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Simple Summary: The heat-loving paper wasp Polistes dominula builds small nests in sheltered places in quite differing habitats, providing a favorable microclimate for brood development. Their careful choice of the nesting site enables them to keep the nest and brood temperature above the ambient air temperature. In temperate Austrian (Central European) climates, the cooling efforts of the adult wasps keep the mean comb temperature from exceeding approximately 39 °C, which seems to be a threshold for optimal development. Measurement of the nest and the body temperature of the wasps at typical nesting sites revealed a close relationship with the air temperature at the nests but a suboptimal correlation with climate data from a local standard weather station or model-generated macroclimate data. The comparison emphasizes the importance of microclimate measurements if it is to judge the vulnerability of insects to climate change. The paper wasp Polistes dominula is a thermophilic species originating from the Mediterranean climate, but is now widely spread in Europe. They live in quite differing habitats; and as synanthropic species, they have been established in human settlement areas. They build a single small comb at protected places with a favorable microclimate. We measured the temperature of the wasps, the nests and their environment at typical nesting sides in Austria (Europe) in the temperate climate, in order to reveal relationships between nest and body temperature and the habitats' microclimate. The temperatures of the comb and of the wasps' body were in a wide range (~20–37 °C) above the ambient air temperature at the nest. This is an advantage as higher temperatures accelerate the development speed of the brood. However, the mean comb temperature did not exceed approximately 38.6 °C. This was managed by cooling efforts of the adult wasps. The ambient air temperature near the nest (~1–2 cm) was always clearly elevated above the ambient air temperature at a local standard weather station in the habitat. A comparison with climate-model-generated macroclimate data revealed the necessity of measuring microclimate data for a reliable description of the insects' thermal environment. [ABSTRACT FROM AUTHOR]

In this work, we investigate the influence of ZnO nanoparticles on the performance of paper-based humidity sensors. The sensors were developed on standard, commercial printing paper with laser-patterned gold interdigitated electrodes (IDE) and ZnO nanoparticles spin-coated by various sol-gels. Blank devices were used as reference sensors in an effort to elucidate the role of ZnO and the dependence of the device performance on the concentration of the sol-gels and the number of spin-coated layers. Resistive measurements were conducted at room temperature to evaluate the devices’ response on known relative humidity levels. Relatively fast rise and response times were observed even at room temperature, while all devices tested did not require refreshing procedures. The deposition of ZnO was found to affect the sensor response, resulting in reduced sensor signal, due to the blocking of water diffusion in the porous paper material. [ABSTRACT FROM AUTHOR]

This research investigated a non-thermal, dielectric-barrier discharge (DBD) plasma-based approach to prepare poly(acrylic acid) (PAA) from acrylic acid in its liquid state at atmospheric temperature and pressure. Neither additives nor solvents were needed, and the polymerization was accomplished both as a film and inside a sheet of mesoporous paper. All prepared samples were characterized and the DBD plasma-initiated kinetics were analyzed for the polymerization of acrylic acid. Using FTIR semi-quantitative analysis, the degree of polymerization was monitored, and the reaction followed an overall second-order kinetic model with respect to the DBD-initiated polymerization. Additionally, the application of a PAA-modified paper as a water retention cloth or 'wet wipe' was investigated. The results showed that the PAA-modified paper substrates using DBD plasma increased water retention as a function of plasma treatment time. [ABSTRACT FROM AUTHOR]

In this paper, we discuss a better method to measure the paper water content of transformers using cellulose isotherms. The advantage of the new method is that the transformer oil and cellulosic insulation do not need to be in thermodynamic equilibrium. Instead, the temperature needs to be cycling in order to determine when the direction of water migration, whether out of or into the oil changes. The reversal in water migration can be used to determine the vapor pressure of the water adsorbed by the cellulose. This method was tested using 12 different conditions similar to those within a normally operating transformer. The results showed close agreement when this method is used. The significance is that isotherm equations can now be used even when insulation media are not in equilibrium. [ABSTRACT FROM PUBLISHER]

A hybrid montmorillonite (Mt)-rich/chitosan composite (MCC) with high adsorption performance was synthesized for the decolorization of water used in the joss paper process. The performance was reported in terms of the dye removal. The composite expressed higher performance than chitosan or Mt-rich clay, respectively. The optimum condition for complete dye removal was achieved when using at least 0.6 g of the composite over a wide pH range (3–10) and initial dye concentration (10–100 mg L−1). The composite showed good reusability without the requirement of regeneration, adsorbing the dye completely for up to eight successive cycles of adsorption (>1.33 gdye gMCC−1). Thermodynamic analyses revealed the degree of spontaneity and the endothermic adsorption process. From the isotherm studies, the Koble–Corrigan isotherm model fitted very well to the experimental data, revealing that the composite had a heterogeneous surface with various active sites to adsorb the dye molecules. This also evidenced the synergistic electrostatic attraction and hydrophobic interaction between the dye and the composite. The pseudo-second-order model best explained the kinetic rate of adsorption. From evaluation of the adsorption process using the Webber and Morris equation and Boyd model, the rate-limiting step consisted of film diffusion and intra-particle diffusion. [ABSTRACT FROM AUTHOR]

Different amounts of a stable aqueous TiO2 hydrosol were used to fabricate paper sheets having photocatalytic activity. The TiO2 hydrosol was prepared in aqueous medium using titanium butoxide as precursor and acetic acid as catalyst for the hydrolysis of titanium butoxide. An aging process at room temperature and atmospheric pressure was finally applied to obtain crystalline anatase TiO2 hydrosol. The effects of different TiO2 hydrosol loadings on the mechanical strength and barrier properties of modified paper sheets were investigated in detail. The photocatalytic behavior of TiO2-modified paper sheets was investigated as well using methylene blue (MB) as target pollutant. [ABSTRACT FROM AUTHOR]

