Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future

Sepideh Karimi; Saeed Karimi; Ahmad Reza Yavari; Mohamad Hosein Niksokhan

doi:doi:10.11648/j.earth.20150403.12

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Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future

Sepideh Karimi, Saeed Karimi, Ahmad Reza Yavari, Mohamad Hosein Niksokhan

Published in Earth Sciences (Volume 4, Issue 3)

Received: 26 April 2015 Accepted: 11 May 2015 Published: 21 May 2015

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Abstract

In recent years the issue of climate change and its effects on various aspects of the environment has become one of the challenges facing planners. It is desirable to analyze and predict the change of critical climatic variables, such as temperature and precipitation, which will provide valuable reference results for future water resources planning and management in the region. The aims of this study are to test the applicability of the Long Ashton Research Station Weather Generator (LARS-WG) model in downscaling daily precipitation and daily maximum (Tmax) and daily minimum (Tmin) temperatures in Damavand catchment in Iran and use it to predict future changes of precipitation and temperature. Future climate of the Damavand catchment is predicted by statistical downscaling outputs from General Circulation Models (GCMs) (HADCM3 for SRES A2 and B2 and A1B scenarios) for the period of 2046–2065.The results showed that the LARS-WG model produces excellent performance in downscaling Tmax and Tmin in the study region but compared to temperature, the model showed more error in downscaling daily precipitation. This issue was confirmed by examining the performance indicators including coefficient of determination, mean absolute error and root-mean square error. Also results showed that precipitation will decrease in future under these scenarios but temperature will increase. Findings of this study will serve as a reference for further studies and planning of future water management strategies in the Damavand catchment.

Published in	Earth Sciences (Volume 4, Issue 3)
DOI	10.11648/j.earth.20150403.12
Page(s)	95-100
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), 2015. Published by Science Publishing Group

Keywords

Climate Change, Prediction, LARS-WG, Statistical Downscaling

References

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APA Style

Sepideh Karimi, Saeed Karimi, Ahmad Reza Yavari, Mohamad Hosein Niksokhan. (2015). Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future. Earth Sciences, 4(3), 95-100. https://doi.org/10.11648/j.earth.20150403.12

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ACS Style

Sepideh Karimi; Saeed Karimi; Ahmad Reza Yavari; Mohamad Hosein Niksokhan. Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future. Earth Sci. 2015, 4(3), 95-100. doi: 10.11648/j.earth.20150403.12

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AMA Style

Sepideh Karimi, Saeed Karimi, Ahmad Reza Yavari, Mohamad Hosein Niksokhan. Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future. Earth Sci. 2015;4(3):95-100. doi: 10.11648/j.earth.20150403.12

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@article{10.11648/j.earth.20150403.12,
  author = {Sepideh Karimi and Saeed Karimi and Ahmad Reza Yavari and Mohamad Hosein Niksokhan},
  title = {Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future},
  journal = {Earth Sciences},
  volume = {4},
  number = {3},
  pages = {95-100},
  doi = {10.11648/j.earth.20150403.12},
  url = {https://doi.org/10.11648/j.earth.20150403.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20150403.12},
  abstract = {In recent years the issue of climate change and its effects on various aspects of the environment has become one of the challenges facing planners. It is desirable to analyze and predict the change of critical climatic variables, such as temperature and precipitation, which will provide valuable reference results for future water resources planning and management in the region. The aims of this study are to test the applicability of the Long Ashton Research Station Weather Generator (LARS-WG) model in downscaling daily precipitation and daily maximum (Tmax) and daily minimum (Tmin) temperatures in Damavand catchment in Iran and use it to predict future changes of precipitation and temperature. Future climate of the Damavand catchment is predicted by statistical downscaling outputs from General Circulation Models (GCMs) (HADCM3 for SRES A2 and B2 and A1B scenarios) for the period of 2046–2065.The results showed that the LARS-WG model produces excellent performance in downscaling Tmax and Tmin in the study region but compared to temperature, the model showed more error in downscaling daily precipitation. This issue was confirmed by examining the performance indicators including coefficient of determination, mean absolute error and root-mean square error. Also results showed that precipitation will decrease in future under these scenarios but temperature will increase. Findings of this study will serve as a reference for further studies and planning of future water management strategies in the Damavand catchment.},
 year = {2015}
}

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TY  - JOUR
T1  - Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future
AU  - Sepideh Karimi
AU  - Saeed Karimi
AU  - Ahmad Reza Yavari
AU  - Mohamad Hosein Niksokhan
Y1  - 2015/05/21
PY  - 2015
N1  - https://doi.org/10.11648/j.earth.20150403.12
DO  - 10.11648/j.earth.20150403.12
T2  - Earth Sciences
JF  - Earth Sciences
JO  - Earth Sciences
SP  - 95
EP  - 100
PB  - Science Publishing Group
SN  - 2328-5982
UR  - https://doi.org/10.11648/j.earth.20150403.12
AB  - In recent years the issue of climate change and its effects on various aspects of the environment has become one of the challenges facing planners. It is desirable to analyze and predict the change of critical climatic variables, such as temperature and precipitation, which will provide valuable reference results for future water resources planning and management in the region. The aims of this study are to test the applicability of the Long Ashton Research Station Weather Generator (LARS-WG) model in downscaling daily precipitation and daily maximum (Tmax) and daily minimum (Tmin) temperatures in Damavand catchment in Iran and use it to predict future changes of precipitation and temperature. Future climate of the Damavand catchment is predicted by statistical downscaling outputs from General Circulation Models (GCMs) (HADCM3 for SRES A2 and B2 and A1B scenarios) for the period of 2046–2065.The results showed that the LARS-WG model produces excellent performance in downscaling Tmax and Tmin in the study region but compared to temperature, the model showed more error in downscaling daily precipitation. This issue was confirmed by examining the performance indicators including coefficient of determination, mean absolute error and root-mean square error. Also results showed that precipitation will decrease in future under these scenarios but temperature will increase. Findings of this study will serve as a reference for further studies and planning of future water management strategies in the Damavand catchment.
VL  - 4
IS  - 3
ER  -

