Global Temperature Research Articles

Efficiency metrics for ocean alkalinity enhancements under responsive and prescribed atmospheric pCO2 conditions

Abstract. Ocean alkalinity enhancement (OAE) and direct ocean removal (DOR) are emerging as promising technologies for enacting negative emissions. The long equilibration timescales, potential for premature subduction of surface water parcels, and extensive horizontal transport and dilution of added alkalinity make direct experimental measurement of induced CO2 uptake challenging. Therefore, the challenge of measurement, reporting, and verification (MRV) will rely to a great extent on general circulation models, parameterized and constrained by experimental measurements. A number of recent studies have assessed the efficiency of OAE using different model setups and different metrics. Some models use prescribed atmospheric CO2 levels, while others use fully coupled Earth system models. The former ignores atmospheric feedback effects, while the latter explicitly models them. In this paper it is shown that, even for very small OAE deployments, which do not substantially change atmospheric pCO2, the change in oceanic CO2 inventories differs significantly between these methods due to atmospheric feedback causing some ocean CO2 off-gassing. An analogous off-gassing occurs during direct air capture (DAC). Due to these feedback effects, care must be taken to compute the correct metrics when assessing OAE efficiency with respect to determining negative emissions credits, as opposed to determining the effect on global temperatures. This paper examines the commonly used metrics of OAE efficiency, their exact physical meanings, the assumptions inherent in their use, and the relationship between them. It is shown that the efficiency metric η(t), used in prescribed pCO2atm simulations, equals the equivalent schedule of a gradual DAC removal and storage in a fully coupled system.

Increased Surface Temperatures of Habitable White Dwarf Worlds Relative to Main-sequence Exoplanets

Abstract Discoveries of giant planet candidates orbiting white dwarf (WD) stars and the demonstrated capabilities of the James Webb Space Telescope bring the possibility of detecting rocky planets in the habitable zones (HZs) of WDs into pertinent focus. We present simulations of an aqua planet with an Earth-like atmospheric composition and incident stellar insolation orbiting in the HZ of two different types of stars—a 5000 K WD and main-sequence K-dwarf star Kepler-62 (K62) with a similar effective temperature—and identify the mechanisms responsible for the two differing planetary climates. The synchronously rotating WD planet's global mean surface temperature is 25 K higher than that of the synchronously rotating planet orbiting K62, due to its much faster (10 hr) rotation and orbital period. This ultrafast rotation generates strong zonal winds and meridional flux of zonal momentum, stretching out and homogenizing the scale of atmospheric circulation, and preventing an equivalent buildup of thick, liquid water clouds on the dayside of the planet compared to the synchronous planet orbiting K62, while also transporting heat equatorward from higher latitudes. White dwarfs may therefore present amenable environments for life on planets formed within or migrated to their HZs, generating warmer surface environments than those of planets with main-sequence hosts to compensate for an ever shrinking incident stellar flux.

From the Rainforest to the Fjords: examining equity in carbon capture and storage climate policy

ABSTRACT Carbon capture and storage (CCS) is considered by some to be a critical climate change mitigation technology, and a key element in efforts to limit the global temperature increases in line with the goals of the Paris Agreement. Implementation of CCS in mitigation scenarios assumes that it provides cost-effective emission reductions, and/or can achieve negative emissions when combined with bioenergy. We conduct a comparative case study of Brazil and Norway, two countries that are leading efforts to accelerate the development and deployment of CCS, to assess how these countries justify their CCS policy choices with respect to equity concerns. The findings show that the current design of CCS mitigation technologies can lead to unjust outcomes, and fossil fuel lock-in. Nevertheless, CCS has uses that go beyond fossil fuel infrastructure, which can improve its climate change mitigation potential.

Mechanisms and Modeling of Sea Level Rise in the Context of Global Warming

Sea level rise due to global warming is an important topic in current climate change research. In this study, we explore how complex natural processes triggered by global warming drive sea level change by analyzing climate models. We focus on the main drivers of sea level rise, including ice sheet melting and ocean thermal expansion. In addition, the article discusses in detail how positive feedback mechanisms and negative feedback mechanisms work together to influence the climate change process. In order to predict the future trend of sea level rise, this article models and simulates the global temperature, glacier changes and ocean dynamics based on the General Circulation Model (GCM). Although the model has some uncertainties, especially in cloud feedback and data completeness, it still provides a valuable predictive tool for understanding future sea level changes. The conclusions of this study point to the possibility of accelerated sea level rise as global temperatures continue to rise, with wide-ranging and far-reaching impacts on coastal ecosystems and human societies around the globe.