Highlights: The paper concerns the possibility of using an innovative railway rail structure in a contactless track: The correct operation of CWR track, due to the occurrence of additional thermal stresses with a value dependent on changes in rail temperature, requires a systematic diagnosis of its condition; The paper presents the research of longitudinal force load tests for a classic rail and for two cases of an innovative railway rail solution. The research presented in the paper shows that: The proposed proprietary design of the rail used for the railroad track can enable the reduction in the longitudinal force occurring as a result of high ambient temperatures; The use of an innovative rail conception will allow for less steel consumption, which means less emissions into the atmosphere during its production (lower carbon footprint). This paper presents the concept of a modified 60E1 rail dedicated to continuous welded rail (CWR) track. The presented solution is the subject of a patent application by the authors of the publication. The paper describes problems associated with the operation of CWR track and the phenomena of so-called "rail stressing", i.e., stresses created in the rail due to thermal shrinkage that, in extreme cases, can lead to the buckling of the rail track. Simulation calculations of longitudinal track loads to represent the occurrence of thermal force as a result of the occurrence of high air temperatures were carried out for the constructed conventional model of the railroad track as well as the track with the proposed solutions. A discussion of the simulation results is presented, indicating the possibility for the wider application of both varieties of modified rail. [ABSTRACT FROM AUTHOR]

In order to understand the application of frost measurement of air source heat pump heat exchanger, a research on frost measurement of air source heat pump heat exchanger based on image recognition processing technology is put forward. In this paper, the scheme design of defrosting control system based on image processing technology is introduced, and the frost degree coefficient of outdoor heat exchanger fin surface is introduced to characterize the frost degree of fin surface. Secondly, the experimental environment room was built, and the conventional defrosting control method of the existing heat pump unit was tested on the spot. It was found that in the air temperature of -6~0 °C and the air relative humidity of 86~92%, the unit appeared the phenomenon of "defrosting in time" and "defrosting without frost". Finally, the change of frost layer on the surface of the outdoor heat exchanger fin during defrosting is analyzed, and the coefficient of frost degree on the surface of the fin is calculated and analyzed. At the beginning of defrosting, due to the large degree of frost, the P-value of the frost degree coefficient on the surface of the fin is close to 1, when the defrosting is carried out for 125 seconds, the P-value of the frost degree coefficient on the surface of the fin decreases sharply to 0.09, when the defrosting is completed, the P-value of the frost degree coefficient on the surface of the outdoor heat exchanger is maintained at about 0.04. The defrosting control method of air source heat pump based on image processing technology is proposed in this paper, and its technical feasibility and effect are verified by experimental tests, which lays a foundation for future popularization and application. [ABSTRACT FROM AUTHOR]

The temperature profile is an important parameter of the atmospheric thermal state in atmospheric monitoring and weather forecasting. The hyperspectral infrared sounder of a geostationary satellite provides abundant spectral information and can retrieve the temperature profile. Based on the mediumwave channel data (independent variable and model input data) of FY-4A/GIIRS (geosynchronous interferometric infrared sounder) and ERA5 reanalysis data (dependent variable and model output data), the atmospheric temperature profile is retrieved by generalized ensemble learning. Firstly, the feature variables of the model are constructed. Because there are many GIIRS channels, a two-step feature selection method is adopted: step 1--establish a blacklist of GIIRS channels; step 2--select feature variables by using the method of importance permutation. Secondly, they are integrated based on optimizing and adjusting the hyperparameters of three basic machine learning models (Random Forest, XGBoost and LightGBM). Generalized ensemble learning nonlinear convex optimization is used to optimize the weight of each basic model. Finally, based on high-frequency GIIRS observations of Typhoon Lekima and Typhoon Higos, testing and method evaluation of the temperature profile retrievals are carried out. The results show that LightGBM achieves the best retrieval result among the three basic models, followed by Random Forest and finally XGBoost. The root-mean-square error of the whole temperature profile in the training dataset of generalized ensemble learning is less than 0.3 K, while that of the testing dataset is less than 1.4 K, and that between 150 hPa and 925 hPa is less than 1 K. The retrieval results correlate well with the radiosonde temperature profile. The performance of generalized ensemble learning is better than the performances of the three basic models, but it depends on the retrieval results of LightGBM. In the Lekima experimental case, compared to other channels selected for temperature retrieval models, the importance of mediumwave channels 9 and 307 of GIIRS ranks first and second, respectively. The method in this paper provides a new solution and technical support for retrieving atmospheric parameters from hyperspectral and other satellite data. [ABSTRACT FROM AUTHOR]

The interannual variability (IAV) in atmospheric CO2 growth rate (CGR) is closely connected with the El Niño-Southern Oscillation. However, sensitivities of CGR to temperature and precipitation remain largely uncertain. This paper analyzed the relationship between Mauna Loa CGR and tropical land climatic elements. We find that Mauna Loa CGR lags precipitation by 4 months with a correlation coefficient of -0.63, leads temperature by 1 month (0.77), and correlates with soil moisture (-0.65) with zero lag. Additionally, precipitation and temperature are highly correlated (-0.66), with precipitation leading by 4-5 months. Regression analysis shows that sensitivities of Mauna Loa CGR to temperature and precipitation are 2.92 ± 0.20 Pg C yr-1 K-1 and -0.46 ± 0.07 Pg C yr-1 100 mm-1, respectively. Unlike some recent suggestions, these empirical relationships favor neither temperature nor precipitation as the dominant factor of CGR IAV. We further analyzed seven terrestrial carbon cycle models, from the TRENDY project, to study the processes underlying CGR IAV. All models capture well the IAV of tropical land-atmosphere carbon flux (CFTA). Sensitivities of the ensemble mean CFTA to temperature and precipitation are 3.18 ± 0.11 Pg C yr-1 K-1 and -0.67 ± 0.04 Pg C yr-1 100 mm-1, close to Mauna Loa CGR. Importantly, the models consistently show the variability in net primary productivity (NPP) dominates CGR, rather than soil respiration. Because NPP is largely driven by precipitation, this suggests a key role of precipitation in CGR IAV despite the higher CGR correlation with temperature. Understanding the relative contribution of CO2 sensitivity to precipitation and temperature has important implications for future carbon-climate feedback using such "emergent constraint". [ABSTRACT FROM AUTHOR]

