Air temperature equation derived from sonic temperature and water vapor mixing ratio for turbulent airflow sampled through closed-path eddy-covariance flux systems

Air temperature (T) plays a fundamental role in many aspects of the flux exchanges between the atmosphere and ecosystems. Additionally, knowing where (in relation to other essential measurements) and at what frequency T must be measured is critical to accurately describing such exchanges. In closed-path eddy-covariance (CPEC) flux systems, T can be computed from the sonic temperature (Ts) and water vapor mixing ratio that are measured by the fast-response sensors of a three-dimensional sonic anemometer and infrared CO2–H2O analyzer, respectively. T is then computed by use of either T=Ts1+0.51q-1, where q is specific humidity, or T=Ts1+0.32e/P-1, where e is water vapor pressure and P is atmospheric pressure. Converting q and e/P into the same water vapor mixing ratio analytically reveals the difference between these two equations. This difference in a CPEC system could reach ±0.18 K, bringing an uncertainty into the accuracy of T from both equations and raising the question of which equation is better. To clarify the uncertainty and to answer this question, the derivation of T equations in terms of Ts and H2O-related variables is thoroughly studied. The two equations above were developed with approximations; therefore, neither of their accuracies was evaluated, nor was the question answered. Based on first principles, this study derives the T equation in terms of Ts and the water vapor molar mixing ratio (χH2O) without any assumption and approximation. Thus, this equation inherently lacks error, and the accuracy in T from this equation (equation-computed T) depends solely on the measurement accuracies of Ts and χH2O. Based on current specifications for Ts and χH2O in the CPEC300 series, and given their maximized measurement uncertainties, the accuracy in equation-computed T is specified within ±1.01 K. This accuracy uncertainty is propagated mainly (±1.00 K) from the uncertainty in Ts measurements and a little (±0.02 K) from the uncertainty in χH2O measurements. An improvement in measurement technologies, particularly for Ts, would be a key to narrowing this accuracy range. Under normal sensor and weather conditions, the specified accuracy range is overestimated, and actual accuracy is better. Equation-computed T has a frequency response equivalent to high-frequency Ts and is insensitive to solar contamination during measurements. Synchronized at a temporal scale of the measurement frequency and matched at a spatial scale of measurement volume with all aerodynamic and thermodynamic variables, this T has advanced merits in boundary-layer meteorology and applied meteorology.

Validity and Reliability of a Protocol to Establish Human Critical Environmental Limits (PSU HEAT)

The PSU HEAT protocol has been used to determine critical environmental limits, i.e., those combinations of ambient temperature and humidity above which heat stress becomes uncompensable and core temperature rises continuously. However, no studies have rigorously investigated the reliability and validity of this experimental protocol. Here, we assessed the (1) between-visit reliability and (2) validity of the paradigm. Twelve subjects (5M/7W; 25±4 yr) completed a progressive heat stress protocol during which they walked on a treadmill (2.2 mph, 3% gradient) in a controllable environmental chamber. After an equilibration period, either dry-bulb temperature (Tdb) was increased every 5 min while ambient water vapor pressure (Pa) was held constant (Tcrit experiments) or Pa was increased every 5 min while Tdb was held constant (Pcrit experiments) until an upward inflection in gastrointestinal temperature (Tgi) was observed. For reliability experiments, 11 subjects repeated the same protocol on a different day. For validity experiments, 10 subjects performed a Tcrit experiment at their previously determined Pcrit or vice versa. The between-visit reliability (intraclass correlation coefficient, ICC) for critical environmental limits was 0.98. Similarly, there was excellent agreement between original and validity trials for Tcrit (ICC = 0.95) and Pcrit (ICC = 0.96). Further, the wet-bulb temperature at the Tgi inflection point was not different during reliability (p = 0.78) or validity (p = 0.32) trials compared to original trials. These findings support the reliability and validity of this experimental paradigm for the determination of critical environmental limits for maintenance of human heat balance.

