Minimum Surface Temperature Research Articles

Assessing and mitigating building fire risk based on the scenario clusters in Bangladesh

The increasing occurrence of fire hazards in residential buildings in Bangladesh has led to severe property damage, physical injuries, and fatalities, underscoring a critical research gap in effective fire risk management. This study aims to address this gap by identifying key fire risks and proposing mitigation strategies using BIM technology. The research employs a comprehensive survey and scenario clustering methodology to identify these risks and assess the efficacy of various fire-resistant materials. Data collection involved questionnaires distributed to 200 respondents, including building owners, occupants, engineers, and firefighters. These clusters are based on the metrics of fatality numbers and property damage to quantify fire risk. Findings highlight the significant role of wall and ceiling lining materials (RII = 0.919) in contributing to fire risk. Further analysis was conducted using a residential building model developed in Autodesk Revit and simulated in Pyrosim software, assessing various lining materials. Quantitative results demonstrated that fire brick is the most effective material, exhibiting the lowest heat release rate (968 kW/m2), minimum adiabatic surface temperature (28°C), minimum heat transfer coefficient (1.75 W/m2/K), and lowest surface burning rate (7.5e−08 Kg/m2/s). These results suggest that fire brick is the optimal choice for enhancing fire resistance in residential buildings.

Development of a thermal diagnostic system for the SPARC tokamak.

The SPARC tokamak will have scrape-off layer parallel heat fluxes on the order of GW/m2. Managing power exhaust of this magnitude will be mandatory for a reactor-scale device. To enable this mission, a thermal diagnostic suite will be deployed to measure the in-vessel structural temperatures to ensure they do not exceed their design limits and to determine the spatial distribution and magnitude of energy deposited onto the first wall. Thermocouples and fiber Bragg gratings have been selected for their environmental compatibility and proven useful on other fusion devices. High-density thermocouple arrays in the divertor will have two spring-loaded thermocouples per divertor target tile, which are being used as calorimeters, and will look to resolve the temperature distribution within the tile due to a swept or static strike point. All systems will need to survive the vacuum vessel bake, set at a minimum plasma facing surface temperature of 350 °C, which presents a particularly challenging environment for the fiber-based subsystem. Along with this temperature design requirement, all the materials in the primary vacuum need to be ultra-high vacuum compatible, able to handle the expected neutron and gamma radiation, as well as tritium exposure, all of which restrict material options. Finally, due to the expected activated environment in SPARC, there will be little chance to replace defective sensors, so system resilience is ensured through toroidal redundancy, probe material selection, and mitigating the impact of common-mode failures. Initial testing of sensors show that intershot structural measurements are sufficiently captured with the raw output, but intrashot measurements of the plasma facing material requires model-based interpretive tools.

Shrinking suitable habitat of a sub-Arctic foundation kelp under future climate scenarios.

Climate change has profound effects on the distribution of kelp forests in the Arctic and sub-Arctic. However, studies on the responses of kelps to climate change, particularly along the sub-Arctic regions of the Alaska coast, are limited. Eualaria fistulosa is a foundational kelp species in the Aleutian Islands, with an east-west distribution that extends from Japan to southern southwest Alaska. In this study, we utilized a species distribution model (SDM) to explore changes in the future habitat suitability of E. fistulosa under contrasting Shared Socioeconomic Pathway (SSP) scenarios. Our model exhibited relatively high predictive performance, validating our SDM predictions. Notably, the SDM results indicate that minimum sea surface temperature, annual range in sea surface temperatures, and annual mean current velocities are the three most important predictor variables determining E. fistulosa's distribution. Furthermore, the projected geographic distribution of Eualaria is generally consistent with its observed occurrence records. However, under high emission scenarios (SSP5-8.5), E. fistulosa is predicted to contract its distribution range by 9.0% by 2100, with widespread disappearance along the southeast Alaskan coast and limited northward migration to Kamchatka Krai in Russia and Bristol Bay in Alaska. These findings contribute valuable insights for conservation strategies via addressing climate-induced alterations in sub-Arctic kelp distribution.