Synergistic exploitation of redundant and complementary information from independent observations of the same target remains a major issue in atmospheric remote-sounding and increasing attention is devoted to investigate optimised or innovative methods for the combination of two or more measured data sets. This paper is focusing on the synergy between middle infrared and millimetre-wave limb sounding measurements of atmospheric composition and temperature and reports the results of a study conducted as part of the preparatory activities of the PREMIER (Process Exploration through Measurements of Infrared and millimetre wave Emitted Radiation) mission candidate to the Core Missions of ESA Earth Explorer 7. The activity was based on data acquired by the MIPAS-STR (Michelson Interferometer for Passive Atmospheric Sounding - STRato-spheric aircraft) and MARSCHALS (Millimetre-wave Airborne Receivers for Spectro-scopic CHaracterisation in Atmospheric Limb Sounding) instruments onboard the high altitude research aircraft M-55 Geophysica during the flight of the PremierEx (PREMIER Experiment) campaign on 10 March 2010 from Kiruna, Sweden for observation of the Arctic upper troposphere and lower stratosphere. The cloud coverage observed along the flight provided representative test cases to evaluate the synergy in three different scenarios: low clouds in the first part, no clouds in the central part and high tro-pospheric clouds at the end. The calculation of synergistic profiles of four atmospheric targets (i.e., O2, HNO3, H2O and temperature) was performed using a posteriori combination of individual retrieved profiles, i.e., Level 2 (L2) data rather than simultaneous inverse processing of observed radiances, i.e., Level 1 (L1) data. An innovative method of data fusion, based on the Measurement Space Solution (MSS) was applied along with the standard approach of inverse processing of MARSCHALS spectral radiances using MIPAS-STR retrieval products as a priori information (L1 + L2 method). A quantitative estimate and cross-check of the results of MSS and (L1 + L2) data fusion was achieved based on a specific set of quantifiers including the total retrieval error, the number of degrees of freedom, the relative information distribution and the synergy factor. [ABSTRACT FROM AUTHOR]

The paper presents the aerodynamic performance of an axial reversible fan for high air temperatures, obtained by applying the similarity theory and numerical flow simulations. This analysis was performed for the possibility of installing the existing structure of an impeller of a reversible fan in a jet fan for the longitudinal ventilation of a tunnel. The direction of forced flow in tunnels changes, and it is always towards low atmospheric pressure, i.e. in the direction of natural air-flow. These fans often work with high air temperatures in the event of a fire. The paper shows the performance of fans for high operating air temperatures, up to 400 °C. The results were obtained through numerical simulations of the flow in an original design fan, whose performance was experimentally determined for normal atmospheric operating conditions (p = 1.2 kg/m3). Performances are given for two fan speeds. Unnecessary corrections of the existing impeller design for use in jet fans for tunnel ventilation were also considered. [ABSTRACT FROM AUTHOR]

The article focuses on the metrics used for comparing greenhouse gases with focus on the Integrated Temperature Change Potential (IGTP). It states that the IGTP and global warming potentials (GWP) are asymptotically equal is the time horizon reaches infinity. It says that the IGTP is equal to the Sustained Global Temperature change Potential (SGTP) under standard assumptions when calculating GWPs.

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]

This paper describes the validation of the SimSphere SVAT model conducted at different ecosystem types in the USA and Australia. Specific focus was given to examining the models' ability in predicting Shortwave Incoming Solar Radiation (Rg), Net Radiation (Rnet), Latent Heat (LE), Sensible Heat (H), Air Temperature at 1.3m (Tair 1.3m) and Air Temperature at 50m (Tair 50m). Model predictions were compared against corresponding in situ measurements acquired for a total of 72 selected days of the year 2011 obtained from 8 sites belonging to the AmeriFlux (USA) and OzFlux (Australia) monitoring networks. Selected sites were representative of a variety of environmental, biome and climatic conditions, to allow for the inclusion of contrasting conditions in the model evaluation. The application of the model confirmed its high capability in representing the multifarious and complex interactions of the Earth system. Comparisons showed a good agreement between modelled and measured fluxes, especially for the days with smoothed daily flux trends. A good to excellent agreement between the model predictions and the in situ measurements was reported, particularly so for the LE, H, Tair 1.3m and Tair 50m parameters (RMSD= 39.47, 55.06 Wm-2, 3.23, 3.77°C respectively). A systematic underestimation of Rg and Rnet (RMSD=67.83, 58.69 Wm-2, MBE= 67.83, 58.69 Wm-2 respectively) was also found. Highest simulation accuracies were obtained for the open woodland savannah and mulga woodland sites for most of the compared parameters. Very high values of the Nash-Sutcliffe efficiency index were also reported for all parameters ranging from 0.720 to 0.998, suggesting a very good model representation of the observations. To our knowledge, this study presents the first comprehensive validation of Sim- Sphere, particularly so in USA and Australian ecosystem types. Findings are important and timely, given the rapidly expanding use of this model worldwide both as an educational and research tool. This includes ongoing research by different Space Agencies examining its synergistic use with Earth Observation data towards the development of global operational products. [ABSTRACT FROM AUTHOR]

