Pythonでやってみる 気象データの可視化と解析: 観測データから学ぶ気象解析の基礎 LabCodeブックス
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- ○概要天気予報のニュースで見かける上空の寒気予想図や降水量予想図を「自分でもPythonで描いてみたい」と思ったことはありませんか？気象データ解析は形式が特殊なうえ、地図描画や気象計算の環境構築でつまずきやすく、独自に解析を進めるのが難しい分野です。本書は、計測装置とデータ解析の両方に精通した著者が、「データの取得」「可視化（地図・グラフ化）」「統計解析」の3点に絞り、実用的なPythonコードとともに手順を解説します。○本書で作れるもの・学べることCartopyとMetPyの導入から、気象衛星「ひまわり」データの輝度温度変換と雲画像描画、NOAA GFS（GRIB2）による上空の寒気・地上風の流線・相当温位を用いた前線の客観解析、高層気象観測データのスクレイピングによるエマグラム作成と大気安定度指標（CAPE・CIN・SSI・K指数など）の計算、そして年最大日降水量への極値分布（グンベル・GEV・平方根指数型）フィッティングによる「50年に一度の大雨」の確率降水量算出まで、全5章で網羅的に扱います○ 対象とする読者- 手作業の天気図解析では物足りず、コンピュータで気象データを解析してみたい方- 防災・気象業務に関心のある方- 雲画像、上空の寒気、前線、エマグラムなど、天気予報の解説で使われる図を自分で描いてみたい方- 気象庁のデータに加えて、衛星データや海外の数値予報データも扱ってみたい方- 大気の安定度や「〇〇年に一度の大雨」を、自分で計算して読み解いてみたい方- Pythonを触ったことがあり、動くコードから理解したい方
| Publication date | September 15, 2026 |
| Language | Japanese |
| File size | 11.6 MB |
| Enhanced typesetting | Enabled |
| X-Ray | Not Enabled |
| Word Wise | Not Enabled |
| Print length | 403 pages |
| Page Flip | Enabled |
| Item Weight | 1 lbs (450 grams) |
Product Description
Pythonでやってみる 気象データの可視化と解析: 観測データから学ぶ気象解析の基礎 LabCodeブックス
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