The Sea Level Rise under Global Warming

Global warming is the biggest environmental issue facing humanity in the 21st century, and the resulting sea level rise (SLR) is a major disaster that humans need to confront. According to predictions, even in the most optimistic scenario, global temperatures will still rise by 0.3-1.7 before 2100, and sea levels will continue to rise by at least 2.3 meters within the next 2000 years. Even though many regions are currently experiencing severe SLR and many countries have implemented corresponding strategies, there is little can be done for small and underdeveloped countries. This study summarizes the current situation and predictions of SLR through a literature review, and compiles various hazards caused by SLR, as well as how different countries in different regions are responding to it, and proposes opinions on how to deal with SLR. It can be used as a reference for readers who want to understand SLR, its hazards, and how to deal with it, so that readers can have a clear understanding of the relevant knowledge about SLR.

Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks

Abstract. Carbon dioxide (CO2) and methane (CH4) are the most important anthropogenic greenhouse gases and the main drivers of climate change. Monitoring their concentrations from space helps detect and quantify anthropogenic emissions, supporting the mitigation efforts urgently needed to meet the primary objective of the Paris Agreement, adopted at the 21st Conference of the Parties to the United Nations Framework Convention on Climate Change (UNFCCC) in 2015, to limit the global average temperature increase to well below 2 °C above pre-industrial levels. In addition, satellite observations can be used to quantify natural sources and sinks, improving our understanding of the carbon cycle. Advancing these goals is one key motivation for the European Copernicus CO2 monitoring mission CO2M. The necessary accuracy and precision requirements for the measured quantities XCO2 and XCH4 (the column-averaged dry-air mole fractions of CO2 and CH4) are demanding. According to the CO2M mission requirements, the spatial and temporal variability of the systematic errors (or spatio-temporal systematic errors) of XCO2 and XCH4 must not exceed 0.5 ppm and 5 ppb, respectively. The stochastic errors due to instrument noise must not exceed 0.7 ppm for XCO2 and 10 ppb for XCH4. Conventional so-called full-physics algorithms for retrieving XCO2 and/or XCH4 from satellite-based measurements of reflected solar radiation are typically computationally intensive and still usually require empirical bias corrections based on supervised machine learning methods. Here we present the retrieval algorithm Neural networks for Remote sensing of Greenhouse gases from CO2M (NRG-CO2M), which derives XCO2 and XCH4 from CO2M radiance measurements with minimal computational effort using artificial neural networks (ANNs). In addition, NRG-CO2M also provides estimates of both the noise-driven uncertainties and the averaging kernels of XCO2 and XCH4 for each sounding. Since CO2M will not be launched until 2026, our study exploits simulated measurements over land surfaces from a comprehensive observing system simulation experiment (OSSE) that includes realistic meteorology, aerosols, surface bidirectional reflectance distribution function (BRDF), solar-induced chlorophyll fluorescence (SIF), and CO2 and CH4 concentrations. We created a novel hybrid learning approach that combines advantages of simulation-based and measurement-based training data to ensure coverage of a wide range of XCO2 and XCH4 values, making the training data representative of future concentrations as well. The algorithm's postprocessing is designed to achieve a high data yield of about 80 % of all cloud-free soundings. The spatio-temporal systematic errors of XCO2 and XCH4 are 0.44 ppm and 2.45 ppb, respectively. The average single sounding precision is 0.41 ppm for XCO2 and 2.74 ppb for XCH4. Therefore, the presented retrieval method has the potential to meet the demanding CO2M mission requirements for XCO2 and XCH4. While the presented results are a solid proof of concept, the actual achievable quality can only be determined once NRG-CO2M is trained on real data, where it is confronted, e.g., with unknown instrument effects and systematic errors in the training truth.

