Instrument development for obtaining microclimate big data of near surface and its impact on numerical weather simulation through data assimilation

2020 Fiscal Year Final Research Report

• Project/Area Number: 18K13840
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 22040:Hydroengineering-related
• Research Institution: Tokyo University of Science
• Principal Investigator: Nakayoshi Makoto 東京理科大学, 理工学部土木工学科, 准教授 (90706475)
• Project Period (FY): 2018-04-01 – 2021-03-31
• Keywords: 市民科学 / WRF / LPWA

Outline of Final Research Achievements

This research project developed an IoT instrument for near-surface microclimate and an algorithm for detecting wind velocity around the altitude of cloud bottoms with digital cameras located on the ground. The IoT instrument measures ambient temperature, humidity, wind speed, short- and long-wave radiation and the data are transmitted via LPWA network. The wind velocimetry is based on stereo vision, which identifies 3D coordinates of cloud features with pairs of images and computes advection velocity of clouds with temporal change of cloud locations. As well as the development of the instrument and the wind velocimetry, numerical simulations assimilating near-surface weather data were conducted for checking the data assimilation impact. Though 1.2 km and 6 km resolutions data over urban regions were assimilated with 3d variational method, no clear improvement on simulation accuracy was observed.

Free Research Field

都市気象

Academic Significance and Societal Importance of the Research Achievements

近年、市民を巻き込んだ科学研究が実施されており、専門家以外も利用できる測器の重要性が増している。本研究で開発された気象IoTデバイスは気象5変数を低消費電力・低コストに測定でき小型化が可能である。市民科学の推進や地上気象データの取得のハードルを下げた点に社会的意義がある。また、上空風速は気象シミュレーションにおいて特に重要な気象因子であり、計測は容易ではない。開発したアルゴリズムにより上空風速を安価・簡易に取得可能となった点に学術的意義がある。