204 Detecting subclinical mastitis in meat-breed ewes using infrared thermography

Abstract Mastitis, the inflammation of the mammary gland most commonly due to bacterial infection, is an important welfare concern in meat-breed sheep. The objective of our study was to evaluate udder surface temperature obtained from infrared thermography as a diagnostic tool for subclinical mastitis. We predicted that udder halves with subclinical mastitis would have greater surface temperatures than healthy udder halves. We enrolled 39 meat-breed ewes (10 Hampshire, 24 Polypay, 5 Targhee; 2 to 9 yr of age) at the University of Wisconsin-Madison sheep unit. All procedures were approved by the UW-Madison Institutional Animal Care and Use Committee. Milk samples from each udder half were collected in duplicate weekly beginning 2 to 4 d postpartum until 8 wk postpartum. Immediately before milk sampling, the udder was photographed from the rear using a thermal camera. A sample was considered a true infection if at least 100 CFU/mL of a bacterial species were isolated. From each photo, we obtained values for minimum, maximum, and mean skin surface temperature for the right and left udders. Three linear mixed models were fit using minimum, maximum, and mean temperatures as the response variables. Fixed effects were infection status (infected or not), weeks postpartum (wk 1-8), and ambient temperature, with a random effect of udder half nested within animal ID. Contrary to our predictions, infection status did not predict udder skin surface temperature (P > 0.12). Healthy udder halves had a mean temperature of 35.5 ± 0.1°C (mean ± SE), minimum temperature of 29.9 ± 0.3°C, and maximum temperature of 37.8 ± 0.1°C. Infected udder halves had a mean temperature of 35.4 ± 0.1°C, minimum temperature of 30.5 ± 0.3°C, and maximum temperature of 37.7 ± 0.1°C. Our results contradict findings in dairy cows, and suggest more research is needed to evaluate the relationship between udder surface temperature and subclinical mastitis in sheep.

The surface temperatures of flat areas on the Moon

Lunar surface temperature (LST) is a quantity of special interest for interpreting the thermal character of the regolith. It is affected by the solar irradiance, earthshine, and heat flow for the flat areas on the Moon. We present an improved transient temperature model to calculate temperatures of lunar flat surfaces. The model consists of one-dimensional thermal diffusion equation and two boundary conditions. The improved lunar surface boundary condition allows one to precisely determine the effective solar irradiance (ESI) and earthshine. The simulated surface temperatures suggest consistency with the measured temperatures from the thermocouples of Apollo 15 and 17 heat flow experiments. From the LST simulated with the improved model, it is found the annual-seasonal variations present obvious latitude characters, with the highest surface temperature occurring in late October, November, and December separately at high (>∼72°) latitudes, middle latitudes, and low (<∼20°) latitudes, respectively; the lowest surface temperatures occur in late July. Furthermore, the discrepancies between the maximum and minimum temperatures decrease as latitude increases, as do the maximum and minimum lunar surface temperatures. The surface daytime temperature would change by 179.4 K with a 1322.5 W/m2 change in the ESI. A 0.12 W/m2 and 0.02 W/m2 change of the earthshine and heat flow would lead to 0.5 and 0.09 K in surface nighttime temperature, respectively.

Initiation mechanism of arcing generated in RF capacitively coupled plasma

In our previous study, we established an arcing generation and measurement system and we observed prior light emission before arcing current development. However, we briefly analyzed those light emissions with strong assumptions without detailed experiment evaluations and thus, the investigation of the formation mechanism in the initiation phase with detailed experiment evaluations has yet to be conducted. In this work, we investigated the initiation mechanism of arcing generated on an arcing inducing probe (AIP) in a radio frequency capacitively coupled plasma (CCP) environment. Here, the AIP is an aluminum rod covered by anodized film and its tip edge is partially stripped to localize arcing on this edge. We measured emission light, voltage, and current waveforms induced by arcing. The spatiotemporal image of the emission light revealed that the tip glow is the brightest intensity and has longest lifetime during arcing, meaning that it is the primary process in whole arcing process. The current waveform induced by arcing corresponds to the time evolution of the tip glow and estimations revealed that the electron emission is the predominant component of the current formation. Furthermore, snapshot images with AIPs having enlarged stripping area exhibited that arcing occurs at the boundary between the alnuminum and anodized film (dielectric), where charging of ions from the CCP on the film surface can induce high-electric field. In addition, we found that the energy relaxation length of emitted electrons for collisions with Ar atoms, which are the background gas, is much larger than the tip glow diameter, meaning that the electon-Ar collision cannot maintain tip glow. This result supports additional source of atoms to sustain the tip glow such as the surface evaporation from arcing spot, of which evidence was speculated our previous study. We estimated minimum aluminum vapor density and surface temperature, which is sufficiently high enough to induce surface vaporization. Combining those experiment results and estimations, that are electron emission, high surface temperature, and surface evaporation, we can speculate that the initiation mechanism of arcing near dielectric surface in radio-frequency CCP environment is the thermionic emission and surface evaporation from arcing spot.

