scholarly journals Wet-Bulb Temperature from Relative Humidity and Air Temperature

2011 ◽  
Vol 50 (11) ◽  
pp. 2267-2269 ◽  
Author(s):  
Roland Stull
Keyword(s):  
Gene Expression ◽  
Relative Humidity ◽  
Sea Level ◽  
Air Temperature ◽  
Mean Absolute Error ◽  
Gene Expression Programming ◽  
Absolute Error ◽  
Sea Level Pressure ◽  
Air Temperatures ◽  
Low Humidity

AbstractAn equation is presented for wet-bulb temperature as a function of air temperature and relative humidity at standard sea level pressure. It was found as an empirical fit using gene-expression programming. This equation is valid for relative humidities between 5% and 99% and for air temperatures between −20° and 50°C, except for situations having both low humidity and cold temperature. Over the valid range, errors in wet-bulb temperature range from −1° to +0.65°C, with mean absolute error of less than 0.3°C.

scholarly journals Direct Calculation of Thermodynamic Wet-Bulb Temperature as a Function of Pressure and Elevation

2013 ◽  
Vol 30 (8) ◽  
pp. 1757-1765 ◽  
Author(s):  
Sayed-Hossein Sadeghi ◽  
Troy R. Peters ◽  
Douglas R. Cobos ◽  
Henry W. Loescher ◽  
Colin S. Campbell
Keyword(s):  
Air Temperature ◽  
Mean Absolute Error ◽  
Direct Calculation ◽  
Ambient Air ◽  
Absolute Error ◽  
Mean Square ◽  
Air Temperatures ◽  
Order Polynomial ◽  
The Mean ◽  
Very High

Abstract A simple analytical method was developed for directly calculating the thermodynamic wet-bulb temperature from air temperature and the vapor pressure (or relative humidity) at elevations up to 4500 m above MSL was developed. This methodology was based on the fact that the wet-bulb temperature can be closely approximated by a second-order polynomial in both the positive and negative ranges in ambient air temperature. The method in this study builds upon this understanding and provides results for the negative range of air temperatures (−17° to 0°C), so that the maximum observed error in this area is equal to or smaller than −0.17°C. For temperatures ≥0°C, wet-bulb temperature accuracy was ±0.65°C, and larger errors corresponded to very high temperatures (Ta ≥ 39°C) and/or very high or low relative humidities (5% < RH < 10% or RH > 98%). The mean absolute error and the root-mean-square error were 0.15° and 0.2°C, respectively.

scholarly journals Recent atmospheric changes and future projections along the Saudi Arabian Red Sea Coast

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Abdulhakim Bawadekji ◽  
Kareem Tonbol ◽  
Nejib Ghazouani ◽  
Nidhal Becheikh ◽  
Mohamed Shaltout
Keyword(s):  
Relative Humidity ◽  
Sea Level ◽  
Air Temperature ◽  
Surface Wind ◽  
Surface Air Temperature ◽  
Saudi Arabian ◽  
Sea Level Pressure ◽  
Ensemble Mean ◽  
Red Sea Coast ◽  
Sea Coast

AbstractRecent and future climate diagrams (surface air temperature, surface relative humidity, surface wind, and mean sea level pressure) for the Saudi Arabian Red Sea Coast are analysed based on hourly observations (2016–2020) and hourly ERA5 data (1979–2020) with daily GFDL mini-ensemble means (2006–2100). Moreover, GFDL mini-ensemble means are calculated based on the results of three GFDL simulations (GFDL-CM3, GFDL-ESM2M, and GFDL-ESM2G). Observation data are employed to describe the short-term current weather variability. However, ERA5 data are considered to study the long-term current weather variability after bias removal via a comparison to observations. Finally, a bias correction statistical model was developed by matching the cumulative distribution functions (CDFs) of corrected ERA5 and mini-ensemble mean data over 15 years (2006–2020). The obtained local statistic were used to statically downscale GFDL mini-ensemble means to study the future uncertainty in the atmospheric parameters studied. There occurred significant spatial variability across the study area, especially regarding the surface air temperature and relative humidity, based on monthly analysis of both observation and ERA5 data. Moreover, the results indicated that the ERA5 data suitably describe Tabuk, Jeddah and Jizan weather conditions with a marked spatial variability. The best performance of ERA5 surface air temperature and relative humidity (surface wind speed and sea level pressure) data was detected in Tabuk (Jeddah). These data for the Saudi Arabian Red Sea coast, 1979–2020, exhibit significant positive trends of the surface air temperature and surface wind speed and significant negative trends of the relative humidity and sea level pressure. The GFDL mini-ensemble mean projection result, up to 2100, contains a significant bias in the studied weather parameters. This is partly attributed to the coarse GFDL resolution (2° × 2°). After bias removal, the statistically downscaled simulations based on the GFDL mini-ensemble mean indicate that the climate in the study area will experience significant changes with a large range of uncertainty according to the considered scenario and regional variations.