The collision induced O2 complex, O2O2, is a very important trace gas in remote sensing measurements of aerosol and cloud properties. Some ground based MAX-DOAS measurements of O2O2 slant column density require correction factors of 0.75 ± 0.1 to reproduce radiative transfer modeling (RTM) results for a near pure Rayleigh atmosphere. One of the potential causes of this discrepancy is believed to be uncertainty in laboratory measured O2O2 absorption cross section temperature and pressure dependence, due to difficulties in replicating atmospheric conditions in the laboratory environment. This paper presents direct-sun (DS) and airborne multi-axis (AMAX) DOAS measurements of O2O2 absorption optical depths under actual Earth atmospheric conditions in two wavelength regions (335-390 nm and 435-490 nm). DS irradiance measurements were made by the research grade MFDOAS instrument from 2007-2014 at seven sites with significant pressure (778-1013hPa) and O2O2 profile weighted temperature (247-275 K) differences. Aircraft MAX-DOAS measurements were conducted by the University of Colorado AMAX-DOAS instrument on 29 January 2012 over the Southern Hemisphere subtropical Pacific Ocean. Scattered solar radiance spectra were collected at altitudes between 9 and 13.2 km, with O2O2 profile weighted temperatures of 231-244 K, and near pure Rayleigh scattering conditions. Due to the well defined DS air mass factors and extensively characterized atmospheric conditions during the AMAX-DOAS measurements, O2O2 "pseudo" absorption cross sections, σ, are derived from the observed optical depths and estimated O2O2 column densities. Vertical O2O2 columns are calculated from the atmospheric sounding temperature, pressure and specific humidity profiles. Based on the atmospheric DS observations, there is no pressure dependence of the O2O2 σ, within the measurement errors (3%). The two data sets are combined to derive peak σ temperature dependence of 360 and 477 nm absorption bands from 231-275 K. DS and AMAX derived peak σ(O2O2) as a function of T can be described by a quadratic function at 360 nm and linear at 477 nm with about 9 ± 2.5% per 44 K rate. Recent laboratory measured O2O2 cross sections by Thalman and Volkamer (2013) agree with these "DOAS apparent" peak σ(O2O2) at 233 K, 253 K and 273 K within 3 %. Changes in the O2O2 spectral band-shape at colder temperatures are for the first time also observed in field data. Temperature effects on spectral band shapes can introduce errors in the retrieved O2O2 column abundances if a single room temperature σ(O2O2) is used in the DOAS analysis. Simultaneous fitting of σ(O2O2) at temperatures that bracket the ambient temperature range can reduce such errors. Our results suggest that laboratory measured σ(O2O2) (Hermans et al. (2011) at 296 K and Thalman and Volkamer (2013)) are applicable for observations over a wide range of atmospheric conditions. Column densities derived using Hermans et al. (2011) σ at 296 K require very small correction factors (0.94 ± 0.02 at 231 K and 0.99 ± 0.02 at 275 K) to reproduce theoretically calculated SCDs for DS and AMAX-DOAS measurements. Simultaneous fitting of σ(O2O2) at 203 and 293 K further improved results at UV and visible wavelengths for AMAX-DOAS. [ABSTRACT FROM AUTHOR]

This research incorporates the Monte Carlo Independent Column Approximation (McICA) scheme with the correlated k-distribution BCC-RAD radiation model into the climate model BCC_AGCM2.0.1 and examines the impacts on modeled climate through several simulations with variations in cloud structures. Results from experiments with consistent sub-grid cloud structures show that both clear-sky radiation fluxes and cloud radiative forcings (CRFs) calculated by the new scheme are mostly improved relative to those calculated from the original one. The modeled atmospheric temperature and specific humidity are also improved due to changes in the radiative heating rates. The vertical overlap of fractional clouds and horizontal distribution of cloud condensation are important for computing CRFs. The maximum changes in seasonal CRF using the general overlap assumption (GenO) with different decorrelation depths (Lcf) are larger than 10 and 20Wm2 for longwave (LW) CRF and shortwave (SW) CRF, respec15 tively, mostly located in the Tropics and mid-latitude storm tracks. Larger (smaller) Lcf in the Tropics (mid-latitude storm tracks) yield better cloud fraction and CRF compared with observations. The inclusion of an observation-based horizontal inhomogeneity of cloud condensation has a distinct impact on LW CRF and SW CRF, with global means of ∼1.2Wm-2 and ∼3.7Wm-2 at the top of atmosphere, respectively, making these much closer to observations. These results prove the reliability of the new model configuration to be used in BCC_AGCM2.0.1 for climate simulations, and also indicate that more detailed realworld information on cloud structures should be obtained to constrain cloud settings in McICA in the future. [ABSTRACT FROM AUTHOR]

The adsorption isotherm and the mechanism of the buffering effect are important controls on phosphorus behaviors in estuaries and are important for estimating phosphate concentrations in aquatic environments. In this paper, we derive phosphate adsorption isotherms in order to investigate sediment adsorption and buffering capacity for phosphorus discharged from sewage outfalls in the Yangtze Estuary and Hangzhou Bay near Shanghai, China. Experiments were also carried out at different temperatures in order to explore the buffering effects for phosphate. The results show that P sorption in sediments with low fine particle fractions was best described using exponential equations. Some P interactions between water and sediment may be caused by the precipitation of CaHPO4 from Ca2+ and HPO42- when the phosphate concentration in the liquid phase is high. Results from the buffering experiments suggest that the Zero Equilibrium Phosphate Concentrations (EPC0) vary from 0.014 mgl-1 to 0.061 mgl-1, which are consistent with measured phosphate concentrations in water samples collected at the same time as sediment sampling. Values of EPC0 and linear sorption coefficients (K) in sediments with high fine particle and organic matter contents are relatively high, which implies that they have high buffering capacity. Both EPC0 and K increase with increasing temperature, indicating a higher P buffering capacity at high temperatures. [ABSTRACT FROM AUTHOR]

Abstract: Mold deterioration of historical library materials in archives and libraries is a frequent and complex phenomenon that may have important economic and cultural consequences. Compactus shelving is one of the systems utilised for the conservation of library materials, because it allows for a more efficient use of space and protection against dust deposition. However, in the last ten years there have been many reports on single species mould infections within Compactus shelves in spite of conventional control of environmental temperature and humidity to recommended standards. Contamination was commonly characterized by white spots of mycelium, measuring 0.5–1.0 cm in diameter and observed on volume binding, especially those of leather, parchment or textile. Until now, the identification of the causal agent at species level has not been reported since attempts to grow it on media for subsequent identification were unsuccessful. Using a range of sampling techniques, including adhesive tape and nitrocellulose membrane, and a combination of conventional culturing methods, direct microscopic observations and molecular methods, we have for the first time identified to species level the fungus causing infections inside Compactus shelves. [Copyright &y& Elsevier]

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]

This paper presents a holistic approach to biological and agricultural research focused on the use of interconnected technologies in the context of climate change. Researchers from different countries have analyzed how smart technologies can help agriculture adapt to these changes. The most representative works in the field are analyzed. Among these technologies are graph database systems such as Neo4j, which have demonstrated success in predicting the studied phenomena. The paper describes the development of a soybean crop productivity prediction model using monthly and annual data of meteorological phenomena such as precipitation, air temperature, hydrothermal coefficient, soil moisture and others. Some of the results of this promising research are also presented. [ABSTRACT FROM AUTHOR]

