Climate Forecast System version 2 (CFSv2), Japanese 55-year Reanalysis, and ECMWF Reanalysis-Interim. A state-of-the-art global operational model is adopted as a supplementary reference. Although all reanalysis datasets can reproduce broad distribution characteristics that are grossly consistent with the 9 km model, there are substantial discrepancies among them in magnitudes. The ability to capture mesoscale signals is closely linked to their resolutions, but it is also impacted by other factors, including, but not limited to, the selected types of energy, seasons, altitudes, latitudes, model diffusions, parametrization schemes, moist condition, assimilation methods, and observation inputs. Moreover, all datasets illustrate conclusive behaviors for the prevalence of the rotational component in the troposphere, whereas only very few products fail to exhibit the dominance of the divergent component in the stratosphere. Overall, stratospheric ERA5 and CFSv2 outperform the other reanalysis datasets, and only these two can reproduce the feature of the canonical kinetic energy spectrum with a distinct shift from a steeper slope (approximately -3) at lower wave numbers to a shallower slope (approximately -5/3) at higher wave numbers. In addition, the relative disparities among datasets increase dramatically with height, and they are more pronounced in the divergent component. It is also found that the correlations among these datasets are much weaker in the Tropics. [ABSTRACT FROM AUTHOR]

Climate model projections of atmospheric circulation patterns, their frequency, and associated temperature and precipitation anomalies under a high-end global warming scenario are assessed over the Pacific Northwest of North America for the final three decades of the twenty-first century. Model simulations are from phase 6 of the Coupled Model Intercomparison Project (CMIP6) and circulation patterns are identified using the self-organizing maps (SOMs) approach, applied to 500-hPa geopotential height (Z500) anomalies. Overall, the range of projected circulation patterns is similar to that in the current climate, especially in winter, whereas in summer the models project a general reduction in the magnitude of Z500 anomalies. Significant changes in pattern frequencies are also projected in summer, with an overall decrease in the frequency of patterns with large Z500 anomalies. In winter, patterns historically associated with anomalously cold weather in northern latitudes are projected to warm the most, and in summer the largest temperature increases are projected over inland areas. Precipitation is found to increase across all seasons and most SOM patterns. However, some summer patterns that are associated with above-average precipitation in the current climate are projected to become significantly drier by the end of the century. [ABSTRACT FROM AUTHOR]

Gyres are central features of large-scale ocean circulation and are involved in transporting tracers such as heat, nutrients, and carbon dioxide within and across ocean basins. Traditionally, the gyre circulation is thought to be driven by surface winds and quantified via Sverdrup balance, but it has been proposed that surface buoyancy fluxes may also contribute to gyre forcing. Through a series of eddy-permitting global ocean model simulations with perturbed surface forcing, the relative contribution of wind stress and surface heat flux forcing to the large-scale ocean circulation is investigated, focusing on the subtropical gyres. In addition to gyre strength being linearly proportional to wind stress, it is shown that the gyre circulation is strongly impacted by variations in the surface heat flux (specifically, its meridional gradient) through a rearrangement of the ocean's buoyancy structure. On shorter time scales (~10 years), the gyre circulation anomalies are proportional to the magnitude of the surface heat flux gradient perturbation, with up to ~0.15 Sv (1 Sv = 106 m³ s-1) anomaly induced per watt per square meter change in the surface heat flux. On time scales longer than a decade, the gyre response to surface buoyancy flux gradient perturbations becomes nonlinear as ocean circulation anomalies feed back onto the buoyancy structure induced by the surface buoyancy fluxes. These interactions complicate the development of a buoyancy-driven theory for the gyres to complement the Sverdrup relation. The flux-forced simulations underscore the importance of surface buoyancy forcing in steering the large-scale ocean circulation. [ABSTRACT FROM AUTHOR]