Multi-objective optimization of transpiration cooling for high pressure turbine vane

Transpiration cooling is a promising cooling measure for high-temperature components in gas turbines. Although the flow and heat transfer characteristics of transpiration cooling have been investigated in several experimental and numerical researches, the design optimization of transpiration cooling is less studied until now. In this paper, a multi-objective optimization framework based on the ANN surrogate model and the NSGA-Ⅱ is built to optimize the transpiration cooling of C3X turbine vane. The transpiration cooled C3X vane consists of multiple porous zones whose porosities could be different and are treated as the design parameters. The optimization objectives are minimum area-averaged vane surface temperature and minimum aerodynamic loss. A total of 960 CFD simulations are conducted to prepare the sample dataset. After the validation of the surrogate-based optimization framework, the Pareto front is obtained as an output. Three representative Pareto-optimal points are chosen from the Pareto front, considering the best cooling performance, the lowest aerodynamic loss, and a balance between them. The porosity distributions and coolant allocations, the cooling performances, and the aerodynamic losses for the three Pareto points are discussed, and the involved flow and heat transfer characteristics are analyzed. The results reveal that to reach a balance between the cooling efficiency and the aerodynamic loss for an optimal transpiration cooled C3X vane, coolant should be appropriately distributed to the leading edge, as well as zones immediately downstream of the leading edge.

A new diagram for performance evaluation of complex models

In the latest years the capacity and complexity of climate and environmental modeling has increased considerably. Therefore, tools and criteria for model performance evaluation are needed to ensure that different users can benefit from model selection. Among graphical tools, Taylor’s diagram is widely used to provide evaluation and comparison of model performances, with particular emphasis on climate models. Taylor’s diagram accounts for different statistical features of model outputs and observations, including correlation, variability and centered root mean square error. Not included is model bias, which is an essential feature for climate model evaluations, and it is usually calculated separately to complement the information embedded in Taylor’s diagram. In this paper a new diagram is proposed, referred to as Aras’ diagram, which allows for visual assessments of the correspondence between model outputs and reference data in terms of total error, correlation, as well as bias and variability ratios through an easy-to-interpret two-dimensional (2D) plot, allowing for proper weighting of different model features. The strengths of the new diagram are exemplified in a case study of performance evaluation of EURO-CORDEX historical experiment over Southern Italy using E-OBS as reference dataset, for three hydrological variables (i.e. daily precipitation, daily surface minimum temperature, and daily maximum surface temperature), and four popular climate indices (i.e. total annual precipitation, annual maxima of daily precipitation, annual minima of daily minimum temperatures, and annual maxima of daily maximum temperatures). The proposed diagram shows interesting properties, in addition to those already included in Taylor’s diagram, which may help promoting climate model evaluations based on their accuracy in reproducing the climatological patterns observed in time and space.

A species distribution model of the giant kelp Macrocystis pyrifera: Worldwide changes and a focus on the Southeast Pacific.

Worldwide climate-driven shifts in the distribution of species is of special concern when it involves habitat-forming species. In the coastal environment, large Laminarian algae-kelps-form key coastal ecosystems that support complex and diverse food webs. Among kelps, Macrocystis pyrifera is the most widely distributed habitat-forming species and provides essential ecosystem services. This study aimed to establish the main drivers of future distributional changes on a global scale and use them to predict future habitat suitability. Using species distribution models (SDM), we examined the changes in global distribution of M. pyrifera under different emission scenarios with a focus on the Southeast Pacific shores. To constrain the drivers of our simulations to the most important factors controlling kelp forest distribution across spatial scales, we explored a suite of environmental variables and validated the predictions derived from the SDMs. Minimum sea surface temperature was the single most important variable explaining the global distribution of suitable habitat for M. pyrifera. Under different climate change scenarios, we always observed a decrease of suitable habitat at low latitudes, while an increase was detected in other regions, mostly at high latitudes. Along the Southeast Pacific, we observed an upper range contraction of -17.08° S of latitude for 2090-2100 under the RCP8.5 scenario, implying a loss of habitat suitability throughout the coast of Peru and poleward to -27.83° S in Chile. Along the area of Northern Chile where a complete habitat loss is predicted by our model, natural stands are under heavy exploitation. The loss of habitat suitability will take place worldwide: Significant impacts on marine biodiversity and ecosystem functioning are likely. Furthermore, changes in habitat suitability are a harbinger of massive impacts in the socio-ecological systems of the Southeast Pacific.

