Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria

Abstract

Precipitable water vapour (PWV) is a vital component of the atmosphere and appreciably controls many atmospheric processes. The PWV is not easy to measure with sufficient spatial and time resolution under all weather conditions. In this paper, three precipitable water vapour models; the Smith, Won and Leckner's models were evaluated and compared for Owerri (Latitude 5.48°N, Longitude 7.00°E, and 91 m above sea level) using meteorological parameters of monthly average daily maximum temperature, minimum temperature and relative humidity during the period of sixteen years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015). The Leckner's model was found most suitable and therefore recommended for estimating PWV for the location with range between 3.253 and 4.662 cm. The highest PWV occurred in June for Won and Leckner's models while for Smith's model it occurred in September; the lowest PWV occurred in January for all the evaluated models. The result showed that high values of dew point temperature (T dew ), PWV and relative humidity (RH) were observed during the raining season and low values in the dry season; this is an indication that the dew point temperature is a reflection of the PWV and RH. The dew point temperature is an opposite reflection of the virtual temperature (T virtual ), potential temperature (T potential ) and mean temperature (T mean ). The dew point temperature increases and decreases with mean temperature in the months from January to March and in July respectively for the location under investigation. The values of the dew point temperature indicated that the air is stable signifying no development of severe weather condition like thunderstorms. The maximum and minimum virtual temperature correction of 3.3246°C and 2.3371°C occurred in June and January respectively while for the dew point depression, it occurred in the months of January and September with 8.7514°C and 2.1094°C. The descriptive statistical analysis shows that the dew point temperature, potential temperature, mean temperature and virtual temperature correction data spread out more to the left of their mean value (negatively skewed), while the virtual temperature and dew point depression data spread out more to the right of their mean value (positively skewed). The dew point temperature and the virtual temperature correction data have positive kurtosis which indicates a relatively peaked distribution and possibility of a leptokurtic distribution while the virtual temperature, potential temperature, mean temperature and dew point depression data have negative kurtosis which indicates a relatively flat distribution and possibility of platykurtic distribution.

Estimation and Correlation of Surface Water Vapour Density in Benin, Nigeria

“…The following expression relates the surface water vapour density (SWVD), vapour pressure (e), and mean temperature (T) [1,16,18] as:…”

“…where RH and 𝑒 𝑠 stand for saturated vapour pressure and relative humidity, respectively. The Claussius Clapeyron equation was used to calculate the saturation vapour pressure [1,16,18] defined as:…”

“…The ambient Temperature T and Partial Pressure Ps are related by a correlation model as reported by [1] which is expressed by the semi empirical equation…”

“…Water vapour plays a very important function in studies on hydrological processes, climate change, weather systems and Earth's energy balance [1][2][3][4]. "The most common greenhouse gas in the atmosphere is the water vapour which accounts for approximately 60 % of the phenomenon of natural greenhouse effect" [1,5].…”

“…Water vapour plays a very important function in studies on hydrological processes, climate change, weather systems and Earth's energy balance [1][2][3][4]. "The most common greenhouse gas in the atmosphere is the water vapour which accounts for approximately 60 % of the phenomenon of natural greenhouse effect" [1,5]. At the surface, the water vapour which is also known as humidity is a key meteorological and climatological parameter that affects the comfort of human [6], also surface evapouration and plants' transpiration.…”