Bias of automatic weather parameter measurement in monsoon area, a case study in Makassar Coast

Nurtiti Sunusi; Giarno; Nurtiti Sunusi; Giarno

doi:10.3934/environsci.2023001

AIMS Environmental Science

2023, Volume 10, Issue 1: 1-15. doi: 10.3934/environsci.2023001

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Bias of automatic weather parameter measurement in monsoon area, a case study in Makassar Coast

Nurtiti Sunusi ^{1
,
,},
Giarno ²

1.
Department of Statistics, Faculty of Mathematics and Natural Sciences, Hasanuddin University, Makassar 90245, Indonesia
2.
State College of Meteorology Climatology and Geophysics, Tangerang 15221, Indonesia

Received: 26 June 2022 Revised: 15 October 2022 Accepted: 18 October 2022 Published: 07 November 2022

The shift from manual weather measurements to automation is almost inevitable. When switching to AWS (Automatic Weather Station), WMO requires parallel data testing between automatic and manual measurements to be performed. The purpose of this paper is to conduct a parallel test of AWS data using a simple statistical test that has been applied to three main weather parameters, namely temperature, pressure, humidity, rainfall, and wind direction and speed. The months of January and June were used as samples to represent the character of the wet and dry seasons in the Makassar monsoon area. The results of the analysis show that during the rainy season, only pressure and temperature are identical and homogeneous. Meanwhile, in the dry season, apart from these two parameters, humidity and wind speed are also homogeneous and rainfall is a non-homogeneous parameter in January and June. Both AWS and manual observations show that the influence of land-sea winds in Makassar is very strong. Considering that there are inhomogeneous parameters, it is highly recommended to test for a longer time, taking into account the season, the influence of other global phenomena, the effect of missing data and incorrect data testing various methods of homogeneity and characteristics in each place and their effect on forecasts.
- accuration,
- bias,
- Makassar,
- automatic,
- manual,
- weather observation
Citation: Nurtiti Sunusi, Giarno. Bias of automatic weather parameter measurement in monsoon area, a case study in Makassar Coast[J]. AIMS Environmental Science, 2023, 10(1): 1-15. doi: 10.3934/environsci.2023001

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Abstract

The shift from manual weather measurements to automation is almost inevitable. When switching to AWS (Automatic Weather Station), WMO requires parallel data testing between automatic and manual measurements to be performed. The purpose of this paper is to conduct a parallel test of AWS data using a simple statistical test that has been applied to three main weather parameters, namely temperature, pressure, humidity, rainfall, and wind direction and speed. The months of January and June were used as samples to represent the character of the wet and dry seasons in the Makassar monsoon area. The results of the analysis show that during the rainy season, only pressure and temperature are identical and homogeneous. Meanwhile, in the dry season, apart from these two parameters, humidity and wind speed are also homogeneous and rainfall is a non-homogeneous parameter in January and June. Both AWS and manual observations show that the influence of land-sea winds in Makassar is very strong. Considering that there are inhomogeneous parameters, it is highly recommended to test for a longer time, taking into account the season, the influence of other global phenomena, the effect of missing data and incorrect data testing various methods of homogeneity and characteristics in each place and their effect on forecasts.

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