Multi layer perceptron model in pattern recognition of surface parameters during pre-monsoon thunderstorm

The concept of Multi Layer Perceptron and Fuzzy logic is introduced in this paper to recognize the pattern of surface parameters pertaining to forecast the occurrence of pre-monsoon thunderstorms over Kolkata (22 ° 32¢ , 88 ° 20¢ ). The results reveal that surface temperature fluctuates significantly from Fuzzy Multi Layer Perceptron (FMLP) model values on thunderstorm days whereas on non-thunderstorm days FMLP model fits well with the surface temperature. The results further indicate that no definite pattern could be made available with surface dew point temperature and surface pressure that can help in forecasting the occurrence of these storms.

Observed and Projected Scaling of Daily Extreme Precipitation with Dew Point Temperature at Annual and Seasonal Scales across the Northeast United Sates

This study investigates how extreme precipitation scales with dew point temperature across the Northeast U.S., both in the observational record (1948-2020) and in a set of downscaled climate projections in the state of Massachusetts (2006-2099). Spatiotemporal relationships between dew point temperature and extreme precipitation are assessed, and extreme precipitation – temperature scaling rates are evaluated on annual and seasonal scales using non-stationary extreme value analysis for annual maxima and partial duration series, respectively. A hierarchical Bayesian model is then developed to partially pool data across sites and estimate regional scaling rates, with uncertainty. Based on the observations, the estimated annual scaling rate is 5.5% per °C, but this varies by season, with most non-zero scaling rates in summer and fall and the largest rates (∼7.3% per °C) in the summer. Dew point temperatures and extreme precipitation also exhibit the most consistent regional relationships in the summer and fall. Downscaled climate projections exhibited different scaling rates compared to the observations, ranging between -2.5 and 6.2% per °C at an annual scale. These scaling rates are related to the consistency between trends in projected precipitation and dew point temperature over the 21st century. At the seasonal scale, climate models project larger scaling rates for the winter compared to the observations (1.6% per °C). Overall, the observations suggest that extreme daily precipitation in the Northeast U.S. only thermodynamic scales with dew point temperature in the warm season, but climate projections indicate some degree of scaling is possible in the cold season under warming.

Establishing Coupled Models for Estimating Daily Dew Point Temperature Using Nature-Inspired Optimization Algorithms

Potential of a classic adaptive neuro-fuzzy inference system (ANFIS) was evaluated in the current study for estimating the daily dew point temperature (Tdew). The study area consists of two stations located in Iran, namely the Rasht and Urmia. The daily Tdew time series of the studied stations were modeled through the other effective variables comprising minimum air temperature (Tmin), extraterrestrial radiation (Ra), vapor pressure deficit (VPD), sunshine duration (n), and relative humidity (RH). The correlation coefficients between the input and output parameters were utilized to determine the most effective inputs. Furthermore, novel hybrid models were proposed in this study in order to increase the estimation accuracy of Tdew. For this purpose, two optimization algorithms named bee colony optimization (BCO) and dragonfly algorithm (DFA) were coupled on the classic ANFIS. It was concluded that the hybrid models (i.e., ANFIS-BCO and ANFIS-DFA) demonstrated better performances compared to the classic ANFIS. The full-input pattern of the coupled models, specifically the ANFIS-DFA, was found to present the most accurate results for both the selected stations. Therefore, the developed hybrid models can be proposed as alternatives to the classic ANFIS to accurately estimate the daily Tdew.

Research and application of natural zeolite in the processes of gas purification and drying

This article describes the adsorption capability of natural zeolites for the purification and dehydration of natural gases. Studies were carried out with natural clinoptilolite treated with various cadmium and titanium solutions. Zeolite-containing rocks were used as a natural adsorbent and experiments using a synthetic CaA zeolite were also carried for comparison. The experiments showed that zeolite from the Ai-Dag deposits possesses the highest activity in terms of sulfur compound. Its activity is closer to that of synthetic CaA zeolite. Studies showed that natural zeolites and adsorbents obtained on their basis allow the gas to be dehydrated to a dew point temperature of minus 40-45 °C. This is sufficient to prepare gas for transportation directly from the fields under any climatic conditions. Keywords: gas dehydration; zeolite; adsorbent; sulfur compounds.

