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Temperature and wind observations from aircraft are regarded of major importance for aviation meteorology and numerical weather prediction (NWP). The European Meteorological Aircraft Derived Data Center (EMADDC) system processes aircraft surveillance data received from air traffic control (ATC) and converts it into observations of wind and temperature. Only so-called Mode-S Enhanced Surveillance data can be used, because this data contains the air vector and ground vector of the aircraft, from which a wind vector can be inferred. To acquire high quality observations, the data is processed in three steps: pre-processing, processing, and post-processing. The pre-processing is needed to obtain high-quality information and to calculate several correction values such as temperature corrections and heading corrections. Processing converts the aircraft data into meteorological information and finally post-processing guarantees that only high-quality information is made available. The quality of the observations produced is verified by comparing these observation to other upper air wind and temperature observations from radiosondes and comparing them with NWP data. This paper presents the EMADDC system, operational since 2019. [ABSTRACT FROM AUTHOR]

Climate projections and their effects in the San Francisco Estuary have been evaluated as part of the US Geological Survey’s CASCaDE2 project. Understanding the ecological effects of climate change can help manage and maintain the ecological health and productivity of the San Francisco Estuary. In this study, we assessed downscaled air temperature data from 10 global climate models (GCMs) under two representative concentration pathway (RCP) trajectories for greenhouse gas concentrations for three regions of the San Francisco Estuary: Sacramento–San Joaquin Delta, Suisun and Grizzly bays, and Suisun Marsh. We also used previously derived regression models to estimate future water temperatures at 16 locations in the upper San Francisco Estuary. We used a thermal regime approach to summarize water temperature projections to investigate changes to the thermal regime of the upper San Francisco Estuary, and used the Delta Smelt (Hypomesus transpacificus) to demonstrate the effects that a warming climate may have on the habitat needs of this fish species. Our results suggested there were no major differences in the extent of airtemperature warming among the three regions. Annual average air temperatures were projected to increase approximately 2.0 °C and 4.7 °C by the end of the century for the low and high RCP scenarios, respectively. We found timing, frequency, and magnitude metrics varied by period and RCP scenario, while duration and variability metrics varied by space for water temperature thermal regimes. For example, the spawning window for Delta Smelt (thermalregime duration metric) is projected to expand in the future, with spawning starting earlier for both RCP scenarios for most sites. Although our thermal-regime analysis focused on the life history of Delta Smelt, similar approaches could be used to assess climate-change threats to a wide array of native and invasive terrestrial and aquatic species found in San Francisco Estuary. [ABSTRACT FROM AUTHOR]

Upper air temperature measurements are critical for understanding weather patterns, boundary-layer processes, climate change, and the validation of space-based observations. However, there have been growing concerns over data discrepancies, the lack of homogeneity, biases, and discontinuities associated with historical climate data records obtained using these technologies. Consequently, this article reviews the progress of utilizing radiosondes and space-based instruments for obtaining upper air temperature records. A systematic review process was performed and focused on papers published between 2000 and 2023. A total of 74,899 publications were retrieved from the Google Scholar, Scopus, and Web of Science databases using a title/abstract/keyword search query. After rigorous screening processes using relevant keywords and the elimination of duplicates, only 599 papers were considered. The papers were subjected to thematic and bibliometric analysis to comprehensively outline the progress, gaps, challenges, and opportunities related to the utilization of radiosonde and space-based instruments for monitoring upper air temperature. The results show that in situ radiosonde measurements and satellite sensors have improved significantly over the past few decades. Recent advances in the bias, uncertainty, and homogeneity correction algorithms (e.g., machine learning approaches) for enhancing upper air temperature observations present great potential in improving numerical weather forecasting, atmospheric boundary studies, satellite data validation, and climate change research. [ABSTRACT FROM AUTHOR]

Upper air temperature measurements are critical for understanding weather patterns, boundary-layer processes, climate change, and the validation of space-based observations. However, there have been growing concerns over data discrepancies, the lack of homogeneity, biases, and discontinuities associated with historical climate data records obtained using these technologies. Consequently, this article reviews the progress of utilizing radiosondes and space-based instruments for obtaining upper air temperature records. A systematic review process was performed and focused on papers published between 2000 and 2023. A total of 74,899 publications were retrieved from the Google Scholar, Scopus, and Web of Science databases using a title/abstract/keyword search query. After rigorous screening processes using relevant keywords and the elimination of duplicates, only 599 papers were considered. The papers were subjected to thematic and bibliometric analysis to comprehensively outline the progress, gaps, challenges, and opportunities related to the utilization of radiosonde and space-based instruments for monitoring upper air temperature. The results show that in situ radiosonde measurements and satellite sensors have improved significantly over the past few decades. Recent advances in the bias, uncertainty, and homogeneity correction algorithms (e.g., machine learning approaches) for enhancing upper air temperature observations present great potential in improving numerical weather forecasting, atmospheric boundary studies, satellite data validation, and climate change research.

In this paper, we study the problem of extracting trends from time series data involving missing values. In particular, we investigate a general class of procedures that impute the missing data and then extract trends using seasonal-trend decomposition based on loess (STL), where loess stands for locally weighted smoothing, a popular tool for describing the regression relationship between two variables by a smooth curve. We refer to them as the imputation-STL procedures. Two results are obtained in this paper. First, we settle a theoretical issue, namely the connection between imputation error and the overall error from estimating the trend. Specifically, we derive the bounds for the overall error in terms of the imputation error. This subsequently facilitates the error analysis of any imputation-STL procedure and justifies its use in practice. Second, we investigate loess-STL, a particular imputation-STL procedure with the imputation also being performed using loess. Through both theoretical arguments and simulation results, we show that loess-STL has the capacity of handling a high proportion of missing data and providing reliable trend estimates if the underlying trend is smooth and the missing data are dispersed over the time series. In addition to mathematical derivations and simulation study, we apply our loess-STL procedure to profile radiosonde records of upper air temperature at 22 Antarctic research stations covering the past 50 years. For purpose of illustration, we present in this paper only the results for Novolazaravskaja station which has temperature records with more than 8.4% dispersed missing values at 8 pressure levels from October/1969 to March/2011. [ABSTRACT FROM AUTHOR]