scholarly journals Saturated Pseudoadiabats—A Noniterative Approximation

2013 ◽  
Vol 52 (1) ◽  
pp. 5-15 ◽  
Author(s):  
Atoossa Bakhshaii ◽  
Roland Stull
Keyword(s):  
Air Temperature ◽  
Mean Absolute Error ◽  
Gene Expression Programming ◽  
Potential Temperature ◽  
Absolute Error ◽  
Final Temperature ◽  
New Variant ◽  
The Mean ◽  
Thermodynamic Domain ◽  
Lifting Condensation Level

AbstractTwo noniterative approximations are presented for saturated pseudoadiabats (also known as moist adiabats). One approximation determines which moist adiabat passes through a point of known pressure and temperature, such as through the lifting condensation level on a skew T or tephigram. The other approximation determines the air temperature at any pressure along a known moist adiabat, such as the final temperature of a rising cloudy air parcel. The method used to create these statistical regressions is a relatively new variant of genetic programming called gene-expression programming. The correlation coefficient between the resulting noniterative approximations and the iterated data such as plotted on thermodynamic diagrams is over 99.97%. The mean absolute error is 0.28°C, and the root mean square error is 0.44 within a thermodynamic domain bounded by −30° < θw ≤ 40°C, P > 20 kPa, and −60° ≤ T ≤ 40°C, where θw, P, and T are wet-bulb potential temperature, pressure, and air temperature.

scholarly journals Quantifying the Independent Influences of Land Cover and Humidity on Microscale Urban Air Temperature Variation in Hot Summer: Methods of Path Analysis and Genetic SVR

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1377
Author(s):  
Weifang Shi ◽  
Nan Wang ◽  
Aixuan Xin ◽  
Linglan Liu ◽  
Jiaqi Hou ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Land Cover ◽  
Path Analysis ◽  
Temperature Variation ◽  
Direct Effect ◽  
Air Temperature ◽  
Urban Areas ◽  
Support Vector ◽  
Urban Air ◽  
Air Temperatures

Mitigating high air temperatures and heat waves is vital for decreasing air pollution and protecting public health. To improve understanding of microscale urban air temperature variation, this paper performed measurements of air temperature and relative humidity in a field of Wuhan City in the afternoon of hot summer days, and used path analysis and genetic support vector regression (SVR) to quantify the independent influences of land cover and humidity on air temperature variation. The path analysis shows that most effect of the land cover is mediated through relative humidity difference, more than four times as much as the direct effect, and that the direct effect of relative humidity difference is nearly six times that of land cover, even larger than the total effect of the land cover. The SVR simulation illustrates that land cover and relative humidity independently contribute 16.3% and 83.7%, on average, to the rise of the air temperature over the land without vegetation in the study site. An alternative strategy of increasing the humidity artificially is proposed to reduce high air temperatures in urban areas. The study would provide scientific support for the regulation of the microclimate and the mitigation of the high air temperature in urban areas.

scholarly journals Assessing the accuracy of microwave radiometers and radio acoustic sounding systems for wind energy applications

2016 ◽  
Author(s):  
Laura Bianco ◽  
Katja Friedrich ◽  
James Wilczak ◽  
Duane Hazen ◽  
Daniel Wolfe ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Relative Humidity ◽  
Mean Absolute Error ◽  
Microwave Radiometer ◽  
Absolute Error ◽  
Acoustic Sounding ◽  
Energy Applications ◽  
Virtual Temperature ◽  
Microwave Radiometers

