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Adsorption isotherms of 3 selected paper-based packaging materials, that is, vegetable parchment (VP) paper, Kraft paper, and solid-bleached-sulfate (SBS) paperboard, were determined at 3 different temperatures (25, 40, and 50 °C). The GAB isotherm model was found to fit adequately for describing experimental adsorption isotherm data for the paper samples. The monolayer moisture content of the paper samples decreased with increase in temperature, which is in the range of 0.0345 to 0.0246, 0.0301 to 0.0238, and 0.0318 to 0.0243 g water/g solid for the MG paper, the Kraft paper, and the SBS paperboard, respectively. The net isosteric heats of sorption ( qst) for the paper samples decreased exponentially with increase in moisture content after reaching the maximum values of 18.51, 27.39, and 26.80 kJ/mol for the VP paper, the Kraft paper, and the SBS paperboard, respectively, at low-moisture content. The differential enthalpy and entropy of 3 paper samples showed compensation phenomenon with the isokinetic temperature of 399.7 K indicating that water vapor had been adsorbed onto the paper samples with the same mechanism. Depending on the paper material, tensile strength of paper samples was affected by moisture content. [ABSTRACT FROM AUTHOR]

Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM‐LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM‐LIN method improved R2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM‐LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation. Plain Language Summary: Natural hazards, such as flooding and extreme heat, can damage our infrastructure and local communities. These hazards often stem from extreme weather conditions such as heavy precipitation and hot temperatures. Global climate change is expected to affect precipitation and air temperature, leading to more extreme weather events and hazards in the future. Predicting frequency and severity of these future events is key to protect our infrastructure and communities. Climate models have been widely used to project statistics of future extremes. However, they come with uncertainties due to numerical approximations, low spatial resolutions etc. Consequently, predictions generated by these models are inherently uncertain. This paper used a new approach to improve future projections of extreme climatic events, focusing on South Florida. Our findings revealed substantial improvements in projecting future events, particularly for extreme precipitation. We also showed that nationally and globally derived simulations may not be suitable for accurately projecting heavy precipitation, but can suffice for air temperature and low/medium precipitation rates. This paper offers promising avenues for refining projections of future weather events. By enhancing our ability to anticipate upcoming weather events more accurately, we can better protect our infrastructure and communities against the challenges posed by climate change. Key Points: A hybrid statistical approach to improve bias correction of GCM precipitation and air temperature simulationsMajor improvements in both climatic variables, especially extreme precipitation, using our hybrid statistical approach in South FloridaCoarse resolution downscaled data may be insufficient for deriving high quantile precipitation at the regional scale [ABSTRACT FROM AUTHOR]

In 2020, Komarabathina and colleagues published the paper above (the original paper). They used the Liagora viscida‐based biosorbent for adsorbing nickel ions from water. Kinetics, isotherm, and thermodynamics are three important components for the correct description of an adsorption process. However, the authors of the original paper introduced several fundamental errors in these three parts. Other important problems in the original paper are inconsistencies between the experimental data and their modeling results, as well as errors in units. Therefore, we present detailed analyses of these mistakes, hoping that this "comment" paper will also be useful to other researchers (especially beginners) to avoid finding such mistakes elsewhere in the future. [ABSTRACT FROM AUTHOR]

The sporadic E‐layer (Es) exhibits unique opportunity for exploring the coupling from lower to upper atmosphere. It was found that the East Asia is with the highest intensity and occurrence probability of Es. By using the long‐term data of 21 ionosonde stations in China and Japan over the past 60 yrs, this paper explores the probable control on the Es layer from the lower layers. It is found that the intensity of the Es layer is strongly correlated with the surface atmospheric temperature, terrain, and land‐sea boundary. The correlation coefficient of the intensity of Es with surface temperature is as high as 0.8204, while that with the terrain and land‐sea boundary is up to 0.6668. Based on the coupling between the lower and upper atmosphere, this paper reveals the probable controls from lower layers on the intensity of the Es in East Asia. Plain Language Summary: As an occasional ionized layer of the ionosphere, the sporadic E‐layer (Es) exhibits unique opportunity for exploring the coupling from lower to upper atmosphere. Despite extensive research on both behavior and mechanism of the Es, none have adequately explained the strong inhomogeneous of its global morphology. It is found in fact that the East Asia is with the highest intensity and occurrence probability of Es. By using the long‐term data of 21 ionosondes in China and Japan over the past 60 yrs, this letter explores the formation mechanism of the strongest Es regions in the world. It is found that the intensity of the Es layer is strongly correlated with the surface atmospheric temperature, terrain, and land‐sea boundary. The correlation coefficient between the intensity of Es and surface temperature is highest, while that with the terrain and land‐sea boundary is also high. By analyzing the data as long as six decades, this letter reveals the probable controls from lower layers on the intensity of the Es in East Asia. Key Points: By analyzing the six‐decade data of 21 ionosondes in East Asia, it reveals probable controls on the strongest Es layer from lower layersFor the first time, it is found that the intensity of Es layer is highly correlated with the surface atmospheric temperatureAn interesting coupling from lower to upper atmosphere may be found by taking advantage of observations longer than half of a century [ABSTRACT FROM AUTHOR]

Dust particles suspended in the dusty Martian atmosphere are prone to being charged. In this paper, we investigate the effect of the net charges carried by dust particles on the radiative properties of Martian dust. We find that net charges carried by dust particles significantly alter the extinction properties and single scattering albedo of dust at thermal infrared radiation band, which results in an enhancement of the infrared heating rate, up to 6.36%. We show that the discrepancy between the atmospheric temperature predicted by the Mars Atmosphere Model and the one detected during the Mars rover landing is reduced to within 11% when the effect of the net charges carried by the dust is considered. Therefore, it is essential to consider the effect of the net charges carried by dust particles for an accurate characterization of the atmospheric temperature. Plain Language Summary: Dust suspended in the atmosphere has long been considered as an important factor in altering Mars atmospheric temperature. The suspended Martian dust particles can scatter and absorb solar radiation and thermal infrared radiation, and their heating effect on the atmosphere is significant. The variation of the size and opacity of Martian dust with altitude affecting the interaction of dust particles with solar visible and infrared radiation has been extensively studied. However, the dust suspended in the Martian atmosphere are prone to being charged, and the effect of the net charges carried by the dust on the radiation effect has been neglected in existing studies. Therefore, we investigate the effect of the net charges carried by dust particles on the radiative properties of Martian dust. We find that the net charge carried by dust particles leads to a significant enhancement of the heating rate. In addition, the atmospheric temperature predicted by the atmospheric model is much closer to the one measured during the Mars rover landing when the effect of the net charge carried by the dust is considered. Key Points: Radiation properties of Martian dust change drastically when these particles are chargedThe net charges carried by dust contribute significantly to the Martian atmosphere heating rateThe difference between the observed and model‐predicted atmospheric temperatures is reduced when the effect of dust charging is considered [ABSTRACT FROM AUTHOR]

In this paper we present the results of quality control and homogenization procedures applied to long time series of daily atmospheric precipitation sums (Rr) and daily mean (Tm), maximum (Tx) and minimum (Tn) air temperature collected in Ukraine. The daily data from 178 meteorological stations covering the period of 1946–2020 were analysed. In order to perform a thorough quality assurance check, we used the R package INQC, while the Climatol homogenization software was used to detect and remove breaks from the time series. The INQC quality assurance tests revealed a relatively small number of erroneous records (around 0.01% for each variable) and suspicious values (up to 0.09%). The application of Climatol resulted in 195, 296, 355 and 359 break points, detected for Rr, Tm, Tx and Tn, respectively. These quantities coincide roughly with the results of the HOMER homogenization procedure applied to monthly time series for the same stations and almost the same period (performed in the previous works of the authors). To verify the homogenization results, statistical comparison of the raw and homogenized time series was performed. The verification demonstrated that the quality control and homogenization procedures detected and removed errors and breaks very well, and air temperature and precipitation fields after the homogenization are more self‐consistent compared to the original raw data. [ABSTRACT FROM AUTHOR]

The onset of periods with very high or low air temperatures has aroused general interest for a long time, which is understandable since it has many dangerous effects directly affecting humans. Such perilous climatic phenomena include exceptionally cold and exceptionally warm months, which this study investigates for all Europe and for its five physico‐geographic regions over the 190‐year period of 1831–2020. Therefore, the research in this paper includes two periods characteristic of the history of climate – the late Little Ice Age (LIA) and present‐day warming. The studies are based on average monthly air temperature values from 40 weather stations in Europe. In this paper, exceptionally cold months (ECMs) or exceptionally warm months (EWMs) are considered to have occurred when the average air temperature at a station differed from the respective long‐term average by at least two standard deviations. The highlights of the study include the identification of a drop in the number of ECMs by 20 over the entire 190‐year period, and a highly statistically significant increase in EWMs by 44 between 1980 and 2020. These changes proceeded with different intensities from one physico‐geographic region of Europe to another. [ABSTRACT FROM AUTHOR]

The ability of satellite instruments to accurately observe long‐term changes in atmospheric temperature depends on many factors including the absolute accuracy of the measurement, the stability of the calibration of the instrument, the stability of the satellite orbit, and the stability of the numerical algorithm that produces the temperature data. We present an example of algorithm instability recently discovered in the temperature data set from the SABER instrument on the NASA TIMED satellite. The instability resulted in derived temperatures that were substantially colder than anticipated from mid‐December 2019 to mid‐2022. This algorithm‐induced change in temperature over 1 to 2 years corresponded to the expected temperature change over several decades from increasing anthropogenic CO2. This paper highlights the importance of algorithm stability in developing Geospace Data Records (GDRs) for Earth's mesosphere and lower thermosphere. A corrected version (Version 2.08) of the temperatures from SABER is described. Plain Language Summary: Instruments on Earth orbiting satellites offer the opportunity to detect long‐term changes in atmospheric temperature. Many factors may affect the ability to identify actual long‐term changes in the temperature and to distinguish these from changes in the instrument or from unintended changes in the algorithm that produces the temperature data from the instrument observations. SABER is an instrument on a NASA satellite that has been observing temperatures from 15 to 110 km (10–68 miles) in altitude for over 20 years. An "instability" in the scientific algorithm used to derive temperature from the instrument observations was recently discovered, beginning in late 2019. An unintended change was made in a parameter central to the derivation of temperature from SABER measurements. The consequence was that the atmospheric temperatures between 85 and 110 km (51–68 miles) from 2020 onward were several degrees colder than they would have been without the unintended change. This has been corrected and an updated version of the SABER temperatures and all other SABER data products, called Version 2.08, is now publicly available. Key Points: The concept of Geospace Data Records (GDRs) and their relevance to accurate detection of long‐term change is introducedAlgorithm instability in a GDR of the 20‐year record of SABER temperatures between 85 and 110 km is described and correctedThe field of Geospace Climate is emerging as a frontier with scientific and economic relevance. Accurate GDRs are essential to both [ABSTRACT FROM AUTHOR]