Quilts play a vital role in the thermal comfort of sleeping people. This study aims to investigate the comfortable indoor temperatures and thermal responses when people sleep in different quilts. The experiment tested three kinds of quilts (down, silk, and polyester), and each kind of quilt involved six filling weights. Sixteen participants (eight males and eight females) conducted whole‐night sleeping trials to acquire skin temperatures, bedding temperatures, and thermal perceptual responses. The lower and upper limits of air temperatures (Tlower$$ {T}_{lower} $$ and Tupper$$ {T}_{upper} $$) for comfortable sleeping were obtained. The results indicated that thermal sensation votes were in the range from 0.1 (close to "neutral") to 1.3 (close to "slightly warm") when participants felt comfortable and preferred "no change" in thermal preference. The corresponding comfortable mean skin and bedding temperatures were 34.6 ~ 35.2°C and 31.2 ~ 32.7°C, respectively. Tlower$$ {T}_{lower} $$ and Tupper$$ {T}_{upper} $$ had good linear correlations with bedding insulations. For the same bedding insulation, the Tlower$$ {T}_{lower} $$ and Tupper$$ {T}_{upper} $$ were highest for using silk quilts, followed by down and polyester quilts. The comfort ranges of air temperatures and quilt insulations were finally determined. The findings may benefit understanding the thermal requirement of quilts and help people select and design quilts to achieve thermal comfort. [ABSTRACT FROM AUTHOR]

A dual thermistor radiosonde (DTR) comprising two (aluminium-coated and black) sensors with different emissivities was developed to correct the effects of solar radiation on temperature probes based on in situ radiation measurements. Herein, the DTR performance is characterised in terms of the uncertainty via a series of ground-based facilities and an intercomparison radiosounding test. The DTR characterisation procedure using laboratory facilities is as follows: individually calibrate the temperature of the thermistors in a climate chamber from - 70 to 30 ∘ C to evaluate the uncertainty of raw temperature measurement before radiation correction; test the effect of temperature on the resistance reading using radiosonde boards in the climate chamber from - 70 to 20 ∘ C to identify a potential source of errors owing to the boards, especially at cold temperatures; individually perform radiation tests on thermistors at room temperature to investigate the degree of heating of aluminium-coated and black sensors (the average ratio = 1 : 2.4) and use the result for obtaining unit-specific radiation correction formulas; and perform parameterisation of the radiation measurement and correction formulas with five representative pairs of sensors in terms of temperature, pressure, ventilation speed, and irradiance using an upper air simulator. These results are combined and applied to the DTR sounding test conducted in July 2021. Thereafter, the effective irradiance is measured using the temperature difference between the aluminium-coated and black sensors of the DTR. The measured irradiance is then used for the radiation correction of the DTR aluminium-coated sensor. The radiation-corrected temperature of the DTR is mostly consistent with that of a commercial radiosonde (Vaisala, RS41) within the expanded uncertainty (∼ 0.35 ∘ C) of the DTR at the coverage factor k = 2. Furthermore, the components contributing to the uncertainty of the radiation measurement and correction are analysed. The DTR methodology can improve the accuracy of temperature measurement in the upper air within the framework of the traceability to the International System of Units. [ABSTRACT FROM AUTHOR]

Remote sensing data are a crucial tool for monitoring climatological changes and glacier response in areas inaccessible for in situ measurements. The Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) product provides temperature data for remote glaciated areas where air temperature measurements from weather stations are sparse or absent, such as the St. Elias Mountains (Yukon, Canada). However, MODIS LSTs in the St. Elias Mountains have been found in prior studies to show an offset from available weather station measurements, the source of which is unknown. Here, we show that the MODIS offset likely results from the occurrence of near-surface temperature inversions rather than from the MODIS sensor's large footprint size or from poorly constrained snow emissivity values used in LST calculations. We find that an offset in remote sensing temperatures is present not only in MODIS LST products but also in Advanced Spaceborne Thermal Emissions Radiometer (ASTER) and Landsat temperature products, both of which have a much smaller footprint (90–120 m) than MODIS (1 km). In all three datasets, the offset was most pronounced in the winter (mean offset >8 ∘C) and least pronounced in the spring and summer (mean offset <2 ∘C). We also find this enhanced seasonal offset in MODIS brightness temperatures, before the incorporation of snow surface emissivity into the LST calculation. Finally, we find the MODIS LST offset to be consistent in magnitude and seasonal distribution with modeled temperature inversions and to be most pronounced under conditions that facilitate near-surface inversions, namely low incoming solar radiation and wind speeds, at study sites Icefield Divide (60.68 ∘ N, 139.78 ∘ W; 2,603 m a.s.l) and Eclipse Icefield (60.84 ∘ N, 139.84 ∘ W; 3017 m a.s.l.). Although these results do not preclude errors in the MODIS sensor or LST algorithm, they demonstrate that efforts to convert MODIS LSTs to an air temperature measurement should focus on understanding near-surface physical processes. In the absence of a conversion from surface to air temperature based on physical principles, we apply a statistical conversion, enabling the use of mean annual MODIS LSTs to qualitatively and quantitatively examine temperatures in the St. Elias Mountains and their relationship to melt and mass balance. [ABSTRACT FROM AUTHOR]

In this study, we focused on the impacts of the planetary boundary layer (PBL) low-level jet (LLJ) on the horizontal distribution, vertical development, and 3D structure of urban heat island (UHI). Observational datasets were collected from 224 automatic weather stations (AWSs), and an intensive sounding experiment was conducted in Beijing from 28 August to 2 September 2016. Three-dimensional simulations were operated by the Weather Research and Forecasting (WRF) Model. The results show the following: Ri was smaller than 0.25 at both urban and suburban stations near the surface when the LLJ was present. Through turbulent mixing, the LLJ extended the horizontal distribution of the canopy UHI downwind and increased the total UHI area by approximately 1 × 103 km2. The temperature lapse rate in the urban area was 0.7°C (100 m)−1 with the LLJ, twice that in the absence of an LLJ. The jet enhanced the vertical mixing above the urban area, accompanied by a near-surface TKE up to 0.52 m2 s−2, elevating the vertical UHI development height to 200 m. The LLJ is capable of increasing the temperature of the downwind urban area by a maximum of 8.5°C h−1 through warm advection. The temperature advection in the upper air caused by the LLJ also tilted the 3D UHI structure as a plume. Results reproduced the process by which the LLJ affect the 3D UHI structure through turbulence and advection, and could also provide ideas regarding the influence of the LLJ in other PBL processes. [ABSTRACT FROM AUTHOR]