Critical environmental limits for young, healthy adults (PSU HEAT)

Critical environmental limits are those combinations of ambient temperature and humidity above which heat balance cannot be maintained for a given metabolic heat production, limiting exposure time and placing individuals at increased risk of heat-related illness. The aim of the present study was to establish those limits in young (18-34 yr) healthy adults during low-intensity activity approximating the metabolic demand of activities of daily living. Twenty-five (12 men/13 women) subjects were exposed to progressive heat stress in an environmental chamber at two rates of metabolic heat production chosen to represent minimal activity (MinAct) or light ambulation (LightAmb). Progressive heat stress was performed with either (1) constant dry-bulb temperature (Tdb) and increasing ambient water vapor pressure (Pa) (Pcrit trials; 36, 38, or 40 °C), or (2) constant Pa and increasing Tdb (Tcrit trials; 12, 16, or 20 mmHg). Each subject was tested during MinAct and LightAmb in 2-3 experimental conditions in random order, for a total of 4-6 trials per participant. Higher metabolic heat production (p < 0.001) during LightAmb compared to MinAct trials resulted in significantly lower critical environmental limits across all Pcrit and Tcrit conditions (all p < 0.001). These data, presented graphically herein on a psychrometric chart, are the first to define critical environmental limits for young adults during activity resembling those of light household tasks or other activities of daily living, and can be used to develop guidelines, policy decisions, and evidence-based alert communications to minimize the deleterious impacts of extreme heat events.

Permafrost, active layer and meteorological data (2010–2020) from a relict permafrost site at Mahan Mountain, Northeast of Qinghai-Tibet Plateau

Relict permafrost presents an ideal opportunity to understand the impacts of climatic warming on the ground thermal regime since it is characterized by mean annual ground temperature close to 0 °C and relatively thin permafrost. The long-term and continuous observations of permafrost thermal state and climate background are of great importance to reveal the links between the energy balance on hourly to annual timescales, to evaluate the variations of permafrost thermal state over multi-annual periods and to validate the remote sensing dataset. Until now there are few data available in relict permafrost regions although those data are important to understand the impacts of climate changes on permafrost especially in the boundary regions between permafrost and seasonally frozen ground regions. In this study, we present 11 years of meteorological and soil data in a relict permafrost site of the Mahan Mountain on the northeast of the Qinghai-Tibet Plateau. The meteorological data are comprised of air and ground surface temperature, relative humidity, wind speed and direction, shortwave and longwave downward and upward radiation, water vapor pressure, and precipitation on half-an-hour timescale. The active layer data include daily soil temperature and soil moisture at five different depths. The permafrost data consist of ground temperature at twenty different depths up to 28.4 m. The high-quality and long-term datasets are expected to serve as accurate forcing data in land surface models and evaluate remote-sensing products for a broader geoscientific community. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.271838, Wu and Xie, 2021).

Water vapor pressure trends in south and southwest Iran

Recognitionanddetectionofclimaticparameters inhave animportant role inclimate change monitoring. In this study, the analysis of oneofthe most importantparameters, water vapor pressure (WVP), was investigated. For this purpose, two non-parametric techniques, Mann-Kendall and Sen's Slope Estimator, were used to analyze the WVP trend and to determine the magnitude of the trends, respectively. To analyze these tests, ground station observations [10 stations for period of 44 years (1967-2010)] and gridded data [pixels with the dimension of 9 × 9 km over a 30-year period (1981-2010)] in South and SouthwestofIran were used. By programming in MATLAB software, the monthly, seasonal and annual WVP time series were extracted and MK and Sen's slope estimator tests were done. The results of monthly MK test on ground station observations showed that the significant downward trends are more considerable than significant upward trends. It also showed that the WVP highest frequency was more in warm months, April to September and the highest frequency of significant trends slope was in February and May. The spatial distribution of MK test of monthly gridded WVP time series showed that the upward trends were detected mostly in western zone and near the Persian Gulf in August. On the other hand, the downward trends through months. The maximum and minimum values of positive trends slope occurred in warm months and cold months, respectively. The analysis of the MK test of the annual WVP time series indicated the upward significant trends in the southeast and southwest zones of study area.

