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This paper proposes a method that allows the detection of trends in the frequency of extreme events and its attribution to changes in atmospheric dynamics characterized through Circulation Types (CTs). The method is applied to summer Extremely Hot Days (EHD) in Spain during the period 1958-2008. For carrying out this exercise, regional series of daily maximum temperature are derived from the regional dataset Spain02. Eight regions with different daily maximum temperature variability are identified. All of them exhibit important trends in the occurrence of EHDs, especially in inner regions. Links between the probability of EHD occurrence in the regions and CTs have been cal10 culated. Furthermore, the consistency of the results to the atmospheric variables used in defining the CTs is analyzed. Sea Level Pressure (SLP), Temperature at 850 hPa Level (T850) and Geopotential Height at 500 hPa Level (Z500) from the ERA40 dataset have been used for the six CT classifications obtained using the variables separately and in different combinations of pairs. The optimum choice of large scale variables depends on the region under consideration, being the combination SLP-T850 the one giving the most suitable characterization for most of them. Finally, an attribution exercise of the regional EHD trends to the dynamics is proposed. Results show that the maximum of attributable EHD trends to changes in dynamics in every region is always below 50%, being even lower than 20% in those regions with the largest EHD trends, mainly located in the center of the Iberian Peninsula (IP). [ABSTRACT FROM AUTHOR]

The paper purpose was to assess the impact of climate change on wheat, maize and sunflower yield in the period 2017-2021, using statistical data from National Institute of Statistics (NIS) and National Administration of Meteorology (NAM) and other sources. Comparison method was used to evaluate the deviations between the registered air temperatures and precipitations and the 1981-2010 climatological norm. Graphic method reflected the dynamics of monthly air temperatures and rainfalls in each year. Descriptive statistics for mean, standard deviation and coefficient of variation reflected an more comprehensive image upon air temperature, precipitations and yield. Correlations and regression equations were used to establish the intensity of the kinks between climate factors and yield. The highest average air temperature In Romania was 12.130C in 2019. In the period 2017-2020, the average annual temperatures exceeded the climatological norm 1981-2010 accounting for 9.10C. The lowest rainfalls, 614.2 mm, were recorded in 2019, being below of 633.1 mm the norm for the period 1981-2010. The high temperatures associated with drought and low precipitations have deeply affected yield of many agricultural crops, including maize, wheat and sunflower. The highest wheat yield 4,888 kg/ha was achieved in 2017, and the lowest one, 2,966 kg/ha in 2020. Maize registered the highest performance of 7,644 kg/ha in 2018, and the lowest one, 3,977 kg/ha in 2020. Sunflower carried out the high performance 3,041 kg/ha in 2018, and the lowest one, 1,858 kg/ha in 2020. The worst agricultural years for these three crops was 2020, but 2017 favored wheat, while 2018 favored maize and sunflower. The correlation coefficient had in general small values between average temperature and yield, but a higher link with precipitations level. The multiple correlation between yield, air temperatures and precipitations was: r= 0.817 for wheat, r = 0.116 for maize and r = 0.504 for sunflower. In the South Eastern Dobrogea, the driest area in Romania, the rainfalls declined by 65% in the period 2018-2020 having a deep negative impact on sunflower seeds yield, which decreased from 4,282 kg/ha in 2018, to 1,503 kg/ha in 2020. The correlation between precipitations and sunflower yield positive and very strong (r = 0.737). As a conclusion, the climate conditions should be analyzed in each farm and farmers have to take measure to adapt the technologies for sustaining production. [ABSTRACT FROM AUTHOR]

Locust swarms had periodically raged in both North American Plains (NAP) and East Asian Plains (EAP) before 1880 AD. After this period, the locust outbreaks almost never recurred in NAP but have continued to occur in EAP. Since large quantities of pesticides were used in the major agriculture regions of NAP in the late 1870s; this has been suggested as a possible major cause of the disappearing of locust outbreaks. Extensive applications of more effective chemical pesticides were also used in the granary regions of EAP in the 1950s in an effort to kill the pests at a much higher intensity. However, locust swarms came back again in many areas of China in the 1960s. Therefore, NAP locust extinction still remains a puzzle. Frequent locust outbreaks in EAP over the past 130 yr may offer clues to probe key control elements in the disappearing of locust outbreaks in NAP. This paper analyzes the climate extremes and monthly temperature-precipitation combines of NAP and EAP, and found the differences in their frequencies of these climate combines caused different locust fates in the two regions: restrained the locust outbreak in NAP but induced such events in EAP. Validation shows that severer EAP locust outbreak years were coincided with the climate extreme combines years. Thus we suggest that climate changes in frequency, extremes and trends can explain why the fate of the locust plague in EAP was different from that in NAP. The study also points out that, under the present global warming, cautions should be taken to make sure the pest hazard being nipped in the-bud. [ABSTRACT FROM AUTHOR]

Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment. [ABSTRACT FROM AUTHOR]

The flux of carbon dioxide from the soil to the atmosphere (soil respiration) is one of the major fluxes in the global carbon cycle. At present, the accumulated field observation data cover a wide range of geographical locations and climate conditions. However, there are still large uncertainties in the magnitude and spatiotemporal variation of global soil respiration. Using a global soil respiration dataset, we developed a climate-driven model of soil respiration by modifying and updating Raich's model, and the global spatiotemporal distribution of soil respiration was examined using this model. The model was applied at a spatial resolution of 0.5° and a monthly time step. Soil respiration was divided into the heterotrophic and autotrophic components of respiration using an empirical model. The estimated mean annual global soil respiration was 91 Pg C yr-1 (between 1965 and 2012; Monte Carlo 95% confidence interval: 87-95 Pg C yr-1) and increased at the rate of 0.09 Pg C yr-2. The contribution of soil respiration from boreal regions to the total increase in global soil respiration was on the same order of magnitude as that of tropical and temperate regions, despite a lower absolute magnitude of soil respiration in boreal regions. The estimated annual global heterotrophic respiration and global autotrophic respiration were 51 and 40 Pg C yr-1, respectively. The global soil respiration responded to the increase in air temperature at the rate of 3.3 Pg C yr-1 °C-1, and Q10 = 1.4. Our study scaled up observed soil respiration values from field measurements to estimate global soil respiration and provide a data-oriented estimate of global soil respiration. Our results, including the modeled spatiotemporal distribution of global soil respiration, are based on a semi-empirical model parameterized with over one thousand data points. We expect that these spatiotemporal estimates will provide a benchmark for future studies and also help to constrain process-oriented models. [ABSTRACT FROM AUTHOR]

