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Abstract Mesoscale convective systems (MCSs) are pivotal in global energy/water cycles and typically produce extreme weather events. Despite their importance, our understanding of their future change remains limited, largely due to inadequate representation in current climate models. Here, using a global storm‐resolving model that accurately simulates MCSs, we conclude contrasting responses to increased SST in their occurrence, that is, notable decreases over land but increases over ocean. This land‐ocean contrast is attributed to the changes in convective available potential energy (CAPE) and convective inhibition (CIN). Over land, notable rises in CIN alongside moderate increases in CAPE effectively suppress (favor) weak to moderate (intense) MCSs, resulting in an overall reduction in MCS occurrences. In contrast, substantial increases in CAPE with minimal changes in CIN over ocean contribute to a significant rise in MCS occurrences. The divergent response in MCS occurrence has profound impacts on both mean and extreme precipitation.

Background There exists limited agreement on the recommendations for the treatment of transitional circulatory instability (TCI) in preterm neonatesObjective To compare the efficacy of various interventions used to treat TCIMethods Medline and Embase were searched from inception to 21st July 2023. Two authors extracted the data independently. A Bayesian random effects network meta-analysis was used. Recommendations were formulated using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) framework.Interventions Dopamine, dobutamine, epinephrine, hydrocortisone, vasopressin, milrinone, volume and placebo.Main outcome measures Mortality, major brain injury (MBI) (intraventricular haemorrhage > grade 2 or cystic periventricular leukomalacia), necrotising enterocolitis (NEC) ≥stage 2 and treatment response (as defined by the author).Results 15 Randomized Controlled Trials (RCTs) were included from the 1365 titles and abstracts screened. Clinical benefit or harm could not be ruled out for the critical outcome of mortality. For the outcome of MBI, epinephrine possibly decreased the risk when compared to dobutamine and milrinone (very low certainty). Epinephrine was possibly associated with a lesser risk of NEC when compared with dopamine, dobutamine, hydrocortisone and milrinone (very low certainty). Dopamine was possibly associated with a lesser risk of NEC when compared with dobutamine (very low certainty). Vasopressin possibly decreased the risk of NEC compared with dopamine, dobutamine, hydrocortisone and milrinone (very low certainty). Clinical benefit or harm could not be ruled out for the outcome response to treatment.Conclusions Epinephrine may be used as the first-line drug in preterm neonates with TCI, the evidence certainty being very low. We suggest future trials evaluating the management of TCI with an emphasis on objective criteria to define it.

To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.

Early prediction of cyclones helps reduce deaths and damage to properties worldwide. With the advancement in satellite imaging technology, obtaining atmospheric images and remotely sensed objects such as cyclones is possible using different modalities. Such images are handy for weather prediction, specifically for forecasting cyclonic storms. However, it has a few limitations for achieving higher prediction accuracy with minimal time. A novel technique, proposed by Czekanowsky Dice Hypergraphic Extended Kalman Momentum Filterization based Bivariate Correlative Deep Structure Learning classification (CDHEKMF-BCDSLC), is introduced to achieve better cyclone prediction accuracy. Initially, the multiple satellite images are gathered from cyclone datasets—the proposed technique comprises four processing steps: segmentation, preprocessing, feature extraction, and classification. At first, Czekanowsky dices the Intensity threshold-based Interval Hypergraph (CDIT-IH) model using a Segmentation process. It minimized to perform cyclone prediction time. After that, preprocessing is applied to a novel invariant extended Kalman momentum filter designed to improve image contrast. Next, Bivariate correlative spatiotemporal feature extraction is performed on each image pixel intensity to extract features over time and location. Finally, a multidimensional deep belief network classification model is applied for accurate cyclone prediction. A multidimensional deep belief network classification model is a machine learning technique that consists of multiple layers for learning the given input (i.e., Spatiotemporal features). This process increases the prediction accuracy. Experimental results reveal that the proposed technique noticeably predicts cyclone conditional variants using prediction accuracy, precision, recall, F-measure, and prediction time concerning the number of cyclone images. The Quantitative results show that the proposed technique achieves 6% better accuracy with 17% minimum prediction time, 5% improved precision and f- f-measure, and 4% recall when compared to the state-of-the-art methods.