Research Related to Turbofan Engines

The development of aerospace technology has become a topic of daily concern and discussion for the benefit of all mankind. As the global temperature rises, the living environment of human beings is threatened, and scientists have decided to work on the development of aerospace technology in order to solve this problem and meet people's needs. Looking at the aviation industry, which is currently accessible to most people, aviation scientists are focusing on aircraft engines. There are different types of engines such as turbojet engines, turbofan engines, paddle fan engines and so on, but the type of engine that meets the needs of most people today is the turbofan engine. This paper introduced the basic information of turbofan engine in the context of literature, for example, the characteristics of turbofan engine such as high efficiency, high thrust, low noise, high reliability, and the problem of durability of high-temperature components that it faces, which can be improved from the research and development of advanced materials and innovative cooling technology

Southern Ocean control on atmospheric CO2 changes across late Pliocene Marine Isotope Stage M2

Abstract. During the Pliocene, atmospheric CO2 concentrations (pCO2) were probably sometimes similar to today's, and global average temperature was ∼3 °C higher than preindustrial. However, the relationships and phasing between variability in climate and pCO2 on orbital timescales are not well understood. Specifically, questions remain about the nature of a lag of pCO2 relative to benthic foraminiferal δ18O in late Pliocene Marine Isotope Stage (MIS) M2 (3300 ka), which was longer than during the Pleistocene. Here, we present a multiproxy paleoceanographic reconstruction of the late Pliocene subtropical–subantarctic zone. New dinoflagellate cyst assemblage data are combined with previously published sea surface temperature reconstructions to reveal past surface conditions, including latitudinal migrations of the subtropical front (STF) over the late Pliocene at Ocean Drilling Program (ODP) Site 1168, offshore of western Tasmania. We observe strong oceanographic variability at the STF over glacial–interglacial timescales, especially the interval (3320–3260 ka) across MIS M2. By providing tight and independent age constraints from benthic foraminiferal δ18O, we find that, much more than benthic δ18O or local SST, latitudinal migrations of the STF are tightly coupled to global pCO2 variations across the M2. Specifically, a northerly position of the STF during the MIS M2 deglaciation coincides with generally low pCO2. We postulate that the Southern Ocean CO2 outgassing varied strongly with migrations of the STF and that this in part accounted for the variability in pCO2 across MIS M2.

Sustainability of regional Antarctic ice sheets under late Eocene seasonal atmospheric conditions

Abstract. The Eocene–Oligocene transition (EOT) is marked by a sudden δ18O excursion occurring in two distinct phases approximately 500 kyr apart. These phases signal a shift from the warm middle to late Eocene greenhouse climate to cooler conditions, with global surface air temperatures decreasing by 3–5 °C and the emergence of the first continent-wide Antarctic ice sheet (AIS). While ice sheet modelling suggests that ice sheet growth can be triggered by declining pCO2, it remains unclear how this transition was initiated, particularly the first growth phase that appears to be related to oceanic and atmospheric cooling rather than ice sheet growth. Recent climate model simulations of the late Eocene show improved accuracy but depict climatic conditions that are not conducive to the survival of incipient ice sheets throughout the summer season. This study therefore examines whether it is plausible to develop ice sheets of sufficient scale to trigger the feedback mechanisms required to disrupt the atmospheric regime above the Antarctic continent during warm and moist late Eocene summers and establish more favourable conditions for ice expansion. We aim to assess the sustainability of an incipient AIS under varying radiative, orbital and cryospheric forcing. To do so, we evaluate Community Earth System Model 1.0.5 simulations, using a 38 Ma geographical and topographical reconstruction, considering different radiative and orbital forcings. The climatic conditions prevailing during (and leading up to) the EOT can be characterised as extremely seasonal and monsoon-like, featuring a short yet intense summer period and contrasting cold winters. A narrow convergence zone with moist convection around the region with high sub-cloud equivalent potential temperature exhibits a ring-like structure, advecting moist surface air from the Southern Ocean in both summer and winter. This advection leads to high values of moist static energy and subsequent precipitation in coastal regions. Paradoxically, this atmospheric regime – particularly its coastal precipitation in winter – appears to be necessary for the sustenance of the moderately sized regional ice sheets we imposed on the continent, contrary to our assumption that these ice sheets would disrupt the atmospheric regime. This underscores a hysteresis effect for regional ice sheets on the Antarctic continent, suggesting the potential for a significant volume of ice on the continent without imminent full glaciation prior to the EOT.