Peatlands in discontinuous permafrost regions occur as a mosaic of wetland types, each with variable sensitivity to climate change. Permafrost thaw further increases the spatial heterogeneity in ecosystem structure and function in peatlands. Carbon (C) fluxes are well characterized in end-member thaw stages such as fully intact or fully thawed permafrost but remain unconstrained for transitional stages that cover a significant area of thawing peatlands. Furthermore, changes in the environmental correlates of C fluxes, due to thaw are not well described: a requirement for modeling future changes to C storage of permafrost peatlands. We investigated C fluxes and their correlates in end-member and a number of transitional thaw stages in a sub-arctic peatland. Across peatland lumped CH4 and CO2 flux data had significant correlations with expected correlates such as water table depth, thaw depth, temperature, photosynthetically active radiation and vascular green area. Within individual thaw states, bivariate correlations as well as multiple regressions between C flux and environmental factors changed variably with increasing thaw. The variability in directions and magnitudes of correlates reflects the range of structural conditions that could be present along a thaw gradient. These structural changes correspond to changes in C flux controls, such as temperature and moisture, and their interactions. Temperature sensitivity of CH4 increased with increasing thaw in bivariate analyses, but lack of this trend in multiple regression analyses suggested cofounding effects of substrate or water limitation on the apparent temperature sensitivity. Our results emphasize the importance of incorporating transitional stages of thaw in landscape level C budgets and highlight that end-member or adjacent thaw stages do not adequately describe the variability in structure-function relationships present along a thaw gradient. [ABSTRACT FROM AUTHOR]

In order to detect shifts in community structure and function associated with global change, the natural background fluctuation in these traits must be known. In a 6-yr study we quantified year to year variability of taxonomic and functional composition of benthic hard bottom communities in the Western Baltic. While taxonomic fluctuations were substantial, functionality of the communities seems preserved in most cases. Environmental conditions potentially driving these fluctuations are winter temperatures and current regimes. We tentatively define a confidence range of natural variability in productivity, composition and diversity a departure from which might help identifying an ongoing regime shift driven by global change. In addition, we propose a statistical procedure distinguishing directional shifts ("signal") from natural fluctuations ("noise"). [ABSTRACT FROM AUTHOR]

The article presents a study on the comparison of four Earth system models to climate engineering. The study compared the two couteracting forcings I G1 of the GeoMIP to the preindustrial climate. The result of the study shows that the reduction in evaporation compensated the reduction of the meridional temperature gradient in all models compared to the control simulation.

This paper compares the ideas contained in the main papers published on climate change since World War II to arrive at a suggested consensus of our present knowledge regarding climatic changes and their causes. Atmospheric carbon dioxide is only suggested as a cause in one theory, which, despite its wide acceptance by Politicians, the media, and the Public, ignores the findings in other studies, including the ideas found in the Milankovitch Cycles. It also does not explain the well-known NASA map of the changes between the global 1951–1978 and the 2010–2019 mean annual temperatures. The other theories by Oceanographers, Earth scientists, and Geographers fit together to indicate that the variations in climate are the result of differential solar heating of the Earth, resulting in a series of processes redistributing the heat to produce a more uniform range of climates around the surface of the Earth. Key factors are the shape of the Earth and the Milankovitch Cycles, the distribution of land and water bodies, the differences between heating land and water, ocean currents and gateways, air masses, and hurricanes. Low atmospheric carbon dioxide levels during cold events could result in too little of this gas to support photosynthesis in plants, resulting in the extermination of most life on Earth as we know it. The 23 ka Milankovitch cycle has begun to reduce the winter insolation received at the surface of the atmosphere in the mid-latitudes of the Northern Hemisphere starting in 2020. This results in extreme weather as the winter insolation reaching the surface of the atmosphere in the higher latitudes of the Northern Hemisphere decreases while the summer air temperatures increase. It heralds the start of the next glaciation. A brief outline is given of some of the climatic changes and consequences that may be expected in western Canada during the next 11.5 ka. [ABSTRACT FROM AUTHOR]

Information on the relationship between cumulative fossil carbon emissions and multiple climate targets are essential to design emission mitigation and climate adaptation strategies. In this study, the transient responses in different climate variables are quantified for a large set of multi-forcing scenarios extended to year 2300 towards stabilization and in idealized experiments using the Bern3D-LPJ carbon-climate model. The model outcomes are constrained by 26 physical and biogeochemical observational data sets in a Bayesian, Monte-Carlo type framework. Cumulative fossil emissions of 1000 GtC result in a global mean surface air temperature change of 1.88 °C (68% confidence interval (c.i.): 1.28 to 2.69 °C), a decrease in surface ocean pH of 0.19 (0.18 to 0.22), and in steric sea level rise of 20 cm (13 to 27 cm until 2300). Linearity between cumulative emissions and transient response is high for pH and reasonably high for surface air and sea surface temperatures, but less pronounced for changes in Atlantic Meridional Overturning, Southern Ocean and tropical surface water saturation with respect to biogenic structures of calcium carbonate, and carbon stocks in soils. The slopes of the relationships change when CO2 is stabilized. The Transient Climate Response is constrained, primarily by long-term ocean heat observations, to 1.7 _C (68% c.i.: 1.3 to 2.2 °C) and the Equilibrium Climate Sensitivity to 2.9 °C (2.0 to 4.2 °C). This is consistent with results by CMIP5 models, but inconsistent with recent studies that relied on short-term air temperature data affected by natural climate variability. [ABSTRACT FROM AUTHOR]

A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen-Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8% for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity. [ABSTRACT FROM AUTHOR]

Average monthly air temperatures in Bosnia and Herzegovina (BiH) exhibit a notable rise during summer, ranging from 0.4 to 0.8 °C per decade, while precipitation experiences a significant decrease of up to 8 mm per decade. Climate models, across various RCP scenarios, project an increase in air temperature, that is most pronounced in the summer season. Additionally, there is a projected frequency and intensity of heavy precipitation during autumn. In BiH, agricultural production faces substantial risks, including droughts, spring and autumn frosts, hail, and floods. Recent years have witnessed extreme hydrological events, notably the 2012 drought and the 2014 floods. Strategic documents highlight the critical importance of addressing floods and droughts for agriculture, as well as their implications for the environment, households, and industry. To assess the severity of extreme hydrological events and their impact on agriculture, with a specific emphasis on autumn and summer in Bosnia and Herzegovina, average and peak values of the Standardized precipitation evapotranspiration index (SPEI) were calculated separately for the periods 1961-1990 and 1991-2020, focusing on October and August. Compared to the reference climatic period the current climate is characterized by shifts between intense wet and dry periods, with very few years exhibiting stable and expected weather conditions. Identified as extremely wet and flood-prone years, SPEI2 October values for 1974 (2.42), 1996 (2.13), 2001 (2.24), and 2014 (2.05) stand out, with only one extremely dry year in 1985 (-2.21). SPEI2 August indicates extremely dry years, notably 2012 (-2.35) and 2017 (-2.25). [ABSTRACT FROM AUTHOR]