Abstract Global greenhouse gas forcing and feedbacks are the primary causes of climate change but have limited direct observations. Here we show that continuous, stable, global, hyperspectral infrared satellite measurements (2003–2021) display decreases in outgoing longwave radiation (OLR) in the CO2, CH4, and N2O absorption bands and increases in OLR in the window band and H2O absorption bands. By conducting global line‐by‐line radiative transfer simulations with 2003–2021 meteorological conditions, we show that increases in CO2, CH4, and N2O concentrations caused an instantaneous radiative forcing and stratospheric cooling adjustment that decreased OLR. The climate response, comprising surface and atmospheric feedbacks to radiative forcings and unforced variability, increased OLR. The spectral trends predicted by our climate change experiments using our general circulation model identify three bedrock principles of the physics of climate change in the satellite record: an increasing greenhouse effect, stratospheric cooling, and surface‐tropospheric warming.

The Clouds and the Earth's Radiant Energy System (CERES) project has now produced over two decades of observed data on the Earth's Energy Imbalance (EEI) and has revealed substantive trends in both the reflected shortwave and outgoing longwave top-of-atmosphere radiation components. Available climate model simulations suggest that these trends are incompatible with purely internal variability, but that the full magnitude and breakdown of the trends are outside of the model ranges. Unfortunately, the Coupled Model Intercomparison Project (Phase 6) (CMIP6) protocol only uses observed forcings to 2014 (and Shared Socioeconomic Pathways (SSP) projections thereafter), and furthermore, many of the ‘observed' drivers have been updated substantially since the CMIP6 inputs were defined. Most notably, the sea surface temperature (SST) estimates have been revised and now show up to 50% greater trends since 1979, particularly in the southern hemisphere. Additionally, estimates of short-lived aerosol and gas-phase emissions have been substantially updated. These revisions will likely have material impacts on the model-simulated EEI. We therefore propose a new, relatively low-cost, model intercomparison, CERESMIP, that would target the CERES period (2000-present), with updated forcings to at least the end of 2021. The focus will be on atmosphere-only simulations, using updated SST, forcings and emissions from 1990 to 2021. The key metrics of interest will be the EEI and atmospheric feedbacks, and so the analysis will benefit from output from satellite cloud observation simulators. The Tier 1 request would consist only of an ensemble of AMIP-style simulations, while the Tier 2 request would encompass uncertainties in the applied forcing, atmospheric composition, single and all-but-one forcing responses. We present some preliminary results and invite participation from a wide group of models.

Satellite observations reveal a significant positive trend in Earth’s energy imbalance, but the contributing drivers have yet to be understood. Here, the authors show that it is exceptionally unlikely that this trend can be explained by internal variability; instead, anthropogenic forcing and feedbacks cause the trend.

Abstract We describe the Geophysical Fluid Dynamics Laboratory's CM4.0 physical climate model, with emphasis on those aspects that may be of particular importance to users of this model and its simulations. The model is built with the AM4.0/LM4.0 atmosphere/land model and OM4.0 ocean model. Topics include the rationale for key choices made in the model formulation, the stability as well as drift of the preindustrial control simulation, and comparison of key aspects of the historical simulations with observations from recent decades. Notable achievements include the relatively small biases in seasonal spatial patterns of top‐of‐atmosphere fluxes, surface temperature, and precipitation; reduced double Intertropical Convergence Zone bias; dramatically improved representation of ocean boundary currents; a high‐quality simulation of climatological Arctic sea ice extent and its recent decline; and excellent simulation of the El Niño‐Southern Oscillation spectrum and structure. Areas of concern include inadequate deep convection in the Nordic Seas; an inaccurate Antarctic sea ice simulation; precipitation and wind composites still affected by the equatorial cold tongue bias; muted variability in the Atlantic Meridional Overturning Circulation; strong 100 year quasiperiodicity in Southern Ocean ventilation; and a lack of historical warming before 1990 and too rapid warming thereafter due to high climate sensitivity and strong aerosol forcing, in contrast to the observational record. Overall, CM4.0 scores very well in its fidelity against observations compared to the Coupled Model Intercomparison Project Phase 5 generation in terms of both mean state and modes of variability and should prove a valuable new addition for analysis across a broad array of applications.

