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Keywords:
modeling climatic parameters solar indices statistical indicators.
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The copyright of a submitted article is only transferred to the publishers if and when the article is accepted for publication. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, electrostatic, mechanical, photocopying, recording or otherwise without the prior written permission of the publishers.
Main Article Content
Estimation of climatic parameters from solar indices using ground based data from Kenya, East Africa
Abstract
The daily meteorological data of relative humidity, maximum, minimum, and average temperatures obtained from five stations of the Kenya Meteorological Department over the period 1986 to 2005 were filtered and reduced to monthly means. Monthly data of solar indices: Sunspot number, F10.7 cm solar radio flux and Mg II core-to-wing ratio covering the same period were
employed to model the meteorological variables using the linear multivariate model and applying least square fittings. Validity of the models was tested using Mean Bias Error (MBE) and Root Mean Square Error (RMSE) statistical indicators. The correlations between the observed and predicted values from the models were significant at above 95% level of confidence. The models
show the effect of solar forcing on the climatic parametErs at different locations in Kenya. Solar forcing of climate is evident in Kenya.
employed to model the meteorological variables using the linear multivariate model and applying least square fittings. Validity of the models was tested using Mean Bias Error (MBE) and Root Mean Square Error (RMSE) statistical indicators. The correlations between the observed and predicted values from the models were significant at above 95% level of confidence. The models
show the effect of solar forcing on the climatic parametErs at different locations in Kenya. Solar forcing of climate is evident in Kenya.