Global climate change has affected vegetation cover in alpine areas. In this paper, we analyzed the correlation between Leaf Area Index (LAI) and climate factors of the Yarlung Tsangpo River basin, and identified their contributions using the quantitative analysis method. The results show that the vegetation cover in the study area generally exhibited an increasing trend. Grassland in the middle- and high-altitude areas was the main contributing area. Temperature is the dominant climatic factor affecting the change, the effect of which increases with the rise in elevation. The influences of precipitation and radiation had obvious seasonality and regionality. The vegetation illustrated a lag response to climate drivers. With the change in the elevation band, the response time to precipitation was significantly less than that to air temperature in the low-elevation area, while the opposite trend was observed in the high-elevation area. In the future, the LAI of the watershed will show different characteristics at different time points, with the increases in the LAI in autumn and winter becoming the main factors for the future increase in the LAI. This provides a crucial basis upon which to explore hydrological and ecological processes as important components of the Third Pole region. [ABSTRACT FROM AUTHOR]

To study the effects of the physical environment on carbon and nutrients cycles dynamics in the north eastern shelf of the Gulf of Cáadiz, changes in currents, tides, salinity, temperature, carbon system parameters (fugacity of CO2 (fCO2), dissolved organic carbon, dissolved inorganic carbon and pH) and others related (dissolved oxygen, total dissolved nitrogen, nutrients and suspended particulate matter) were measured in transects across the Guadalquivir Estuary and Bay of Cáadiz mouths. Thus, the main objective of this study is to investigate the influence of these inner ecosystems on the carbon and nutrient distributions in the adjacent continental shelf. Three cruises have been undertaken in June 2006, November 2006 and February 2007, each one covering one complete tidal cycle during June, both systems were exporting components to the adjacent continental shelf of the Gulf of Cáadiz. In an annual scale, Guadalquivir Estuary exported components while Bay of Cáadiz imported them. Diurnal variability of fCO2 could have a potentially important implication on the estimate of air-sea CO2 fluxes. Monthly studies should be undertaken to completely understand this dynamic system. [ABSTRACT FROM AUTHOR]

Carbon use efficiency (CUE) is a functional parameter that could possibly link the current increasingly accurate global estimates of gross primary production with those of net ecosystem exchange, for which global predictors are still unavailable. Nevertheless, CUE estimates are actually available for only a few ecosystem types, while information regarding agro-ecosystems is scarce, in spite of the simplified spatial structure of these ecosystems that facilitates studies on allocation patterns and temporal growth dynamics. We combined three largely deployed methods, eddy covariance, soil respiration and biometric measurements, to assess monthly values of CUE, net primary production (NPP) and allocation patterns in different plant organs in an apple orchard during a complete year (2010). We applied a measurement protocol optimized for quantifying monthly values of carbon fluxes in this ecosystem type, which allows for a cross-check between estimates obtained from different methods. We also attributed NPP components to standing biomass increments, detritus cycle feeding and lateral exports. We found that in the apple orchard both net ecosystem production and gross primary production on yearly basis, 380±30gCm-2 and 1263±189gCm-2 respectively, were of a magnitude comparable to those of natural forests growing in similar climate conditions. The largest differences with respect to forests are in the allocation pattern and in the fate of produced biomass. The carbon sequestered from the atmosphere was largely allocated to production of fruits: 49% of annual NPP was taken away from the ecosystem through apple production. Organic material (leaves, fine root litter, pruned wood and early fruit falls) contributing to the detritus cycle was 46% of the NPP. Only 5% was attributable to standing biomass increment, while this NPP component is generally the largest in forests. The CUE, with an annual average of 0.71±0.09, was higher than the previously suggested constant values of 0.47-0.50. Low nitrogen investment in fruits, the limited root-apparatus, and the optimal growth temperature and nutritional condition observed at the site are suggested to be explanatory variables for the high CUE observed. [ABSTRACT FROM AUTHOR]

This paper evaluates the relative contribution of light and temperature on net ecosystem CO2 uptake during the 2006 growing season in a polygonal tundra ecosystem in the Lena River Delta in Northern Siberia (72º220 N, 126º300 E). We demonstrate that the timing of warm periods may be an important determinant of the magnitude of the ecosystem's carbon sink function, as they drive temperature-induced changes in respiration. Hot spells during the early portion of the growing season are shown to be more influential in creating mid-day surface-to-atmosphere net ecosystem CO2 exchange fluxes than those occurring later in the season. In this work we also develop and present a bulk flux partition model to better account for tundra plant physiology and the specific light conditions of the arctic region that preclude the successful use of traditional partition methods that derive a respiration-temperature relationship from all night-time data. Night-time, growing season measurements are rare during the arctic summer, however, so the new method allows for temporal variation in the parameters describing both ecosystem respiration and gross uptake by fitting both processes at the same time. Much of the apparent temperature sensitivity of respiration seen in the traditional partition method is revealed in the new method to reflect seasonal changes in basal respiration rates. Understanding and quantifying the flux partition is an essential precursor to describing links between assimilation and respiration at different time scales, as it allows a more confident evaluation of measured net exchange over a broader range of environmental conditions. The growing season CO2 sink estimated by this study is similar to those reported previously for this site, and is substantial enough to withstand the long, low-level respiratory CO2 release during the rest of the year to maintain the site's CO2 sink function on an annual basis. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) vegetation plays an important role in the local ecosystem, which responds significantly to climate change and can affect local and large-scale weather and climate anomalies. However, little attention has been paid to its year-to-year variation. In this paper, using two NDVI datasets (GIMMS and MODIS) originated from satellite remote sensing, the variability characteristics of NDVI over the TP on the interannual time scale and associated local climatic factors were investigated. The results show that two primary patterns of NDVI governed TP during the main growing season (June–September, JJAS) for the period 1982–2020. The first one is a uniform pattern, with a consistent spatial variation over the entire TP, and the second is a dipole pattern, with an out-of-phase spatial variation of NDVI between the northern and southern TP. Interannual variations of the different climatic factors regulate the NDVI variability over the different regions of the TP. The interannual variability of the uniform NDVI pattern is mainly affected by the two local climatic factors, the preceding May–August precipitation and simultaneous JJAS sunshine duration. Specifically, NDVIs over the southern and eastern TP have a more significant response to the preceding precipitation and simultaneous sunshine duration, respectively. The variability of the dipole NDVI pattern is primarily modulated by the preceding May–August precipitation and simultaneous surface air temperature, ground surface temperature, and sunshine duration. However, NDVIs over the northern and southern TP have different degrees of response to the four climatic factors, with the most significant response being to preceding precipitation. The combined effect of these factors contributes to the formation of the interannual variability in the uniform and dipole patterns. This paper may shed light on deeply understanding the reasons for the inconsistency in variations of vegetation over the different regions of the TP under climate change. In addition to the effect of local climatic factors that this study focuses on, the influence of external climatic factors on the variability of the TP NDVI deserves further research in the future. [ABSTRACT FROM AUTHOR]

The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables. [ABSTRACT FROM AUTHOR]