In recent decades, the winter surface air temperature (SAT) anomaly in the Northern Hemisphere has exhibited a warm Arctic‐cold Eurasia (WACE) dipole pattern and this has undergone significant decadal variation. In this paper, the physical cause of the decadal variability of the WACE pattern is explored, and it is shown to be mediated by the phases of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO). Although the negative PDO (PDO−) or positive AMO (AMO+) favors the WACE pattern, the meridional structure of the pattern is significantly influenced by whether PDO− or AMO+ dominates. During PDO− (AMO+) phase, the winter‐mean WACE pattern shows an asymmetric dipole with weak (strong) warm anomaly over the Barents‐Kara Seas or BKS and strong (weak) cold anomaly over central Eurasia or Siberia, which corresponds to Ural blocking (UB) concurring with the negative (positive) phase of North Atlantic Oscillation in a winter‐mean field. The winter asymmetric WACE pattern is more strongly related to PDO− than AMO+. It is further found that an asymmetric sub‐seasonal WACE dipole pattern with strong (weak) warm anomaly over BKS and weak (strong) cold anomaly over Siberia is usually formed during the UB episode due to favored (suppressed) sub‐seasonal downward infrared radiation and turbulent heat flux over BKS during AMO+ (PDO−), which leads to a strong asymmetric dipole of the winter WACE pattern. Plain Language Summary: The most prominent climate change in the Northern Hemispheric mid‐high latitudes in recent decades is that the winter surface air temperature anomaly has exhibited a warm Arctic‐cold Eurasia (WACE) dipole pattern. However, it is still unknown what causes the decadal variability of the winter WACE pattern and its meridional asymmetry. In this paper, we address this issue by examining the different effects of Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) on the winter WACE pattern. It is shown that PDO− (AMO+) plays an important role in the occurrence of the asymmetric WACE dipole with weak (strong) warm anomaly over the Barents‐Kara Seas and strong (weak) cold anomaly over central Eurasia or Siberia through modulating Ural blocking and associated sub‐seasonal cold anomaly. It is also found that the asymmetric WACE dipole is more strongly dependent on PDO− than AMO+. Our findings are of great significance for understanding the physical cause of the decadal variability of the WACE dipole pattern in spatial structure. Key Points: Ural Blocking plays an important role in the occurrence of the sub‐seasonal warm Arctic‐cold Eurasia (WACE) dipole pattern in winterUral blocking can amplify the winter‐mean Warm Arctic‐cold Eurasia (WACE) patternWarm Arctic‐cold Eurasia (WACE) is linked to the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) [ABSTRACT FROM AUTHOR]

In this paper, we constructed the Exospheric Temperature Models (ETM) on the basis of CHAMP and GRACE data using different empirical orthogonal functions (EOFs). The EOFs of the exospheric temperature can be derived either from satellite data directly or from the outputs of the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) and MSIS models by applying the Principal Component Analysis method. Then, the thermospheric mass densities calculated from ETM are used to compare with the observed data in order to evaluate the performance of different ETM models. It was found that all these three models can provide good specification of thermospheric density including day‐night, seasonal, and latitudinal variations. However, the ETM based on CHAMP and GRACE data gives a better performance in modeling the Equatorial Thermospheric Anomaly and the Midnight Density Maximum features than the MSIS‐ETM and TIEGCM‐ETM. Specifically, independent SWARM‐C data comparison showed that the Relative Deviations and corresponding Root‐Mean‐Square‐Errors of our Texo models are less than 8.9% and 22.8%, much better than the MSIS‐00 model. Plain Language Summary: Exospheric temperature, the atmospheric temperature at an altitude above 300 km, is a critical parameter used in most thermospheric density models. In this study, we use different mathematical functions to construct the exospheric temperature models (ETM) named ETM, MSIS‐ETM, and Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM)‐ETM, respectively based on the CHAMP and GRACE density observations. The mathematical functions can be derived either using the data‐driven method or using the model‐driven method. Our purpose is to evaluate the performance of these constructed models in reflecting the thermosphere, and we found that all these models can provide good specification of the thermosphere such as the typical day‐night, seasonal, and latitudinal variation characteristics. Overall, the ETM constructed by using the data‐driven method gives a better performance than the MSIS‐ETM and TIEGCM‐ETM, and it can effectively simulate the physical features that are observed in the thermosphere. Our results indicate that compared with the model‐driven method utilizing the sufficient data‐driven PCA method to bend the exospheric temperature model is also an effective way. Key Points: Exospheric Temperature Models (ETM) are constructed on the basis of CHAMP and GRACE data using different empirical orthogonal functions (EOFs)The three ETM models can provide good specification of thermospheric density after they are embedded in the MSISThe ETM with EOFs directly from the observations gives a better performance than those with EOFs obtained from the MSIS and Thermosphere Ionosphere Electrodynamics General Circulation Model models [ABSTRACT FROM AUTHOR]

The annular structure of Antarctic oscillation (AAO) is a research hotpot, but its asymmetry receives less attention. In this paper, the self‐organizing map method is employed to cluster the AAO patterns into symmetric and asymmetric modes in austral autumn. The asymmetry is mainly reflected in the Pacific‐Atlantic sector, and the AAO evolves toward asymmetric positive polarity, with the most pronounced asymmetry in May. Originating from near Australia, the asymmetry indicates a zonal wave train in the Pacific‐Atlantic sector. Both modeled and observed results demonstrate that the sea surface temperature anomaly in the equatorial western Pacific stimulates a local meridional circulation anomaly and induces anomalous Rossby wave sources near Australia subsequently. An anomalous wave train propagating toward the Antarctic Peninsula is formed, and the associated geopotential anomaly enhances the asymmetry of AAO. Asymmetric AAO is conducive to the Antarctic dipole, which modulates the air temperature and sea ice anomalies around Antarctica. Plain Language Summary: The zonal symmetry of the Antarctic oscillation (AAO; also named southern annular mode) is well known to researchers, while the zonal asymmetry has received less attention. We use a clustering method to cluster the AAO modes in austral autumn into symmetric modes and asymmetric modes. The asymmetry of AAO is mainly reflected in the Pacific‐Atlantic sector. The results show that the AAO mode evolves to a positive asymmetric mode, and the asymmetry is most obvious in May. Both simulations and observations suggest that this asymmetry stems from sea surface temperature anomaly in the equatorial western Pacific that stimulates an anomalous local meridional circulation near Australia, and in turn triggers an anomalous wave train propagating toward the Antarctic Peninsula. The associated geopotential anomalies enhance the asymmetry of AAO. The asymmetric AAO favors the Antarctic dipole, regulating the air temperature and sea ice anomalies around Antarctica. Key Points: Via a cluster method, we obtained the zonal asymmetric Antarctic oscillation (AAO) mode, and analyzed its trend and preferred monthThe source of its asymmetry is from the sea surface temperature anomaly in the tropical western PacificThe asymmetric AAO mode has a vital influence on the Antarctic dipole [ABSTRACT FROM AUTHOR]

Detecting trace gases such as hydrogen chloride (HCl) in Mars' atmosphere is among the primary objectives of the ExoMars Trace Gas Orbiter (TGO) mission. Terrestrially, HCl is closely associated with active volcanic activity, so its detection on Mars was expected to point to some form of active magmatism/outgassing. However, after its discovery using the mid‐infrared channel of the TGO Atmospheric Chemistry Suite (ACS MIR), a clear seasonality was observed, beginning with a sudden increase in HCl abundance from below detection limits to 1–3 ppbv in both hemispheres coincident with the start of dust activity, followed by very sudden and rapid loss at the southern autumnal equinox. In this study, we have investigated the relationship between HCl and atmospheric dust by making comparisons in the vertical distribution of gases measured with ACS and aerosols measured co‐located with the Mars Climate Sounder (MCS). This study includes HCl, water vapor, and ozone measured using ACS MIR, water vapor and temperature measured with the near infrared channel of ACS, and temperature, dust opacity, and water ice opacity measured with MCS. In part 1, we show that dust loading has a strong impact in temperature, which controls the abundance of water ice and water vapor, and that HCl is very closely linked to water activity. In part 2, we investigate the quantitative correlations between each quantity and discuss the possible source and sinks of HCl, their likelihood given the correlations, and any issues arising from them. Plain Language Summary: After four full Martian years in orbit since 2018, the ExoMars Trace Gas Orbiter (TGO) has observed three Martian dusty seasons, which occur when it is spring and summer in the southern hemisphere. The first, starting in summer 2018, featured a global dust storm (GDS) after which we made the first detection of hydrogen chloride (HCl) in the Martian atmosphere using the Atmospheric Chemistry Suite (ACS) instrument. Finding this gas was a priority of ExoMars because its presence may indicate that the planet is volcanically active. Since then, we have observed two more dusty periods without a GDS and observed the reappearance of HCl each time. Here, we present the climatology of HCl in both hemispheres over these three dusty periods (in Mars years 34, 35, and 36) and investigate their relationships with temperature and water vapor measured by ACS, and with airborne dust and water ice measured with the Mars Climate Sounder (MCS) on the Mars Reconnaissance Orbiter (MRO). In this paper, we examine how the vertical structure of each quantity changes over time. We show that there is a close relationship between HCl and H2O, and that both are controlled by temperature, driven by dust loading. Key Points: Comparison of trace gas abundance and aerosol extinction between Atmospheric Chemistry Suite on ExoMars TGO and Mars Climate Sounder on Mars Reconnaissance OrbiterReveal the seasonal changes in hydrogen chloride on MarsShow that dust affects atmospheric temperature, which controls water vapor abundance and ice extinction, and thus impacts HCl abundance [ABSTRACT FROM AUTHOR]