The purpose of this study is to determine the size of air temperature changes with altitude in the mountains of the arid zone, on the example of the Upper Dades valley (High Atlas, Morocco). The air temperature change with altitude was determined on the basis of 5 years data from three meteorological stations. The analysis was carried out on an annual and seasonal basis. The annual and daily variations of thermal gradients between pairs of stations were also determined. It was found that the average thermal gradient in the Upper Dades valley was -1.02°C per 100 m. The highest values of the thermal gradient occur in winter and the lowest in summer. In winter, the thermal gradient was characterized by the greatest variability. Minima of the daily variation of air temperature gradients were observed in early morning hours and maxima around midday. In the lower part of the valley, air temperature inversion frequently developed between 10 AM and 3 PM UTC. The obtained results show high thermal gradients in the mountains of the arid zone, with their annual amplitude increasing in the lower parts of the valley. The instantaneous values of the gradients were significantly modified by the supply of latent heat and the occurrence of dust storms. It has been shown that the advection factor plays an important role in shaping large gradient values. The study contains novel results of thermal gradient measurements in high mountains of arid zone. [ABSTRACT FROM AUTHOR]

A dual thermistor radiosonde (DTR) comprising two (white and black) sensors with different emissivities was developed to correct the effects of solar radiation on temperature sensors based on in-situ radiation measurements. Herein, the DTR performance is characterised in terms of the uncertainty via a series of ground-based facilities and an intercomparison sounding test. The DTR characterisation procedure using laboratory facilities is as follows: individually calibrate the temperature of the thermistors in a climate chamber; test the effect of temperature on the resistance reading using radiosonde boards in the climate chamber; individually perform radiation tests on thermistors; and perform parameterisation of the radiation measurement and correction formulas using an upper air simulator with varying temperature, pressure and ventilation speed. These results are combined and applied to the DTR sounding test conducted in July, 2021. Thereafter, the effective irradiance is measured using the temperature difference between the white and black sensors of the DTR. The measured irradiance is then used for the radiation correction of the DTR white sensor. The radiation-corrected temperature of the DTR is mostly consistent with that of a commercial radiosonde (Vaisala, RS41) within the expanded uncertainty (~0.35 ℃) of the DTR at the coverage factor k = 2. Furthermore, the components contributing to the uncertainty of the radiation measurement and correction are analysed. The DTR methodology can improve the accuracy of temperature measurement in the upper air within the framework of the traceability to the International System of Units. [ABSTRACT FROM AUTHOR]

The extension of the ERA5 reanalysis back to 1950 supplements the previously published segment covering 1979 to the present. It features the assimilation of additional conventional observations, as well as improved use of early satellite data. The number of observations assimilated increases from 53,000 per day in early 1950 to 570,000 per day by the end of 1978. Accordingly, the quality of the reanalysis improves throughout the period, generally joining seamlessly with the segment covering 1979 to the present. The fidelity of the extension is illustrated by the accurate depiction of the North Sea storm of 1953, and the events leading to the first discovery of sudden stratospheric warmings in 1952. Time series of ERA5 global surface temperature anomalies show temperatures to be relatively stable from 1950 until the late 1970s, in agreement with the other contemporary full-input reanalysis covering this period and with independent data sets, although there are significant differences in the accuracy of representing specific regions, Europe being well represented in the early period but Australia less so. The variability of ERA5 precipitation from month to month agrees well with observations for all continents, with correlations above 90% for most of Europe and generally in excess of 70% for North America, Asia and Australia. The evolution of upper air temperatures, humidities and winds shows smoothly varying behaviour, including tropospheric warming and stratospheric cooling, modulated by volcanic eruptions. The Quasi-Biennial Oscillation is well represented throughout. Aspects to be improved upon in future reanalyses include the assimilation of tropical cyclone data, the spin-up of soil moisture and stratospheric humidity, and the representation of surface temperatures over Australia. [ABSTRACT FROM AUTHOR]

Currently available data are consistent with increased severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) replication at temperatures encountered in the upper airways (25–33°C when breathing room temperature air, 25°C) compared to those in the lower airways (37°C). One factor that may contribute to more rapid viral growth in the upper airways is the exponential increase in SARS‐CoV‐2 stability that occurs with reductions in temperature, as measured in vitro. Because SARS‐CoV‐2 frequently initiates infection in the upper airways before spreading through the body, increased upper airway viral growth early in the disease course may result in more rapid progression of disease and potentially contribute to more severe outcomes. Similarly, higher SARS‐CoV‐2 viral titer in the upper airways likely supports more efficient transmission. Conversely, the possible significance of air temperature to upper airway viral growth suggests that prolonged delivery of heated air might represent a preventative measure and prophylactic treatment for coronavirus disease 2019. Highlights: The stability of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) in vitro increases exponentially with decreases in temperature proximate to normal core body temperature (37°C).Even room temperature air (25°C) cools upper airway surfaces to several degrees below body temperature (25–33°C), which may promote rapid viral growth.Increased upper airway viral growth may contribute to higher transmission rates and more severe disease.Heated, humidified air may represent a postexposure prophylactic treatment for coronavirus disease 2019. [ABSTRACT FROM AUTHOR]

The present work experimentally studied two novel solar dryers' designs, novel indirect solar dryer (NISD) and novel mixed indirect solar dryer (NMISD). The purpose behind this work is to compare the thermal performance of the proposed dryers with that of a traditional indirect solar dryer (TISD). The testing method involved building and thermally testing the three dryers. The NISD is a novel drying chamber with three absorbed surfaces. The NMISD consisted of a flat plate solar collector and NISD. The air temperature at the drying chamber entrance increased by 60% and 68% for the TISD and NMISD, respectively. In the lower space of the drying chamber, the air temperature was decreased by 35% while increased by 39% for the NISD and NMISD, respectively, compared to the TISD. The air temperature in the upper space of the drying chamber increased by 14% and 49% for the NISD and NMISD, respectively, compared to the TISD. The temperature variations through the drying chamber were -26%, 33%, and 3% in the TISD, NISD, and NMISD, respectively. The thermal efficiencies of the NISD and NMISD were 9% and 55%, respectively, higher than the TISD's. [ABSTRACT FROM AUTHOR]