JULES-crop is a parametrisation of crops in the Joint UK Land Environment Simulator (JULES). We investigate the sources of the interannual variability in the modelled maize yield, using global runs driven by reanalysis data, with a view to understanding the impact of various approximations in the driving data and initialisation. The standard forcing dataset for JULES consists of a combination of meteorological variables describing precipitation, radiation, temperature, pressure, specific humidity and wind, at subdaily time resolution. We find that the main characteristics of the modelled yield can be reproduced with a subset of these variables and using daily forcing, with inter nal disaggregation to the model timestep. This has implications in particular for the use of the model with seasonal forcing data, which may not have been provided at subdaily resolution for all required driving variables. We also investigate the effect on annual yield of initialising the model with climatology on the sowing date. This approximation has the potential to considerably simplify the use of the model with seasonal forecasts, since obtaining observations or reanalysis output for all the initialisation variables required by JULES for the start date of the seasonal forecast would present significant practical challenges. [ABSTRACT FROM AUTHOR]

Peatlands are a major terrestrial carbon store and a persistent natural carbon sink during the Holocene, but there is considerable uncertainty over the fate of peatland carbon in a changing climate. It is generally assumed that higher temperatures will increase peat decay, causing a positive feedback to climate warming and contributing to the global positive carbon cycle feedback. Here we use a new extensive database of peat profiles across northern high latitudes to examine spatial and temporal patterns of carbon accumulation over the past millennium. Opposite to expectations, our results indicate a small negative carbon cycle feedback from past changes in the long-term accumulation rates of northern peatlands. Total carbon accumulated over the last 1000 yr is linearly related to contemporary growing season length and photosynthetically active radiation, suggesting that variability in net primary productivity is more important than decomposition in determining long-term carbon accumulation. Furthermore, northern peatland carbon sequestration rate declines over the climate transition from the Medieval Climate Anomaly (MCA) to the Little Ice Age (LIA), probably because of lower LIA temperatures combined with increased cloudiness suppressing net primary productivity. Other factors including changing moisture status, peatland distribution, fire, nitrogen deposition, permafrost thaw and methane emissions will also influence future peatland carbon cycle feedbacks, but our data suggest that the carbon sequestration rate could increase over many areas of northern peatlands. [ABSTRACT FROM AUTHOR]

Impairment of the photosynthetic machinery of the algal endosymbiont ("zooxanthellae") is the proximal trigger for the thermal breakdown of the coral-algae symbiosis ("coral bleaching"). Yet, the primary site of thermal damage is not well resolved. In this perspective essay, I consider further a recent hypothesis which proposes an energetic disruption to the carbon-concentrating mechanisms (CCMs) of the coral host, and the resultant onset of CO2-limitation within the photosynthetic "dark reactions", as a unifying cellular mechanism. The hypothesis identifies the enhanced retention of photosynthetic carbon for zooxanthellae (re)growth following an initial irradiance-driven expulsion event as the cause of the energetic disruption. If true, then it implies that the onset of the bleaching syndrome and setting of upper thermal bleaching limits are emergent attributes of the coral symbiosis that are ultimately underpinned by the characteristic growth profile of the intracellular zooxanthellae; which is known to depend not just on temperature, but also external (seawater) nutrient availability and zooxanthellae genotype. Here, I review this proposed bleaching linkage at a variety of observational scales, and find it to be parsimonious with the available evidence. This provides a new standpoint to consider the future prospects of the coral symbiosis in an era of rapid environmental change, including the now crucial importance of reef water quality in co-determining thermal bleaching resistance. [ABSTRACT FROM AUTHOR]

de Freitas et al. (2015) (henceforth dFDB) report a trend of 0.28 °C per century over the period 1909-2009 for New Zealand land surface temperatures, from their reanalysis of a composite of seven long-term records. This is much lower than the warming trend of about 0.9 °C per century reported previously by other researchers and much smaller than trends estimated from independent sea surface temperature data from the surrounding region. We show these differences result primarily from the way inhomogeneities in temperature time series at individual stations due to site or instrument changes are identified and adjusted for in the dFDB paper. The adjustments reported in that paper are based on a method designed by one of us (Salinger), but use only a short (1-2-year) overlap period with comparison stations and consider only inhomogeneities in monthly mean (rather than monthly maximum and minimum) temperatures. This leads to underestimates of the statistical significance of individual temperature discontinuities and hence rejection of many valid adjustments. Since there was a systematic tendency for the seven-station sites to be relocated to colder locations as the early half of the twentieth century progressed, this rejection of valid adjustments produces an artificially low rate of warming. We therefore disagree with the trend calculations in the dFDB paper and consider there is no reason to reject the previous estimates of around 0.9 °C warming per century. [ABSTRACT FROM AUTHOR]

We use the process-based VS (Vaganov-Shashkin) model to investigate whether a regional Pinus halapensis tree-ring chronology from Tunisia can be simulated as a function of climate alone by employing a biological model linking day length and daily temperature and precipitation (AD 1959-2004) from a climate station to ring-width variations. We use two periods to calibrate (1982-2004) and verify (1959-1981) the model. We have obtained highly significant positive correlation between the residual chronology and estimated growth curve (r = 0.76 p < 0.001). The model shows that the average duration of the growing season is 191 days. On average, soil moisture limits tree-ring growth for 128 days and temperature for 63 days. [ABSTRACT FROM AUTHOR]

The article discusses the Hadley Centre Global Environment Model version 2 (HadGEM2) family of climate configurations that comprises a range of specific model configurations. It offers a detailed descriptions and evaluations of HadGEM2 family members and its overall performance using a set of model metrics. It notes that HadGEM2 family of configurations includes atmosphere and ocean components with well-resolved stratosphere and earth-system.

In recent years, the water level of the Dongting Lake (DTL) has been continuously low, and the wetland area and landscape pattern have changed significantly. Considering the obvious spatial heterogeneity of water regime changes in different waters of the DTL, this paper takes two core areas of the South Dongting Lake Nature Reserve (SDLNR) as study areas and analyzes the spatial distribution characteristics of the wetland blue–green landscape patterns by using remote sensing image data and hydrological and meteorological data. The multi-scale correlation between runoff, precipitation, temperature, and evapotranspiration in the SDLNR was studied via cross-wavelet transform analysis. The results show the following: (1) The change in the blue–green spatial patterns in different regions in different periods is inconsistent, and this inconsistency is related to the topography, climate, and human activities in each region; (2) there are seasonal fluctuations in precipitation, air temperature, and evapotranspiration in the SDLNR. Among them, the annual mean temperature shows a rising trend and passes the significance test with 95% confidence, while the annual mean precipitation and annual mean evapotranspiration show no significant change trend; and (3) our Pearson correlation analysis and cross-wavelet change results show that precipitation and temperature are strongly correlated with runoff, with a resonance period of 8–16 months, while the correlation between evapotranspiration and runoff is not significant. We recommend that policymakers establish an effective early warning system and make plans to store water through micro-terrain transformation in possible climate change treatments and strategies. [ABSTRACT FROM AUTHOR]

