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Wind Compass - Windygo

Wind Compass - Windygo

Adam Fahlman

Weather免费v1.9
App Store
评分

4.8

274 条评分

星级

★★★★★

最近更新

2026年5月15日

发布日期

2024年2月29日

更新内容

v1.9

Thank for using Windygo! Here’s what’s new: • Clock compass now available • Bug fixes and UI improvements

应用信息

开发者
Adam Fahlman
分类
Weather
价格
免费
版本
1.9
App ID
6476741938

简介

Windygo is a full-featured weather app built around the wind — essential for drone pilots, photographers, surfers, golfers, and everyone in between. Key Features: • Wind Compass: The wind compass will always point in the direction of the wind, no matter which way you are facing. • Privacy: No account needed. Windygo does not track your data in any way. Your location is only used to fetch your local weather forecast. • Widgets: Get the weather right on your Home Screen. • Kp Index: Important metric for drone owners. • Unit Selection: Choose to display the wind speed in miles/hour (mph), kilometres/hour (km/h), meters/second (mps) or knots (kn). • Custom Location Names: Search for any location and rename it to your liking. Maybe you have a favorite beach, hunting spot or hiking trail! Windygo Free • Weather for current location • 24-hour forecast • 5-day forecast (hourly details available on first 2 days) • Current and forecasted Kp Index Windygo Pro Upgrade to Windygo Pro and get access to all the features, which include: • Remove ads • The full 10-day forecast with hourly details available for each day • Unlimited saved locations • Custom location names • Widgets Request More Features We appreciate your feedback! If you need a feature that isn’t currently available, we’ll definitely consider adding it to the app. You can submit feedback directly within the app. Reporting Bugs If you find a bug, please notify us so we can quickly get that fixed! You can submit bug reports directly within the app. Terms of Use https://www.apple.com/legal/internet-services/itunes/dev/stdeula/

下载量预测

专业 · 预览

预估总下载量

20K14K39K
保守估计乐观估计

507

低 / 月

752

预估 / 月

1K

高 / 月

基于274 条评分
假设评分率1.4%
应用年龄27 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。