The development of a limited area model (LAM) capability for the nonhydrostatic Finite‐Volume Cubed‐Sphere (FV3) dynamical core is described and compared with a globally nested approach featuring two‐way feedback. Comparisons of the computational performance of the LAM relative to the two‐way nest reveal that the LAM configuration exhibits considerable improvement in efficiency. High‐resolution (i.e., 3‐km) LAM and nest configuration forecasts covering a 1‐month period show statistically comparable results for most parameters. Forecast differences between the two configurations primarily arise in the upper air temperature and height fields, which show a statistically significant increase in the magnitude of negative biases in geopotential height and upper‐air temperature using the LAM configuration relative to the nest at forecast lead times >24‐h. Precipitation forecasts over the full 60‐h forecast period are also evaluated and depict no statistically significant differences between the two configurations, with the nest configuration exhibiting slightly improved scores. Overall results suggest that while the FV3 LAM approach can introduce degradations into the forecast relative to the two‐way interactive nest at lead times >24‐h, these errors are generally small in magnitude and are accompanied by considerable improvement in computational efficiency. Plain Language Summary: In this study, we describe and evaluate a new limited area model (LAM) capability for the Finite‐Volume Cubed‐Sphere dynamical core. This capability provides a way to run the dynamical core over any region without the need for simultaneous integration of a global model counterpart, thus saving considerable computational resources. However, this framework is susceptible to errors from lateral boundaries, which are provided by an external model at a coarse temporal frequency compared to a global model employing a nest with two‐way feedback. Short range forecasts at 3‐km grid spacing over the contiguous United States show generally similar performance between the limited area and nest configurations for a month‐long period in 2019, with the nest showing slightly better forecast scores near the end of the studied forecast length of 60 h. These results suggest that use of the LAM performs similarly to the more sophisticated, and computationally expensive, two‐way nest configuration for convection‐allowing, short range forecasts to 60 h. Key Points: A limited area modeling capability has been developed for the Finite‐Volume Cubed‐Sphere dynamical coreThis capability was evaluated for a month‐long period against a similarly configured two‐way nest driven by a global modelThe limited area model is statistically comparable to the two‐way nest for the first 24 h, with minor degradation by 48–60 h [ABSTRACT FROM AUTHOR]

The use of fossil fuels for energy needs increases atmospheric greenhouse gas (GHG) concentrations to levels that can significantly exacerbate the climate on earth. Assessing the vulnerability of regional crop production systems to such an altered climate in the future is essential for implementing appropriate adaptation and mitigation strategies for sustainable agriculture. We investigated the possible impacts of climate change (CC) projected by multiple global climate models (GCMs) on rainfed and irrigated corn (Zea mays L., a C4 plant) in the Lower Mississippi Delta region (LMD), USA. The CSM-CROPGRO-Maize v4.6 module in the RZWQM2 model (hereafter referred to as the "corn model") was previously calibrated and validated for modeling corn at Stoneville, Mississippi, a representative location in the LMD was used. The CC scenarios considered in this study were ensembles of climate projections of multiple GCMs (97 ensemble members) that participated in the Climate Model Inter-comparison and Improvement Program 5. These CC scenarios were bias-corrected and spatially downscaled (BCSD) at the location for the years 2050 and 2080. Four representative GHG concentration pathways (RCP) 2.6, 4.5, 6.0, and 8.5 drove these CC scenarios. Under both irrigated and rainfed conditions, corn yield responses to enhanced CO2 were weak; thus, yield declined significantly in response to the enhanced air temperatures under all the RCP scenarios in both 2050 and 2080. The yield declines across RCPs ranged between 10 and 62% under irrigated conditions, and between 9 and 60% under rainfed conditions, mainly due to increased frequency of extreme temperatures and reduced crop durations. Water use efficiency declined between 22 and 150% under irrigated, and 8 and 54% under rainfed management. As an adaptation measure, planting corn up to 9 weeks earlier in the season, in general, failed to boost yields from increased crop duration and reduction in upper extreme air temperatures, as incidences of lower extreme temperatures also increased alarmingly. Development of cultivars that are more heat tolerant and produce higher yields under extreme temperatures would be required to combat corn yield decline in the region from climate change. [ABSTRACT FROM AUTHOR]

Echoes from meteor trails can be analyzed to derive diffusion coefficient and thereafter estimates of neutral temperatures, typically around 90 km altitude. The method entails some assumptions and, usually, use of model pressures. Even so, variations in derived temperatures have been assumed to be representative and indicators of other mesospheric processes. However, we now find that the observed variations, seen as enhancements, are very closely associated with enhancements in geomagnetic activity. Here we introduce a metric for describing geomagnetic activity (as an alternative to, e.g., the k‐index) and suggest a methodology for near‐real‐time correction of results. Plain Language Summary: It is possible to estimate upper air temperatures by observing expansion of meteor trails (akin to condensation trails from jet aircraft). We show that strong geomagnetic activity can result in wrong estimates. Key Points: Mesospheric temperatures determined by meteor wind radarGeomagnetic disturbances give rise to incorrect determination [ABSTRACT FROM AUTHOR]

The microwave humidity sounder (MWHS) onboard the Fengyun-3D satellite is providing the data for profiling atmospheric temperature and moisture and has become an important data source for improving the weather forecasts. In this article, three data sources are utilized for assessing the MWHS on-orbit performance, including Global Navigation Satellite System Occultation Sounder (GNOS), ECMWF (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA)-Interim reanalysis, and Advanced Technology Microwave Sounder (ATMS) data. GNOS-retrieved atmospheric profiles and the reanalysis data are used as inputs to the community radiative transfer model (CRTM) for simulating the MWHS brightness temperatures at the top of the atmosphere in July 2018 for characterizing the instrument performance. Since ATMS is a well-calibrated microwave sounding instrument onboard both Suomi NPP and NOAA-20 satellites, its measurements are also collocated with MWHS data for a consensus analysis using the simultaneous nadir overpasses (SNOs) method. In comparing GNOS simulations, MWHS upper air temperature sounding channels (3–6) have relatively larger biases (less than 2.5 K) than the water vapor sounding channels. However, the standard deviation of the difference between observations and simulations (O-B) is larger for water vapor sounding channels. For ERA simulations, MWHS sounding channels exhibit negative biases similar to GNOS results but the standard deviation of O-B at the water vapor channels is much smaller. When compared with ATMS water vapor channels, MWHS biases are mostly negative and agree with those from ERA simulation. Thus, the large uncertainty in simulating MWHS water vapor sounding channels from GNOS could result from the poor input water vapor profiles and high water vapor variability in the lower troposphere. [ABSTRACT FROM AUTHOR]

The present framework explores the climatic variability and impact of El Niño–Southern Oscillation (ENSO) on precipitation over 11 meteorological stations of the Jhelum River catchment (JRC) over a 43-year period (1971–2013). Nonparametric Mann-Kendall (MK) and innovative trend analysis methods were applied to determine variations in climatic parameter (precipitation and temperature time-series) and illuminate how variations in the ENSO index with extreme precipitation changes over time. The MK test generally assessed increasing and decreasing trends in the area, whereas the innovative trend analysis represented the trend magnitude and direction. Comparison of the 20-year return period during El Niño and La Niña years, as well as seasonal variation in air temperature at central and upper parts of the JRC (northeast of the Karakoram mountains), exerts a significant impact on maximum air temperature from −2.09 to −2.53°C/year. A significant trend in seasonal and annual precipitation of 3.62 mm/year was also detected at the upper part of the JRC. In addition, the quantitative variation in precipitation due to global air temperature was determined and revealed the risk of extreme, high intensity precipitation increases across high altitudes, which decrease at middle altitudes of the JRC under the warm scenario. However, all seasons showed the heightened effect of ENSO over the area, varying from 1% to 36%, for extreme precipitation events. The findings are providing the uncertainties associated with the influence of ENSO on future development activities to cope with wet and dry seasons. [ABSTRACT FROM AUTHOR]