In this paper, we describe the results of a climate data rescue (DARE) activity conducted at the Ukrainian Hydrometeorological Institute (Kyiv, Ukraine) in cooperation with the Justus Liebig University Giessen (Giessen, Germany), the World Meteorological Organization (WMO) and Met Office Hadley Centre (Exeter, United Kingdom). The focus of our work is on pre‐1850 sub‐daily meteorological observations conducted on the territory of modern Ukraine. Data from eight stations (stored in special hard copy tables/books, with handwritten records) have been digitized during the DARE process, resulting in 291,103 rescued values in total. More than half of this number (165,980, ~57%) are related to air temperature data, 124,376 data values (~42.7%) concern atmospheric pressure records and 747 values (~0.3%) are precipitation data. Simple quality control of the digitized data has been conducted, including an intercomparison between stations as well as comparison with monthly temperature data previously digitized from other paper sources. The quality control procedures revealed fairly good agreement between rescued time series on the monthly time scale as well as with the monthly data from independent sources. However, several periods for a few stations should be used with caution due to relatively large discrepancies that were found. The rescued digital database can be used for extreme value analysis for the pre‐1850 period in comparison with today's climate, regional climatological studies and will be used for future Reanalysis. In addition, for the first time, we show that subdaily temperature from Kyiv during 'the year without summer' 1816 in Western and Central Europe were not anomalous in this part of Eastern Europe. [ABSTRACT FROM AUTHOR]

It is important to know the process of hot spot creation to improve the safety of working with melted TNT. One of the probabilities is the air bubbles in TNT that melted during the firing and internal ballistics, which are the results of casting problems. Thus, in this paper, the accuracy of this probability was studied. Melted TNT is a highly viscous fluid, so in this study by improving the numerical code, the effects of the temperature‐dependent physical properties have been seen in the calculations. The results show that the viscosity work makes the bubble heated and rises, its temperature in comparison with the fluid environment. But the variations are a maximum of 4 °K. Therefore, it seems that the studied factors in this paper can′t be the reason for melted TNT undesirable ignition. [ABSTRACT FROM AUTHOR]

Long‐term climate monitoring by universities provides fundamental data for various disciplines in the natural sciences. Kyoto University once managed 10 university forest stations and is currently managing five. At these stations, climate data have been monitored almost since the establishment of each station until today, with the exception of the stations in foreign countries. We compiled and report the monthly climate data at these forest stations from the start of monitoring until December 2018. These data are important for investigating environmental changes in East Asia, including China (Taiwan), South Korea (Chosen) and Russia (Sakhalin, Karafuto) over the last 100 years. Long‐term monitoring often involves minor and major changes in the monitoring procedures, devices and even monitoring sites due to unavoidable circumstances, such as technological advances, changes in standard methods and climatic and anthropogenic disasters. Therefore, associated metadata on the monitoring methods are also important. We also compiled metadata on changes in monitoring methods. In addition, to examine the effects of changes in the methods on the observed climate data, we compared the values recorded before and after the change for each climate variable at each monitoring site. Methodological changes affected only a few variables, with the exception of humidity. Careful interpretation may be required when a researcher uses humidity data in any analysis. The complete data set for this abstract published in the Data Paper section of the journal is available in electronic format in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/ERDP-2020-03.1/jalter-en. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the relationships between soil moisture, cloud cover, solar radiation, air temperature and humidity, and precipitation during the warm half of the year in East‐Central Europe over the years 1971–2020. The temporal and spatial variability of these meteorological elements is presented in association with the occurrence of anticyclonic blocking events over the study area. It demonstrates that changes in soil moisture in East‐Central Europe point to the combined influence of many meteorological factors resulting from the atmospheric circulation, and are an indicator of the comprehensive relationships among those factors. The main factors affecting soil water content are precipitation and evapotranspiration, which in turn depend on air humidity, cloudiness, intensity of solar radiation and air temperature. The increase in the frequency and duration of sequences of days with blocking events in East‐Central Europe has contributed to an increased probability of longer periods with soil moisture negative anomalies. [ABSTRACT FROM AUTHOR]

Separating existing historical precipitation data into solid and liquid precipitation remains a challenge in the study of climate change, extreme precipitation, and hydrological modelling. Based on historical daily air temperature and precipitation data, as well as visual observations of precipitation phase (weather phenomena records) in China mainland, this study proposed a snow‐day direct definition method (SDDM) to determine the threshold air temperature (TAT) of rainfall and snowfall, and analysed the spatial pattern and its influential factors. The main findings include: (1) the TAT based on the SDDM varied from −1.2 to 6.3°C, with a mean value of 2.8°C for the entire study region; (2) TAT was generally higher and more variable in the low‐latitude areas, and the Qinghai‐Tibet Plateau was characterized by an abnormally high average TAT of 5.2°C, almost twice as large as that of the eastern monsoon region; (3) TAT exhibited a significant positive correlation with altitude and negative correlation with precipitation and relative humidity. The results presented in this paper have potential application for studies of large‐scale snowfall climatology and climate change, weather forecasting techniques, and hydrological model parameterization in areas with complex and diverse geographical and climatic conditions. [ABSTRACT FROM AUTHOR]

In the fruit processing industry, a large volume of residue is generated, which is usually discarded. However, fruit residues may have appeal as functional ingredients due to the presence of bioactive compound. In this study, the drying of acerola residue in a medium‐sized conventional spouted bed was investigated. The residue was characterized; vitamin C and 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) were determined to evaluate the effect of drying on bioactive compounds. To overcome the difficulty of material fluidization, a mixture composed of in natura acerola residue and acerola residue previously dried in an oven as an inert material was used. The effect of air temperature (40 and 60°C) and velocity (28 and 36 m/s) and amount of in natura residue in the mixture (20% and 30%) was evaluated during drying. As expected, higher temperatures and air velocities and lower percentages of in natura residue favored the reduction of moisture. For a mixture containing 20% in natura residue, air velocity of 36 m/s, and temperature of 60°C, it was possible to achieve a final moisture content suitable for storage (14.23% w.b.) and the highest percentage of DPPH free radical capture activity (85.31%). Moreover, a mixture containing 30% in natura residue, velocity of 28 m/s, and temperature of 40°C conserved more vitamin C (48.30 mg of ascorbic acid/100 g). Finally, spouted bed can be considered a good technique for drying acerola residue as it was able to reduce a high amount of moisture content preserving bioactive compounds during short drying periods at low temperatures. Practical Applications: The acerola processing generates a residue that consists basically of the seeds, bagasse, and peels, which is rich in ascorbic acid, phenolic compounds, flavonoids, anthocyanins, and organic acids. This residue can be used to generate new food products, which reduces the environmental problem of its disposal and the loss of raw material in fruit processing. To extend the residue shelf life, it must be subjected to a drying process. In this paper, the drying of acerola residue was investigated in a medium‐sized spouted bed. The spouted bed proved effectiveness in drying the acerola residue and in conserving bioactive compounds when operating for short periods and with low temperature. Thus, it can be considered as a promising technique for drying food products. Also, the data provided in this study can contribute to the solution of the scale‐up problem in spouted beds. [ABSTRACT FROM AUTHOR]

This work introduces a comprehensive model of sound attenuation and speed on Mars, in light of the recent operation of several microphones on the surface of Mars. The proposed acoustic model calculates the sound speed and attenuation throughout the near‐surface Martian atmosphere based on first‐principles. We evaluate the effects of the seasonal and diurnal cycle of air temperature, pressure and CO2, as well as the concentration of airborne dust on the sound attenuation. The attenuation and speed of sound are most sensitive to the air temperature and, therefore, they vary with the diurnal temperature cycle and to a lesser degree with the seasonal changes in temperature. The speed of sound also varies with the seasonal variations of the concentration of CO2. The main outcome of this work is an acoustic model capable of computing the sound speed and attenuation for any location at the Martian surface at any time of year and any time of day. Plain Language Summary: Sound offers new means of investigating the Martian environment. To study the properties of sound sources on Mars, or to derive atmospheric properties from the way sound travels in the Martian atmosphere, a model of the sound attenuation and speed on Mars is needed. In this paper, we propose such a model that allows the sound attenuation and speed at the Martian surface to be computed at any point and time. We investigate how these two properties change with air temperature, pressure, the chemical composition of the Martian atmosphere, the concentration of airborne dust, and with time of day and season. This paints the picture of Mars as a very contrasting planet acoustically, with a very wide range of attenuation and speed of sound compared to Earth because of the daily variations of temperature and the yearly variations of pressure and chemical composition. Key Points: Attenuation and speed of sound are modeled at every point of the Martian surfaceSound attenuation and speed are most affected by the variation of pressure and temperature associated with the diurnal and seasonal cyclesThe variations of sound attenuation and speed during a given day are very strong compared to Earth [ABSTRACT FROM AUTHOR]

The international Atmospheric Circulation Reconstructions over the Earth (ACRE) initiative works to recover global climate history and build an accessible databank, with data from the past 250 years of terrestrial and marine surface. Argentina is part of that effort with ACRE Argentina recovering data from various sources that have been recorded throughout the country since the 19th century. In this paper, weather observations transcribed from the original records into digital form and taken every day during the years 1860–1879 at Bahía Blanca and from 1873–1886 at Corrientes are presented. The digitization was carried out through the project Meteorologum ad Extremum Terrae (MET) launched in the Zooniverse interface, which is currently working with near 900 citizen scientist volunteers per day. The present analysis corresponds to data retrieved from the collection 'Anales de la Oficina Meteorológica Argentina' and contains information on atmospheric pressure, air temperature, relative humidity, cloud cover, cloud types, wind direction, wind speed, rainfall and weather remarks. For the present analysis, only temperature and pressure values, measured in °C and mm of Hg, respectively, were considered, after a quality control of the digitization process was applied. Data values were tested and used to rebuild the time series of both places and correlation with SOI index and monthly pressure values for both places was tested using Spearman correlation. Results show that the influence of El Niño episode during 1877–1878 can be found in the pressure values at Corrientes. [ABSTRACT FROM AUTHOR]

