Volume 8, Issue 3, June 2019, Page: 28-36
Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria
Davidson Odafe Akpootu, Department of Physics, Usmanu Danfodiyo University, Sokoto, Nigeria
Mukhtar Isah Iliyasu, Physics Unit, Umaru Ali Shinkafi Polytechnic, Sokoto, Nigeria
Wahidat Mustapha, Nigerian Meteorological Agency (NIMET), Abuja, Nigeria
Simeon Imaben Salifu, Department of Physics, Kogi State College of Education Technical, Kabba, Nigeria
Hassan Taiwo Sulu, Physics Unit, Umaru Ali Shinkafi Polytechnic, Sokoto, Nigeria
Samson Philip Arewa, Department of Physics, Usmanu Danfodiyo University, Sokoto, Nigeria
Mohammed Bello Abubakar, Physics Unit, Umaru Ali Shinkafi Polytechnic, Sokoto, Nigeria
Received: Aug. 26, 2019;       Accepted: Sep. 16, 2019;       Published: Oct. 9, 2019
DOI: 10.11648/j.wros.20190803.11      View  46      Downloads  8
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 (2000-2015). 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 (Tdew), 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 (Tvirtual), potential temperature (Tpotential) and mean temperature (Tmean). 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.
Precipitable Water Vapour, Dew Point Temperature, Relative Humidity, Virtual Temperature, Potential Temperature and Mean Temperature
To cite this article
Davidson Odafe Akpootu, Mukhtar Isah Iliyasu, Wahidat Mustapha, Simeon Imaben Salifu, Hassan Taiwo Sulu, Samson Philip Arewa, Mohammed Bello Abubakar, Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria, Journal of Water Resources and Ocean Science. Vol. 8, No. 3, 2019, pp. 28-36. doi: 10.11648/j.wros.20190803.11
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Held, I. M and Soden, B. J (2000). Water vapor feedback and global warming, Annual Review of Environment and Resources. vol. 25, pp. 441-475.
Trenberth, K. E., Fasullo, J and Smith, L (2005). Trends and variability in column-integrated atmospheric water vapor. Climate Dynamics, vol. 24, no. 7-8, pp. 741-758.
Wang, J., Carlson, D. J., Parsons, D. B et al (2003). Performance of operational radiosonde humidity sensors in direct comparison with a chilled mirror dew-point hygrometer and its climate implication. Geophysical Research Letters. vol. 30, no. 16.
Wagner, T., Beirle, S., Grzegorski, M et al (2006). Global trends (1996-2003) of total column precipitable water observed by Global Ozone Monitoring Experiment (GOME) on ERS 2 and their relation to near-surface temperature. Journal of Geophysical Research: Atmospheres. vol. 111, no. 12, Article IDD12102.
Dai, A (2006). Recent climatology, variability, and trends in global surface humidity,” Journal of Climate. vol. 19, no. 15: pp. 3589- 3606.
Dai, A., Wang, J., Thorne, P. W et al (2011). A new approach to homogenize daily radiosonde humidity data. Journal of Climate. vol. 24, no. 4: pp. 965-991.
Zhao, T., Dai, A and Wang, J (2012). Trends in tropospheric humidity from 1970 to 2008 over china from a homogenized radiosonde dataset. Journal of Climate. vol. 25, no. 13: pp. 4549-4567.
Mieruch, S., No¨el, S., Bovensmann, H et al (2008). Analysis of global water vapour trends from satellite measurements in the visible spectral range. Atmospheric Chemistry and Physics. vol. 8, no. 3, pp. 491-504.
Zhang, L., Wu, L and Gan, B (2013). Modes and mechanisms of global water vapor variability over the twentieth century. Journal ofClimate. vol. 26, no. 15, pp. 5578-5593 USA.
Peng, W., Tongchuan, X., Jiageng, D et al (2017). Trends and Variability in Precipitable Water Vapor throughout North China from 1979 to 2015. Hindawi Advances in Meteorology. Volume 2017, Article ID 7804823, PP 1-10.
Kiehl, J. T and Trenberth, K. E (1997). Earth’s Annual Global Mean Energy Budget. Bull Am Meteorol Soc. 78: 197-208.
Adeyemi, B (2009). Empirical Formulations for Inter-Layer Precipitable Water Vapor in Nigeria. The Pacific Journal of Science and Technology. Volume 10, Number 2: Pp 35-45.
Dupont, J. C., Haeffelin, M., Drobinski, P et al (2008). Parametric model to estimate clear-sky long wave irradiance at the surface on the basis of vertical distribution of humidity and temperature. J. Geophys. Res. 113, D07203. http://dx.doi.org/10.1029/2007JD009046
Lanzante, J. R., Klein, S. A and Seidel, D. J (2003). Temporal homogenization of monthly radiosonde temperature data. Part II: Methodology. J. Climate 16: 224-240.
