An automated auroral detection system using deep learning: real-time operation in Tromsø, Norway

The activity of citizen scientists who capture images of aurora borealis using digital cameras has recently been contributing to research regarding space physics by professional scientists. Auroral images captured using digital cameras not only fascinate us, but may also provide information about the energy of precipitating auroral electrons from space; this ability makes the use of digital cameras more meaningful. To support the application of digital cameras, we have developed artificial intelligence that monitors the auroral appearance in Tromsø, Norway, instead of relying on the human eye, and implemented a web application, “Tromsø AI”, which notifies the scientists of the appearance of auroras in real-time. This “AI” has a double meaning: artificial intelligence and eyes (instead of human eyes). Utilizing the Tromsø AI, we also classified large-scale optical data to derive annual, monthly, and UT variations of the auroral occurrence rate for the first time. The derived occurrence characteristics are fairly consistent with the results obtained using the naked eye, and the evaluation using the validation data also showed a high F1 score of over 93%, indicating that the classifier has a performance comparable to that of the human eye classifying observed images

A statistical study of convective and dynamic instabilities in the polar upper mesosphere above Tromsø

We have studied the convective (or static) and dynamic instabilities between 80 and 100 km above Tromsø (69.6° N, 19.2° E) using temperature and wind data of 6 min and 1 km resolutions primarily almost over a solar cycle obtained with the sodium lidar at Tromsø. First, we have calculated Brunt–Väisälä frequency (N) for 339 nights obtained from October 2010 to December 2019, and the Richardson number (Ri) for 210 nights obtained between October 2012 to December 2019. Second, using those values (N and Ri), we have calculated probabilities of the convective instability (N2<0) and the dynamic instability (0≤Ri<0.25) that can be used for proxies for evaluating the atmospheric stability. The probability of the convective instability varies from about 1% to 24% with a mean value of 9%, and that of the dynamic instability varies from 4 to 20% with a mean value of 10%. Third, we have compared these probabilities with the F10.7 index and local K-index. The probability of the convective instability shows a dependence (its correlation coefcient of 0.45) of the geomagnetic activity (local K-index) between 94 and 100 km, suggesting an auroral infuence on the atmospheric stability. The probability of the dynamic instability shows a solar cycle dependence (its correlation coefcient being 0.54). The probability of the dynamic instability shows the dependence of the 12 h wave amplitude (meridional and zonal wind components) (C.C.=0.52). The averaged potential energy of gravity waves shows decrease with height between 81 and 89 km, suggesting that dissipation of gravity waves plays an important role (at least partly) in causing the convective instability below 89 km. The probability of the convective instability at Tromsø appears to be higher than that at middle/low latitudes, while the probability of the dynamic instability is similar to that at middle/low latitudes

オウシュウ ヒカンショウ サンラン (EISCAT) レーダー カンソクジョ ノ タハチョウ フォトメータデータ ヲ モチイタ ソウジョウ デンリケン デンドウド ノ スイテイ

本研究では,多波長フォトメータデータ(427.8 nm, 557.7 nm, 630.0 nm)を利用してオーロラ発生時の高緯度電離圏における電気伝導度推定の手法開発を行った.本手法の特徴は層状の電気伝導度を導出することが可能な点である.この層構造を持つ電気伝導度を光学データから導出するためのモデル関数を,高度分解能がある欧州非干渉散乱(EISCAT)UHF レーダーデータから推定した電気伝導度を用いて決定した.本研究により,電離圏を3 層(高度95-110 km, 110-170 km, 170-300 km)に分割しても,従来の方法と同程度の信頼度を持つ電気伝導度を光学データから導出できることが確認された.This study aimed to develop a methodology for estimating ionospheric conductance at auroral latitudes using data from a multi-wavelength photometer (427.8, 557.7, and 630.0 nm). An advantage of the approach is that the ionosphere is divided into layers and conductance is computed for each layer. From optical data, the layer conductance was determined by using height-resolved conductivity derived from the European Incoherent Scatter (EISCAT) Tromso UHF radar. The developed method can provide conductance from optical data with some confidence (at least at the same level as previous methods) even after separating the ionosphere into three layers, 95-110 km, 110-170 km, and 170-300 km

昭和基地高機能ライダーの機能拡張のための波長可変共鳴散乱ライダー開発の現状

第6回極域科学シンポジウム分野横断型セッション：[IM] 横断　中層大気・熱圏11月17日（火）　国立極地研究所１階交流アトリウ

昭和基地レイリー/ラマンライダーライダーで観測された高度15-70kmの重力波活動度

第6回極域科学シンポジウム分野横断型セッション：[IM] 横断　中層大気・熱圏11月17日（火）　統計数理研究所 セミナー室2（D304

2011-2015年の昭和基地レイリー/ラマンライダーを用いた大気温度鉛直構造の観測

第6回極域科学シンポジウム分野横断型セッション：[IM] 横断　中層大気・熱圏11月17日（火）　国立極地研究所１階交流アトリウ

Status of developing a new multi-wavelength resonance scatter lidar - improvement of Syowa lidar system -

第3回極域科学シンポジウム/第36回極域宙空圏シンポジウム 11月26日（月） 国立極地研究所 2階大会議

Acceleration of the lower-thermospheric wind measured with a Fabry-Perot interferometer around substorm onsets at Tromsø, Norway

第3回極域科学シンポジウム/第36回極域宙空圏シンポジウム 11月26日（月）、27日（火） 国立極地研究所 2階ラウン