Monitoring the Expansion of Unplanned Urbanization and its Impact on Climate Change based on Google Earth Engine Service, a Case Study of Baghdad / Iraq

The earth's surface comprises different kinds of land cover, water resources, and soil, which create environmental factors for varied animals, plants, and humans. Knowing the significant effects of land cover is crucial for long-term development, climate change modeling, and preserving ecosystems. In this research, the Google Earth Engine platform and freely available Landsat imagery were used to investigate the impact of the expansion and degradation in urbanized areas, watersheds, and vegetative cover on the land surface temperature in Baghdad from 2004 to 2021. Land cover indices such as the Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index (NDVI, NDWI, and NDBI) were determined to examine the effects of land cover changes. In addition, the land surface temperature was calculated to assess urbanization expansion's impact on Baghdad's climate warming. The results showed a drastic decrease in vegetative cover and green land, on the other hand, a significant expansion in urbanized areas. Hence, from 2004 to 2021, the urbanized areas and open land rose by 37% and 3%, respectively, while the vegetative cover decreased by 41%. The maximum land surface temperature has risen 4° C, and the minimum land surface temperature has risen 2.5°C.

The Effect of Blended Palm Oil Biodiesel Droplet Properties on Evaporation Characteristics

The evaporation characteristics of a single fuel droplet of diesel fuel (DF) and the Malaysian palm oil biodiesel-diesel blend (B10-B50) were studied experimentally. The fuel droplet properties consisted of different ratios of palm oil biodiesel mixtures which could influence the droplet behaviour when impinged on the heated surface. By employing the hot surface deposition test (HSDT) method, the droplets impinging on the heated surface of an aluminum alloy plate were observed to evaluate the droplet's evaporation characteristics including the evaporation lifetime and maximum evaporation point (MEP) of the tested fuels. Furthermore, the deposit’s surface temperature for dry condition (timp=7 seconds) and wet condition (timp=3 seconds) test were also measured during the deposition test. Finally, the deposit development on the heated surface was evaluated through a logarithmic expression of MR/mD = αNDβ. The results showed that the evaporation lifetime of each test fuel decreased with increasing hot plate surface temperature. Furthermore, the MEP was the highest for B30 (380°C), followed by B20 and B40 (375°C), B10 and B50 (365°C), and DF (360°C). In the dry condition test, the recorded average minimum and maximum deposit surface temperatures were observed to be within the range of Td=295°C to Td=325°C for DF and Td=290°C to Td=350°C for B10-B50 fuels. On the other hand, for the wet condition test, the recorded average minimum deposit surface temperatures for both DF and B10-B50 fuels were consistently lower than the hot plate temperature. DF exhibited the most variation, ranging from Td=200°C to Td=300°C, whereas, for B10-B50, the recorded deposit surface temperature was only ranging from Td=150°C to Td=200°C.

Trend and Variations of Surface Air Temperatures across Selected Eco-Climatic Zones in Nigeria

The trends and variability in surface air temperatures over selected eco-climatic zones in Nigeria were assessed using Merra-2 datasets from 1981 to 2018. A total of 15 stations spread across the eco-climatic zones in Nigeria were used for this study. The Mann-Kendall, linear trend and Sen’s slope trend test, time series plots and descriptive statistics were used. The coefficients of variability of surface air maximum temperature showed low variability for the Mangrove-swamp rainforest and moderate variability for the Guinea-wooded, Sudan and Sahel savannas. Similarly, the coefficients of variability of surface air minimum temperature showed moderate variability for all the selected eco-climatic zones. The M-K trend test showed that 14 stations had upward trends and 1 downward trend, with 13 stations having statistically significant trend in air surface maximum temperature. All the stations had statistically significant upward trends in air surface minimum temperature. The average increase in maximum and minimum air surface temperatures is estimated to be about 0.035°C and 0.036°C per year, respectively. For Nigeria, the average air surface temperature is estimated to increase by about 0.036°C per year, and the average air surface temperature is estimated to have increased by about 1.4°C over the 38 years. This study then gives a linear trend projection of about 4.3°C increase in estimated mean air surface temperature by year 2100 in Nigeria.