Multifractal Analysis on Ozone Depletion and Climate Change: The Time Series Approaches

The ozone layer has acted as the planet’s natural sunscreen, protecting people, plants, and animals from harmful ultraviolet rays. The Antarctic ozone hole was first announced in a paper by the British Antarctic Survey’s Joe Farman, Brian Gardiner, and Jonathan Shanklin in 1985. Many investigations are still conducting to determine the connection between ozone depletion and climate change. This research study investigates the impact of the ozone layer’s depletion at the Antarctic pole on global climate change data such as temperature and precipitation, after the year 1985 through a fractal dimension, Multifractal Detrended Fluctuation Analysis (MFDFA), and standard correlation coefficient. For this, the research work has analyzed 45 years of climate change variables such as global monthly temperature anomaly, global monthly precipitation anomaly, and Southern Hemisphere minimum ozone time series data from 1979 to 2023. The fractal dimension of the time series is obtained by rescaled range analysis, which is used to identify the fractality of the time series and long-range correlations and persistence. To study the multifractality of these fractal time series, MFDFA procedure has been applied. By applying MFDFA to these time series data, this research has identified significant multifractal characteristics, indicating complex dynamics and long-range correlations, and identified potential nonlinear patterns. This research provides valuable insights into the complex dynamics of time series data, as revealed by the calculated exponent values and MFDFA spectrum. The strong correlation observed between the exponent values of temperature anomalies, and precipitation anomalies, with ozone depletion time series provides compelling evidence for the significant impact of ozone depletion on climate change. These results highlight the potential of multifractality for understanding the intricate mechanisms underlying climate change.

Heatwave Future Changes From an Ensemble of Km‐Scale Regional Climate Simulations Within CORDEX‐FPS Convection

AbstractAs global temperatures continue to rise, the impact of heatwaves becomes increasingly striking. The increasing frequency and intensity of these events underscore the critical need to understand regional‐scale mechanisms and feedback, exacerbating or mitigating heatwave magnitude. Here, we use an ensemble of convection‐permitting regional climate models (CPRCMs) to elucidate future heatwave changes at fine spatial scales. We explore whether the recently highlighted drier/warmer signal introduced by CPRCMs improves summer temperature extremes representation and if it modulates future heatwave changes compared to convection‐parameterizing regional climate models (RCMs). In historical runs, CPRCMs show a more realistic representation of summer maximum temperature especially on a ground‐station‐based evaluation. CPRCMs project substantially drier conditions than RCMs. This is associated with a modulation of heatwave temperature changes which show diversified spatial patterns, magnitudes, and signs. CPRCMs ensemble shows an overall reduction in heatwave metrics future changes inter‐model spread compared to the RCMs ensemble.

Mitigating anthropogenic climate change with aqueous green energy

Reaching net zero emissions and limiting global warming to 2 °C requires the widespread introduction of technology-based solutions to draw down existing atmospheric levels and future emissions of CO2. One such approach is direct air CO2 capture and storage (DACCS), a readily available, yet energy-intensive process. The combination of DACCS and ocean thermal energy conversion (OTEC) allows for independently powered carbon capture plants to inject concentrated carbon into deep marine sediments where storage is generally safe and permanent. OTEC is a form of electricity production that exploits the temperature difference between deep and shallow ocean waters, and can power DACCS on floating platforms at a price competitive with coal-generated electricity. Here we highlight the scale of the challenge facing society. We show that a safe and sustainable level of OTEC-generated electricity powering DACCS for 70 years could result in up to a 35% decrease in the relative global mean temperature warming compared to a business-as-usual emissions scenario.

Examining the impact of Ag-decorated CuO-H2O nanofluid on pressure and thermal efficiency in a channel with metal foam heat sinks: an experimental study

ABSTRACT In this study, nanofluids were produced from CuO nanoparticles decorated with Ag atoms at different mass concentrations, and their cooling performance was examined in a channel containing metal foam heat sinks (MFHS) with pore densities of 10 and 40 pore per inch (PPI). CuO-H2O/2% Polyethylene Imine (PEI) nanofluid with a concentration of 0.1% by mass was used. The surfaces of the CuO nanoparticles were decorated with Ag at mass concentrations of 0.03%, 0.05%, and 0.1%. Experiments were performed for volumetric flow rates varying from 17.6 L/h to 76.5 L/h in laminar conditions, and the heat fluxes applied to the bottom of the channel were chosen in the range of 3267 W/m2-5400 W/m2. The base fluid (BF)-empty surface case was used as the reference for all measurements. In the findings of experiments conducted on the base surface, it was found that decorating CuO nanoparticles with 0.03% and 0.05% Ag atoms effectively lowers the surface temperatures compared to the BF. On the contrary, an increase in surface temperatures was detected when 0.1% Ag atoms were used. Passing a 0.1% CuO-0.05% Ag/2% PEI-H2O (NF3) nanofluid through 40 PPI MFHS’ achieved the highest improvement in mean surface temperatures, with a 37.4% increase compared to using the BF on the empty surface.

The short-term comprehensive impact of the phase-out of global coal combustion on air pollution and climate change.