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Author Information

Sepideh Karimi

Department of Environmental Education, Management & Planning, Faculty of Environment, University of Tehran, Tehran, Iran
Saeed Karimi

Department of Environmental Education, Management & Planning, Faculty of Environment, University of Tehran, Tehran, Iran
Ahmad Reza Yavari

Department of Environmental Education, Management & Planning, Faculty of Environment, University of Tehran, Tehran, Iran
Mohamad Hosein Niksokhan

Department of Environmental Engineering, Faculty of Environment, University of Tehran, Tehran, Iran

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APA Style

Sepideh Karimi, Saeed Karimi, Ahmad Reza Yavari, Mohamad Hosein Niksokhan. (2015). Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future. Earth Sciences, 4(3), 95-100. https://doi.org/10.11648/j.earth.20150403.12

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ACS Style

Sepideh Karimi; Saeed Karimi; Ahmad Reza Yavari; Mohamad Hosein Niksokhan. Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future. Earth Sci. 2015, 4(3), 95-100. doi: 10.11648/j.earth.20150403.12

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AMA Style

Sepideh Karimi, Saeed Karimi, Ahmad Reza Yavari, Mohamad Hosein Niksokhan. Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future. Earth Sci. 2015;4(3):95-100. doi: 10.11648/j.earth.20150403.12

Copy | Download

@article{10.11648/j.earth.20150403.12,
  author = {Sepideh Karimi and Saeed Karimi and Ahmad Reza Yavari and Mohamad Hosein Niksokhan},
  title = {Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future},
  journal = {Earth Sciences},
  volume = {4},
  number = {3},
  pages = {95-100},
  doi = {10.11648/j.earth.20150403.12},
  url = {https://doi.org/10.11648/j.earth.20150403.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20150403.12},
  abstract = {In recent years the issue of climate change and its effects on various aspects of the environment has become one of the challenges facing planners. It is desirable to analyze and predict the change of critical climatic variables, such as temperature and precipitation, which will provide valuable reference results for future water resources planning and management in the region. The aims of this study are to test the applicability of the Long Ashton Research Station Weather Generator (LARS-WG) model in downscaling daily precipitation and daily maximum (Tmax) and daily minimum (Tmin) temperatures in Damavand catchment in Iran and use it to predict future changes of precipitation and temperature. Future climate of the Damavand catchment is predicted by statistical downscaling outputs from General Circulation Models (GCMs) (HADCM3 for SRES A2 and B2 and A1B scenarios) for the period of 2046–2065.The results showed that the LARS-WG model produces excellent performance in downscaling Tmax and Tmin in the study region but compared to temperature, the model showed more error in downscaling daily precipitation. This issue was confirmed by examining the performance indicators including coefficient of determination, mean absolute error and root-mean square error. Also results showed that precipitation will decrease in future under these scenarios but temperature will increase. Findings of this study will serve as a reference for further studies and planning of future water management strategies in the Damavand catchment.},
 year = {2015}
}

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TY  - JOUR
T1  - Prediction of Temperature and Precipitation in Damavand Catchment in Iran by Using LARS –WG in Future
AU  - Sepideh Karimi
AU  - Saeed Karimi
AU  - Ahmad Reza Yavari
AU  - Mohamad Hosein Niksokhan
Y1  - 2015/05/21
PY  - 2015
N1  - https://doi.org/10.11648/j.earth.20150403.12
DO  - 10.11648/j.earth.20150403.12
T2  - Earth Sciences
JF  - Earth Sciences
JO  - Earth Sciences
SP  - 95
EP  - 100
PB  - Science Publishing Group
SN  - 2328-5982
UR  - https://doi.org/10.11648/j.earth.20150403.12
AB  - In recent years the issue of climate change and its effects on various aspects of the environment has become one of the challenges facing planners. It is desirable to analyze and predict the change of critical climatic variables, such as temperature and precipitation, which will provide valuable reference results for future water resources planning and management in the region. The aims of this study are to test the applicability of the Long Ashton Research Station Weather Generator (LARS-WG) model in downscaling daily precipitation and daily maximum (Tmax) and daily minimum (Tmin) temperatures in Damavand catchment in Iran and use it to predict future changes of precipitation and temperature. Future climate of the Damavand catchment is predicted by statistical downscaling outputs from General Circulation Models (GCMs) (HADCM3 for SRES A2 and B2 and A1B scenarios) for the period of 2046–2065.The results showed that the LARS-WG model produces excellent performance in downscaling Tmax and Tmin in the study region but compared to temperature, the model showed more error in downscaling daily precipitation. This issue was confirmed by examining the performance indicators including coefficient of determination, mean absolute error and root-mean square error. Also results showed that precipitation will decrease in future under these scenarios but temperature will increase. Findings of this study will serve as a reference for further studies and planning of future water management strategies in the Damavand catchment.
VL  - 4
IS  - 3
ER  -

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