Assessment of Temporal Trend in Surface Air Temperatures across Some Selected Eco-Climatic Zones in Nigeria

Temporal trends in surface air temperatures across some selected eco-climatic zones in Nigeria from 1981 to 2018 were assessed using the Merra-2 reanalysis dataset. A total of 15 stations spread across the eco-climatic zones in Nigeria were used for this study. The Mann-Kendall (M-K) trend test was used to detect direction, significance, coefficients of time trends, while the linear regression and the Sen’s slope trend tests were used to estimate the trend magnitudes. The M-K trend test showed that the surface air maximum temperature of 14 stations had monotonic increasing trends, of which 13 stations were statistically significant at the 0.01 significance level, and 1 station was statistically significant at the 0.05 significance level. However, the M-K trend test also showed that surface air minimum temperature for all the 15 stations (representing 100%), showed monotonic upward trends, statistically significant at the 0.01 significance level. The Sen's slope and linear trend tests showed higher trend magnitudes at most stations, particularly stations in the Guinea-wooded, Sudan and Sahel savannas. The estimated mean trend magnitudes of maximum and minimum air surface temperatures increased by approximately 0.035°C/year and 0.036°C/year, respectively. The estimated mean air surface temperature increased by approximately 0.036°C/year and approximately 1.4°C for Nigeria over the 38-year period. The study then presents a linear trend projection of mean air surface temperature increase in Nigeria of approximately 4.3°C by 2100. This is 0.2°C below maximum levels and within the range of approximately 1.5 to 4.5°C that global air surface temperature is projected to rise by 2100 in the Intergovernmental Panel on Climate Change (IPCC) 2007 report. The M-K and linear trend tests were fully consistent with the standardized time series anomaly plots. Mean annual values of the air surface temperatures showed latitudinal dependence. The manifestation of significant long-term trends at high confidence levels in the air surface temperatures over the period, provides a clear evidence that the climate of Nigeria is witnessing a possible human-induced radiative forcing and a strong tendency for the occurrences of climate-related extreme events and their resulting adverse implications.

Unstable spray pattern and cooling performance of cryogen spray coupled with cold air jet: An experimental study

This study focuses on the interactions between cryogen spray cooling (CSC) and cold air jet (CAJ), as well as the heat transfer performance upon CAJ-CSC impingement assisted for laser dermatology. CAJ is found to collapse downstream spray on the windward side, enhancing fluctuations of R1234yf spray width. Standard deviation (SD) distribution identifies that fluctuations at nozzle exit are attributed to ambient-to-spray interactions, which is also confirmed by the proper orthogonal decomposition (POD) analysis. The third POD mode highlights jet-to-spray interactions on the windward side of spray, yielding an enhanced instability by 1.72 times when CAJ flow rate (Q) increases from 4 to 8 m3/h. The closer location to the spray center on the same radial side corresponds to a faster thermal response and a lower temperature drop (ΔT). ΔT on the windward side decreases due to the considerable CAJ-induced droplet swarm drift. The heat transfer degrades on the leeward side due to the thermal gas boundary layer originating from the inclined CAJ sweep. Nevertheless, the CAJ with a small flow rate (4 m3/h) enhances the heat transfer at spray center, yielding a minimum surface temperature of −32.3 °C. Comparative investigation indicates R134a has superior cooling performance but more significant instabilities inside spray plume. R1234yf serves a relatively stable sub-cooling region within a radial distance of ±1 mm from spray center characterized by low spray fluctuations and high temperature drops at Q = 4 m3/h. Substitution of R1234yf for R134a still needs heat transfer enhancement for clinical considerations.