Abstract. To assess current remote-sensing capabilities for wind energy applications, a remote-sensing system evaluation study, called XPIA (eXperimental Planetary boundary layer Instrument Assessment), was held in the spring of 2015 at NOAA’s Boulder Atmospheric Observatory (BAO) facility. Several remote-sensing platforms were evaluated to determine their suitability for the verification and validation processes used to test the accuracy of numerical weather prediction models. The evaluation of these platforms was performed with respect to well-defined reference systems: the BAO’s 300-m tower equipped at 6 levels (50, 100, 150, 200, 250, and 300 m) with 12 sonic anemometers and 6 temperature and relative humidity sensors; and approximately 60 radiosonde launches. In this study we first employ these reference measurements to validate temperature profiles retrieved by two co-located microwave radiometers, as well as virtual temperature measured by co-located wind profiling radars equipped with radio acoustic sounding systems. Results indicate a mean absolute error in the temperature retrieved by the microwave radiometers below 1.5 °C in the lowest 5 km of the atmosphere, and a mean absolute error in the virtual temperature measured by the radio acoustic sounding systems below 0.8 °C in the layer of the atmosphere covered by these measurements (up to approximately 1.6–2 km). We also investigated the benefit of the vertical velocity applied to the speed of sound before computing the virtual temperature by the radio acoustic sounding systems. We find that using this correction frequently increases the RASS error, and that it should not be routinely applied to all data. Water vapor density profiles measured by the MWRs were also compared with similar measurements from the soundings, showing the capability of MWRs to follow the vertical profile measured by the sounding, and finding a mean absolute error below 0.5 g m−3 in the lowest 5 km of the atmosphere. However, the relative humidity profiles measured by the microwave radiometer lack the high-resolution details available from radiosonde profiles. An encouraging and significant finding of this study was that the coefficient of determination between the lapse rate measured by the microwave radiometer and the tower measurements over the tower levels between 50 and 300 m ranged from 0.76 to 0.91, proving that these remote-sensing instruments can provide accurate information on atmospheric stability conditions in the lower boundary layer.

scholarly journals Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1919 ◽  
Author(s):  
Federico Carotenuto ◽  
Lorenzo Brilli ◽  
Beniamino Gioli ◽  
Giovanni Gualtieri ◽  
Carolina Vagnoli ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Relative Humidity ◽  
Air Temperature ◽  
Meteorological Parameters ◽  
Low Cost ◽  
Absolute Error ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Svalbard Archipelago ◽  
Arctic Environment

The Arctic is an important natural laboratory that is extremely sensitive to climatic changes and its monitoring is, therefore, of great importance. Due to the environmental extremes it is often hard to deploy sensors and observations are limited to a few sparse observation points limiting the spatial and temporal coverage of the Arctic measurement. Given these constraints the possibility of deploying a rugged network of low-cost sensors remains an interesting and convenient option. The present work validates for the first time a low-cost sensor array (AIRQino) for monitoring basic meteorological parameters and atmospheric composition in the Arctic (air temperature, relative humidity, particulate matter, and CO2). AIRQino was deployed for one year in the Svalbard archipelago and its outputs compared with reference sensors. Results show good agreement with the reference meteorological parameters (air temperature (T) and relative humidity (RH)) with correlation coefficients above 0.8 and small absolute errors (≈1 °C for temperature and ≈6% for RH). Particulate matter (PM) low-cost sensors show a good linearity (r2 ≈ 0.8) and small absolute errors for both PM2.5 and PM10 (≈1 µg m−3 for PM2.5 and ≈3 µg m−3 for PM10), while overall accuracy is impacted both by the unknown composition of the local aerosol, and by high humidity conditions likely generating hygroscopic effects. CO2 exhibits a satisfying agreement with r2 around 0.70 and an absolute error of ≈23 mg m−3. Overall these results, coupled with an excellent data coverage and scarce need of maintenance make the AIRQino or similar devices integrations an interesting tool for future extended sensor networks also in the Arctic environment.

scholarly journals Prediction of the Void Ratio Parameter in Mineral Tailings Using Gene Expression Programming

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ali Akbar Heshmati R. ◽  
Hossein Salehzadeh ◽  
Mehdi Shahidi
Keyword(s):  
Gene Expression ◽  
Void Ratio ◽  
Gene Expression Programming ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Physical Parameters ◽  
Experimental Database ◽  
Initial Void Ratio ◽  
Different Sources ◽  
Initial Prediction

Mineral tailing deposits are one of the most important issues in the field of geotechnical engineering. The void ratio of mineral tailings is an essential parameter for investigating the geotechnical behavior of tailings. However, there has not yet been a comprehensive empirical formulation for initial prediction of the void ratio of mineral tailings. In this study, the void ratio of various types of mineral waste is estimated by using gene expression programming (GEP). Therefore, taking into consideration the effective physical parameters that affect the estimation of this parameter, eight different models are presented. A reliable experimental database collected from different sources in the literature was applied to develop the GEP models. The performance of the developed GEP models was measured based on coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE). According to the results, the model with effective stress σ ′ , initial void ratio (e0), and parameters of R2 = 0.92, MAE = 0.109, and RMSE = 0.180 performed the best. Finally, a new empirical formulation for the initial prediction of the void ratio parameter is proposed based on the aforementioned analyses.