Atmospheric extreme events cause severe damage to human societies and ecosystems. The frequency and intensity of extremes and other associated events are continuously increasing due to climate change and global warming. The accurate prediction, characterization, and attribution of atmospheric extreme events is, therefore, a key research field in which many groups are currently working by applying different methodologies and computational tools. Machine learning and deep learning methods have arisen in the last years as powerful techniques to tackle many of the problems related to atmospheric extreme events. This paper reviews machine learning and deep learning approaches applied to the analysis, characterization, prediction, and attribution of the most important atmospheric extremes. A summary of the most used machine learning and deep learning techniques in this area, and a comprehensive critical review of literature related to ML in EEs, are provided. The critical literature review has been extended to extreme events related to rainfall and floods, heatwaves and extreme temperatures, droughts, severe weather events and fog, and low-visibility episodes. A case study focused on the analysis of extreme atmospheric temperature prediction with ML and DL techniques is also presented in the paper. Conclusions, perspectives, and outlooks on the field are finally drawn. [ABSTRACT FROM AUTHOR]

The climate change–built environment nexus is complex and intertwined. Recognizing the rising air temperatures and solar radiations owing to climate-induced global warming, it is critical to manage the increased building energy and cooling loads in the Middle East Gulf states' hot desert climates (Bwh). One of the top climate priorities is to promote climate resilience by reducing risks and enhancing adaptation options. This study aims to systematically review the existing literature to document building energy performances in and the associated adaptation measures of the Middle East Gulf states, regarding the implications of climate change. It is accomplished by answering the following questions: 'How well do we understand the effects of climate change on building energy use in hot urban deserts?' and 'What are the most appropriate adaptation strategies to reduce energy use in hot urban deserts?'. Using the Preferred Reporting Items for Systematic review and Meta-Analysis protocols (PRISMA), 17 studies on the influence of present and future weather scenarios on building performance are examined, considering variations in typology, methods, and input variables. Finally, the paper identifies the preferred methods and input variables for modelling building energy performance under predicted climatic changes. Passive design considerations are considered highly effective in mitigating and adapting to climate change implications. Thermal insulation and efficient window glazing are identified as the best-performing strategies, while the use of solar Photovoltaic (PV) is considered efficient in meeting the primary energy demands. The study's findings can assist planners and designers in projecting future climatic influences on the energy usage of existing buildings. [ABSTRACT FROM AUTHOR]

One of the most conspicuous global challenges in the 21st century is global warming and climate change, attributable to long-term shifts in global temperatures and weather patterns due to persistent greenhouse gases emissions in the atmosphere. Fossil fuels production had been identified severally as a major culprit in the continous release of greenhouse gases in the atmosphere. Hence, there have been agitations from various stakeholder groups including international organizations, national governments, civil societies, etc., seeking ways to address these challenges. These agitations have led to the evolution of the global energy transition agenda, whereby the world is making a shift from fossil fuels production and consumption to cleaner and more sustainable energy sources. Such energy transition implies that fossil fuels facilities, including oil and gas facilities, are fast approaching the end of their productive life. The question therefore is, what becomes of these facilities at the end of their productive life? This invariably calls for an increased attention to oil and gas decommissioning. This is because proper and sustainable decommissioning of oil and gas facilities is significant for environmental protection and sustainable development. Hence, this paper evaluates the various options available for oil and gas decommissioning so as to identify their adverse environmental impacts, and other challenges posed by their implementation. The paper further evaluates the emerging rigs-to-reefs program, and proposes this program as a more sustainable decommissioning option for oil and gas platforms. [ABSTRACT FROM AUTHOR]

The paper presents the results of studying the spatial and seasonal atmospheric temperature characteristics of Jalingo metropolis, Nigeria, with the aim of assessing seasonal temperature variations for thermal comfort planning. Temperature data for this study was collected across the local climate zones, otherwise known as thermal climate zones (TCZ), following the TZC classification of the area. Temperature data was collected for 30 days continuously and simultaneously across the TCZ. The collection of temperature data was done in the months of April and August 2021, and January 2022 - representing the dry season, the rainy season and the Harmattan period respectively. A Thermochron Ibutton sensor by Maxim Incorporation was used to collect temperature data, while the specific series used was DS1921. An improvised automated weather station was constructed to house the sensor. The result of the study indicates that air temperature varies considerably within Jalingo metropolis, as well as throughout the seasons, thus affecting human thermal comfort in the study area, as temperature is found to correlate well with both human morbidity and mortality, especially regarding cardiovascular diseases. The paper recommends increasing ventilation and naturebased solution to reduce high temperatures through tree planting in order to improve human thermal comfort in Jalingo metropolis area. [ABSTRACT FROM AUTHOR]

The article reports on the climate impacts of anthropogenic carbon dioxide emissions. In its Fourth Assessment Report, the Intergovernmental Panel on Climate Change (IPCC) suggests that about 50 percent of a carbon dioxide increase will be removed from the atmosphere within 30 years. It is reported that the logarithmic relationship between carbon dioxide and its radiative forcing implies that the time scale at which atmospheric temperature declines will be longer.

The influence of land processes and in particular of diffuse/direct radiation partitioning on surface fluxes and associated regional-scale climate feedbacks is investigated. ERA-40 driven simulations over Europe are performed using the COSMO-CLM² Regional Climate Model (RCM). Two alternative Land Surface Models (LSMs), a 2nd generation LSM (TERRA ML) and a more advanced 3rd generation LSM (Community Land Model version 3.5), and two versions of the atmospheric component are tested, as well as a revised coupling procedure allowing for variations in diffuse/direct light partitioning at the surface, and their accounting by the land surface component. Overall, the RCM performance for various variables (e.g., surface fluxes, temperature and precipitation) is improved when using the more advanced 3rd generation LSM. These improvements are of the same order of magnitude as those arising from a new version of the atmospheric component, demonstrating the benefit of using a realistic representation of land surface processes for regional climate simulations. Taking into account variability in diffuse/direct light partitioning at the surface further improves the model performance in terms of summer temperature variability at the monthly and daily time scales. Comparisons with observations show that the RCM realistically captures temporal variations in diffuse/direct light partitioning as well as the evapotranspiration sensitivity to these variations. Our results suggest that a modest but consistent fraction (up to 3%) of the overall variability in summer temperature can be explained by variations in the diffuse to direct ratio. [ABSTRACT FROM AUTHOR]