Modeling Slope Microclimates in the Mars Planetary Climate Model

AbstractA large number of surface features (e.g., frost, gullies, slope streaks, recurring slope lineae) are observed on Martian slopes. Their activity is often associated with the specific microclimates on these slopes, which have been mostly studied with one‐dimensional radiative balance models to date. We develop here a parameterization to simulate these microclimates in 3D Global Climate Models. We first demonstrate that any Martian slope can be thermally represented by a poleward or equatorward slope, that is, the daily average, minimum, and maximum surface temperatures depend on the North‐South component of the slope. Based on this observation, we implement here a subgrid‐scale parameterization to represent slope microclimates (radiative fluxes, volatile condensation, ignoring slope winds for now) in the Mars Planetary Climate Model and validate it through comparisons with surface temperature measurements and frost detections on sloped terrains. With this new model, we show that slope microclimates do not have a significant impact on the seasonal CO2 and H2O cycles on a global scale. Furthermore, short‐scale slopes (i.e., less than ∼1 km in length) do not significantly impact the thermal state of the atmosphere. Ninety‐one percent of the active gullies are found where our model predicts CO2 frost, suggesting that their activity is related to processes involving CO2 ice. However, the low thicknesses (≤tens of cm) predicted at mid‐latitudes rule out mechanisms involving large amounts (∼meters) of ice. This model opens the way to new studies on surface‐atmosphere interactions in present and past climates.

How Do Extreme Lake Water Temperatures in Poland Respond to Climate Change?

Lakes are vital components of the Earth’s hydrological cycle and are susceptible to the impacts of climate change. Understanding the changes in terms of minimum and maximum lake surface temperatures is crucial for assessing the effects of climate change on freshwater ecosystems. This study focuses on ten lakes in Poland to investigate the impacts of climate change on lake temperatures in different geographical regions. The Mann–Kendall (MK) and Sen tests were employed to analyze trends and changes in minimum and maximum water temperatures, respectively. The results reveal significant increases in the minimum and maximum temperatures, particularly in May and June. Different lakes exhibit varying trends and variability in temperature changes over time, indicating the vulnerability of these ecosystems. The current study also examines the magnitude of annual temperature changes and classifies them into different levels. This analysis highlights the complex relationship between air temperature, seasonal cycles, and lake morphometric characteristics in shaping variations in lake surface water temperature. These findings contribute to understanding the impacts of climate change on Poland’s lakes and provide valuable insights for developing conservation strategies and adaptive measures to protect freshwater resources.

Influences of teleconnections on climate variables in northern and northeastern Thailand

Abstract Teleconnection events can influence normal regional weather patterns and affect weather forecast accuracy. To improve the forecast ability, the relationship between main teleconnections such as El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Madden–Julian Oscillation (MJO), and climate variables (rainfall, maximum and minimum surface temperature, vertical mixing ratio, and vertical maximum temperature) was established using lag correlation coefficient and t-test methods. The results reveal moderately significant correlations between El Niño, positive IOD and rainfall, and vertical mixing ratio, which can be associated with lower-than-usual rainfall. The coincidence between El Niño and positive IOD events can worsen drought. Even though the MJO and regional weather correlations were significant, the magnitude of correlation coefficients was negligible. In addition, the spatiotemporal distribution of ENSO shows that the strong El Niño has more influence on rainfall anomalies in the post-1980s. Since there are insufficient studies on the association between teleconnections and climate variables, especially vertical mixing ratio, our findings can benefit prediction development for teleconnection-induced regional climate anomalies for extreme events and water management preparations in northern and northeastern Thailand.

Quantifying the influence of climate, host and change in land-use patterns on occurrence of Crimean Congo Hemorrhagic Fever (CCHF) and development of spatial risk map for India

Crimean Congo Hemorrhagic Fever (CCHF), is an emerging zoonosis globally and in India. The present study focused on identifying the risk factors for occurrence of CCHF in the Indian state of Gujarat and development of risk map for India. The past CCHF outbreaks in India were collated for the analyses. Influence of land use change and climatic factors in determining the occurrence of CCHF in Gujarat was assessed using Bayesian spatial models. Change in maximum temperature in affected districts was analysed to identify the significant change points over 110 years. Risk map was developed for Gujarat using Bayesian Additive Regression Trees (BART) model with remotely sensed environmental variables and host (livestock and human) factors. We found the change in land use patterns and maximum temperature in affected districts to be contributing to the occurrence of CCHF in Gujarat. Spatial risk map developed using CCHF occurrence data for Gujarat identified density of buffalo, minimum land surface temperature and elevation as risk determinants. Further, spatial risk map for the occurrence of CCHF in India was developed using selected variables. Overall, we found that combination of factors such as change in land-use patterns, maximum temperature, buffalo density, day time minimum land surface temperature and elevation led to the emergence and further spread of the disease in India. Mitigation measures for CCHF in India could be designed considering disease epidemiology and initiation of surveillance strategies based on the risk map developed in this study.