Gas exchange between streams and overlying air is an important physical‐chemical environmental process that is typically determined by injecting a tracer gas into a stream at a steady rate and sampling steady‐state tracer gas concentrations in the stream water. Previous modes of tracer gas injection allow gas‐water partitioning of the tracer gas, making the rate of gas injection and thus the measured gas transfer velocity potentially sensitive to temperature variation. Presented here is a modification to the tracer solution injection method in which a tracer gas solution was prepared in Tedlar® bags from which all headspace was removed before injecting the solution into the stream. Along with four other strategies to prevent a headspace from forming in the bags during tracer injection in the field, this zero‐headspace tracer solution method prevents gas‐water partitioning anywhere in the injection system, allowing a steady delivery of tracer gas to the stream even in the presence of variation in air and/or stream water temperature. A field test of the method in Nebraska yielded a gas transfer velocity of 4.1 m/day, within the range found in the literature for similarly‐sized streams. Plain Language Summary: This paper reports on the development and testing of a method that allows injection of tracer gases into streams and rivers at a constant rate even if the temperature of the air or water is changing over time. The new method allows accurate estimation of gas transfer velocities from injected tracer gases at times and places with significant temporal variation in temperature. Key Points: Steady tracer gas injections are regularly used to measure the gas exchange velocity (v) between streams and the overlying airTemperature variation affects tracer gas solubility, which can lead to unsteady gas injection rate and error in measured vA zero‐headspace tracer solution method was field tested and is proposed to measure v in the presence of large temperature variation [ABSTRACT FROM AUTHOR]

The Community Long‐term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) spans more than two decades of soundings from infrared and microwave instrument pairs on Aqua, Suomi‐NPP, and NOAA‐20. CLIMCAPS builds on three decades of research within the National Aeronautics and Space Administration Atmospheric Infrared Sounder Science Team (AST) to retrieve profiles of atmospheric temperature, water vapor, ozone, and many other trace gases as well as cloud and surface properties. In this paper, we highlight four innovative aspects of the AST retrieval methodology that allows the CLIMCAPS record (2002 to present) to bridge technology differences, maintain global coverage and stay updated with fast reprocessing times. CLIMCAPS improves on the AST method with rigorous optimal estimation uncertainty quantification for improved understanding of the signal‐to‐noise in sounding retrievals to allow their use in scientific research. Plain Language Summary: The Atmospheric Infrared Sounder (AIRS) was the first instrument of its kind in space. It has been making measurements daily at ∼1:30 a.m./p.m. since 2002. The Community Long‐term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) uses AIRS measurements to retrieve variables that characterize the thermodynamic and chemical state of the atmosphere. National Aeronautics and Space Administration is funding CLIMCAPS to continue the AIRS record with retrievals from the Cross‐track Infrared Sounder launched on three satellites in similar orbits since 2014 and scheduled for launch on two additional satellites in future. Accurate, consistent, long‐term records of observations are critically important for our understanding of an evolving Earth system. Key Points: Community Long‐term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) extends the Atmospheric Infrared Sounder (AIRS) + Atmospheric Microwave Sounding Unit record with sounding retrievals from Cross‐track Infrared Sounder + Advanced Technology Microwave SounderKey aspects of the AIRS Science Team retrieval methodology are embedded in the CLIMCAPS algorithm to help bridge technology differencesThe CLIMCAPS algorithm design enables an atmospheric sounding product with global coverage in clear and partly cloudy conditions [ABSTRACT FROM AUTHOR]

The ultrasound‐assisted hot air drying characteristics of Phyllanthus emblica was investigated in this paper. The effects of hot air temperature (60°C, 65°C, 70°C, and 75°C), ultrasonic pretreatment time (2, 4, 6, and 8 min), and ultrasonic power (200, 250, 300, and 350 W) on the drying rate, energy consumption, color change, and rehydration rate were evaluated and compared. It was found that the drying rate of Phyllanthus emblica increased with the hot air temperature. The drying time of Phyllanthus emblica with ultrasonic pretreatment was reduced by 10.0%, 25.0%, 21.4%, and 9.0% at 60°C, 65°C, 70°C, and 75°C, respectively. However, the hot air drying was not proportionally promoted by the increase of ultrasonic power or the extension of pretreatment time. Only an appropriate ultrasonic power or pretreatment time can not only improve the drying rate and rehydration rate, but also reduce the energy consumption and the total color change of the dried samples. A new drying model that considered the influences of hot air temperature, pretreatment time, and ultrasonic power was developed to fit the drying process. The results showed that the new model can accurately predict the hot air drying process of Phyllanthus emblica with and without ultrasonic pretreatment. Practical applications: Phyllanthus emblica contains a variety of nutrients and has various biological activities. However, the harvest period and shelf life of Phyllanthus emblica is very short, and the fruit is prone to mildrew and browning after picking, which in turn leads to the loss of its nutritional and economical value. Thus, for the long‐term preservation of Phyllanthus emblica, drying techniques are needed. In the food industry, hot air drying is widely used due to its low cost and easy operation; however, it also has some disadvantages such as long drying time, the oxygen‐rich drying environment. These shortcomings lead to a low quality of dried materials. Ultrasonic pretreatment before hot air drying can improve drying efficiency without adversely affecting the drying quality of the material. In recent years, ultrasonic pretreatment before food drying has become a research hotspot. [ABSTRACT FROM AUTHOR]

This paper describes the construction of a 0.25° × 0.25° daily soil temperature (TS) data set at six soil depths (i.e., 0, 5, 10, 15, 20, and 40 cm) based on a homogenized TS at more than 2,000 meteorological stations across mainland of China for 1960–2017. First, at each station, the observed TS is split into a daily climatology of 1981–2010 and a daily anomaly for 1960–2017. Then, they are respectively interpolated to 0.25° × 0.25° horizontal resolution by using the thin‐plain spline and the angular distance weight interpolation methods. Finally, a gridded multilayer TS data set is constructed from the sum of the above two gridded products. Latitude, longitude, and high‐resolution digital elevation models are explicitly incorporated into the interpolation processes. Selectivity tests indicate that the optimal interpolation distance for the TS anomaly field is 500 km, where the gridded data set may have maximum coverage of the entire Chinese mainland. The results show that the gridded TS climatology is slightly lower than the station observations. The differences between gridded and the station‐based TS varies ±3°C, with relatively large in SW and TIBET. For the gridded anomaly fields, the cross‐validation shows that the mean absolute errors between gridded and station‐based TS are generally less than 0.6°C in the YZ, SW, and SC, but they are above 1.0°C in the NW and TIBET due to the sparse station distribution and large topographic relief. From 1961 to 2016, the seasonal variability of the gridded TS is generally consistent with that of the surface air temperature. The gridded TS over the majority of land displays significantly positive trends in both summer and winter (p > 95%), indicating an overall warming land surface in China. The long‐term gridded TS data not only preserves the spatial features represented in the station observations, but also provides a spatio‐temporal continuous long‐term product of mainland China. Thus, it may be used in future studies, for example, evaluation of land surface model simulations, validation of satellite retrievals, land‐atmosphere interactions, and climate change. [ABSTRACT FROM AUTHOR]

Medium Energy Electron (MEE) precipitation (≳30 keV) ionizes the mesosphere and initiates chemical reactions, which ultimately can reduce mesospheric and stratospheric ozone. Currently, there are considerable differences in how existing parameterizations represent flux response, timing, and duration of MEE precipitation, especially considering its high‐energy tail (≳300 keV). This study compares the nature of ≳300 to ≳30 keV electron fluxes to better understand differences within MEE precipitation. The MEE fluxes are estimated from measurements by the Medium Energy Proton and Electron Detector (MEPED) onboard the Polar Orbiting Environmental Satellite (POES) from 2004 to 2014. The fluxes are explored in the context of solar wind drivers: corotating high‐speed solar wind streams (HSSs) and coronal mass ejections (CMEs) alongside their associated solar wind properties. Three key aspects of ≳300 keV electron fluxes are investigated: maximum response, peak timing, and duration. The results reveal a structure‐dependent correlation (0.89) between the peak fluxes of ≳30 and ≳300 keV electrons. The epsilon coupling function correlates well (0.84) with the ≳300 keV peak flux, independent of solar wind structure. The ≳300 keV flux peaks 0–3 days after the ≳30 keV flux peaks. The highest probability (∼42%) occurs for a 1‐day delay, while predictive capabilities increase when accounting for solar wind speed. The ≳300 keV flux response has the highest probability of lasting 4 days for both CMEs and HSSs. The results form a base for a stochastic MEE parameterization that goes beyond the average picture, enabling realistic flux variability on both daily and decadal scales. Plain Language Summary: Electrons with energies >30 keV precipitating into the Earth's atmosphere is known as medium energy electron (MEE) precipitation. Solar wind properties drive the rate and energy of MEE. MEE precipitation is a relevant solar forcing as it produces ozone‐depleting substances. Variations in ozone concentration can modify the atmospheric temperature profile and lead to changes in atmospheric circulation that can map down onto surface climate. The community's capability of parameterizing MEE precipitation is an active field of research. This study aims to build a foundation for an MEE parameterization that represents realistic variability on daily and decadal scales by exploring the variability in the context of different solar wind properties. The study focuses on three key aspects regarding the differences within the energy spectrum of MEE precipitation: maximum response, timing, and duration. The key aspects are evaluated regarding the probability of a specific response. This study looks at an entire solar cycle (11 yr). It is found that solar wind properties, such as solar wind speed, can help determine the probability of a particular MEE response. The results from this paper will be key elements for constructing an MEE precipitation parameterization to be applied in a chemistry‐climate model. Key Points: The solar wind parameter ε best predicts the peak flux of the >292 keV electron precipitation independent of solar wind structureThe delay in the peak flux of >292 keV electron precipitation relative to that of >43 keV electrons is influenced by solar wind speedOn average, electron precipitation >292 keV persists 2–3 days longer than electron precipitation >43 keV [ABSTRACT FROM AUTHOR]