Data obtained from long-term sediment trap experiments in the Indian Ocean in conjunction with satellite observations illustrate the influence of primary production and the ballast effect on organic carbon flux into the deep sea. They suggest that primary production is the main control on the spatial variability of organic carbon fluxes at most of our study sites in the Indian Ocean, except at sites influenced by river discharges. At these sites the spatial variability of organic carbon flux is influenced by lithogenic matter content. To quantify the impact of lithogenic matter on the organic carbon flux, the densities of the main ballast minerals, their flux rates and seawater properties were used to calculate sinking speeds of material intercepted by sediment traps. Sinking speeds in combination with satellite-derived export production rates allowed us to compute organic carbon fluxes. Flux calculations imply that lithogenic matter ballast increases organic carbon fluxes at all sampling sites in the Indian Ocean by enhancing sinking speeds and reducing the time of organic matter respiration in the water column. We calculated that lithogenic matter content in aggregates and pellets enhances organic carbon flux rates on average by 45 % and by up to 62 % at trap locations in the river-influenced regions of the Indian Ocean. Such a strong lithogenic matter ballast effect explains the fact that organic carbon fluxes are higher in the low-productive southern Java Sea compared to the high-productive western Arabian Sea. It also implies that land use changes and the associated enhanced transport of lithogenic matter from land into the ocean may significantly affect the CO2 uptake of the organic carbon pump in the receiving ocean areas.

Anthropogenic aerosol and greenhouse gas concentrations are spatially uncorrelated, but the climate response to each shows a similar spatial pattern. Here the authors show that two-thirds of the spatial similarity in the full response manifests through fast-acting atmosphere and land surface processes alone.

At present, the Arabian Sea has a permanent oxygen minimum zone (OMZ) at water depths between about 100 and 1200 m. Active denitrification in the upper part of the OMZ is recorded by enhanced δ15N values in the sediments. Sediment cores show a δ15N increase during the middle and late Holocene, which is contrary to the trend in the other two regions of water column denitrification in the eastern tropical North and South Pacific. We calculated composite sea surface temperature (SST) and δ15N ratios in time slices of 1000 years of the last 25 kyr to better understand the reasons for the establishment of the Arabian Sea OMZ and its response to changes in the Asian monsoon system. Low δ15N values of 4–7 ‰ during the last glacial maximum (LGM) and stadials (Younger Dryas and Heinrich events) suggest that denitrification was inactive or weak during Pleistocene cold phases, while warm interstadials (ISs) had elevated δ15N. Fast changes in upwelling intensities and OMZ ventilation from the Antarctic were responsible for these strong millennial-scale variations during the glacial. During the entire Holocene δ15N values > 6 ‰ indicate a relatively stable OMZ with enhanced denitrification. The OMZ develops parallel to the strengthening of the SW monsoon and monsoonal upwelling after the LGM. Despite the relatively stable climatic conditions of the Holocene, the δ15N records show regionally different trends in the Arabian Sea. In the upwelling areas in the western part of the basin, δ15N values are lower during the mid-Holocene (4.2–8.2 ka BP) compared to the late Holocene ( δ15N values in the northern and eastern Arabian Sea rose during the last 8 kyr. The displacement of the core of the OMZ from the region of maximum productivity in the western Arabian Sea to its present position in the northeast was established during the middle and late Holocene. This was probably caused by (i) reduced ventilation due to a longer residence time of OMZ waters and (ii) augmented by rising oxygen consumption due to enhanced northeast-monsoon-driven biological productivity. This concurs with the results of the Kiel Climate Model, which show an increase in OMZ volume during the last 9 kyr related to the increasing age of the OMZ water mass.

This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ∼ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available.

Seasonal cycle of biogenic fluxes obtained from sediment trap at two locations 5°24' N, 86°46' E (southern Bay of Bengal trap; SBBT) and 3°34' N, 77°46' E (equatorial Indian Ocean trap; EIOT) within the equatorial Indian Ocean (EIO) were examined to understand the factors that control them. The sediment trap data at SBBT was collected for ten years from November 1987 while that at EIOT was for a one year period from January 1996. The characteristic of biogenic flux at SBBT was the strong seasonality with peak flux in August, while lack of seasonality characterised the flux at EIOT. The high chlorophyll biomass at the SBBT during the summer monsoon was supported by a combination of processes such as wind-mixing and advection, both of which supplied new nitrogen to the upper ocean. In contrast, the elevated chlorophyll at EIOT during summer monsoon was supported only by wind mixing. High cell counts of phytoplankton (> 5 μm) at SBBT dominated by diatoms suggest the operation of classical food web and high carbon export. On the contrary, dominance of pico-phytoplankton and one-and-a-half time higher magnitude of micro-zooplankton biomass along with 2-fold lesser meso-zooplankton at EIOT indicated the importance of microbial loop. The substantial decrease in the carbon export at EIOT indicated faster remineralization of photosynthetically produced organic matter.