A new, two-layer canopy module with thermal inertia as part of the detailed snow model SNOWPACK (version 3.2.1) is presented and evaluated. This module is designed to reproduce the difference in thermal response between leafy and woody canopy elements, and their impact on the underlying snowpack energy balance. Given the number of processes resolved, the SNOWPACK model with its enhanced canopy module constitutes a very advanced, physics-based atmosphere-to-soil-through-canopy-and-snow modelling chain. Comparisons of modelled sub-canopy thermal radiation to stand-scale observations at an Alpine site (Alptal, Switzerland) demonstrate the improvements of the new canopy module. Both thermal heat mass and the two-layer canopy formulation contribute to reduce the daily amplitude of the modelled canopy temperature signal, in agreement with observations. Particularly striking is the attenuation of the night-time drop in canopy temperature, which was a key model bias. We specifically show that a single-layered canopy model is unable to produce this limited temperature drop correctly. The impact of the new parameterizations on the modelled dynamics of the subcanopy snowpack is analysed and yields consistent results but the frequent occurrence of mixed-precipitation events at Alptal prevents a conclusive assessment of model performance against snow data. The new model is also successfully tested without specific tuning against measured tree temperatures and biomass heat storage fluxes at the boreal site of Norunda (Sweden). This provides an independent assessment of its physical consistency and stresses the robustness and transferability of the parameterizations used. [ABSTRACT FROM AUTHOR]

There have been fruitful publications on thermal comfort of urban residential buildings in China. However, there is a lack of reviews on this topic to perform a comprehensive analysis and find opportunities to meet occupants' thermal comfort needs while improving building energy efficiencies. This paper addresses this issue by presenting a systematic review on the advancements in research on thermal comfort in urban residential buildings in China. Firstly, two common thermal comfort research approaches, i.e., field studies and laboratory studies, are discussed. Secondly, eleven main thermal comfort evaluation indicators are summarized. Finally, this paper analyzes the thermal comfort survey data from different researchers, discusses the impacts of adaptive behaviors on human thermal comfort, and provides recommendations for future research on urban residential thermal comfort. It was found that people have higher and higher requirements for their indoor thermal environment as time goes by, especially in the winter; the thermoneutral temperature is higher in warmer climate regions in the summer but lower in the winter than in colder climate regions; the thermoneutral temperature tends to increase with the indoor air temperature due to an adaptation to the indoor thermal environment. The outcomes of this paper provide valuable information on thermal comfort behaviors of urban residents in different climate zones in China, which can serve as a resource for the academic community conducting future research on thermal comfort and assist policymakers in enhancing building energy efficiencies without compromising the occupants' comfort. [ABSTRACT FROM AUTHOR]

This paper describes the metrological procedure carried out for the evaluation of the building influence on air temperature measurements. This evaluation aims to produce reliable conclusions, information, and data to contribute to the WMO siting classification schemes for air temperature measurements. For this purpose, a field experiment was designed, deployed, and carried out. As a result, one-year-lasting air temperature measurements were collected and analyzed. In this field experiment, a 200 m wide building is the unique artificial heat source and the unique object projecting shades over a flat surface (no discernible slope) in an open space bigger than 40,000 m2, covered with short grass. Eight calibrated thermometers, equipped with the same model of artificially ventilated radiation shields, were set up at a height of 1.5 m from the ground and at different distances from a 200 m wide building. This configuration provides the observation of the horizontal air temperature radially distributed from the building and, as a conclusion, it enables the quantification of the building influences on air temperature measurements at different distances from the building. This document describes the field experiment, the analysis procedure, the evolution of the building influence on air temperature measurements along the day, and the impact of other meteorological parameters on this building effect. Two different building effects are observed: the positive building effect, where the air temperature decreases with the distance to the building, and the negative building effect, where the air temperature increases with the distance to the building. It is also noticed that the building influence is higher on clear days and the daily maximum building influence values are directly linked with the corresponding maximum solar irradiance. The influence of wind on the building effect is also analyzed, reaching the conclusion that due to characteristic of local winds, in terms of low speed and direction, the wind impact could be considered as negligible. The maximum values of building influence on air temperature measurements, the associated uncertainty analysis, and the conclusions are presented in this paper. All these points have been addressed using metrological principles with the purpose of giving consistency and robustness to the evidence presented here. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is changing the Earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose of investigating future hazards. BARPA-R, a limited-area model, has a 17 km horizontal grid spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA5 reanalysis. Here, an assessment of this evaluation experiment is provided. Performance-based evaluation results are benchmarked against ERA5, with comparable performance between the free-running BARPA-R simulations and observationally constrained reanalysis interpreted as a good result. First, an examination of BARPA-R's representation of Australia's surface air temperature, precipitation, and 10 m winds finds good performance overall, with biases including a 1 ∘ C cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm per month in inland Australia. Recent trends in daily maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in precipitation show underestimated wetting in northern Australia. Precipitation and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10 m winds are improved over ERA5 in six out of eight of the Australian regions considered. Secondly, the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the South Pacific Convergence Zone (SPCZ), the Northwest Cloudband, and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extratropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 global climate models (GCMs). [ABSTRACT FROM AUTHOR]

Energy has an effective role in economic growth and development of societies. This paper is studying the impact of climate factors on performance of solar power plant using machine learning techniques for underlying relationship among factors that impact solar energy production and for forecasting monthly energy production. In this context this work provides two machine learning methods: ANN for forecasting energy production and decision tree useful in understanding the relationships in energy production data. Both structures have horizontal irradiation, sunlight duration, average monthly air temperature, average maximal air temperature, average minimal air temperature and average monthly wind speed as inputs parameters and the energy production as output. Results have shown that used machine learning models perform effectively, ANN predicted the energy production of the PV power plant with a correlation coefficient higher than 0.97. The results can help stakeholders in determining energy policy planning in order to overcome uncertainties associated with renewable energy resources. [ABSTRACT FROM AUTHOR]