Digital databases of monthly means of daily extreme, minimum (Tn) and maximum (Tx) air temperature collected in Ukraine were created. The databases contain temperature records of 371/340 (Tn/Tx) climatological stations which recorded data on the territory of Ukraine anytime during 1881–2015. The significant part of the data sets (~48/47%) was obtained after conducting a data rescue process, recovering historical paper records. Due to a great deal of missing data during World War I and II, homogenization was possible to perform only for 178 time series covering the period of 1946–2015. A homogenization procedure, conducted by means of the HOMER software, revealed 323 break points for minimum temperature (~1.8 breaks per station) and 310 for maximum temperature (~1.7 breaks per station). Approximately 37/33% (Tn/Tx) of the breaks can be explained by metadata. Shift amplitudes in Tn time series ranged between −1.18 and 1.71 °C, while for maximum temperature the range was slightly less from −0.99 to 1.15 °C. For both temperatures, mean values of shift amplitudes were near zero (−0.04/−0.05 °C). To validate the homogenization results, several statistical procedures were performed to compare inhomogeneous and homogeneous time series. The conducted statistical calculations provide the proofs that inhomogeneity of the Ukrainian extreme air temperature data should be taken into account when analysing regional climate change and variability. Detection of recent climate changes is a problem that is mainly solved based on analysis of long time series of observed/measured meteorological variables such as air temperature and precipitation. However, such the time series are usually affected by outliers and artificial abrupt shifts and/or gradual trends, which are not related to climate but reflect changes in observing practices and/or the surrounding environment. Furthermore, an amplitude of the shifts is frequently the same order of magnitude as an amplitude of a climate signal. Therefore, in order to conduct climatological studies of high quality and draw reliable conclusions it is necessary to use quality controlled and homogeneous data. In this paper, homogeneity of long monthly mean of daily extreme (minimum and maximum) air temperature time series collected in Ukraine has been investigated by means of the HOMER software. Revealed shifts and their influence on the time series have been studied in details. [ABSTRACT FROM AUTHOR]

Land surface temperature anomalies can be linked to changes in local surface energy balance, although the relationship between surface temperature variability and individual radiative processes remains unclear. In this paper, we quantify the contributions of surface radiative effects and non‐radiative heat fluxes to the variance of monthly land surface temperature using European Centre for Medium‐Range Weather Forecasts Reanalysis v5 data and Coupled Model Intercomparison Project Phase 6 simulations. The surface energy budget equation is used to link changes in surface radiation, surface heat fluxes and land surface temperature. Subsequently, surface radiation is decomposed into the radiative effects of clouds, air temperature, surface albedo and relative humidity using radiative kernels. The contributions of these radiative processes, including their coupling effects, are quantified using covariance matrices. The results reveal the air temperature radiative effect to be the most significant contributor to the variability of land surface temperature. In addition, the covariance terms reveal important coupling effects. For example, the contribution from the cloud radiative effect is found to be substantially dampened by its coupling with surface heat fluxes. The air temperature radiative effect is further decomposed into a forcing component and a feedback component using different regression methods, in an attempt to separate the air temperature radiative effect as the driver of the surface temperature variability. The cloud radiative effect becomes the primary contributor to the variance of surface temperature after separating the air temperature feedback, while the contribution of the air temperature radiative forcing remains important. Plain Language Summary: Land surface temperature is critical environmental variable. Through a statistical analysis of the European Centre for Medium‐Range Weather Forecasts Reanalysis v5 data and Coupled Model Intercomparison Project Phase 6 multi‐model simulations, we have explained the land surface temperature variability in relation to the surface energy fluxes. Specifically, we have attributed the variability of monthly surface radiation to the effects of different meteorological variables such as clouds, air temperature, surface albedo and relative humidity. Our findings suggest that the radiative effect of air temperature is the primary contributor to the variance of land surface temperature in most regions, although this effect includes a strong feedback effect of air temperature to surface temperature changes. After separating this feedback effect, the cloud radiative effect becomes the primary contributor. On the other hand, the contribution from cloud radiative effect is significantly counteracted by its coupling with surface heat fluxes. Key Points: The variance of land surface temperature is decomposed to contributions from surface radiative effects and heat fluxesThe radiative effect of air temperature is found to contribute the most to surface temperature variabilityThe cloud radiative effect is found to be the primary contributor after decoupling the air and surface temperature variations [ABSTRACT FROM AUTHOR]

Low global warming potential (GWP) refrigerants are vital to mitigating the effect of heat systems on climate change. A low GWP mixture, RGT2 (R134a/R1234yf/R161, 54%/43%/3% weight), was proposed as an alternative refrigerant for R134a in heat pump systems. This article presented the results of an experimental investigation evaluating RGT2 as a possible replacement for R134a in a closed heat pump drying (CHPD) system and studying the drying characteristics of fig slices. The experiment concluded that RGT2 has a higher coefficient of performance (COPhp) value than R134a, on average, by 1.92%, achieving lower discharge temperature and pressure ratio at different condensing temperatures (45°C–70°C). Although the heating capacity of RGT2 was slightly lower, it still met the requirements of HPD. With careful consideration of the environment, performance, and safety, RGT2 was a suitable substitute for R134a in the drying field. In addition, the drying characteristics of fig slices were significantly affected by the air temperature. The effective diffusion coefficient (Deff) and specific moisture extracted ratio (SMER) are increased by increasing temperature and air flow rate. The two‐term model was the better model to accurately predict the fig slices drying process. The highest mean Deff and SMER of CHPDS were obtained as 6.4518 × 10−10 m2/s and 39.197 g/kWh, respectively, at the highest drying air temperature. Practical Application: A mixed refrigerant (RGT2) was proposed to replace R134a, and its GWP value was about 61% lower than that of R134a. Most of the studies on substituting R134a in the literature are simulations. This paper aims to evaluate the substitutions' feasibility theoretically and experimentally. The results have been assessed to provide better information about RGT2 as a potential substitute for R134a with superior comprehensive performance. Drying kinetics has also been determined experimentally, which helped to simulate fig drying. This study will provide a reference for refrigerants replacement in heat pump drying. [ABSTRACT FROM AUTHOR]

Climate is a powerful driver of agricultural and natural systems, and spatial climate datasets are currently in great demand. This is especially true in the Arequipa Department of Peru, a region with low seasonal precipitation, remarkable topographic variability, and significant water demand in a highly managed water system. This paper presents the Arequipa Climate Maps (ACM) datasets, a high resolution (1 km) spatial 30‐year (1988–2017) climate dataset for the Arequipa Region, in Peru. Four interpolation methods, and combinations of those methods, were tested to produce 30 years of daily precipitation, maximum and minimum air temperature: Ordinary Kriging (OK), Thin Plate Splines (TPS), Regression Kriging (RK), and Regression Thin Plate Splines (RTPS). The mixed method RTPS‐TPS and RTPS using locally fitted polynomial and potential regressions were found to best represent the spatial variability of precipitation and daily extreme temperatures, respectively, and helped compensate the bias resulting from the lack of weather stations at higher elevations. These methods were then selected to create the ACM dataset, which contains climate maps of 30‐year annual and monthly climate normals (ACM–Normals) and 30 years of annual, monthly, and daily climate maps (ACM–YMD). In addition, insights on weather station gap filling in mountainous areas and bias corrections for avoidance of anomalous precipitation and to assure consistency between annual, monthly and daily data are presented, together with discussion about the quality and limitations of the dataset, and its comparison with other datasets. [ABSTRACT FROM AUTHOR]

Monitoring and quantifying high‐latitude atmospheric circulation variability and trends are important towards understanding the anatomy of extreme events and constraining their probabilities under continued Arctic change. The greater Alaska region stands out as one region of enhanced warming and environmental changes over the Arctic amplification era, which has shown proclivity to extreme events and speaks to the need to consistently monitor overlying atmospheric variability. In this paper, we describe the creation and analysis of an updated, daily mid‐tropospheric Alaska Blocking Index (ABI) time series from 1948 to 2020. Sensitivity testing and index modifications from the initial dataset are discussed, and the new ABI is evaluated over the full period and subperiods. Additionally, we assess the role of the ABI as a regional climate indicator by analysing its variability against surface air temperature and precipitation from 13 climate divisions across Alaska as well as broader‐scale hemispheric temperatures. Months of the highest ABI means mainly transpired in the most recent climatological period, 1991–2020, and most notably during the spring and autumn transition seasons, reflecting the nonstationary nature of the jet stream magnitude through time atop Alaska. ABI trends are positive across all months, seasons, and annually only in the 1991–2020 period. Contemporaneous ABI values are strongly and positively correlated with air temperature across all Alaskan climate divisions during the warm season, but negatively correlated with winter temperatures over southeastern Alaska. Meanwhile, the ABI is significantly anticorrelated with summer precipitation over Interior and southern Alaska, but only over southeastern Alaska in other seasons. The ABI is statistically differentiated from the primary modes of atmospheric variability as shown by its generally weak correlations with the Arctic Dipole and the Arctic Oscillation (r ≤ 0.40). [ABSTRACT FROM AUTHOR]

The rise in the Earth's global average surface temperature and the increase of extreme weather events have been the focus of scientific discussion in the last decades. Extreme heat combined with other environmental extremes, like high concentrations of air pollution, may induce health problems—especially in socioeconomically vulnerable populations. Spring in South America requires particular attention due to its association with hot, dry weather and air pollution in most parts of the continent. This paper intends to better comprehend the behaviour of heatwaves during the austral winter–spring transition. We propose identifying the spatial coverage, frequency and intensity of heatwaves in homogeneous areas of maximum air temperature near the surface (Tmax). We employed cluster analyses during the period between July and October for 41 years (1979–2019) through the ERA5 reanalysis. Homogeneous Tmax areas in South America were defined by cluster analyses that indicated three homogeneous Tmax regions, as follows: a larger area of the continent including the tropical region (Area 1), eastern and southeastern South America (Area 2) and southernmost and steep areas in the Andes (Area 3). The heatwave events identified via ERA5 reanalysis were classified according to their intensity (intense, moderate and weak events). Spatial frequency and trend analyses were also performed regarding the intensity and persistence of heatwave episodes. These methods allowed the identification of the behavioural aspect of heatwaves spanning the last four decades. The Mann–Kendall statistical test (MK) was applied in order to analyse the heatwave trend with a statistical significance level of 5%. A total of 191 heatwave episodes were identified. Of this total, 47.12, 35.60 and 17.28% of episodes occurred in Areas 2, 3 and 1, respectively. The hotter area extending from northeast to southwest in central South America stood out by its largest frequencies of intense heatwave episodes. Across the continent there was a significant increase in the intensity and persistence of heatwaves over the period of 1979 through to 2019. [ABSTRACT FROM AUTHOR]