It is well known that El Niño events can induce worldwide impacts. However, the fact that strong El Niño events do not necessarily induce strong impacts raises a new research question: how to estimate the impacts of El Niño events in advance? To address this question, we studied the El Niño impacts from the perspective of complex network. By comparing the results from five El Niño events with distinct impacts, we found that the phase transition of the surface air temperature network over tropical Pacific is closely related to the El Niño impacts. This phenomenon was used to explain the less‐than‐expected impacts of the strong 2015/2016 El Niño, which is suggested more like a Central Pacific‐Eastern Pacific mixed El Niño. To monitor the impacts objectively, we further proposed an index, which can be used in real‐time operations. Plain Language Summary: It is well known that El Niño event has substantial impacts on climate, which can induce extreme events or even natural disasters. There are a variety of indices (e.g., Niño3.4 index) to measure the strength of the El Niño, but the fact that strong El Niño does not necessarily mean strong impacts calls for appropriate approaches to quantify the El Niño impacts. Here we proved a close relation between the El Niño impacts and the state of the surface air temperature field over the tropical Pacific. That is, if an El Niño event is not strong enough to significantly alter the state of the upper surface air temperature field, then its influences will not be able to be remarkably transported to remote regions via atmospheric bridges. Using complex network analysis, we quantified the state changes of the surface air temperature field and proposed a new index to measure the El Niño impacts. The new index well distinguished the Eastern Pacific and the Central Pacific El Niño and explained the less‐than‐expected impacts of the 2015/2016 El Niño. Since the calculations are based on past observations, the approach proposed here can be used in operations for objective estimation of the El Niño impacts. Key Points: The El Niño impacts are linked with network phase transition analysisThe less‐than‐expected impacts of the El Niño in 2015/2016 are explainedEastern Pacific and Central Pacific El Niño events are well distinguished [ABSTRACT FROM AUTHOR]

For the accurate measurement of temperature in the upper air by using radiosondes, one prerequisite is the compensation of solar radiation effects that cause sensor heating. The development at the Korea Research Institute of Standards and Science (KRISS) of an upper air simulator (UAS) that can simulate radiation effects is reported. The UAS can independently control four environmental parameters: irradiance, temperature, pressure and air speed. An entire radiosonde can be installed in the test chamber and the measurement data transmitted remotely via an antenna. Solar irradiance is mimicked by using a solar simulator that irradiates the radiosonde sensor. The temperature of the test chamber is controlled from −70 to 20°C by placing it inside a climatic chamber. The pressure and ventilation speed in the test chamber are modulated using combinations of sonic nozzles, a mass flow controller and a vacuum pump. A ventilation speed of 5 m·s−1, which mimics the speed of ascent of the radiosondes when lifted using a balloon, is achieved at pressures as low as 7 hPa. The capability of controlling the environmental parameters independently and the stability of each parameter are presented. As a proof of concept, the radiation‐induced bias on the temperature sensor of a commercial radiosonde Vaisala RS41 is measured. The effect of each parameter is investigated by varying it while keeping the other parameters fixed. Radiosonde calibration using the UAS at the KRISS will help improve the traceability of upper air measurements to the International System of Units. [ABSTRACT FROM AUTHOR]

The article presents a study on the effects of the increasing the air temperature of indoor pools during swim trainings in Ohio. It reports that the air temperature and the concomitant humidity, an individual's body composition, and the types of physical activity that an individual is engaged at affect how individuals perceive water temperature. It suggests the potential model that influences the perception and water experience.

Determination of the long wave (LW) atmospheric radiation (λ = 4–100 μm) is of great importance for several applications. In this study, the effect of screen level and upper air temperatures and water vapour contents on the LW radiation for clear skies has been investigated using 4 years of measurements conducted in Adelaide (34.9° S;130.6° E), South Australia. A two-variable model, which depends on the screen level temperature and vapour pressure, has been developed to calculate the LW radiation. The model can predict the hourly measured data with a correlation coefficient of 0.88, giving mean bias error (MBE) of 0.21 W/m2, root mean square error (RMSE) of 17.3 W/m2, and a mean percentage error (MPE) of − 0.11% with respect to hourly observations. The performance of the multilinear model was tested against a 1-year independent data set. In this case, the MBE, RMSE, MPE, and correlation coefficient were 0.94 W/m2, − 2.2 W/m2, 18.1 W/m2, − 0.5%, and 0.85, respectively. Using radiosonde data, the total atmospheric water content has been calculated and its effect on the LW radiation has been investigated. A simple model that uses the screen level temperature and the precipitable water vapour (PWV) has been proposed. The correlation coefficient, MBE, and RMSE for this model were 0.93, 0.08 W/m2, and 12.12 W/m2, respectively; an MPE of 0.09% was reported by the model. The predictions of ten well-known clear sky models have been evaluated against the measured LW radiation data. These models were, then, adjusted and their performances have been assessed. The impact of the atmospheric mean weighted temperature on the LW radiation was studied. We have found that this temperature has less of an effect on the LW atmospheric radiation than screen level temperature. Finally, the clear sky model which uses the screen level parameters has been adjusted to account for the effect of clouds on the LW radiation. The model shows an acceptable predictability for the LW radiation under all sky conditions. The MBE, RMSE, MPE, and correlation coefficient for this model were 0.51 W/m2, 22.5 W/m2, 0.2% and 0.80, respectively. [ABSTRACT FROM AUTHOR]