Air Humidity Characteristics in “Local Climate Zones” of Novi Sad (Serbia) Based on Long-Term Data

This study aims to investigate spatial and temporal dynamics and relationship between air temperature and five air humidity parameters (relative humidity, water vapor pressure, absolute humidity, specific humidity, and vapor pressure deficit) in Novi Sad, Serbia, based on two-year data (Dec 2015–Dec 2017). The analysis includes different urban areas of Novi Sad, which are delineated in five built (urban) types of local climate zones (LCZ) (LCZ 2, LCZ 5, LCZ 6, LCZ 8, and LCZ 9), and one land cover (natural) local climate zone (LCZ A) located outside the urban area. Temporal analysis included annual, seasonal, and monthly dynamics of air temperature and air humidity parameters, as well as their patterns during the extreme periods (heat and cold wave). The results showed that urban dry island (UDI) occurs in densely urbanized LCZ 2 from February to October, unlike other urban LCZs. The analysis of the air humidity dynamics during the heat wave shows that UDI intensity is most pronounced during the daytime, but also in the evening (approximately until midnight) in LCZ 2. However, lower UDI intensity is observed in the afternoon, in other urban LCZs (LCZ 6, LCZ 8, and LCZ 9) and occasionally in the later afternoon in LCZ 5. Regression analysis confirms the relationship between air temperature and each of the analyzed air humidity parameters.

Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points

Atmospheric radio refractivity has an obvious influence on the signal transmission path and communication group delay effect. The uncertainty of water vapor distribution is the main reason for the large error of tropospheric refractive index modeling. According to the distribution and characteristics of water vapor pressure, temperature, and pressure, which are the basic components of the refractive index, a method for retrieving atmospheric refractivity profile based on GNSS (Global Navigation Satellite System) and meteorological sensor measurement is introduced and investigated in this study. The variation of the correlation between zenith wet delay and water vapor pressure is investigated and analyzed in detail. The partial pressure profiles of water vapor are retrieved with relevance vector machine method based on tropospheric zenith wet delay calculated by single ground-based GPS (Global Positioning System) receiver. The atmospheric temperature and pressure is calculated with the least square method, which is used to fit the coefficients of the polynomial model based on a large number of historical meteorological radiosonde data of local stations. By combining the water vapor pressure profile retrieving from single ground-based GPS and temperature and pressure profile from reference model, the refractivity profile can be obtained, which is compared to radiosonde measurements. The comparison results show that results of the proposed method are consistent with the results of radiosonde. By using over ten years’ (through 2008 to 2017) historical radiosonde meteorological data of different months at China Big-Triangle Points, i.e., Qingdao, Sanya, Kashi, and Jiamusi radiosonde stations, tropospheric radio refractivity profiles are retrieved and modeled. The comparison results present that the accuracies of refractivity profile of the proposed method at Qingdao, Sanya, Kashi, and Jiamusi are about 5.48, 5.63, 3.58, and 3.78 N-unit, respectively, and the annual average relative RMSE of refractivity at these stations are about 1.66, 1.53, 1.49, and 1.23%, respectively.

Dead Fuel Moisture Content (DFMC) Estimation Using MODIS and Meteorological Data: The Case of Greece