This paper investigated the trends and variability in warmest daily maximum (TXx) and warmest daily minimum (TNx) air temperatures, and heatwave characteristics in Turkey in May during 1950–2020. It also analysed the climatological and synoptic meteorological evolutions of heatwave (HW) observed in May 2020. Trend analysis revealed significant increasing trends in TXx and TNx series and heatwave characteristics in May since 1950. Since the mid‐1980s, a continuously increasing trend in TXx and TNx series, and the number, frequency, and magnitude of the heatwaves were observed that accelerated with the mid‐1990s. The most severe heatwave in Turkey since 1950 in May was observed in 2020. The record‐breaking daily maximum (daily minimum) air temperatures were noted at 32 (23) of 96 stations in May 2020, mainly over Turkey's western and southern parts. Record‐high maximum (minimum) air temperature was 43.2°C (31.1°C) reached for the first time in May since 1950. The generalized extreme value model applied to the May TXx and TNx series revealed that the daily air temperatures in May 2020 exceeded 100 years' return periods at many stations of Turkey. This heatwave was linked to a regionalized strong anticyclonic blocking anomaly circulation and other associated atmospheric anomalies in May 2020. This also resulted in the centring of an unprecedented subsiding, calm, and stable warm air mass over Turkey. Adiabatic warming and drying developed very likely under subsidence control because of relatively weak circulation conditions. Such circumstances resulted in extremely hotter conditions in May 2020 compared to the long‐term averages. [ABSTRACT FROM AUTHOR]

There is growing interest in the international scientific community in characterizing climate variability in Antarctica because of the continent's fundamental role in regulating the world's climate. Researchers have intensively studied the Antarctic Peninsula since the warming that began in the mid‐1950s. This was followed by a subsequent cooling period over the last decades. For this paper, using the available data, we analysed the variability in surface air temperatures at five meteorological stations located on King George Island (KGI) (a subantarctic island that is part of the South Shetland Islands); we also investigated the relationships between the air temperatures and large‐scale atmospheric patterns from 1968 to 2019. In this study we found that summer temperatures are above 0°C from December to March and close to melting temperatures (extreme values) in spring and autumn; consequently, a small increase in temperature can have a significant impact on the cryosphere. The statistical analysis of the mean temperatures confirmed a trend toward cooling during the summer and in the mean monthly maximum temperatures over the 1990s at most of the weather stations whose data we analysed. Analysing the teleconnection patterns showed that the Southern Annular Mode (SAM) had strong, direct, and positive correlations during the autumn and less strong connections in spring, winter, and on an annual scale. Furthermore, we observed a lesser influence of El Niño‐Southern Oscillation (ENSO). [ABSTRACT FROM AUTHOR]

The suggestion that variations in solar irradiance affect Earth's weather and climate is based on correlations between solar and meteorological parameters. Solar activity influences the Earth's magnetic field. The geomagnetic activity index (GAI) is one of the indexes that measure this influence. In this paper, we researched the link between GAI and the passage of atmospheric cold fronts (CFs) over the Belgrade region, Serbia. Three years of daily data for solar (coronal holes, protons velocity and density), geomagnetic (GAI, electrical potential of Earth's atmosphere) and meteorological (air temperature, wind and precipitation) parameters were analysed. We developed a methodology that established pairs of GAI peaks and CFs and found the time interval (TI) between them. In 88.5% of cases, we were able to pair a GAI and a CF, while in 11.44% pairing could not be established. The number of GAI peaks without assigned CFs increased as mean values of GAI decreased. Most frequently, following an increase in the GAI, a CF passed after 7 days (relative frequency 22.8%), followed by 6 days (19.9%) and 8 days (18.5%). These three TIs covered, in sum, 61.3% of cases. Mean TI value was 6.82 days. The warm part of the year had the same TI distribution but the cold part of the year produced a bimodal frequency, with a maximum of 8 days (21.6%), followed by 5 (18.3%) and 6 days (17.6%). The most frequent CFs passing over Belgrade are from WNW‐N (67.1%) and SSW‐W (27.6%) quadrants. [ABSTRACT FROM AUTHOR]

Tropical convection is expected to decrease with warming, in a variety of ways. Specific incarnations of this idea include the "stability‐iris" hypothesis of decreasing anvil cloud coverage, as well as the decrease of both tropospheric and cloud‐base mass fluxes with warming. This paper seeks to encapsulate these phenomena into three "rules," and to explore their interrelationships and robustness, using both analytical reasoning as well as cloud‐resolving and global climate simulations. We find that each of these rules can be derived analytically from the usual expression for clear‐sky subsidence, so they all embody the same essential physics. But, these rules do not all provide the same degree of constraint: the stability‐iris effect is not entirely robust due to unconstrained microphysical degrees of freedom, and the decrease in cloud‐base mass flux is not entirely robust due to unconstrained effects of entrainment and detrainment. Tropospheric mass fluxes on the other hand are shown to be well‐constrained theoretically, and when evaluated in temperature coordinates they exhibit a monotonic decrease with warming at all vertical levels and across a hierarchy of models. Plain Language Summary: Tropical convection and high cloudiness are expected to decrease with global warming, in a variety of ways. This phenomenon has a few different manifestations in the literature, whose relationships are unclear. We show analytically that these explanations all embody the same essential physics, but are not equally robust and thus do not all have the same predictive power. Key Points: Three constraints on tropical convection can all be derived analytically from clear‐sky subsidenceTropospheric mass fluxes at a fixed isotherm should robustly decrease under global warmingDecreases in anvil cloud area and cloud‐base mass flux are not as robust [ABSTRACT FROM AUTHOR]

Background: Simple isotherm models, such as the Langmuir and Freundlich equations, are frequently used to correlate water contaminant adsorption data. In the conventional data fitting approach, the Langmuir and Freundlich equations are fitted to experimental data by minimizing the difference between the measured and calculated adsorbed phase concentrations. However, some isotherm equations are implicit in adsorbed phase concentration. Such isotherms must be converted to explicit forms to allow the use of standard nonlinear regression methods in data correlation. This paper explores the use of the Lambert W function to invert the loading‐implicit isotherms of Elovich, Volmer, and Jossens to solve for adsorbed phase concentration as a function of liquid phase concentration. Results: The inverted Elovich, Volmer, and Jossens isotherms were fitted to literature adsorption data of water contaminants using the standard nonlinear regression procedure in Excel. Data fitting was accomplished by making use of a freely available Excel add‐in and a highly accurate analytical approximation to evaluate the Lambert W function. The inverted isotherms were tested against the experimental isotherms of cobalt, uranium, and cephalosporin C. In all cases studied, satisfactory fits were obtained, validating the practicability of the proposed data fitting approach. Conclusions: The loading‐implicit Elovich, Volmer, and Jossens isotherms can be formulated as loading‐explicit equations in terms of the Lambert W function, thus allowing the use of conventional least‐squares fitting procedures in data correlation. The practical implementation of the Lambert W function in Excel provides a novel method to fit loading‐implicit isotherms to experimental data of water contaminants. © 2022 Society of Chemical Industry (SCI). [ABSTRACT FROM AUTHOR]

Air temperature has exhibited a clear positive trend over the past several decades throughout the arctic, including Alaska. Other variables, such as precipitation, have much more uncertain trends due to inhomogeneities in measurement and high internal variability. The use of linear regression to analyse precipitation in Alaska has resulted in often contradictory results. This paper proposes the use of Bayesian models such as the R package Rbeast to allow for the more nuanced analysis. The examples given in this paper show how Bayesian analysis can be used to detect subtle changes and better constrain the disagreement between data sources. Applied to gridded data, Bayesian analysis shows how precipitation has changed overtime across Alaska. Change has accelerated over the past decade, but only precipitation increase on the North Slope can be assigned high confidence. Overall, this analysis highlights how Bayesian techniques may be uniquely useful to climate research in regions with heterogeneous data sources and substantial internal variability. [ABSTRACT FROM AUTHOR]

Accurately predicting the production of a photovoltaic (PV) plant is essential to its economic evaluation. Ambient temperature is a major environmental factor affecting how much power a PV plant generates. However, weather bureaus in most developing countries can only provide the daily or monthly mean ambient temperatures, rather than the real mean working temperature in the vicinity of the PV plant. Moreover, the difference between the real daily or monthly mean working temperature and the corresponding daily or monthly mean temperature is large in the Gobi, desert, and Qinghai‐Tibet Plateau, causing some errors in some present PV power predictive models. Using Datafit 9.0 software in this paper, regression equations were created for Beiluhe (Qinghai‐Tibet Plateau) and Desert Knowledge Australia Solar Centre (DKASC) (desert) data relating the difference of the real daily or monthly mean working temperature and the corresponding mean temperature (Y factor) as well as the daily or monthly temperature difference (X factor). One general equation: Td10d = 1.290 + 0.475 × Tdmm − 1.331 × Tdmm0.5 (Equation 6) could represent all of the regression equations obtained from the Beiluhe and DKASC data. These basic findings are valuable for improving accuracy of present PV power predictive model by including the daily or monthly mean air temperature. Another, the research result will be helpful for PV plant site selection and evaluation. [ABSTRACT FROM AUTHOR]