The mobile ocean weather observation system, named Marine Weather Observer (MWO), developed by the Institute of Atmospheric Physics (IAP), consists of a fully solar-powered, unoccupied vehicle and meteorological and hydrological instruments. One of the MWOs completed a long-term continuous observation, actively approaching the center of Typhoon Sinlaku from 24 July to 2 August 2020, over the South China Sea. The in situ and high-temporal-resolution (1 min) observations obtained from MWO were analyzed and evaluated through comparison with the observations made by two types of buoys during the evolution of Typhoon Sinlaku. First, the air pressure and wind speed measured by MWO are in good agreement with those measured by the buoys before the typhoon, reflecting the equivalent measurement capabilities of the two methods under normal sea conditions. The sea surface temperature (SST) between MWO and the mooring buoys is highly consistent throughout the observation period, indicating the high stability and accuracy of SST measurements from MWO during the typhoon evolution. The air temperature and relative humidity measured by MWO have significant diurnal variations, generally lower than those measured by the buoys, which may be related to the mounting height and sensitivity of sensors. When actively approaching the typhoon center, the air pressure from MWO can reflect some drastic and subtle changes, such as a sudden drop to 980 hPa, which is difficult to obtain by other observation methods. As a mobile meteorological and oceanographic observation station, MWO has shown its unique advantages over traditional observation methods, and the results preliminarily demonstrate the reliable observation capability of MWO in this paper. [ABSTRACT FROM AUTHOR]

The environmental temperature and humidity are crucial factors for the normal growth and development of arbor tree cuttings by altering their hormone levels and influencing their physiological activities. Developing a temperature and humidity environmental model for arbor tree cuttings serves as a key technique to improve the adjustment performance of environmental parameters in facility agriculture systems and enhance the rooting rate of cuttings. This paper provides a comprehensive summary of current research on the inherent characteristics of cuttings and the factors influencing environmental temperature and humidity. It explores the mechanisms of interaction between the inherent characteristics of cuttings and the factors influencing environmental temperature and humidity. This paper investigates the interactive relationships among the factors affecting environmental temperature and humidity. It analyzes methods to improve the efficiency of constructing temperature and humidity environmental models for arbor tree cuttings. To enhance the transferability of the environmental model, the necessary physiological activities under the influence of plant hormones are generalized as common physiological traits in the growth and development of cuttings. In addition, this paper explores the factors influencing the air and substrate temperature and the humidity in facility agriculture systems as well as two types of facilities for controlling environmental temperature and humidity. Furthermore, it reviews the research progress in environmental models from both mechanistic and data-driven perspectives. This paper provides a comparative analysis of the characteristics associated with these two model categories. Building upon this, the paper summarizes and discusses methods employed in constructing temperature and humidity environmental models for arbor tree cuttings. In addition, it also anticipates the application of deep learning techniques in the construction of temperature and humidity environmental models for arbor cuttings, including utilizing machine vision technology to monitor their growth status. Finally, it proposes suggestions for building physiological models of fruit tree-like arbor cuttings at different growth stages. To enhance the transferability of environmental models, the integration of physiological models of cuttings, environmental models, and control system performance are suggested to create an environmental identification model. This paper aims to achieve control of the common physiological activities of cuttings. [ABSTRACT FROM AUTHOR]

In this paper, desorption isotherms of two jerky products were studied (whole-muscle jerky -- sample 1 and minced jerky -- sample 2). The work focused on the comparison of the Dynamic Dewpoint Isotherm (DDI) method and the Saturated Salt Slurry (SSS) method and testing the newly applied model for modelling desorption isotherms for dried meat. Data were statistically processed using 8 models [Guggenheim-Anderson-de Boer (GAB), Double Log Polynomial (DLP), Henderson, Chin, Smith, Oswin, Hasley, and newly applied model] and statistically evaluated using coefficient of determination (R2), root mean squared error (RMSE) and mean relative percentage deviation (P-value). The DLP model (25 °C) reached R² ≥ 0.999, P-value ≤ 1.84 for DDI, and R2 ≥ 0.998, P-value ≤ 4.37 for SSS method. The GAB model reached R² ≥ 0.997, P-value ≤ 2.58 for DDI, and for SSS method the GAB model reached R² ≥ 0.998, P-value ≤ 5.47. The new model reached P-value ≤ 5.73 for DDI and P-value ≤ 3.48 for SSS method. All models reached the P-value < 10% except for Smith and Chin models. The DDI method and newly applied model prove to be a suitable and precise approach to the evaluation of isotherms of dried meat products. [ABSTRACT FROM AUTHOR]

The article focuses on a study which aims at assessing Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation retrieval product. In the study, radiosonde data is used to verify radio occultation retrieval product of the COSMIC radio sounding system. It shows similarities in the temperature data from COSMIC with the radiosonde data.

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]

The global burden of carbon monoxide, CO, is rather uncertain. In this paper we address the potential of UV-induced CO emission by terrestrial surfaces. Real-time measurements of [CO] were made with a cavity enhanced laser connected in closed loop to either an ecosystem chamber or a leaf scale chamber. Sand and leaves of all examined plant species exhibited emission of CO in response to artificial UV-radiation and the UV-component of natural solar radiation. The UV-induced rate of CO emission exhibited a rather low dependence on temperature, indicating an abiotic process. The emission of CO in response to the UV-component of natural solar radiation was also evident at the ecosystem scale. When scaled to the global level, the UV-induced emission of CO by the major types of terrestrial surfaces, living leaves and soil (here represented by sand), amounts up to 28 Tgyr-1. This source has till now not been accounted for by IPCC, but is equivalent to 14-56% of the 50-200 Tgyr-1 from sources currently accounted for (IPCC 2001). In addition to this are other known sources that ought to be considered. The hitherto unaccounted for terrestrial sources of CO amounts up to 207 Tgyr-1 , almost two-thirds of the latest estimated global CO burden of 360 Tgyr-1 (IPCC, 2001). [ABSTRACT FROM AUTHOR]

The article presents a study on the effect of land use induced land cover change (LULCC) on temperature and rainfall extremes. It states that four climate models within the land use and climate, identification of robust impacts (LUCID) project protocol were used. It concludes that there is a similarity between the changes in temperature extremes and mean temperature caused by LULCC.