Sediments deposited on the Northern and Eastern Andaman Shelf along with a few sediments from the Irrawaddy and the Salween Rivers are studied for their elemental, Sr and Nd concentrations and their isotope composition to identify their sources, constrain their transport pathways and assess the factors influencing the erosion in the catchment and their dispersal and deposition over the Andaman Shelf region. Major elemental compositions of the shelf sediments suggest mafic lithology such as ophiolites and ultrabasic rocks in the Irrawaddy drainage and over Indo – Burman – Arakan (IBA) ranges as their dominant source. 87Sr/86Sr ratios in sediments of the Northern and Eastern Andaman Shelf range between 0.712245 and 0.742183 whereas, εNd varies from -6.29 to -17.25. Sediments around Mergui have the highest 87Sr/86Sr and the lowest εNd values. Sr and Nd isotope composition of these sediments along with that in the potential sources suggest four major sources of these sediments to the Andaman Shelf, (i) the Irrawaddy River, (ii) the Salween River, (iii) Rivers draining the IBA ranges and (vi) Rivers draining the Western/Central granitic ranges of the Southern Myanmar and Western Thailand such as the Tavoy and the Tanintharyi Rivers. Erosion in the catchment is controlled by the precipitation and topography. Intensely focused precipitation over the higher relief of the western slopes of the IBA and western/central granitic ranges causes higher erosion over this mountainous region, supplying huge sediments through the Kaladan, Irrawaddy, Salween, and the Tanintharyi Rivers to the western Myanmar Shelf, Northern, and Eastern Andaman Shelves respectively. The majority of the sediments produced in the drainage are delivered to the shelf during the south-west monsoon which is dispersed eastward by sea-surface circulation from the mouth of the Irrawaddy Rivers towards the Gulf of Martaban and further southward. The Andaman Shelf receives very little sediment, if any, from the Ganga-Brahmaputra Delta. Higher erosion over the Western/Central granitic belt of the Southern Myanmar and Western Thailand and its importance in delivering sediments to the Eastern Andaman Shelf around the Mergui Archipelago are highlighted for the first time in this study.

Tropospheric aerosols emitted from biomass burning reduce solar radiation at the surface and locally heat the atmosphere. Equilibrium simulations using an atmospheric general circulation model (GFDL AGCM) indicate that strong atmospheric absorption from these particles can cool the surface and increase upward motion and low-level convergence over southern Africa during the dry season. These changes increase sea level pressure over land in the biomass burning region and spin-up the hydrologic cycle by increasing clouds, atmospheric water vapor, and, to a lesser extent, precipitation. Cloud increases serve to reinforce the surface radiative cooling tendency of the aerosol. Conversely, if the climate over southern Africa were hypothetically forced by high loadings of scattering aerosol, then the change in the low-level circulation and increased subsidence would serve to decrease clouds, precipitation, and atmospheric water vapor. Surface cooling associated with scattering-only aerosols is mitigated by warming from cloud decreases. The direct and semi-direct climate impacts of biomass burning aerosol over southern Africa are sensitive to the total amount of aerosol absorption and how clouds change in response to the aerosol-induced heating of the atmosphere.

An accelerated diffusion of alumina precursor species in-between the gallery region of montmorilloniteclays by the use of ultrasonic technique is described. This method offers a faster, efficient and attractiveroute for the synthesis of alumina-pillared clay catalysts. Out of the several preparative parameters studied,the role of pre-exchanged cations influenced the optimum duration of ultrasonic agitation and treatment forthe pillaring process. By comparing ultrasonic route and conventional preparation procedure, it is revealedthat uniform spacing of alumina pillars in the clay means homogeneously distributed acid centers. Theinfluence of calcination temperature on the acidity and hence the catalytic activity is described. The choiceof three different montmorillonite clays with different cation exchange capacities enables one to tune thepore dimensions of the pillared clays. The catalytic applications include studies on cumene cracking, dehy-dration of propan-2-ol and alkylation of benzene with linear olefins.

A political scientist and thinker talks about protest movements in his city, Kolkata, during the period from the late 1980s. The CPI(M)-led Left Front was elected to government in the state of West Bengal without interruption from 1977. It wielded enormous power over society. The turnaround finally came in 2007, with a wave of protest agitations that eventually allowed the opposition politician, Mamata Banerjee, to lead her party to electoral victory in 2011. At the time of the interview, in 2008, Samaddar talks about the ‘Mamata phenomenon’, locating the roots of her populist politics in the protest stream of the 1980s and 1990s. This period saw protest attempting to find its feet once again in the now blighted city. Samaddar points to the emergence of a new politics in the wake of the death of the old left politics. The conversation with Ranabir Samaddar helps one to better understand the political transformation in West Bengal, and also throws light on a way of thinking and a praxis whose roots lie in the robust civic and political life of that state.