在2021年旱季期间,通过WhatsApp和谷歌表格使用自愿天气观测验证天气预测

G. Giarno, M. Munawar, Ervan Ferdiansyah, Fendy Arifianto, A. Pratiwi, Silvia Yulianti
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引用次数: 0

摘要

可以通过政府机构获得的天气数据非常有限,而为了提高天气预报的准确性,需要均匀而密集的数据分布。因此,有必要增加数据量,本研究的目的是通过STMKG天气监测计划创建一种简单有效的方法来鼓励印度尼西亚的天气观测数量。表单制作得尽可能容易让受访者理解,简单,不花时间。使用Google表单开发,并通过当今最流行的社交媒体,即WhatsApp分发。测试结果表明,社交媒体有潜力用于支持自愿天气数据。所做的表格是足够的,因此受访者在表格的主要内容上犯的错误相对较少。此外,受访者经常犯的错误包括填写身份证,以及输入需要人工更正的街道。根据在印度尼西亚几乎所有省份开展的自愿观察结果,获得的最多数据来自中爪哇省和东爪哇省。根据4个月的测试评估结果,可以准确地识别天气变化及其预测,平均准确率为0.79。验证方法的差异可能会影响准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Verification of Weather Predictions Using Voluntary Weather Observations Via WhatsApp and Google Forms During the Dry Season 2021
The weather data that can be obtained through government institutions is very limited, whereas in order to increase the accuracy of weather predictions a homogeneous and dense distribution of data is needed. Therfore it is necessary to increase the data and the purpose of this research is to create a simple and effective way to encourage the number of weather observations in Indonesia through the STMKG Weather Care program. Forms that are made as easy as for respondents to understand, simple, and don't take the time. Developed using Google Form and distributed via the most popular social media today, namely WhatsApp. The test results showed that social media has the potential to be used to support voluntary weather data. The form made is sufficient so that the respondents make relatively few mistakes in terms of the main content of the form. Moreover, the mistakes that are often made by respondents include filling in ID, and typing sub-districts that require manual correction. Based on the results of voluntary observations spread in almost all provinces of Indonesia with the most incoming data coming from the provinces of Central Java and East Java. Based on the evaluation results of 4 months of testing, weather variations and their predictions can be identified with an accurate distribution, with an average accuracy of 0.79. Differences in methods used in verification may affect accuracy.
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来源期刊
CiteScore
0.10
自引率
0.00%
发文量
11
审稿时长
15 weeks
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