The article discusses the interpretation and definition of quantities relating to climate sensitivity in the discussions paper "Climate sensitivity in the Anthropocene," by M. Previdi and colleagues. It states that the paper brought several errors and inconsistencies in the discussion of climate sensitivity. It says that definition of temperature which denoted surface temperature was inconsistent.

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The commonly used reference atmospheric profiles for the validation of retrieved atmospheric profiles for microwave sounders have bias compared with real atmospheric profile values, which is detrimental to the validation of the retrieval. Microwave sounder observations are the direct measurements of microwave radiation in atmospheric conditions and are a true representation of the status of the atmosphere. This paper proposed a validation method for the retrieved atmospheric temperature and atmospheric humidity profiles of the satellite-based microwave sounder using its own in-orbit observations. The validation experiments are performed both for the retrievals of the microwave temperature sounder-II (Xi'an Branch, China Academy of Space Technology, Xi'an, China. MWTS-II) and the microwave humidity and temperature sounder (National Space Science Center, Chinese Academy of Sciences, Beijing, China. MWHTS). The validation results show that the retrieved temperature profiles of MWTS-II have higher accuracy compared to the temperature profiles of ERA5 in the atmospheric pressure range of 3–30 hPa, and the accuracy of the rest of the pressure range is comparable between the profiles of ERA5 and the retrieved profiles. And the retrieved temperature profiles of MWHTS have higher accuracy compared to the temperature profiles of ERA5 in the atmospheric pressure level around 50 hPa and lower accuracy in the rest of the pressure levels. In addition, the retrieved humidity profiles of MWHTS have higher accuracy compared to the humidity profiles of ERA5 in the atmospheric pressure range of 350–925 hPa. The proposed validation method for the retrieved atmospheric temperature and atmospheric humidity profiles of MWHTS using its own observations is promising for improving the feasibility and reliability of the validation, and can be a good reference for the application of the satellite in-orbit observations and the optimization of the microwave sounders. [ABSTRACT FROM AUTHOR]

Steel structures with light weight, high rigidity, and easy assembly have become the first choice for large-span complex building materials. At the same time, transparent materials are widely used for the sake of practicality and aesthetics. However, steel structures will be deformed due to changes in temperature, which will affect the accuracy of closure. The components are restricted from free deformation as a result of multiple statically indeterminate structures. A safety hazard will occur if the residual temperature stress is not released. At present, the strain law of open-air steel structures caused by temperature change is still unclear, and the corresponding temperature–strain model has not been established. This paper is based on the third-phase reconstruction and expansion project of Taiyuan Wusu Airport in Xiaodian District, Taiyuan City, Shanxi Province (37°45′ N, 112°38′ E, average altitude of 774 m), winter long time series temperature measured data, deduced daily temperature change laws, and the established relationship model between air temperature and steel surface temperature. Based on the measured data of long-term stress and strain in winter, the strain law of open-air steel columns under temperature change is discussed. According to the results, the air temperature can be utilized to determine the strain of the open-air steel column during winter. The determination coefficient of the temperature–stress model can reach 0.868, and the radial bending stress caused by the change in daily temperature cannot be ignored, accounting for 15.7% of the radial stress at the same time, which can provide a reference for stress calculations of similar structures. [ABSTRACT FROM AUTHOR]

Agricultural sustainability is dependent on the ability to predict crop yield, which is vital for farmers, consumers, and researchers. Most of the works used the amount of rainfall, average monthly temperature, relative humidity, etc. as inputs. In this paper, an attempt was made to predict the yield of the citrus crop (Washington Navel orange, Valencia orange, Murcott mandarin, Fremont mandarin, and Bearss Seedless lime) using weather factors and the accumulated heat units. These variables were used as input parameters in an artificial neural network (ANN) model. The necessary information was gathered during the growing seasons between 2010/2011 and 2021/2022 under Egyptian conditions. Weather factors were daily precipitation, yearly average air temperature, and yearly average of air relative humidity. A base air temperature of 13.0 °C was used to determine the accumulated heat units. The heat use efficiency (HUE) for cultivars was determined. The Bearss Seedless lime had the lowest HUE of 9.5 kg/ha °C day, while the Washington Navel orange had the highest HUE of 20.2 kg/ha °C day. The predictive performance of the ANN model with a structure of 9-20-1 with the backpropagation was evaluated using standard statistical measures. The actual and estimated yields from the ANN model were compared using a testing dataset, resulting in a value of RMSE, MAE, and MAPE of 2.80 t/ha, 2.58 t/ha, and 5.41%, respectively. The performance of the ANN model in the training phase was compared to multiple linear regression (MLR) models using values of R2; for MLR models for all cultivars, R2 ranged between 0.151 and 0.844, while the R2 value for the ANN was 0.87. Moreover, the ANN model gave the best performance criteria for evaluation of citrus yield prediction with a high R2, low root mean squared error, and low mean absolute error compared to the performance criteria of data mining algorithms such as K-nearest neighbor (KNN), KStar, and support vector regression. These encouraging outcomes show how the current ANN model can be used to estimate fruit yields, including citrus fruits and other types of fruit. The novelty of the proposed ANN model lies in the combination of weather parameters and accumulated heat units for accurate citrus yield prediction, specifically tailored for Egyptian regional citrus crops. Furthermore, especially in low- to middle-income countries such as Egypt, the findings of this study can greatly enhance the reliance on statistics when making decisions regarding agriculture and climate change. The citrus industry can benefit greatly from these discoveries, which can help with optimization, harvest planning, and postharvest logistics. We recommended furthering proving the robustness and generalization ability of the results in this study by adding more data points. [ABSTRACT FROM AUTHOR]