Suitable habitat of Lepidochelys olivacea and the changes under climate change.

As a vulnerable species identified by the International Union for Conservation of Nature (IUCN), Lepidochelys olivacea has attracted extensive attention in recent years. To examine its current distribution and that under future climate change scenarios, we compiled the occurrence data of L. olivacea. With eight predictor variables, including depth, offshore distance, mean primary productivity, minimum primary productivity, mean sea surface temperature, minimum sea surface temperature, mean sea surface salinity, and minimum sea surface salinity, we predicted its distribution in an ensemble species distribution model. The accuracy of the model was evaluated with the parameters of areas under curves (AUC) and true skill statistics (TSS). The results showed that the AUC and TSS values were 0.96 and 0.81, respectively, indicating a good predictive performance of the ensemble model. Sea surface temperature and salinity were the two most important variables determining the distribution of L. olivacea, with the suitable temperature ranging from 23 to 29 ℃ and salinity below 34. The current distribution range of L. olivacea was between 30° N-25° S. Under future climate scenarios, its distribution range would decrease, especially under the RCP85 scenario in the 2100s (with a 28% reduction in the suitable survival range). The results of model validation showed that it had high accuracy and could make accurate predictions of the distribution. This study would provide references for the development of more rational conservation measures and management strategies.

TIMBER v0.1: a conceptual framework for emulating temperature responses to tree cover change

Abstract. Land cover changes have been proposed to play a significant role, alongside emission reductions, in achieving the temperature goals agreed upon under the Paris Agreement. Such changes carry both global implications, pertaining to the biogeochemical effects of land cover change and thus the global carbon budget, and regional or local implications, pertaining to the biogeophysical effects arising within the immediate area of land cover change. Biogeophysical effects of land cover change are of high relevance to national policy and decision makers, and accounting for them is essential for effective deployment of land cover practices that optimise between global and regional impacts. To this end, Earth system model (ESM) outputs that isolate the biogeophysical responses of climate to land cover changes are key in informing impact assessments and supporting scenario development exercises. However, generating multiple such ESM outputs in a manner that allows comprehensive exploration of all plausible land cover scenarios is computationally untenable. This study proposes a framework to explore in an agile manner the local biogeophysical responses of climate under customised tree cover change scenarios by means of a computationally inexpensive emulator, the Tree cover change clIMate Biophysical responses EmulatoR (TIMBER) v0.1. The emulator is novel in that it solely represents the biogeophysical responses of climate to tree cover changes, and it can be used as either a standalone device or as a supplement to existing climate model emulators that represent the climate responses from greenhouse gas (GHG) or global mean temperature (GMT) forcings. We start off by modelling local minimum, mean, and maximum surface temperature responses to tree cover changes by means of a month- and Earth system model (ESM)-specific generalised additive model (GAM) trained over the whole globe; 2 m air temperature responses are then diagnosed from the modelled minimum and maximum surface temperature responses using observationally derived relationships. Such a two-step procedure accounts for the different physical representations of surface temperature responses to tree cover changes under different ESMs whilst respecting a definition of 2 m air temperature that is more consistent across ESMs and with observational datasets. In exploring new tree cover change scenarios, we employ a parametric bootstrap sampling method to generate multiple possible temperature responses, such that the parametric uncertainty within the GAM is also quantified. The output of the final emulator is demonstrated for the Shared Socioeconomic Pathway (SSP) 1-2.6 and 3-7.0 scenarios. Relevant temperature responses are identified as those displaying a clear signal in relation to their surrounding parametric uncertainty, calculated as the signal-to-noise ratio between the sample set mean and sample set variability. The emulator framework developed in this study thus provides a first step towards bridging the information gap surrounding biogeophysical implications of land cover changes, allowing for smarter land use decision making.