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Towards Increasing Data Availability for Meteorological Services: Inter-Comparison of Meteorological Data from a Synoptic weather station and Two Automatic weather stations in Kenya

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American Journal of Climate Change 2021年第3期10卷 300-316页

作者： Richard Muita Paul Kucera Stella Aura David Muchemi David Gikungu Samuel Mwangi Martin Steinson Paul Oloo Nicholas Maingi Ezekiel Muigai Mwaura Kamau Kenya Meteorological Department Institute for Meteorological Training and Research Nairobi Kenya University Corporation for Atmospheric Research/National Centre for Atmospheric Research (UCAR/NCAR) Boulder USA

Meteorological data is useful for varied applications and sectors ranging from weather and climate forecasting, landscape planning to disaster management among others. However, the availability of these data requires a good network of manual meteorological stations and other support systems for its collection, recording, processing, archiving, communication and dissemination. In sub-Saharan Africa, such networks are limited due to low investment and capacity. To bridge this gap, the National Meteorological Services in Kenya and few others from African countries have moved to install a number of Automatic weather stations (AWSs) in the past decade including a few additions from private institutions and individuals. Although these AWSs have the potential to improve the existing observation network and the early warning systems in the region, the quality and capacity of the data collected from the stations are not well exploited. This is mainly due to low confidence, by data users, in electronically observed data. In this study, we set out to confirm that electronically observed data is of comparable quality to a human observer recorded data, and can thus be used to bridge data gaps at temporal and spatial scales. To assess this potential, we applied the simple Pearson correlation method and other statistical tests and approaches by conducting inter-comparison analysis of weather observations from the manual synoptic station and data from two Automatic weather stations (TAHMO and 3D-PAWS) co-located at KMD Headquarters to establish existing consistencies and variances in several weather parameters. Results show there is comparable consistency in most of the weather parameters between the three stations. Strong associations were noted between the TAHMO and manual station data for minimum (r = 0.65) and maximum temperatures (r = 0.86) and the maximum temperature between TAHMO and 3DPAWS (r = 0.56). Similar associations were indicated for surface pressure (r = 0.99) and R

关键词： Meteorological Data manual weather station Automatic weather station Correlation

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