Copyright of IUG Journal of Humanitarian Research is the property of Islamic University of Gaza and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract A recent research showed that data centers consumed about 1.3% of total worldwide electricity. Thus, energy conservation in data centers should be paid enough attention to. The impacts of server lower-side terminal baffles (SLTBs) on the thermal environment in data center are optimized by experiments and simulations. In this paper, three different sizes (4 cm × 46 cm, 8 cm × 46 cm and 12 cm × 46 cm) of baffles with six different baffle angles (0°, 15°, 30°, 45°, 60° and 75°) are applied to investigate the optimum airflow distribution. The simulation model was validated by on-site experiments, while the experimental results are in good agreement with numerical results. The measurements show that the use of 45° angle and 8 cm × 46 cm SLTBs can effectively eliminate the heat accumulation and improve the airflow distribution and cooling efficiency in data center. In addition, it can decrease the temperature of the rack hotspot 1.9–2.5K, that reduces significantly the risk of local hotspot and avoid catastrophic damages to the servers. Furthermore, the exhaust air temperature distribution of the upper and lower parts of rack was quite uniform and by using the optimal baffles, the maximum temperature difference reduced from 2.2K to 0.5K. Highlights • An innovative airflow management method in data center is applied in this paper. • Flexible baffles are set on the lower side of servers' rear terminal to improve thermal environment. • The optimum thermal distribution appears in data center with 45° and 8 cm server lower-side baffles. • The exhaust air temperature distribution of the upper and lower parts of the rack was relatively uniform. • The temperature drop of rack hotspot reaches 1.9–2.5 °C reducing the risk of local hotspot damages to the servers. [ABSTRACT FROM AUTHOR]

Observations from the microwave sounding unit (MSU), from 1978 to 2006 and its successor, the Advanced Microwave Sounding Unit-A (AMSU-A, 1998–present), and onboard the National Oceanic and Atmospheric Administration’s polar-orbiting satellites have been widely used for estimating global climate trends. The MSU has a long-term data set, but it is difficult to obtain cloud information like the cloud liquid water path (LWP) directly from this data set. To monitor and investigate the cloud effect on global upper air temperature trends using MSU observations, a cloud detection algorithm must be developed for the MSU. Considering the similar center frequencies of MSU channel 1 and AMSU-A channel 3, a new cloud detection algorithm is established based on the differences between observed and model-simulated brightness temperatures ($O$ - $B$ - $\mu $ ($\alpha$)- $\mu $ ($\phi $)) of MSU channel 1 or AMSU-A channel 3 over oceans, where $\mu $ ($\phi$) is a latitudinal dependent global mean bias and $\mu $ ($\alpha$) is the global mean bias depending on scan angle. If a data point satisfies the condition of $O$ - $B$ - $\mu $ ($\alpha$)- $\mu (\phi) \ge 1$ K, it is removed from the clear sky data set. In order to ensure that those points that are partially affected by the clouds, such as clear and cloud mixed fields-of-views located near cloud edges and/or within optically thin clouds, all data points within the 60-km radial distance of the detected point are removed. Validated with the AMSU-A derived LWP retrievals, about 50% of the clear sky data are successively identified and 99% of the cloudy radiances are successively removed for all NOAA-15 AMSU-A data on January 15, April 15, July 15, and October 15, 2002. [ABSTRACT FROM AUTHOR]

In winter, icing is one of the key factors that restrict the generation of wind power in high-altitude mountains. In this paper, through analyzing the upper air temperature profile of wind farms by using microwave radiometer, we established the water drop temperature calculation formula under non-phase change conditions. Three vertical temperature structures conditions and the relationship between ground water drop temperature and icing efficiency under different conditions are analyzed. This study makes up for the deficiency that the wind turbine icing numerical prediction model can only give the three-dimensional ambient temperature, but cannot give the icing efficiency, which will improve the prediction accuracy of wind turbine icing.

Urban heat island affects cities climate and results in higher air temperature with respect to the surrounding rural zones. Anthropogenic heat released by human activities exacerbates this phenomenon which impacts on environmental and energy fields. Air conditioning is commonly used to achieve comfort indoor conditions in the warmer urban climate but it is also one of the serious cause of the urban heat islands. The heat rejected by the condensers of air conditioning systems, increases the air temperature next to the buildings in which they are installed. In this paper a system consisting of a ground-source heat pump, a low temperature thermal network and a series of electric heat pumps, is analysed. The thermal grid is the heat source/sink for the water to water electric heat pumps that are installed at each end-user of a multi-purpose six floors building located in Naples (Southern of Italy). In cooling mode the condenser heat is discarded in the ground by the ground source heat pump that operates between the lower temperature thermal grid and the borefield. In the heating period the thermal network is heated by the ground source heat pump, that draws energy from the ground. The models simulating the energy conversion systems, the low temperature thermal network and the building, are implemented in the dynamic simulation software TRNSYS 17. A first advantage of the proposed configuration is the avoided interaction with the outside air and the corresponding mitigation of the urban heat island phenomenon. A second one is the higher coefficient of performance of the water to water electric heat pumps, operating with a lower temperature gap with respect to the case in which the electric heat pumps interact with the outside air. Furthermore, the interaction with thermal grid allows high seasonal performance due to the low fluctuation of the temperature with respect to the air. Finally this energy efficient system could be simply installed not only in the new buildings, but also in refurbishments. The proposed system is compared with a conventional one installed in each dwelling consisting of an air to water air conditioner for cooling operation and a boiler for heating. Interesting global and local environmental advantages are obtained. [ABSTRACT FROM AUTHOR]

Using multiple datasets, including three grid datasets (ERA-Interim, WFDEI, and SURF) and one station dataset, we analyzed the climatological distributions and trends of daily maximum air temperature (DMAT) and number of heat days (NHD) over China from 1979 to 2012. In general, all the three grid datasets show the highest climatological DMAT and NHD values in Xinjiang and southeast China, and increasing trends of DMAT and NHD in most of China. Nevertheless, both the climatological condition and trend exhibit differences in detail among the three grid datasets. Using the observed grid dataset (SURF) as a reference, the results show that the WFDEI dataset is closer to SURF than ERA-Interim in characterizing climatological features of DMAT and NHD, and the values from ERA-Interim dataset are lower than the SURF in most part of China. Since the trends of NHD in WFDEI are smaller than those in the other two grid datasets, especially in the middle and lower beaches of the Yangtze River, ERA-Interim is better than WFDEI in representing the trends of NHD. In four regions: Chuanyu, Huanghuai, Xinjiang, and Southeast where the NHD occurs frequently and increases rapidly, the WFDEI is more reliable than ERA-Interim due to the fact that the changes of regional NHD in WFDEI are more consistent with those in observed datasets. Because there exist biases in the records of DMAT between the ERA-interim and WFDEI, it is better to adopt percentile index than absolute threshold to study the changes of China extreme air temperature when using reanalysis datasets. [ABSTRACT FROM AUTHOR]