Gerding, M., Christoph, R., Marion, M et al (2004). Tropospheric water vapour soundings by lidar at high Arctic latitudes. Atmos. Res. 71 (4), 289-302.
Kuwahara, T., Mizuno, A., Nagahama, T et al (2008). Groundbased millimeter-wave observations of water vapor emission (183 GHz) at Atacama. Chile. Adv. Space Res. 42 (7): 1167-1171.
Eng, R. S., Kelley, P. L., Mooradian, A et al (1973). Tunable laser measurements of water vapor transitions in the vicinity of 5 lm. Chem. Phys. Lett. 19 (15), 524-528.
Bevis, M., Businger, S., Herring, T. A et al (1992). GPS meteorology. Remote sensing of atmospheric water vapour using the Global Positioning System. J. Geophys. Res. 97: 15784-15801.
Hagemann, S., Bengtsson, L and Gendt, G (2003). On the determination of atmospheric water vapor from GPS measurements. J. Geophys. Res., 4678.
Li, G., Kimura, F., Sato, T et al (2008). A composite analysis of diurnal cycle of GPS precipitable water vapor in central Japan during Calm Summer Days. Theoret. Appl. Climatol. 92 (1/2): 15.
Stoew, B., Elgered, G., Johansson, J. M (2001). An assessment of estimates of integrated water vapor from ground-based GPS data. Meteorol. Atmos. Phys. 77, 99-107.
Pramualsakdikul, S., Haas, R., Elgered, G et al (2007). Sensing of diurnal and semi diurnal variability in the water vapour content in the tropics using GPS measurements. Meteorol. Appl. 14, 403-412.
Maghrabi, A and Al Dajani, H. M (2013). Estimation of precipitable water vapour using vapour pressure and air temperature in an arid region in central Saudi Arabia. Journal of the Association of Arab Universities for Basic and Applied Sciences. 14, 1-8.
Dee, D. P., Uppala, S. M., Simmons, A. J et al (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society. vol. 137, no. 656, pp. 553-597.
Easterling, D. R and Peterson, T. C (1995). A new method for detecting undocumented discontinuities in climatological time series. International Journal of Climatology. vol. 15, no. 4: pp. 369-377.
Raymond, A. S (1991). College physics. Saunders College Publishing, Harrisonburg, Virginia.
Kingsley, E. U., Samuel, O. A., Abiodun, I. C. A et al (2017). Approximation of the Dew Point Temperature Using a Cost Effective Weather Monitoring System. Physical Science International Journal. 14 (3): 1-6.
Moss, M (2016). Capitol broadcasting company. Raleigh, North Carolina, USA; 2016.
Wallace, J. M and Hobbs, P. V (2006). Atmospheric Science, An Introductory Survey, 2nd Edition, Elsevier, pp 66-82.
Okorie, F. C., Okeke, I., Nnaji, A et al (2012). Evidence of Climate Variability in Imo State of Southeastern Nigeria. Journal of Earth Science and Engineering. 2 (2012) 544-553.
Okorie, F. C (2010). Great Ogberuru in Its Contemporary Geography, Cape Publishers, Owerri, Nigeria.
Smith, W (1966). Note on the relationship between total precipitable water and surface dew point. J. Appl. Meteorol. 5, 726-727.
Atwater, M. A and Ball, J. T (1976). Comparisons of radiation computations using observed and estimated precipitable water. Appl. Meteorol. 15: 1319-1320.
Won, T (1977). The simulation of hourly global radiation from hourly reported meteorological parameters Canadian Prairie Area. Conference, 3rd, Canadian Solar Energy Society Inc., Radiative Processes in Meteorology and Climatology. American Elsevier, New York.
Paltridge, G. W and Platt, C. M. R (1976). Radiative Processes in Meteorology and Climatology. American Elsevier, New York, 1976.
Leckner, B (1978). The spectral distribution of solar radiation at the earth's surface—elements of a model. Sol Energy 20 (2), 143-150.
Lawrence, M. G (2005). The relationship between relative humidity and the dewpoint temperature in moist air: A simple conversion and applications. Bull. Amer. Meteor. Soc., 86, 225-233. doi: http;//dx.doi.org/10.1175/BAMS-86-2-225.
Akpootu, D. O., Iliyasu, M. I., Mustapha, W et al (2017). The Influence of Meteorological Parameters on Atmospheric Visibility over Ikeja, Nigeria. Archives of Current Research International. 9 (3): 1-12. doi: 10.9734/ACRI/2017/36010.
Hejase, H. A. N and Assi, A. H (2011). Time-Series Regression Model for Prediction of Monthly and Daily Average Global Solar Radiation in Al Ain City-UAE. Proceedings of the Global Conference on Global Warming held on 11-14 July, 2011, Lisbon, Portugal. Pp 1-11.
Iqbal, M (1983). An Introduction to Solar Radiation. Academic Press, New York.
Browse journals by subject