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

Davidson Odafe Akpootu; Mukhtar Isah Iliyasu; Wahidat Mustapha; Simeon Imaben Salifu; Hassan Taiwo Sulu; Samson Philip Arewa; Mohammed Bello Abubakar

doi:doi:10.11648/j.wros.20190803.11

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

Davidson Odafe Akpootu, Mukhtar Isah Iliyasu, Wahidat Mustapha, Simeon Imaben Salifu, Hassan Taiwo Sulu, Samson Philip Arewa, Mohammed Bello Abubakar

Received: 26 August 2019 Accepted: 16 September 2019 Published: 9 October 2019

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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 (2000-2015). 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.

DOI	10.11648/j.wros.20190803.11
Published in	Journal of Water Resources and Ocean Science (Volume 8, Issue 3, June 2019)
Page(s)	28-36
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Precipitable Water Vapour, Dew Point Temperature, Relative Humidity, Virtual Temperature, Potential Temperature and Mean Temperature

References

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Davidson Odafe Akpootu, Mukhtar Isah Iliyasu, Wahidat Mustapha, Simeon Imaben Salifu, Hassan Taiwo Sulu, et al. (2019). 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, 8(3), 28-36. https://doi.org/10.11648/j.wros.20190803.11

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Davidson Odafe Akpootu; Mukhtar Isah Iliyasu; Wahidat Mustapha; Simeon Imaben Salifu; Hassan Taiwo Sulu, et al. Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria. J. Water Resour. Ocean Sci. 2019, 8(3), 28-36. doi: 10.11648/j.wros.20190803.11

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AMA Style

Davidson Odafe Akpootu, Mukhtar Isah Iliyasu, Wahidat Mustapha, Simeon Imaben Salifu, Hassan Taiwo Sulu, et al. Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria. J Water Resour Ocean Sci. 2019;8(3):28-36. doi: 10.11648/j.wros.20190803.11

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@article{10.11648/j.wros.20190803.11,
  author = {Davidson Odafe Akpootu and Mukhtar Isah Iliyasu and Wahidat Mustapha and Simeon Imaben Salifu and Hassan Taiwo Sulu and Samson Philip Arewa and Mohammed Bello Abubakar},
  title = {Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria},
  journal = {Journal of Water Resources and Ocean Science},
  volume = {8},
  number = {3},
  pages = {28-36},
  doi = {10.11648/j.wros.20190803.11},
  url = {https://doi.org/10.11648/j.wros.20190803.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wros.20190803.11},
  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 (2000-2015). 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.},
 year = {2019}
}

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TY  - JOUR
T1  - Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria
AU  - Davidson Odafe Akpootu
AU  - Mukhtar Isah Iliyasu
AU  - Wahidat Mustapha
AU  - Simeon Imaben Salifu
AU  - Hassan Taiwo Sulu
AU  - Samson Philip Arewa
AU  - Mohammed Bello Abubakar
Y1  - 2019/10/09
PY  - 2019
N1  - https://doi.org/10.11648/j.wros.20190803.11
DO  - 10.11648/j.wros.20190803.11
T2  - Journal of Water Resources and Ocean Science
JF  - Journal of Water Resources and Ocean Science
JO  - Journal of Water Resources and Ocean Science
SP  - 28
EP  - 36
PB  - Science Publishing Group
SN  - 2328-7993
UR  - https://doi.org/10.11648/j.wros.20190803.11
AB  - 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.
VL  - 8
IS  - 3
ER  -

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Author Information

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

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Davidson Odafe Akpootu, Mukhtar Isah Iliyasu, Wahidat Mustapha, Simeon Imaben Salifu, Hassan Taiwo Sulu, et al. (2019). 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, 8(3), 28-36. https://doi.org/10.11648/j.wros.20190803.11

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ACS Style

Davidson Odafe Akpootu; Mukhtar Isah Iliyasu; Wahidat Mustapha; Simeon Imaben Salifu; Hassan Taiwo Sulu, et al. Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria. J. Water Resour. Ocean Sci. 2019, 8(3), 28-36. doi: 10.11648/j.wros.20190803.11

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AMA Style

Davidson Odafe Akpootu, Mukhtar Isah Iliyasu, Wahidat Mustapha, Simeon Imaben Salifu, Hassan Taiwo Sulu, et al. Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria. J Water Resour Ocean Sci. 2019;8(3):28-36. doi: 10.11648/j.wros.20190803.11

Copy | Download

@article{10.11648/j.wros.20190803.11,
  author = {Davidson Odafe Akpootu and Mukhtar Isah Iliyasu and Wahidat Mustapha and Simeon Imaben Salifu and Hassan Taiwo Sulu and Samson Philip Arewa and Mohammed Bello Abubakar},
  title = {Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria},
  journal = {Journal of Water Resources and Ocean Science},
  volume = {8},
  number = {3},
  pages = {28-36},
  doi = {10.11648/j.wros.20190803.11},
  url = {https://doi.org/10.11648/j.wros.20190803.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wros.20190803.11},
  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 (2000-2015). 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.},
 year = {2019}
}

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TY  - JOUR
T1  - Models for Estimating Precipitable Water Vapour and Variation of Dew Point Temperature with Other Parameters at Owerri, South Eastern, Nigeria
AU  - Davidson Odafe Akpootu
AU  - Mukhtar Isah Iliyasu
AU  - Wahidat Mustapha
AU  - Simeon Imaben Salifu
AU  - Hassan Taiwo Sulu
AU  - Samson Philip Arewa
AU  - Mohammed Bello Abubakar
Y1  - 2019/10/09
PY  - 2019
N1  - https://doi.org/10.11648/j.wros.20190803.11
DO  - 10.11648/j.wros.20190803.11
T2  - Journal of Water Resources and Ocean Science
JF  - Journal of Water Resources and Ocean Science
JO  - Journal of Water Resources and Ocean Science
SP  - 28
EP  - 36
PB  - Science Publishing Group
SN  - 2328-7993
UR  - https://doi.org/10.11648/j.wros.20190803.11
AB  - 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.
VL  - 8
IS  - 3
ER  -

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