Subseasonal variability of surface air temperature (SAT) over East Asia is analyzed using the NCEP–NCAR reanalysis of 34 Northern Hemisphere extended summers. An empirical orthogonal function (EOF) analysis is performed with pentad SAT data to identify the leading modes of subseasonal SAT variability. The first (EOF1) and second (EOF2) modes, which together account for about 35% of the total variance, correspond to a monopole structure of SAT anomaly in the whole East Asian region and a dipole structure with opposite signs of variability over the north and south East Asian continent, respectively. Lead–lag regressions are calculated in order to analyze how the large-scale atmospheric circulation evolves in association with the development of the leading SAT modes. An eastward propagation of the Rossby wave from the midlatitude Atlantic Ocean is observed about three pentads before EOF1. EOF2 is influenced by both the tropical Madden–Julian oscillation (MJO) and a midlatitude wave train. These results indicate that there is potential for prediction of the dominant SAT modes on the subseasonal time scale. The subseasonal prediction of the two dominant modes is further evaluated in the operational monthly forecasting system of Environment and Climate Change Canada (ECCC). The model shows a better forecast skill than the persistence forecast. The strength of the subseasonal signal in initial conditions impacts the forecast skill. The forecasts starting with strong EOF in the initial condition are more skillful than those initialized with weak EOF. The findings in the study contribute to improving the understanding of the subseasonal variability and SAT subseasonal forecasting in East Asia. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the relationship between near-surface air temperature (T) and precipitation (P) over Europe simulated by regional climate models (RCMs) from the EURO-CORDEX project. Simulations of two RCMs (RCA4 and CCLM4-8-17) driven by four different global climate models (GCMs) in the period 1971–2000 were analysed. Two different coefficients, the Pearson correlation coefficient based on monthly anomalies and the T-P index (TPI) based on daily values, were used for this evaluation. First, the comparison of T-P correlation and TPI patterns calculated from E-OBS data was made. Afterwards, simulated T-P relationship patterns were briefly evaluated. We especially focused on evaluating the RCM and GCM influence on the simulated T-P relationship pattern. Our results indicate that RCM simulations captured the basic seasonal dependence of the T-P relationship over Europe represented by both T-P correlation and TPI patterns. The simulated T-P relationship pattern is more strongly influenced by an RCM than a driving GCM in contrast to temperature means in winter and precipitation and temperatures changes, which are more strongly influenced by driving GCM as shown in previous studies. The simulations of the CCLM4-8-17 RCM demonstrated noticeably better agreement with observed T-P relationship fields than the RCA4 RCM simulations. The T-P relationship simulated by RCA4 tends to shift to positive values in comparison to E-OBS values. These findings were found for both TPI and T-P correlation. [ABSTRACT FROM AUTHOR]

Residential building heating plays a critical role in building energy conservation in China as it consumes a large proportion of the total primary energy use. Heating energy consumption in China is much larger than that in leading countries. This study investigated the energy saving potential from the building envelope design and actual operation optimization. Results showed that the heating energy consumption target specified in latest forth-step energy efficiency standard in Tianjin still leads to 30.9% higher energy consumption than German building energy efficiency standard EnEv'2009 and 49.7% higher than Passivhaus standard used in Germany. Via field measurement and questionnaire survey during operation, major findings are: (1) high indoor air temperature and window opening for ventilation are accountable for the high heating energy consumption during the operation; (2) radiator heating consumes less energy than radiant floor heating system; (3) temperature-type thermostatic valve and compartment automatic control mode have the best control performance; (4) ventilation device with purifying air unit helps to improve the indoor air quality in the terrible haze weather and to reduce the window opening demand of occupants; (5) heat metering and occupants' energy saving awareness should be encouraged. [ABSTRACT FROM AUTHOR]

Temperature is one of the most important aspects of mountain climates. The relationships between air temperature and rockfalls at high-elevation sites are very important to know, but are also very difficult to study. In relation to this, a reliable method to estimate air temperatures at high-elevation sites is to apply the altitudinal temperature lapse rates (ATLR). The aims of this work are to quantify the values and the variability of the hourly ATLR and to apply this to estimated temperatures at high-elevation sites for rockfalls studies. To calculate ATLR prior the rockfalls, we used data acquired from two automatic weather stations that are located at an elevation above 2500 m. The sensors/instruments of these two stations are reliable because subjected to an accurate control and calibration once for year and the raw data have passed two automatic quality controls. Our study has yielded the following main results: (i) hourly ATLR increases slightly with increasing altitude, (ii) it is possible to estimate temperature at high-elevation sites with a good level of accuracy using ATLR, and (iii) temperature plays an important role on slope failures that occur at high-elevation sites and its importance is much more evident if the values oscillate around 0 °C with an amplitude of ±5 °C during the previous time-period. For these studies, it is not enough to improve the knowledge on air temperature, but it is necessary to develop an integrated knowledge of the thermal conditions of different materials involved in these processes (rock, debris, ice, water). Moreover, this integrated knowledge must be acquired by means of sensors and acquisition chains with known metrological traceability and uncertainty of measurements. [ABSTRACT FROM AUTHOR]

Copyright of Journal of College of Education is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Historical rainfall records reveal that the frequency and intensity of extreme precipitation events, during the summer monsoon (June-September) season, have significantly risen over the Western Himalayas (WH) and adjoining upper Indus basin since 1950s. Using multiple datasets, the present study investigates the possible coincidences between an increasing trend of precipitation extremes over WH and changes in background flow climatology. The present findings suggest that the combined effects of a weakened southwest monsoon circulation, increased activity of transient upper-air westerly troughs over the WH region, enhanced moisture supply by southerly winds from the Arabian Sea into the Indus basin have likely provided favorable conditions for an increased frequency of certain types of extreme precipitation events over the WH region in recent decades. [ABSTRACT FROM AUTHOR]

Differences between lapse rate tropopauses ( LRTs) and LRT-like tropopauses retrieved from mandatory levels ( LRTMs) were studied for height, pressure and temperature at 37 locations of the Indian subcontinent on a long-term annual, summer and winter basis covering the period 1973-2015. LRTM is usually found below LRT and statistical distinctions hinder the use of the former tropopause as a replacement for the latter one, yet significant positive Spearman's correlations show a relationship through a monotonic increasing function that enable the estimation of LRT variables from the corresponding LRTM ones. The slope and the intercept for a linear function relating corresponding variables were obtained at each location. [ABSTRACT FROM AUTHOR]