How the climate responded to orbital forcing during the Neoproterozoic snowball Earth events, the most extreme glaciations on Earth, is still unclear. Here, we investigate this problem using a climate model. To simplify the analysis, continents are removed. The results show that even in this simplified situation, the snowball Earth climate is sensitive to orbital configurations. The globally averaged annual surface temperature can differ by 2.4°C, and the maximum monthly mean temperature can differ by 3.7°C under different orbital configurations. Therefore, a snowball Earth could be deglaciated more easily in some orbital configurations than in others. The climatic effect of a particular orbital parameter is highly dependent on the values of other parameters. For example, the effect of obliquity on tropical surface temperature is generally small (<1°C), but it can become large (3.8°C) when eccentricity is large and the northern autumn occurs at perihelion (precession = 180°). Surprisingly, the global temperature is generally lower at high eccentricity than at near-zero eccentricity, even though the total insolation received by Earth is higher in the former than in the latter. Moreover, we find that the Milankovitch hypothesis is valid not only in the extratropical region, but also in the tropics; the snow thickness in the tropical region is inversely proportional to the maximum monthly insolation received in this region. [ABSTRACT FROM AUTHOR]

A hierarchy of general circulation models (GCMs) is used to investigate the linearity of the response of the climate system to changes in Antarctic topography. Experiments were conducted with a GCM with either a slab ocean or fixed SSTs and sea ice, in which the West Antarctic ice sheet (WAIS) and coastal Antarctic topography were either lowered or raised in an idealized way. Additional experiments were conducted with a fully coupled GCM with topographic perturbations based on an ice-sheet model in which the WAIS collapses. The response over the continent is the same in all model configurations and is mostly linear. In contrast, the response has substantial nonlinear elements over the Southern Ocean that depend on the model configuration and are due to feedbacks with sea ice, ocean, and clouds. The atmosphere warms near the surface over much of the Southern Ocean and cools in the stratosphere over Antarctica, whether topography is raised or lowered. When topography is lowered, the Southern Ocean surface warming is due to strengthened southward atmospheric heat transport and associated enhanced storminess over the WAIS and the high latitudes of the Southern Ocean. When topography is raised, Southern Ocean warming is more limited and is associated with circulation anomalies. The response in the fully coupled experiments is generally consistent with the more idealized experiments, but the full-depth ocean warms throughout the water column whether topography is raised or lowered. These results indicate that ice sheet–climate system feedbacks differ depending on whether the Antarctic ice sheet is gaining or losing mass. Significance Statement: Throughout Earth's history, the Antarctic ice sheet was at times taller or shorter than it is today. The purpose of this study is to investigate how the atmosphere, sea ice, and ocean around Antarctica respond to changes in ice sheet height. We find that the response to lowering the ice sheet is not the opposite of the response to raising it, and that in either case the ocean surface near the continent warms. When the ice sheet is raised, the ocean warming is related to circulation changes; when the ice sheet is lowered, the ocean warming is from an increase in southward atmospheric heat transport. These results are important for understanding how the ice sheet height and local climate evolve together through time. [ABSTRACT FROM AUTHOR]

The southwest monsoon delivers over 70% of India's annual rainfall and is crucial to the success of agriculture across much of South Asia. Monsoon precipitation is known to be sensitive to sea surface temperature (SST) in the Bay of Bengal (BoB). Here, we use a configuration of the Unified Model of the Met Office coupled to an ocean mixed layer model to investigate the role of upper-ocean features in the BoB on southwest monsoon precipitation. We focus on the pronounced zonal and meridional SST gradients characteristic of the BoB; the zonal gradient in particular has an as-yet unknown effect on monsoon rainfall. We find that the zonal SST gradient is responsible for a 50% decrease in rainfall over the southern BoB (approximately 5 mm day−1), and a 50% increase in rainfall over Bangladesh and northern India (approximately 1 mm day−1). This increase is remotely forced by a strengthening of the monsoon Hadley circulation. The meridional SST gradient acts to decrease precipitation over the BoB itself, similarly to the zonal SST gradient, but does not have comparable effects over land. The impacts of barrier layers and high-salinity subsurface water are also investigated, but neither has significant effects on monsoon precipitation in this model; the influence of barrier layers on precipitation is felt in the months after the southwest monsoon. Models should accurately represent oceanic processes that directly influence BoB SST, such as the BoB cold pool, in order to faithfully represent monsoon rainfall. [ABSTRACT FROM AUTHOR]

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]