With the continuous intensification of global warming, the reduction and ultimate phase-out of coal combustion is an inevitable trend in the future global energy transformation. This study comprehensively analyzed the impact of phasing out coal combustion on global emissions and concentrations of air pollutants, radiative fluxes, meteorology and climate using Community Earth System Model 2 (CESM2). The results indicate that after the global phase-out of coal combustion, there is a marked decrease in the concentrations of sulfur dioxide (SO2), nitrogen oxides (NOx) and fine particulate matter (PM2.5), with some regions experiencing a reduction of exceeding 50%. There is no significant change in global ozone (O3) concentration. There are decreasing AOD and positive radiative fluxes globally in the short term, though the cloud contributes minor negative radiative fluxes. The global air temperature may increase by approximately (0.02±0.15) °C on average with regional and seasonal variations, and the precipitation may potentially increase by approximately (2.7±40.6) mm yr-1 globally and over 20% in equatorial regions in the short term. But combined with the decreasing trend of cloud water content in the Northern Hemisphere, it indicates a potential increase in the extremity of precipitation events. This study provides references for global control of air pollution, mitigation strategies of climate change, and transformation of energy structures under the objective of "carbon neutrality", such as focusing on the negative climate impacts of exacerbating regional warming and increasing extreme precipitation resulting from the rapid reduction of aerosols in the short term.

Temperature Overshoot Would Have Lasting Impacts on Hydrology and Water Resources

AbstractModels of climate change impacts could be missing significant risks to hydrologic and water infrastructure systems through a shared feature: the idea that temperatures rise monotonically. By contrast, temperature overshoot pathways describe non‐monotonic warming trajectories, in which global temperatures first exceed a given target before declining to that target. Risks from overshoot pathways are qualitatively different from risks associated with monotonic warming trajectories, and are likely underestimated in current research and policy. Models suggest overshoot may be almost unavoidable if the more stringent Paris Agreement target limiting warming to 1.5°C over preindustrial levels is to be met by 2100. While overshoot has been relatively widely described in the climate literature, the impacts of overshoot on individual system characteristics have not. We suggest that failure to consider disparities between monotonic and overshoot warming impacts on hydrology and water resources presents particular risks due to divergent adaptation needs. Processes with decadal hysteresis are especially vulnerable. These include glacial contributions to streamflow; hydrologic consequences of vegetation change; altered groundwater; higher water use for fossil fuel combustion and carbon dioxide removal; and water infrastructure and policy that depends on climate conditions. We argue that risks of overshoot cannot be fully captured in current integrated assessment models and that overshoot needs to be specifically evaluated to adequately characterize risk in the water system. We consider how current modeling tools could be adapted to evaluate overshoot consequences, but also recognize that decisions must be made even without perfect knowledge.

إمكانية تطبيق الطاقة الشمسية في مدن الجنوب الليبي: التحديات والصعوبات

Renewable Energy Sources (RES) become important in recent years in research that enlightens the lives of people by meeting their daily electricity demand. This work focuses on shedding light on the utilization of renewable energy sources such as PV in some of the Libyan southern cities (Sebha, Murzuk, Ghat, Ubari, and Wadi Alshatti) to spread peace and avoid internal migrants. Libya with the help of the availability of resources of solar irradiance and wind speed, the load can be met along with reducing the deficit. The obtained green energy from RESs could play a substantial role in meeting Sustainable Development Goal 7 (SDG7) and Climate Action Goal 13 (CAG13) solutions. Hopefully, this study is expected to be a guideline to researchers in the field to assist them in their future studies. In this study, we compared five cities located in southern Libya in terms of global solar radiation, temperatures, and relative humidity, and also compared the productivity of PV modules for a full year by simulating 1 kW of PV modules in each city and the results were good for installing solar panel plants in the aforementioned cities. Keywords: Renewable Energy Sources, Libyan southern cities, Sustainable Development Goal Seven, 1 kW of PV, solar panel.