CORRELATION COMMUNICATION BETWEEN METEOROLOGICAL PARAMETERS AT EXTREME VALUES OF MAXIMUM AIR TEMPERATURES

2020 ◽  
pp. 101-112
Author(s):  
S.V. Savchuk ◽  
V.E. Timofeev ◽  
O.A. Shcheglov ◽  
V.A. Artemenko ◽  
I.L. Kozlenko
Keyword(s):  
Air Temperature ◽  
Meteorological Parameters ◽  
Extreme Values ◽  
Daily Temperature ◽  
Sea Level Pressure ◽  
Maximum Daily Temperature ◽  
The North ◽  
Air Temperatures ◽  
Average Maximum ◽  
Maximum Air Temperature

The object of the study is the maximum daily air temperature during the months of the year over 1991-2016 by the data of 186 meteorological stations of Ukraine. Extreme values of the maximum daily temperature equal to or exceeded their 95th (Tmax95p and above, ºС) percentile were taken as extreme. The article sets the dates (137 cases) of extreme values of maximum air temperature on more than 60 % of the territory. For these dates, 13 meteorological parameters were selected: average, minimum, and maximum air temperatures; average, minimum and maximum relative humidity; station and sea-level pressure; average, maximum (from 8 synoptic hours) wind speed; rainfall; height of snow cover. The purpose of this work is to determine the correlation coefficient (K), in particular, statistically significant (K≤-0.6, K≥0.6), on these dates between selected meteorological parameters at 186 meteorological stations of Ukraine for 1991-2013. The density of the cases of statistically significant dependence between the meteorological parameters in extremely warm days in separate seasons is determined. In extremely warm days, meteorological parameters and areas with statistically significant correlations at K≤-0.6 were detected: T and F (focally in southern and some western regions with significant density) − in winter; T and F (with the highest density ubiquitous or almost ubiquitous), P and V (in a large number of regions, usually west or right-bank, but with less frequency) − in the transition seasons, and in the autumn between − T and F (in the south with smaller density) and P and F (in some areas of the north, northwest, west, lower east). In all seasons, such a correlation between other meteorological parameters had a focal distribution, usually with a smaller density. In these days, a focal distribution with a small frequency of dependencies at K≥0.6 was found between the meteorological parameters detected (F and V in transition seasons, T and F in winter), except for similar ones. However, such dependence is observed between T and V in some regions in winter and autumn and in some areas of south, southeast, east with a smaller density. The study of the maximum daily temperature is relevant, because from the level of natural hydrometeorological phenomena it is accompanied by dangerous phenomena, negatively affecting the weather dependent industries.

DETERMINATION OF THE CORRELATION BETWEEN INDIVIDUAL METEOROLOGICAL VALUES AT THE BEGINNING OF THE DEPOSITION OF ICE ON THE TERRITORY OF UKRAINE BY THE MONTHS OF THE COLD PERIOD OF THE YEAR DURING 2001-2013 AND THEIR SPATIAL DISTRIBUTION

2019 ◽  
pp. 140-151
Author(s):  
S.I. Pyasetska ◽  
N.P. Grebenyuk ◽  
S.V. Savchuk
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Sea Level ◽  
Meteorological Parameters ◽  
Cold Period ◽  
Sea Level Pressure ◽  
Average Maximum ◽  
Average Relative Humidity ◽  
Maximum Minimum

The article presents the results of the study of the determination of the correlation connection between a number of meteorological values at the beginning of the deposition of ice on the wires of a standard ice-cream machine in certain months of the cold period of the year on the territory of Ukraine during 2001-2013. The research was conducted for 3 winter months, as well as for March and November. The pair of meteorological parameters have been determined at the beginning of the deposition of ice that have a statistically significant correlation coefficient and a spatial-temporal distribution of the distribution in certain months across the territory of Ukraine has been obtained. The most common variant of the statistically significant connection between individual meteorological parameters was the connection between the temperature of the water column (average, maximum, minimum) and relative humidity of air (average, maximum). Thus, for almost all months studied, a statistically significant correlation between the temperature of the vapor (average, maximum, minimum) and relative humidity of air (average, maximum) was established. For the winter months, the correlation coefficient of this connection was positive, and for March and November, it was negative. A widespread version of a statistically significant connection was the relationship between the air temperature (average, maximum, minimum) and the height of the snow cover. This connection for the months studied turned out to be negative. The variants of negative statistically significant connection between average wind speed and average relative humidity of air (January-February, December), average and maximum wind speed and sea-level pressure (November), and also between daily amount precipitation and snow (March), daily rainfall and wind speed (average, maximum), and pressure at sea level (November). During the months of the cold period of the year, statistically significant connections between the air temperature (average, maximum) and pressure at sea level (November), wind speed (average, maximum) and average humidity (January, December), pressure on sea levels and average relative humidity (March). Also, there were isolated cases of statistically significant correlation between snow and sea level pressure (December). The most frequently statistically significant connections between meteorological values at the dates of deposition of ice on the wires of a standard icing machine were observed at stations in the central, northeastern, eastern and separate southern regions.

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