Sounding rockets launched by China have collected data on the upper atmosphere for nearly 50 years. In this work, the data accuracy and variable characteristics of upper atmosphere temperature data, gathered at heights of 20-60 km over Jiuquan, China, during 1974-2014, were analyzed. The relative accuracy of sounding rocket temperature data was determined by comparing the data with Mass Spectrometer and Incoherent Scatter (MSIS) model data by season, and with Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) from the Thermosphere, Ionosphere, Mesosphere Energetics and Dynamics (TIMED) satellite by year. The sounding rocket temperature data showed differences from MSIS in every season, with the minimum difference occurring in summer, the next smallest difference in winter, and the maximum difference occurring in autumn. The sounding rocket data showed smaller differences from the SABER data, although the deviation still fluctuated depending on the date and hour of the observations. In addition, the temperature distributions of the temperature profiles were examined at different times at the same heights. By linearly fitting the mean temperature profiles of each season, the statistical characteristics of the temperature changes with height were explored. [ABSTRACT FROM AUTHOR]

The performance of a 3D urban microclimate model (ENVI-met Version 3.1) is evaluated with data collected during mostly clear and calm conditions in a compact low-rise residential neighbourhood of tropical Singapore. Observations are obtained from seven canopy-layer air temperature, T a , sensors at 2 m above ground, including a fully equipped microclimate station measuring mean radiant temperature, MRT , at 1.1 m above ground. The model is capable of capturing the spatial variability across all stations during most of the eight simulation days. Spatially-averaged T a predictions are closer to the observations during wet (based on five simulation days) compared to dry (three days) periods. Daytime model performance for MRT is variable but peak values are well predicted. Systematic errors dominate most simulations. The present model evaluation metrics are smaller than reported in similar work, which is likely due to the more accurate determination of model input variables using locally measured soil relative humidity and leaf area density profiles. A modification to how the model calculates MRT also helps to improve its daytime performance. Finally, the model is used to predict the effect of five temperature mitigation/planning strategies. The varying results highlight the micro- and bioclimatic complexities inherent in a heterogeneous urban system, with no one scenario providing consistent cooling throughout both day- and nighttime. Overall the present results suggest that ENVI-met is a useful planning tool for assessing T a and daytime extremes in outdoor thermal comfort, but the model requires detailed local information for proper initialization and awareness of its limitations. [ABSTRACT FROM AUTHOR]

Amplified and persistent ridges in western North America are recurring features associated with drought conditions in California. The recent drought event (2012-2016) lasted through both La Niña and El Niño episodes, suggesting additional climate drivers are important in addition to the commonly perceived El Niño-Southern Oscillation. Diagnostic analyses presented here suggest that, while the Pacific North American (PNA) and North Pacific Oscillation (NPO) do not directly cause drought in California, the relationships between them and with the upper air circulation pattern do modulate the spatial drought pattern. The positive PNA relative circulation leads drier northern California, and (-NPO) relative circulation leads southern California to be drier. The types of drought in this region emerge mostly from the combination of two PNA and NPO relative oceanic and atmospheric oscillations. At present, climate model projections do not indicate any significant change in these particular drought-modulating processes. [ABSTRACT FROM AUTHOR]

A comparison is made of the calculated values of solar radiation incident on the upper atmospheric boundary with the measured values of surface temperature on the territory of the Crimean Peninsula. It is shown that the long-term temperature regime on the territory of the Crimean Peninsula is characterized by a stability. It is determined that the stability of the long-term regime of mean annual surface air temperatures is associated with the characteristics of the latitudinal distribution of solar radiation incident on the upper atmospheric boundary. The incident solar radiation increases in the regions of heat sources and decreases in the regions of heat sink. Stability of long-term mean annual values of surface air temperature is associated with the location of the Crimea on the boundary of the regions of heat sources and sinks. The study revealed the chronological structure of long-term changes in surface air temperature. The anomaly in the long-term surface air temperature variability is characterized by short-duration variations. An analysis is made of the chronological structure of interannual variability in surface air temperature on the territory of the peninsula. The dominant interannual and 2-3-year periodicities in the temperature regime variations are correlated with variations in incident solar radiation. In 62.7% of cases, the sign of interannual variability in surface air temperature corresponds to the sign of interannual variability in incident solar radiation. Thus it is shown that a small tendency in the long-term surface air temperature variability on the territory of the Crimean Peninsula, and the characteristics of its variations are determined largely by the specific character of the input and distribution of solar radiation incident on the upper atmospheric boundary. [ABSTRACT FROM AUTHOR]

In mountainous areas, cold air drainage from high to low elevations has pronounced effects on local temperature, which is a critical driver of many ecosystem processes, including carbon uptake and storage. Here, we leverage new approaches for interpreting ecosystem carbon flux observations in complex terrain to quantify the links between macro-climate condition, drainage flows, local microclimate, and ecosystem carbon cycling in a southern Appalachian valley. Data from multiple long-running climate stations and multiple eddy covariance flux towers are combined with simple models for ecosystem carbon fluxes. We show that cold air drainage into the valley suppresses local temperature by several degrees at night and for several hours before and after sunset, leading to reductions in growing season respiration on the order of ~8%. As a result, we estimate that drainage flows increase growing season and annual net carbon uptake in the valley by >10% and >15%, respectively, via effects on microclimate that are not be adequately represented in regional- and global-scale terrestrial ecosystem models. Analyses driven by chamber-based estimates of soil and plant respiration reveal cold air drainage effects on ecosystem respiration are dominated by reductions to the respiration of aboveground biomass. We further show that cold air drainage proceeds more readily when cloud cover and humidity are low, resulting in the greatest enhancements to net carbon uptake in the valley under clear, cloud-free (i.e., drought-like) conditions. This is a counterintuitive result that is neither observed nor predicted outside of the valley, where nocturnal temperature and respiration increase during dry periods. This result should motivate efforts to explore how topographic flows may buffer eco-physiological processes from macroscale climate change. [ABSTRACT FROM AUTHOR]

ABSTRACT Solar radiation affects temperature measurements by radiosondes considerably in the upper air. In the present study, the effect of both radiation intensity and air pressure on the temperature measurement of radiosonde sensors, as well as reference temperature sensors for comparison, was studied using a home-built chamber allowing light transmission and pressure control. Temperature measurements were conducted both in the illuminated area and the shaded area inside the radiosonde chamber and the temperature difference ( ΔT) between the two was considered for the compensation of radiation. It was found that the temperature difference is linearly proportional to the radiation intensity experimentally as well as theoretically. The effect of air pressure is significant in such a way that the temperature difference rapidly increases up to about 5.5 K under 356.5 W m−2 as the air pressure is decreased down to 1 kPa. The characteristic behaviours of the pressure-dependent temperature deviation are explained by heat transfer equations. The present study emphasizes the importance of considering both radiation intensity and air pressure in efforts to calibrate radiosonde sensors for the solar radiation effect using ground facilities. [ABSTRACT FROM AUTHOR]