This paper analyzed the variations of two air temperature indices, diurnal temperature range (DTR) and annual temperature range (ATR), calculated based on observations at the Zagreb Grič Observatory over a period of 133 years (1887–2019). In intense climate changes strongly manifested by the increased air temperature, these two climate indices were determined to significantly impact human health and the environment. This effect is especially evident in urban areas. The Zagreb Grič Observatory is located in the center of Zagreb and has not changed its location during the observed period. It has a long homogeneous series of climatological observations, enabling a detailed study of climate variation in the city, which is strongly influenced by various urbanization processes. In 133 years, both of the analyzed indicators showed a statistically insignificant downward trend. The Rescaled Adjusted Partial Sums (RAPS) method revealed statistically significant differences in DTR's time series between three sub-periods: 1887–1953, 1954–1989, and 1990–2019. The time series of ATR during 133 years behaved statistically differently in four sub-periods: 1887–1905; 1906–1926; 1927–1964; and 1965–2019. The analysis of monthly values of DTR showed that the DTR values are the highest in the warm part of the year, from May to August, when they are twice as high as those during the cold period from November to December. With an increase in precipitation, the DTR values decrease, while they increase as the mean annual temperature increases. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) plays a crucial role in the climate change of China as well as global climate change. It is therefore of great practical significance to study vegetation and its dynamic changes for regional ecological protection. The combination of a dry climate and notable temperature disparities can lead to intricate effects on the region's vegetation. However, there are few studies exploring the complex effects of diurnal temperature variations on vegetation growth that differ from the effects of mean temperature on the TP, especially under different frozen ground types. Based on the long-time series maximum temperature (Tmax), minimum temperature (Tmin), and Normalized Difference Vegetation Index (NDVI) of the TP, we conducted a comparative study of the warming effects on plant growth under different frozen types. The results exhibit that it warms up faster at night (0.223 °C de−1; p < 0.01) than during the day (0.06 °C de−1; p < 0.01), resulting in a significant decrease in the temperature difference between day and night (−0.078 °C de−1; p < 0.01) in the past few decades. The principal finding of this paper is that Tmin is the dominant temperature indicator for vegetation growth on the TP, which dominates 63.3% of the area for NDVI and 61.4% of the area for GPP, respectively. The results further identify a stronger correlation between air temperature and vegetation growth in seasonal frozen grounds (R = 0.68, p < 0.01) and permafrost regions (R = 0.7, p < 0.01) compared to unfrozen grounds (R = 0.58, p < 0.01). Moreover, the physiological mechanism underlying the asymmetric influence of Tmin and Tmax on vegetation growth is further elucidated in this study. Given that future climate changes are expected to exacerbate these changes, it is imperative to explore additional avenues in pursuit of potential mechanisms that can offer adaptive strategies for safeguarding the ecology of the TP. [ABSTRACT FROM AUTHOR]

Meteorological drought (MDr) causes considerable economic losses in many countries, including in relation to agriculture. To examine the diversity of seasonal meteorological drought in Poland, the study uses monthly precipitation sums in the period from March to November, collected from 74 ground-based meteorological stations in 1951–2020. The paper defines meteorological drought on the basis of the standardized precipitation index in three seasons (SPI-3) and differentiates three degrees of drought intensity: extreme, severe and moderate. The study also calculates the size of Poland's area affected by meteorological drought (AAMDr) and determines the relationship between AAMDr and SPI-3. MDr in Poland occurred more frequently in spring and autumn (every 4–5 years) than in summer (every 7 years). In the areas affected by extreme drought, precipitation was below the average, mainly ≤50% of the climatic norm, and air temperature values were below or above the average of the climatic norm, mainly ranging from −1.0 to 1.0 °C. A significant negative correlation between AAMDr and SPI-3 indices was found. The obtained results could be useful for managing climatic risk and developing regional and local agriculture adaptation plans aimed at mitigating the effects of climate change. [ABSTRACT FROM AUTHOR]

Drought is a natural phenomenon that occurred in Central Europe in the past, but it is becoming a more serious problem due to the changes in its occurrence and intensity related to climate change. The main aim of this paper was to determine changes in air temperature and precipitation amounts in Slovakia from 1931 to 2020 and to identify changes in drought occurrence and intensity using the Standardised Precipitation and Evapotranspiration Index (SPEI). Cluster analysis was used to determine regions with similar drought occurrences. For each of the identified five clusters, drought characteristics were determined and compared between two reference periods 1961–1990 and 1991–2020. While a decrease in the number of months with SPEI-1 below − 1 was observed in autumn, spring and summer months showed a drying tendency. Overall, we can say that we observed a shift in drought occurrence from autumn and winter months to spring and summer months. This is an important finding for the agriculture or forestry because it affects work management and planning. The clearest tendency in drought events was observed in the western part of Slovakia covering areas with agriculturally intensive land use. Besides prolonging drought events, there was also a higher accumulated deficit for each event. The increase in drought intensity was not spatially consistent over the cluster area, mostly reaching a slight decline of about − 0.1 to − 0.3, which means slight intensification of drought periods in 1991–2020. [ABSTRACT FROM AUTHOR]

Wildfires are natural occurrences of the forests’ ecosystems and vital for the renewal of biomes and survival of some plant species. Studies indicate that in recent times, in many parts of the world, the frequency, extent, and austerity of wildfires have been escalating and occurring in places where they rarely occurred before. Several reports indicate that the environment is gradually warming up and is associated with severe droughts that could be responsible for such wildfire escalations. The humans’ role in climate change is vastly debated. Whereas some scientists believe that the current rise in atmospheric temperature is due to the changes in solar activities and is a part of natural climate cycle where humans have no accountabilities, the others disagree and suggest that the rise in atmospheric temperatures is aided by anthropogenic activities. Regardless of the scientific opinions on the mechanism of climate change, shifting climatic conditions are evidenced and supported by many scientific studies. This paper reports on some brutal wildfire activities in 2021 that severely impacted various parts of the world where extreme weather conditions were reported and where drought and environmental temperature surpassed all previous records. [ABSTRACT FROM AUTHOR]

In the context of the ongoing United Nations Framework Convention on Climate Change (UNFCCC) process, it seems important to focus attention not only on global mean surface air temperature (GSMT) but also on the climate of specific regions in order to gain insights into the dynamics of the changes, the timescales of the periodic components, the local trends and the relationships between climatic variables in the region of interest. This is important for scientists as well as for policymakers. This paper provides an analysis of the changes in local air temperature and precipitation depth in exceptionally long observational records and examines the relationships between these two variables. The focus is on monthly values. Temperature maximum, minimum, range, and cumulative precipitation depth are considered. The wavelet analysis shows that the scale of variation is different for temperature and precipitation and that the behavior of the temperature range values diverges from the behavior of the minimum and maximum values. The timescale of important changes in the long-term trend is, however, similar. Results also suggest that the main mode of variability is persistent through time in the series of temperature maximum, minimum, and range but not in precipitation depth. This is a clear evidence of climate change. All series show variances that change over time and are, as expected, nonstationary. The analysis of the wavelet coherence shows that the relationship between precipitation and temperature evolves through time, and its intensity varies considering different time scales. The association between these climatic variables is particularly strong in the last decade. Is it noteworthy that the analysis of the coherence suggests that temperature is leading to rain and not the other way around. This highlights the impact of global warming on the hydrologic cycle and on related human activities. [ABSTRACT FROM AUTHOR]