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Temperature and density in the upper Martian atmosphere, above ∼100 km, are key diagnostic parameters to study processes of the species' escape, investigate the impact of solar activity, model the atmospheric circulation, and plan spacecraft descent or aerobraking maneuvers. In this paper, we report vertical profiling of carbon dioxide (CO2) density and temperature from the Atmospheric Chemistry Suite (ACS) solar occultations onboard the ExoMars Trace Gas Orbiter. A strong CO2 absorption band near 2.7 μm observed by the middle infrared spectrometric channel (ACS MIR) allows the retrieval of the atmospheric thermal structure in an unprecedentedly large altitude range, from 20 to 180 km. We present the latitudinal and seasonal climatology of the thermal structure for 1.5 Martian years (MYs), from the middle of MY 34 to the end of MY 35. The results show the variability of distinct atmospheric layers, such as a mesopause (derived from 70 to 145 km) and homopause, changing from 90 to 100 km at aphelion to 120–130 km at perihelion. Some short‐term homopause fluctuations are also observed depending on the dust activity. Plain Language Summary: We report vertical distributions of the density and temperature in the Martian atmosphere in the altitude range from 20 to 180 km. This broad interval of heights embraces regions of the troposphere (<50 km), the mesosphere (50–100 km), and the thermosphere (>100 km). Knowledge of thermal structure in the middle and upper atmosphere (above 50 km) is unique for the Martian climate modeling, studying the atmospheric escape and the impact of solar activity, as well as planning spacecraft maneuvers. Our data are based on remote measurements of the carbon dioxide (CO2) absorption in the atmosphere at very high altitude resolution of one kilometer. Sensing this major component, 95% of the total density, in the infrared wavelength range allows us to derive the atmospheric temperature as well. We observe the climatology of different atmospheric layers depending on latitude and seasons for 1.5 Martian years, from May 2018 to January 2021. For example, we reveal extremely high variability of the coldest layer, mesopause, from 70 km in the southern winter to 150 km in the southern summer. Key Points: Seasonal variability of the Martian atmospheric thermal structure at altitudes 20–180 km is reported from CO2 infrared spectroscopyThe mesopause altitude rises from 70 to 90 km in the high‐winter latitudes to 130–150 km in the summer season for both hemispheresThe homopause altitude varies from 90 km at aphelion to 130 km at perihelion in the Martian years 34 and 35, and it depends on dust activity [ABSTRACT FROM AUTHOR]

This study investigates some of the uncertainties sources associated with the pseudo global warming (PGW) approach which was employed to project future patterns of tropical cyclones (TCs) over the Arabian Sea (AS). First, the climate variables controlling the patterns of tropical cyclones were extracted from reanalysis datasets of ERA5, ERAI, CFSR, and NCEP/NCAR. Then, each dataset was evaluated against long‐term measurements to identify the best‐performing reanalysis dataset. ERA5 showed the best performance for most of the variables. Outputs of 20 CMIP5 global climate models (GCMs) were then evaluated against the ERA5 data resulting in an ensemble of the best performing GCMs. A PGW framework was then used to project the changes in patterns of three significant historical cyclones: Gonu, Phet, and Ashobaa. In doing so, the signals of future climate variables were extracted from the GCMs ensemble to modify the initial and boundary conditions of the WRF model which was previously tuned for reproducing the historical TCs. Different tests were conducted to address the sources of uncertainty in the PGW approach, including the selection of the climate variables contributing to the computation of the signals, the selection of GCMs, and the spatial variation of signals. A considerable sensitivity of the projected track and intensity of TCs to the choice of GCMs was observed, acknowledging the importance of GCMs evaluation before calculating the signals. Moreover, it was found that among all variables, signals of sea surface temperature and air temperature have major effects on the cyclone's track and intensity. Apart from that, when the signals were applied to the domain of the WRF model uniformly, compared to applying spatially varying signals, different tracks and intensities for future TCs were also observed. Overall, the findings of this paper challenge the reliability of the projected changes in TCs patterns obtained from PGW. [ABSTRACT FROM AUTHOR]

The surface air temperature (SAT) trend on the Tibetan Plateau (TP) was 3.45°C 100 years−1 from 1961 to 2014. The multi‐model ensemble (MME) of 33 coupled models participated in the Coupled Model Intercomparison Project phase six (CMIP6) was about 1°C 100 years−1 lower than the observation. Although MME generally shows better skill in reproducing the distribution of SAT trend over TP than most of the CMIP6 models, its performance is greatly degraded by a small group of models, about 12% on average, with large biases. In this paper, the constrained multi‐model ensemble (CMME) based on a certain observation‐based threshold is used to constrain future projections of the SAT trend over TP. Compared with the MME results, the improvements in CMME are mainly over the eastern plateau in historical simulation and are relative to the reduction of the model biases to carbon dioxide (CO2) forcing. Under the high‐emission SSP5‐8.5 scenario, SAT increases significantly over the entire TP. The constraint of CMME on the MME is mainly over the eastern plateau with a difference of 0.5°C 100 years−1, about 6% of the MME results. Under the intermediate‐emission scenario SSP2‐4.5, the effect of CMME is relatively smaller, but the corresponding spatial distribution is similar to that under the SSP5‐8.5 scenario. The CMIP6 models tend to underestimate the warming trend projections over the water source regions in the northeastern plateau and should be noticed. Key Points: The Coupled Model Intercomparison Project phase six model ensemble in surface air temperature trend reproduction on the Tibetan Plateau are greatly degraded by a small group of models with large biasesThe impact of constrained ensemble (CMME) is mainly over the eastern plateau in relative to the reduction of model biases to CO2 forcingThe CMME results indicate the underestimated warming projections in multi‐model ensemble over the northeastern plateau [ABSTRACT FROM AUTHOR]

This paper uses monthly surface air temperature (SAT) data from the Climatic Research Unit dataset and the Coupled Model Intercomparison Project phase 6 multimodel ensemble simulations to investigate the variations in the annual‐mean and four seasons SAT across the Eurasian and North Africa landmasses and the possible causes. The SAT over multiple timescales has significant seasonal and regional differences. The trend, variance of decadal variation (DV), and variance of interannual variability (IV) show that the differences between Siberia and mid‐low latitudes are much larger in winter and spring than in summer and autumn. The SAT exhibits a robust warming trend over Siberia in winter (0.21–0.42°C·decade−1) than over mid–low latitudes in summer (<0.07°C·decade−1). The cause is the combined diversity effects of greenhouse gases (GHG) and anthropogenic aerosols (AA) in four seasons over different regions. The warming trend of Siberia in winter is affected by the combination of strong warming effect by GHG and the weak cooling effect by AA, and the trend of mid–low latitudes in summer is opposite. The leading modes of the DV show a consistent spatial pattern over the whole Eurasia in four seasons while the IV show a meridional dipole pattern across 40°N except in summer. The internal climate variability is the main driver of the SAT IV and DV, but the effect of anthropogenic activity and natural forcing may reinforce the IV and DV in some regions. The combined role of GHG and AA forcings can significantly enlarge the DV in many parts of Eurasia, and the AA and natural forcing have significant effect on the IV in the high latitudes. [ABSTRACT FROM AUTHOR]

Radio occultation (RO) measurement is an established technique for profiling planetary atmosphere/ionosphere. The accuracy of the derived physical parameters (atmospheric temperature, pressure, and density in the lower atmosphere, and electron density in the ionosphere) however depends on uncertainty in the observed frequency and robustness of the retrieval algorithm. The objective of this paper is to identify all possible sources of errors in RO experiments and their propagation to the retrieved atmospheric profiles. Quantification of errors due to assumptions used in the retrieval algorithm has also been attempted. We used the data from one‐way downlink single‐frequency (X‐band) radio signals, transmitted from the radio science payload onboard Akatsuki spacecraft orbiting Venus and received at Indian Deep Space Network, Bengaluru, India for this study. We followed the standard signal processing technique to analyze the raw data. Atmospheric profiles were retrieved using the basic concept of geometrical optics. Possible sources of errors in RO experiments are identified and their magnitude range has been quantified. The propagation of errors in obtained atmospheric profiles is also discussed. These results would be useful while devising RO experiments for future planetary explorations. Key Points: Identification of error sources in the planetary radio occultation experimentsQuantification of errors in the Doppler residualEstimation of propagation of errors in the retrieved atmospheric profiles [ABSTRACT FROM AUTHOR]

Multi‐instrument data from Jang Bogo Station (JBS) in Antarctica were utilized to study ionospheric responses to the 11 May 2019 moderate geomagnetic storm. These include Vertical Incident Pulsed Ionospheric Radar (VIPIR)/Dynasonde, Fabry‐Perot Interferometer (FPI), GPS vertical total electron content (vTEC), and magnetometer. The VIPIR/Dynasonde observed long‐lasting (>11 hr) severe depletion of the electron density in the F‐region ionosphere over JBS. During the depletion interval, GPS TEC also correspondingly decreased, FPI neutral temperature was significantly enhanced, and the polar magnetic field variations showed positive and negative excursions in the Y (east) and Z (vertical) components, respectively. GK‐2 A satellite, located ∼2.5 hr west of JBS, observed negative magnetic field perturbations in the azimuthal BD component at geosynchronous orbit during the depletion of ionospheric plasma. Such a BD perturbation at geosynchronous orbit is due to the field‐aligned currents flowing out of the ionosphere. From these observations we suggest that transpolar ionospheric currents connected to the field‐aligned currents flowing on a substorm wedge‐shaped circuit act as a source of polar atmospheric heating during the moderate geomagnetic storm interval and that elevated heavy molecular gases (O2 and N2) by atmospheric heating contribute to the electron density depletion via increased recombination rate. Plain Language Summary: Geomagnetic storms considerably influence the high‐latitude ionosphere in its density distributions as well as dynamics. In the present paper, we report results of multi‐instruments observations of the stom‐time ionospheric changes with simultaneously observed thermospheric anc magnetospheric changes. The Vertical Incident Pulsed Ionospheric Radar/Dynasonde and total electron contents measured by ground GPS receiver observed depletion of the ionospheric electron density. We confirmed from model results that the depletion was caused by the upwelling atmospheric molecular gases. The heated neutral atmosphere was also confirmed by the observations for the themosphere from a Fabry‐Perot interferometer. The current system is a key process to enhanced the lower atmospheric temperature. During the depletion interval, the magnetic field on the ground showed significant variations. The geosynchronous satellite also observed negative fluctuations in the azimuthal component at around Jang Bogo Station, which corresponds to the fluctuation of the ground magnetic field. Such fluctuations at geosynchronous orbit are strongly related with field‐aligned current that are part of a current system associated with substorm. These observations support that field‐aligned current plays as a source of polar ionospheric heating during the moderate geomagnetic storm. Key Points: The disappearance of the F‐region ionosphere was observed during storm in the polar cap regionThe disappearance is associated with the atmospheric upwelling and resulting enhancement of the recombinationThe polar cap ionosphere can be significantly affected by substorm‐induced field‐aligned currents [ABSTRACT FROM AUTHOR]