The frequent occurrence of large and high-intensity wildfires in the Mediterranean region poses a major threat to people and the environment. In this context, the estimation of dead fine fuel moisture content (DFMC) has become an integrated part of wildfire management since it provides valuable information for the flammability status of the vegetation. This study investigates the effectiveness of a physically based fuel moisture model in estimating DFMC during severe fire events in Greece. Our analysis considers two approaches, the satellite-based (MODIS DFMC model) and the weather station-based (AWSs DFMC model) approach, using a fuel moisture model which is based on the relationship between the fuel moisture of the fine fuels and the water vapor pressure deficit (D). During the analysis we used weather station data and MODIS satellite data from fourteen wildfires in Greece. Due to the lack of field measurements, the models’ performance was assessed only in the case of the satellite data by using weather observations obtained from the network of automated weather stations operated by the National Observatory of Athens (NOA). Results show that, in general, the satellite-based model achieved satisfactory accuracy in estimating the spatial distribution of the DFMC during the examined fire events. More specifically, the validation of the satellite-derived DFMC against the weather-station based DFMC indicated that, in all cases examined, the MODIS DFMC model tended to underestimate DFMC, with MBE ranging from −0.3% to −7.3%. Moreover, in all of the cases examined, apart from one (Sartis’ fire case, MAE: 8.2%), the MAE of the MODIS DFMC model was less than 2.2%. The remaining numerical results align with the existing literature, except for the MAE case of 8.2%. The good performance of the satellite based DFMC model indicates that the estimation of DFMC is feasible at various spatial scales in Greece. Presently, the main drawback of this approach is the occurrence of data gaps in the MODIS satellite imagery. The examination and comparison of the two approaches, regarding their operational use, indicates that the weather station-based approach meets the requirements for operational DFMC mapping to a higher degree compared to the satellite-based approach.

Dynamic Changes in Plant Resource Use Efficiencies and Their Primary Influence Mechanisms in a Typical Desert Shrub Community

Understanding plant resource use efficiencies (RUEs) and their tradeoffs in a desert shrub community, particularly as it concerns the usage of water, light, and nitrogen, remains an ecological imperative. Plant RUEs have been widely used as indicators to understand plant acclimation processes to unfavorable environmental conditions. This study aimed to examine seasonal dynamics in RUEs in two widely distributed plant species in a typical desert shrub community (i.e., Artemisia ordosica and Leymus secalinus) based on in-situ measurements of leaf photosynthesis, specific leaf area (SLA), leaf nitrogen concentration (i.e., Nmass + Narea), and several site-related abiotic factors. Both species exhibited significant seasonal variation in RUEs, with a coefficient of variation (CV) > 30% and seasonal divergence among the various RUEs. Seasonal divergence was largely controlled by variation in stomatal conductance (Gs), which was in turn influenced by variation in soil water content (SWC) and water vapor pressure deficit (VPD). RUEs between species converged, being positively correlated, yielding: (i) r2 = 0.40 and p < 0.01 for WUE; (ii) r2 = 0.18 and p < 0.01 for LUE；and (iii) r2 = 0.25 and p < 0.01 for NUE. RUEs for A. ordosica were mostly larger than those for L. secalinus, but less reactive to drought. This suggests A. ordosica was more conservative in its usage of available resources and was, therefore, better able to adapt to arid conditions. Resource use strategies between species differed in response to drought. Desert shrubs are projected to eventually replace grasses, as drought severity and duration increase with sustained regional climate change.

Comparisons of Different Methods to Determine Starting Altitudes for Dry Air Atmosphere by GNSS-RO Data

Boundary profile evaluation (BPV) is an approach proposed in order to estimate water vapor content in the atmosphere. It exploits radio occultation (RO) observations of the signals emitted by the satellites of global navigation systems (GNSS) which are eclipsing (rising) as viewed by a low earth orbit satellite (LEO). BPV requires, as a preliminary step, the estimation of the dry background atmosphere model of refractivity (i.e., obtained from bending angle profiles) to be subtracted from the real observations in order to extract water vapor profiles. The determination of the lowest layer of the atmosphere over which the concentration of water vapor can be deemed negligible is particularly crucial for a correct application of the BPV method. In this study, we have applied three methods to set the starting altitudes for the dry air layers of the atmosphere: (1) by air temperature below some threshold values (for example, 250 K); (2) by “smooth” bending angle profiles in ROs; (3) by saturated water vapor pressure. These methods were tested with thermodynamic and bending angle profiles from 912 radiosonde excursions colocated with RO observations. For every dry air starting altitude we determined the best estimator from each of the three methods. In particular, by comparing those estimators with the quantiles and momenta of the dry air starting altitude distributions, we achieved improvements of up to 50% of the humidity profiles.