Climate change is a major concern in agriculture; in grapevine production, climate change can affect yield and wine quality as they depend on the complex interactions between weather, plant material, and viticultural techniques. Wine characteristics are strongly influenced by microclimate of the canopy affecting primary and secondary metabolites of the grapevine. Air temperature and water availability can influence sugar and acid concentration in grapes and relative wines, and their content of volatile compounds such as norisoprenoids. This becomes relevant in sparkling wine production where grapes are generally harvested at a relatively low pH, high acidity, and low sugar content and where the norisoprenoids significantly contributes to the final aroma of the wine. The effect of climate change on grapevine and wine, therefore, calls for the implementation of on-field adaptation strategies. Among them canopy management through leaf removal and shading have been largely investigated in the wine growing sector. The present study, conducted over 4 years (2010-2013) aims at investigating how leaf removal and artificial shading strategies affect grape maturation, must quality and the production of norisoprenoids, analyzed using an untargeted approach, in sparkling wine. Specifically, this paper investigates the effect of meteorological conditions (i.e., water availability and temperatures) and the effect of leaf removal and shading on Vitis vinifera L. cv. Chardonnay and Pinot noir, which are suitable to produce sparkling wine in the DOCG Franciacorta wine growing area (Lombardy, Italy). The effect of leaf removal and shading practices on norisoprenoids has been the focus of the study. No defoliation and artificial shading treatments play an important role in the preservation of the acidity in warm seasons and this suggests calibrating defoliation activities in relation to the meteorological trend without standardized procedures. This is particularly relevant in the case of sparkling wine, where the acidity is essential to determine wine quality. The enhanced norisoprenoid aromas obtained with a total defoliation represent a further element to direct defoliation and shading strategies. The obtained results increase knowledge about the effect of different defoliation and artificial shading applications in relation to meteorological condition supporting the management decision-making in the Franciacorta wine growing area. [ABSTRACT FROM AUTHOR]

This paper examines the long-term changes in temperature and precipitation in the karst region of Imotski, Croatia, which is of particular interest due to its abundance of karst phenomena. This study analyses temperatures and precipitation on monthly and annual scales at two climatological stations in the region, Imotski and Ričice. Linear regression, the Theil–Sen estimator (β), and the Mann–Kendall test were used to determine the trends and statistical significance. The homogeneity of the data was checked using the Standard Normal Homogeneity Test (SNHT), and the F-test and t-test were used to test the significance of the mean shift between the two subseries. Additionally, the coefficient of variability, standardized rainfall anomaly, and precipitation concentration index were employed to analyze the precipitation variability. The study found a statistically significant (p < 0.05) upward trend in the mean (β = 0.0437) and maximum (β = 0.0590) annual air temperature at the Imotski station and the mean (β = 0.0387) annual temperature at the Ričice station. The SNHT test showed a statistically significant (p < 0.05) shift in the mean annual temperatures after 2007 and maximum annual temperatures after 1998 at the Imotski station. Similarly, a statistically significant (p < 0.05) shift in the mean annual temperatures after 2011 and the maximum annual temperatures after 1998 was found at the Ričice station. A seasonal distribution of precipitation is observed at both the Ričice and Imotski stations, with a downward trend (β = −2.7693) at Ričice and an upward trend (β = 6.0575) at Imotski; however, neither trend is statistically significant (p > 0.05). An increase in the intensity of dry periods and the occurrence of extreme events was also noted. The climatological analysis, conducted for the first time in this area, is a crucial step toward understanding local climate patterns and making informed decisions toward sustainable development and adaptation strategies. [ABSTRACT FROM AUTHOR]

The periods of warming and cooling of the weather on Earth followed one another with great irregularity and caused significant variations in air temperature but allowed the existence of life and especially of the human species. In this paper we have analysed the variation of air temperature in Oltenia in the period 1961-2021. A number of our other works have analysed the variability of the climate in this part of Romania. After the warm period of 1945-1955, a gradual cooling of the weather followed in summers and during the period 1966-1984 (for 20 years). In summers, no thermal maximum of ≥40°C was registered. The period 2000-2021 (22 years) was the warmest of all the meteorological observations in Oltenia and many annual, monthly and daily climate records were surpassed. At the same time, during the analysed interval, the melting rate of the ice in the polar areas intensified a lot and exceptional thermal maxima were registered. The heat waves during the summers were more and more intense, more frequent and longer in duration. The paper is useful to all those interested in climate variability in Oltenia. [ABSTRACT FROM AUTHOR]

Analyzing the impact of climate variables into the operational planning processes is essential for the robust implementation of a sustainable power system. This paper deals with the modeling of the run-of-river hydropower production based on climate variables on the European scale. A better understanding of future run-of-river generation patterns has important implications for power systems with increasing shares of solar and wind power. Run-of-river plants are less intermittent than solar or wind but also less dispatchable than dams with storage capacity. However, translating time series of climate data (precipitation and air temperature) into time series of runof-river-based hydropower generation is not an easy task as it is necessary to capture the complex relationship between the availability of water and the generation of electricity. This task is also more complex when performed for a large interconnected area. In this work, a model is built for several European countries by using machine learning techniques. In particular, we compare the accuracy of models based on the Random Forest algorithm and show that a more accurate model is obtained when a finer spatial resolution of climate data is introduced. We then discuss the practical applicability of a machine learning model for the medium term forecasts and show that some very context specific but influential events are hard to capture. [ABSTRACT FROM AUTHOR]

Work of researchers from various areas is focused on problematics of urban heat islands. Its importance is rising with the global climate change. The difference of the air temperatures within the area can be also caused by the measurement error. Usual error is not the accuracy of the sensor, but the radiation shield or location of the weather station. In this case, averaged difference can be up to 80 %. Difference of temperatures between the weather stations within the analyzed area can vary from 0.2 up to 6 °C. Difference depends usual on the size of the city and the location influenced by the surrounding geomorphology. In this paper three different radiation shields are compared which influenced the measurement and analyzed are also the results from four different weather stations, two of them are within the University of Zilina campus. One of them is placed on the roof, which is a usual location for the solar radiation measurement; the second one is placed on the grass land at the end of the campus. Other two stations belong to the national weather institute. Comparison is made for two very hot days of August 2020. Averaged difference was 0.3 °C for the whole month and 0.5 °C for selected days. [ABSTRACT FROM AUTHOR]

The subject of this paper is the analysis of possible influence of climate change on the energy performance of building and indoor temperatures. The model is based on the Maison Air et Lumière house, which concept was developed as part of the Model Homo 2020 project. It was a low-energy, single family, detached house. The model was divided into three thermal zones and developed by using SketchUp software. The analysis of the climate change was made on the example of the city in Poland - Kielce and described in the first part of the paper. Dynamic calculations of the building model were performed by using the TRNSYS software. The calculations were made for three different scenarios relating to existing technical systems: ventilation, ventilation + heating, ventilation + heating + cooling. Annual energy consumption and rooms air temperature changes were estimated for each variant. The results showed higher risk of summer discomfort and change in energy balance of building what indicates the need to use the cooling system in the future during the summer to reduce the discomfort of overheating. In the variant without the cooling system, the percentage of time with an indoor temperature above 27°C increased from 23.7% to 44.2% in zone 2. The energy demand for heating was reduced by 23.4% compared to the current climate, and the energy consumption for cooling (with the cooling option) increased significantly by 232% compared to the current demand. Summarizing, research indicates that with global warming, the energy demand for heating will decrease and the cooling demand will increase significantly in order to maintain the required user comfort. [ABSTRACT FROM AUTHOR]