Crowdsourced vehicle-based observations have the potential to improve forecast skill in convection-permitting numerical weather prediction (NWP). The aim of this paper is to explore the characteristics of vehicle-based observations of air temperature in the context of data assimilation. We describe a novel low-precision vehicle-based observation dataset obtained from a Met Office proof-of- concept trial. In this trial, observations of air temperature were obtained from built-in vehicle air-temperature sensors, broadcast to an application on the participant's smartphone, and uploaded, with relevant metadata, to the Met Office servers. We discuss the instrument and representation uncertainties associated with vehicle-based observations and present a new quality-control procedure. It is shown that, for some observations, location metadata may be inaccurate due to unsuitable smartphone application settings. The characteristics of the data that passed quality control are examined through comparison with United Kingdom variable-resolution model data, roadside weather information station observations, and Met Office integrated data archive system observations. Our results show that the uncertainty associated with vehicle-based observation-minus-model comparisons is likely to be weather-dependent and possibly vehicle-dependent. Despite the low precision of the data, vehicle-based observations of air temperature could be a useful source of spatially-dense and temporally-frequent observations for NWP. [ABSTRACT FROM AUTHOR]

A priori, cosmic‐ray measurements offer a unique capability to determine the vertical profile of atmospheric temperatures directly from ground. However, despite the increased understanding of the impact of the atmosphere on cosmic‐ray rates, attempts to explore the technological potential of the latter for atmospheric physics remain very limited. In this paper, we examine the intrinsic limits of the process of cosmic‐ray data inversion for atmospheric temperature retrieval, by combining a detection station at ground with another one placed at an optimal depth, and making full use of the angular information. With that aim, the temperature‐induced variations in cosmic rays (c.r.) rates have been simulated resorting to the theoretical temperature coefficients WT(h, θ, Eth) and the temperature profiles obtained from the ERA5 atmospheric reanalysis. Muon absorption and Poisson statistics have been included to increase realism. The resulting c.r. sample has been used as input for the inverse problem and the obtained temperatures compared to the input temperature data. Relative to early simulation works, performed without using angular information and relying on underground temperature coefficients from a suboptimal depth, our analysis shows a strong improvement in temperature predictability for all atmospheric layers up to 50 hPa, nearing a factor 2 error reduction. Furthermore, the temperature predictability on 6‐h intervals stays well within the range 0.8–2.2 K. Most remarkably, we show that it can be achieved with small‐area m2‐scale muon hodoscopes, amenable nowadays to a large variety of technologies. For mid‐latitude locations, the optimal depth of the underground station is around 20 m. Plain Language Summary: Cosmic rays (c.r.) are a form of natural radiation that comes from outer space and traverses the atmosphere. Analogously to X‐ray radiation, we can extract information from the object they pass through, the atmosphere in this case. Cosmic radiation can be measured at the Earth's surface using sophisticated instruments. In our work, we examine in detail the possibility of retrieving the vertical profile of temperatures from c.r. measurements, by using two detection stations, one placed at the surface and another one at an optimal depth. We make full use of a feature which is characteristic of modern c.r. detectors, the angular information. This refers to the capability of measuring c.r. from different directions. To analyze the limits of the suggested approach, we estimate temperatures from simulated c.r. data that would be measured under realistic atmospheric conditions and compare them with the original ones. Relative to early simulation works, our method estimates temperatures with a greater accuracy at higher temporal resolutions and for atmospheric layers up to 20 km. Most remarkably, we show that this performance can be achieved with small and affordable detectors, bringing the possibility of complementing satellite‐borne temperature retrieval with a technology cheaper to assemble and maintain. Key Points: Improved approach to obtain atmospheric temperature from cosmic‐ray data by introducing a pair of detection stations and angular informationResults show a significant retrieval improvement over earlier methods with high accuracy up to 20 km of heightThe use of affordable and small‐scale cosmic‐ray telescopes is suggested as a possible complement to satellite temperature measurements [ABSTRACT FROM AUTHOR]

Accurate and high‐resolution air temperature prediction is important in many different applications. Hourly air temperature forecasting in mountainous areas is necessary and important because mountainous areas are becoming increasingly important areas of human activities. At present, scientists successfully employ numerical weather prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, to achieve reliable forecasts. However, air temperature forecasting and modeling over complex geographical zones are still difficult tasks. The WRF model is a mesoscale model and does not adequately account for the influence of terrain on the air temperature. It is important to downscale larger‐scale models to a much finer scale. In this paper, a statistical temperature downscaling method based on geographically weighted regression (GWR) and diurnal temperature cycle (DTC) models is proposed. A statistical downscaling scheme of WRF simulation data is designed to forecast the hourly air temperature from 1‐km spatial resolution to 30 m, up to 24 hr in advance. The combined downscaling model's root‐mean‐square error (RMSE) decreased by 0.87°C at the automatic weather station (AWS) level and 0.62°C over the domain when compared to WRF simulations, and the mean absolute error (MAE) decreased by 0.71°C and 0.51°C, respectively, at these two levels. The results reveal that the combined downscaling model performs very well in correcting and downscaling the air temperature in WRF simulations in the study areas. Key Points: A statistical downscaling scheme was designed for weather research and forecasting (WRF) simulationsTo downscale the hourly air temperature from 1‐km spatial resolution to 30‐m, up to 24 hr in advance in a mountainous areaCompared to WRF simulation results, root‐mean‐square error (RMSE) and mean absolute error (MAE) of WRF‐downscaled results decreased by 0.87°C and 0.71°C, respectively, at the automatic weather station (AWS) level [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive analysis of the effect of urbanization on the surface air temperature (SAT) from 1951 to 2018 in the Philippines. The daily minimum temperature (Tmin) and daily maximum temperature (Tmax) records from 34 meteorological stations were used to derive extreme temperature indices. These stations were then classified as urban or rural based on satellite night‐lights. The results showed a significant difference in the SAT trends between urban and rural stations, indicative of the effect of urbanization in the country. Larger and more significant warming trends were observed in indices related to Tmin than those related to Tmax. In particular, the effects of urbanization were significant in the annual index series of Tmin, diurnal temperature range, minimum Tmin, percentage of days when Tmin was less than the 10th percentile (TN10p), percentage of days when Tmin was greater than 90th percentile (TN90p), and the number of coldest nights. The effects of urbanization were not as clear on the index series of maximum Tmax (TXx), minimum Tmax (TXn), percentage of days when Tmax was less than 10th percentile (TX10p), and the number of hottest days. The effects of urbanization on the annual series of extreme temperature indices were statistically significant at the 95% confidence level, with the exception of Tmax, TXn, TXx, TX10p, and the number of hottest days. Further analysis revealed that the effect of urbanization was the greatest during the DJF (December–January–February) season. These findings serve as a baseline study that focuses on the countrywide effect of urbanization on SAT trends in the Philippines. [ABSTRACT FROM AUTHOR]

The Atmospheric Chemistry Suite (ACS) onboard the ExoMars Trace Gas Orbiter monitors the Martian atmosphere through different spectral intervals in the infrared light. We present a retrieval algorithm tailored to the analysis of spectra acquired in nadir geometry by Thermal InfraRed channel in honor of professor Vassilii Ivanovich Moroz (TIRVIM), the thermal infrared channel of ACS. Our algorithm simultaneously retrieves vertical profile of atmospheric temperature up to 50 km, surface temperature, and integrated optical depth of dust and water ice clouds. The specificity of the TIRVIM data set lies in its capacity to resolve the diurnal cycle over a 54 sol period. However, it is uncertain to what extent can the desired atmospheric quantities be accurately estimated at different times of day. Here we first present an Observing System Simulation Experiment (OSSE). We produce synthetic observations at various latitudes, seasons and local times and run our retrieval algorithm on these synthetic data, to evaluate its robustness. Different sources of biases are documented, in particular regarding aerosol retrievals. Atmospheric temperature retrievals are found robust even when dust and/or water ice cloud opacities are not well estimated in our OSSE. We then apply our algorithm to TIRVIM observations in April–May 2018 and perform a cross‐validation of retrieved atmospheric temperature and dust integrated opacity by comparisons with thousands of colocated Mars Climate Sounder (MCS) retrievals. Most differences between TIRVIM and MCS atmospheric temperatures can be attributed to differences in vertical sensitivity. Daytime dust opacities agree well with each other, while biases are found in nighttime dust opacity retrieved from TIRVIM at this season. Plain Language Summary: The Martian surface and atmosphere undergo strong variations in temperature and amount of aerosols (dust or water ice cloud particles). Our knowledge on their variations at diurnal scale is however limited, due to lack of appropriate observations. We present a method to analyze thermal emission spectra of Mars' surface and atmosphere recorded by Thermal InfraRed channel in honor of professor Vassilii Ivanovich Moroz (TIRVIM), a spectrometer onboard the ExoMars Trace Gas Orbiter. We have developed a program to derive surface and atmospheric temperatures from these spectra, along with an estimation of the amount of aerosols. The specificity of the TIRVIM data set is its capacity to resolve the diurnal cycle over a 54 sol period. However, atmospheric quantities cannot be accurately estimated at all times of day. One of the goals of our paper is to assess the robustness of our algorithm with the help of simulated observations. The retrieval of aerosol opacity is assessed to be challenging at some times of day, but atmospheric temperature is well determined. We have then applied our algorithm to tens of thousands of TIRVIM observations obtained in April–May 2018 and showed that our derived atmospheric temperatures compare very well with independent measurements obtained from the Mars Climate Sounder, reinforcing our confidence in our method. Key Points: We exploit Thermal InfraRed channel in honor of professor Vassilii Ivanovich Moroz (TIRVIM) spectra to determine Martian atmospheric, surface temperature, as well as integrated opacity of dust and water ice cloudsDifferent sources of biases are investigated with the help of simulated observations at different local times, latitudes and seasonsAtmospheric temperatures retrieved from TIRVIM in April–May 2018 are in excellent agreement with colocated Mars Climate Sounder observations [ABSTRACT FROM AUTHOR]