Relationship between weather parameters and risk of exertional heat injuries during military training

Introduction: The Singapore Armed Forces (SAF) collaborated with the Meteorological Service Singapore (MSS) to study the relationship between weather parameters and the incidents of exertional heat injury (EHI) to mitigate the risk of EHI in a practical manner. Methods: Data from the SAF’s heat injury registry and MSS’ meteorological data from 2012 to 2018 were used to establish a consolidated dataset of EHI incidents and same-day weather parameters rank-ordered in deciles. Poisson regression modelling was used to determine the incidence rate ratios (IRRs) of the EHI, referencing the first decile of weather parameters. Two frames of analysis were performed - the first described the relationship between the weather parameters and the adjusted IRR for the same day (D), and the second described the relationship between the weather parameters and the adjusted IRR on the following day (D+1). Results: For wet-bulb temperature, the IRR on D+1 approximated unity for the first nine deciles but rose to 3.09 at the tenth decile. For dew-point temperature, the IRR on D+1 approximated unity for the first nine deciles but rose to 3.48 at the tenth decile. By designating a single dew-point temperature cut-off at  25.1°C (transition between the ninth and tenth decile), the adjusted IRR on D +1 was 2.26 on days with dew-point temperature  25.1°C,. Conclusion: Integrating the data from the SAF and MSS demonstrated that a dew-point temperature ≥ 25.1°C on D correlates statistically with the risk of EHI on D +1and could be used to supplement the risk mitigation system.

Estimate of The Dynamical Change of Air TemperAture, Relative Humidity and Dew Point TemperaTure for Some Selected Station in Iraq

Relative humidity can be inferred from the dew point values. When the air temperature and dew point temperatures are very close, the air has high relative humidity. The converse is true when there is a large difference between the air temperature and the dew point temperature, indicating the presence of low humidity air. To understand the expected changes in the climatic elements in the atmosphere, changes in temperature behavior, dew point, and relative humidity have been studied This study used data obtained from the European Center (ECMWF), which includes monthly and annual mean temperatures, dew, and relative humidity during the period (1988-2018) for selected stations in Iraq. The highest values of temperature and dew were recorded in July and August, and they were accompanied by a decrease in relative humidity. The highest value of relative humidity was recorded in December and January, accompanied by a decrease in temperature and dew, as we note through the results that there is an inverse relationship between relative humidity, temperature, and dew point Relative humidity changes when the temperature rises or falls, and the relative humidity may be higher in the morning when the temperature drops. The lowest amount of relative humidity during the day is when the temperature rises, the highest temperature value was recorded on 21July 2017 (12:00 PM) for Basra Station, while the highest relative value is humidity in Basra Governorate. Mosul station on January 21, 2014 (12:00 AM), and the reason is due to meteorological factors and the nature of the geographical area.

Analysis of perspective air preparation network designs in launch complex temperature control systems

The purpose of the research is to perform a comparative analysis of compressed air preparation systems on the basis of moisture content. The article discusses conventional and perspective methods for drying compressed air using condensation, adsorption and membrane technologies. The article considers a temperature control system with the required dew point of minus 25°С at the exit under standard conditions, which corresponds to the dew point temperature plus 3 °С at a pressure of 1.0 MPa, or class 4 according to GOST R ISO 8573-1–2016. The main advantages of using advanced technological drying system designs are described, including the design of a modern drier with a rotary adsorber that can reduce the dew point temperature of compressed air to minus 25…30 °С at 1.0 MPa pressure without any losses on the adsorbent regeneration. This research is the first to analyze the applicability of modern adsorption and membrane modules to the launch complex functions. All the air drying designs were considered in this paper in relation to air temperature control systems based on air refrigerators using the I-d hygrometric chart for variable pressures.