Aiming at the problems of large error and redundancy in the multi-node data acquisition of multi-greenhouse photo growth environmental information, a three-level fusion algorithm based on adaptive weighting, an LMBP network, and an improved D-S theory is proposed. The box-and-line graph method recognizes the original data and then replaces it based on the mean value method; the air temperature, humidity, and light intensity measurements are unbiased estimations of the true value to be estimated, so the first level of fusion chooses the adaptive weighted average algorithm to find the optimal weights of each sensor under the condition of minimizing the total mean-square error and obtains the optimal estimation of the weights of the homogeneous sensors of a greenhouse. The Levenberg–Marquardt algorithm was chosen for the second level of fusion to optimize the weight modification of the BP neural network, i.e., the LMBP network, and the three environmental factors corresponding to "suitable", "uncertain" and "unsuitable" potato growth environments were trained for the three environmental factors in the reproductive periods. The output of the hidden layer was converted into probability by the Softmax function. The third level is based on the global fusion of evidence theory (also known as D-S theory), and the network output is used as evidence to obtain a consistent description of the multi-greenhouse potato cultivation environment and the overall scheduling of farming activities, which better solves the problem of the difficulty in obtaining basic probability assignments in the evidence theory; in the case of a conflict between the evidence, the BPA of the conflicting evidence is reallocated, i.e., the D-S theory is improved. Example validation shows that the total mean square error of the adaptive weighted fusion value is smaller than the variance of each sensor estimation, and sensors with lower variance are assigned lower weights, which makes the fusion result not have a large deviation due to the failure of individual sensors; when the fusion result of a greenhouse feature level is "unsuitable", the fusion result of each data level is considered comprehensively, and the remote control agency makes a decision, which makes full use of the complementary nature of multi-sensor information resources and solves the problem of fusion of multi-source environmental information and the problem of combining conflicting environmental evaluation factors. Compared with the traditional D-S theory, the improved D-S theory reduces the probability of the "uncertainty" index in the fusion result again. The three-level fusion algorithm in this paper does not sacrifice data accuracy and greatly reduces the noise and redundancy of the original data, laying a foundation for big data analysis. [ABSTRACT FROM AUTHOR]

We implement a new stomatal conductance model, based on the optimality approach, within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. Coupled land-atmosphere simulations are then performed using CABLE within the Australian Community Climate and Earth Systems Simulator (ACCESS) with prescribed sea surface temperatures. As in most land surface models, the default stomatal conductance scheme only accounts for differences in model parameters in relation to the photosynthetic pathway, but not in relation to plant functional types. The new scheme allows model parameters to vary by plant functional type, based on a global synthesis of observations of stomatal conductance under different climate regimes over a wide range of species. We show that the new scheme reduces the latent heat flux from the land surface over the boreal forests during the Northern Hemisphere summer by 0.5 to 1.0 mm day-1. This leads to warmer daily maximum and minimum temperatures by up to 1.0 °C and warmer extreme maximum temperatures by up to 1.5 °C. These changes generally improve the climate model's climatology and improve existing biases by 10-20 %. The change in the surface energy balance also affects net primary productivity and the terrestrial carbon balance. We conclude that the improvements in the global climate model which result from the new stomatal scheme, constrained by a global synthesis of experimental data, provide a valuable advance in the long-term development of the ACCESS modelling system. [ABSTRACT FROM AUTHOR]

We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leaf trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models. [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]

The paper examines outdoor thermal comfort in summer in the multi-family housing area Duvanište in the city of Niš, Serbia, combining objective and subjective evaluation assessments. Objective evaluation obtained field measurements of microclimatic parameters at selected sites and mean radiant temperature, predicted mean vote, and psychological equivalent temperature calculation using RayMan software. Subjective methodology assessment is performed using survey questionnaires based on thermal sensation vote and overall comfort vote. The paper aims to find the correlation between measured and calculated parameters on one side and Thermal Sensation Vote values. The results show that air temperature signifi- cantly correlates to human thermal sensation in the subject area. Obtained results also indicate high prediction accuracy of psychological equivalent temperature in the outdoor thermal comfort evaluation in summer. Finally, to feel comfortable, neither warm nor cold, in continental climate regions with hot summer conditions, the neutral psychological equivalent temperature should be between 15-24.3 °C. [ABSTRACT FROM AUTHOR]

This paper considers subsonic turbojet aircraft fuel consumption minimization problem during cruise phase, assuming fixed time of arrival. The problem takes into account real atmosphere data. We utilize tailwind/headwind component values at various flight levels, as well as air temperatures and atmospheric pressures at various altitudes. The solution to the altitude and speed flight profile optimization problem is through constrained coordinate descent method. The paper considers optimizing the fuel consumption of a medium-haul aircraft during the cruise phase using sample data set on temperature, pressure, and wind speed. The proposed approach achieves a decrease in fuel consumption of 1.2% when optimizing with regard to real atmosphere. [ABSTRACT FROM AUTHOR]

In order to improve the design effect of venues, this paper establishes the evaluation model of indoor thermal comfort for the humid and hot subtropical areas, which provides theoretical reference for venue design. This paper investigates the thermal sensation of basketball players by questionnaire, analyzes the relationship between thermal sensation vote and standard effective temperature, predicted mean vote, and wet bulb globe temperature, and develops an index called predicted thermal sensation by using the least square method. The relationship between outdoor air temperature and indoor working temperature under neutral conditions is obtained by measuring data. The results show that the correlation between thermal sensation vote and air temperature is the strongest, R² is 0.753, while the relationship between thermal sensation vote and air speed is weak, R² is 0.012. Thermal sensation vote and set, predicted mean vote and wet bulb globe temperature are not suitable for athletes in the field environment. [ABSTRACT FROM AUTHOR]

Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by e.g. topography and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that leverages the good description of the atmospheric column provided by climate models, together with high resolution DEM's, to derive a consistent topography-based, scaling of coarse grid climate variables to fine-scale. We test the method together with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure-levels: air temperature, relative humidity, wind speed and incoming longwave radiation. It is expected that this method can be used to improve inputs to numerical simulations in complex and/or remote terrain especially when statistical methods are not possible due to lack of observations i.e. remote areas or future periods. [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 focuses on a study which aims at analyzing the effect of atmospheric water vapor in detecting turbulence based on the Thorpe method. It describes the Thorpe method in which potential temperature and density are sorted in ascending order. It concludes increase in turbulent faction of the troposphere during saturation of atmospheric water vapor.