Since the mid-1990s, there has been a marked decrease in the sea ice extent (SIE) in the Arctic Ocean. After reaching an absolute minimum in September 2012, the seasonal variations in the SIE have settled at a new level, which is almost one-quarter lower than the average climatic norm of 1979–2022. Increased melting and accelerated ice export from marginal seas ensure an increase in the open water area, which affects the lower atmosphere and the surface layer of the ocean. Scientists are cautiously predicting a transition to a seasonally ice-free Arctic Ocean as early as the middle of this century, which is about 50 years earlier than was predicted just a few years ago. Such predictions are based on the fact that the decrease in sea ice extent and ice thinning that occurred at the beginning of this century, initially caused by an increase in air temperature, triggered an increase in the thermal and dynamic contribution of the ocean to the further reduction in the ice cover. This paper reviews published evidence of such changes and discusses possible mechanisms behind the observed regional anomalies of the Arctic Sea ice cover parameters in the last decade. [ABSTRACT FROM AUTHOR]

Most scleractinian corals and many other cnidarians host intracellular photosynthetic dinoflagellate symbionts ("zooxanthellae"). The zooxanthellae contribute to host metabolism and skeletogenesis to such an extent that this symbiosis is well recognised for its contribution in creating the coral reef ecosystem. The stable functioning of cnidarian symbioses is however dependent upon the host's ability to maintain demographic control of its algal partner. In this review, I explain how the modern envelope of seawater conditions found within many coral reef ecosystems (characterised by elevated temperatures, rising pCO2, and enriched nutrient levels) are antagonistic toward the dominant host processes that restrict excessive symbiont proliferation. Moreover, I outline a new hypothesis and initial evidence base, which support the suggestion that the additional "excess" zooxanthellae fraction permitted by seawater pCO2 levels beyond 260 ppmv significantly increases the propensity for symbiosis breakdown ("bleaching") in response to temperature and irradiance extremes. The relevance of this biological threshold is discussed in terms of historical reef extinction events, glacial-interglacial climate cycles and the modern decline of coral reef ecosystems. [ABSTRACT FROM AUTHOR]

Stable carbon isotopes have been used to assess the coupling between changes in environmental conditions and the response of soil or ecosystem respiration, usually by studying the time-lagged response of δ13C of respired CO2 (δ13CR) to changes in photosynthetic carbon isotope discrimination (Δi). However, the lack of a systematic response of δ13CR to environmental changes in field studies stresses the need to better understand the mechanisms to this response. We experimentally created a wide range of carbon allocation and respiration conditions in Fagus sylvatica mesocosms, by growing saplings under different temperatures and girdling combinations. After a period of drought, a water pulse was applied and the short-term responses of δ13C in soil CO2 efflux (Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed.) and δ13C in aboveground plant respiration (Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed.) were measured, as well as leaf gas exchange rates and soil microbial biomass δ13C responses. Both Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed. values of all the trees decreased immediately after the water pulse. These responses were not driven by changes in Δi, but rather by a fast release of C stored in roots and shoots. Changes in Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed. associated with the water pulse were significantly positively correlated with changes in stomatal conductance, showing a strong impact of the plant component on Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed.. However, three days after the water pulse in girdled trees, changes in Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed. were related to changes in microbial biomass δ13C, suggesting that changes in the carbon source respired by soil microorganisms also contributed to the response of Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed.. Our study shows that improving our mechanistic understanding of the responses of δ13CR to changes in environmental conditions requires the understanding of not only the plant's physiological responses, but also the responses of soil microorganisms and of plant-microbial interactions. [ABSTRACT FROM AUTHOR]

Impacts of low-latitude, explosive volcanic eruptions on climate and the carbon cycle are quantified by forcing a comprehensive, fully coupled carbon cycle-climate model with pulse-like stratospheric sulfur release. The model represents the radiative and dynamical response of the climate system to volcanic eruptions and simulates a decrease of global and regional atmospheric surface temperature, regionally distinct changes in precipitation, a positive phase of the North Atlantic Oscillation, and a decrease in atmospheric CO2 after volcanic eruptions. The volcanic-induced cooling reduces overturning rates in tropical soils, which dominates over reduced litter input due to soil moisture decrease, resulting in higher land carbon inventories for several decades. The perturbation in the ocean carbon inventory changes sign from an initially weak carbon sink to a carbon source. Positive carbon and negative temperature anomalies in subsurface waters last up to several decades. The multi-decadal decrease in atmospheric CO2 yields an additional radiative forcing that amplifies the cooling and perturbs the Earth System on much longer time scales than the atmospheric residence time of volcanic aerosols. In addition, century-scale global warming simulations with and without volcanic eruptions over the historical period show that the ocean integrates volcanic radiative cooling and responds for different physical and biogeochemical parameters such as steric sea level or dissolved oxygen. Results from a suite of sensitivity simulations with different amounts of sulfur released and from global warming simulations show that the carbon cycle-climate sensitivity, expressed as change in atmospheric CO2 per unit change in global mean surface temperature, depends on the perturbation. On decadal time scales, modeled is several times larger for a Pinatubo-like eruption than for the industrial period and for a high emission, 21st century scenario. [ABSTRACT FROM AUTHOR]

This paper presents the results of 30 years of permafrost thermal monitoring in the Tiksi area in the eastern Russian Arctic. At a stone ridge site, the mean annual temperatures in the upper 30 m of the ground have increased by 1–2.4 °C compared to the first years of observations, with trends of °C/yr. At the same time, its change was uneven. In the last 20 years, the rate of increase has increased compared with the first decade of observations. At wet tundra sites in the foothill plain, the mean annual temperatures at the top of permafrost have increased by 2.4–2.6 °C between 2005 and 2022 at rates of 0.11–0.15 °C/yr, and the active layer thicknesses have increased at rates of 0.05–0.41 cm/yr. [ABSTRACT FROM AUTHOR]

Global warming is causing an intensification of extreme climate events with significant changes in frequency, duration, and intensity over many regions. Understanding the current and future influence of this warming in northeastern Brazil (NEB) is important due to the region's greater vulnerability to natural disasters, as historical records show. In this paper, characteristics of climate change projections (precipitation and air temperature) over NEB are analyzed using 15 models of Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathways (SSPs: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) scenarios. By using the Taylor diagram, we observed that the HadGEM3-GC31-MM model simulates the seasonal behavior of climate variables more efficiently. Projections for NEB indicate an irreversible increase in average air temperature of at least 1 °C throughout the 21st century, with a reduction of up to 30% in annual rainfall, as present in scenarios of regional rivalry (SSP3-7.0) and high emissions (SSP5-8.5). This means that a higher concentration of greenhouse gases (GHG) will increase air temperature, evaporation, and evapotranspiration, reducing rainfall and increasing drought events. The results obtained in this work are essential for the elaboration of effective strategies for adapting to and mitigating climate change for the NEB. [ABSTRACT FROM AUTHOR]