DETERMINAÇÃO DE BIODIESEL METÍLICO DE DENDÊ EM MISTURAS COM DIESEL UTILIZANDO A RESOLUÇÃO MULTIVARIADA DE CURVAS COM MÍNIMOS QUADRADOS ALTERNADOS

DETERMINATION OF PALM METHYL BIODIESEL IN DIESEL BLENDS USING MULTIVARIATE CURVE RESOLUTION WITH ALTERNATING LEAST SQUARES. The increase in the average temperature of the Earth due to excess CO2 and other greenhouse gases has caused glaciers to melt and sea levels to rise. The burning of fossil fuels is one of the main causes of this problem, so the use of biofuels is important for mitigating this environmental impact. In Brazil, biodiesel is mixed with mineral; however, irregularities have been detected, reducing the expected positive effects. Therefore, this study proposes the use of multivariate curve resolution with alternating least squares (MCR-ALS) to quantify the content of methyl palm oil biodiesel in diesel blends and determine the concentration of the adulterant automotive lubricating oil in the blend. The model for quantifying biodiesel in diesel obtained R2 = 0.9997, root mean square error of calibration (RMSEC) = 0.56% (v v-1) and prediction (RMSEP) = 0.65% (v v-1), while the determination of adulteration in the biodiesel-diesel blend showed RMSEC = 0.67% (v v-1), RMSEP = 0.81% (v v-1) and R2 = 0.9992. These results demonstrate the ability of the models developed to predict both the content and quantity of possible adulterants in blends of palm oil biodiesel and mineral diesel, contributing to the quality control of this fuel.

One Ocean – Stopping Oceanic Pollution is the biggest Challenge of Climate Change

This is the first paper in a series on our oceans. There has been a concentration of climate change solutions on air pollution which ignores one vital factor. That the ocean covers 70 percent of Earth's surface, containing about 1.35 billion cubic kilometres of water, constituting about 97 percent of all water on Earth. The ocean’s size means that it plays a key role in determining weather patterns and hence both local and world climatic events. The critical role of the ocean is in balancing global temperatures as water absorbs heat in the summer and releases it in the winter. Without the ocean to help regulate global temperatures, Earth’s climate would be bitterly cold. This paper discusses reasons for dramatic changes in weather patterns known as catastrophic events, emphasizing the role of oceanic currents and pollution. The second paper will discuss solutions. Keywords: Climate change, pollution, carbon capture, oceanic biosphere, continental linkages, sewage

A neural network-based adaptive cut-off approach to normality testing for dependent data

AbstractThere is a wide availability of methods for testing normality under the assumption of independent and identically distributed data. When data are dependent in space and/or time, however, assessing and testing the marginal behavior is considerably more challenging, as the marginal behavior is impacted by the degree of dependence, which typically leads to an inflation in Type I error rates. We propose a new approach to assess normality for dependent data by non-linearly incorporating existing statistics from normality tests as well as sample moments such as skewness and kurtosis through a neural network with adaptive cut-offs by which the Type I error inflation issue is fixed. We calibrate (deep) neural networks by simulated normal and non-normal data with a wide range of dependence structures and we determine the probability of rejecting the null hypothesis. We compare several approaches for normality tests and demonstrate the superiority of our method in terms of statistical power through an extensive simulation study. A real world application to global temperature data further demonstrates how the degree of spatio-temporal aggregation affects the marginal normality in the data.

Enhancing building resilience: the role of future weather data in building design

With climate change driving unprecedented shifts in global weather patterns, the need to future-proof building designs has become critical. Current design practices predominantly rely on simulations and analysis that use Typical Meteorological Year (TMY) files, which are based on historical weather data and may not reflect future climatic conditions. This could result in buildings that may not be able to adapt to long-term climate change. Our study examines whether the use of future weather data in design analysis points to different strategies and is necessary to successfully predict building performance.We used predicted future weather data for 2080 in Bangalore, India, which forecasts a global temperature of 4°C temperature increase and historical Typical Meteorological Year (TMY) data, compared these data, conducted analysis to determine the passive and active strategies that get prioritised from the analysis and compare these. We used a calibrated Building Energy Simulation (BES) model of a building in Bangalore to determine how the performance of the building changes under future weather conditions.The future weather indicates significant temperature rise across all seasons, increase in summer temperatures of 10°C; decreasing relative humidity in summer and increasing in winter; a reduction of 16.2% for number of hours in the comfort range. The design analysis indicated that different active and passive design strategies gets prioritised for the future weather scenario.The calibrated models shows that while the passive design features incorporated in the building are adequate for the TMY weather conditions, they may fail to maintain thermal comfort in the future. The percentage of discomfort hours in the future condition increased by 37%.These findings indicate for future-proof our buildings it is necessary to use future weather data during the design stages while selecting climate-responsive strategies. Analysis methods must incorporate future weather conditions for climate resilient building. The findings also indicate that the sole use of current weather data results in passive and active strategies that will not be appropriate for future climate-changed forced weather conditions.