女朋友天天氣我怎么辦

帶有扭曲的天氣應用 (A Weather App with a Twist)

Is My Weather Weird?? is a weather app with a twist — it offers a simple answer to a common question we’ve all asked. To do this we look at how often weather like today’s used to happen in the past, using the best data available.

我的天氣很奇怪嗎？ ?是一款帶有扭曲功能的氣象應用程序-它為我們都提出的常見問題提供了簡單的答案。 為此，我們使用可獲得的最佳數據來查看過去的今天天氣的頻率。

Fun Fact: every day of weird weather calculations involves over 10 million data points

有趣的 事實 ：怪異的天氣計算，每天涉及超過10萬個數據點

定義“天氣” (Define “Weather”)

This might seem obvious, but there are two important points to understand.

這看起來似乎很明顯，但是有兩個重要的方面需要理解。

First, weather refers to conditions right now, or on a particular day, at a given location. Examples of weather include the amount of rain in Tulsa today, or the current temperature in Seattle. This differs from climate, which is the average weather at a given location, such as the typical number of days of rain in Tulsa in May, or the average high temperature in Seattle for the second week of January.

首先， 天氣是指當前或特定日期在給定位置的狀況。 天氣的例子包括今天塔爾薩的降雨量或西雅圖的當前溫度。 這與氣候不同， 氣候是給定位置的平均天氣，例如5月份塔爾薩的典型降雨天數，或1月第二周西雅圖的平均高溫。

Second, Is My Weather Weird?? (or IMWW for short) measures daily weirdness for three specific aspects of weather: high temperature, low temperature, and total precipitation. There are other weather measurements we’d love to use, such as humidity or wind speed, but a large majority of historical weather measurements tracked only those three items, so that’s what we have to work with.

其次，“我的天氣怪異”?(或簡稱IMWW)測量天氣三個特定方面的每日怪異度： 高溫 ， 低溫和總降水量 。 我們還希望使用其他天氣測量方法，例如濕度或風速，但是大多數歷史氣象測量結果僅跟蹤這三個項目，因此我們必須配合使用。

Weather is what’s happening outside any given moment or day; climate is average weather for a given location.

天氣是任何給定時刻或白天以外發生的事情； 氣候是給定位置的平均天氣。

定義“ 怪異” (Define “Weird”)

Basically, weather is weird if you wouldn’t expect it to happen at a given location and time of year. A high temperature of 90 F in January would be bizarre in a place like Chicago, but not too weird for somewhere like Miami.

基本上，如果您不希望天氣在一年中的給定位置和時間發生，那就很奇怪。 一月份90°F的高溫在像芝加哥這樣的地方是奇怪的，但是對于像邁阿密這樣的地方來說并不奇怪。

IMWW uses a weirdness score that corresponds to how often a given type of weather used to happen, as described below.

IMWW使用一個怪異評分，該分數與給定類型的天氣過去發生的頻率相對應，如下所述。

Weird Weather Scores and corresponding frequencies奇怪的天氣評分和相應的頻率

定義“過去的樣子” (Define “How things used to be”)

To say weather is weird, we need to compare it against normal. For this purpose, we use the 20th century as our definition of normal, more specifically the weather before 1990. This is a fairly common date to use for before & after comparisons of weather and climate, because this about when changing temperatures became impossible to ignore. Older folks will remember pre-1990 as the normal that they grew up with, and the timeframe is further relevant because our built world, such as homes and infrastructure, was largely designed for 20th century conditions.

要說天氣很怪異，我們需要將其與正常情況進行比較。 為此，我們將20世紀作為正常的定義，更確切地說是1990年之前的天氣。這是比較天氣和氣候之前和之后使用的相當普遍的日期，因為關于何時溫度變化的這一點變得不容忽視。 老年人會記得1990年前是他們成長的常態，而且時間范圍更重要，因為我們的建筑世界(例如房屋和基礎設施)主要是為20世紀的條件設計的。

IMWW compares today’s weather with weather patterns from before 1990.

IMWW將今天的天氣與1990年之前的天氣模式進行了比較。

數據 (The Data)

歷史天氣 (Historical Weather)

IMWW uses historical weather records from the Global Historical Climatology Network (GHCN) the most comprehensive database of daily weather data available, with measurements from over 100,000 weather stations in 180 countries going back as far as the 1700s.

IMWW使用來自全球歷史氣候學網絡 (GHCN)的歷史天氣記錄，該歷史記錄是可用的最全面的每日天氣數據數據庫，其數據可追溯到180個國家的100,000多個氣象站，可追溯到1700年代。

IMWW uses daily high temperature, low temperature, and precipitation depth (rain and snow water equivalent) from approximately 6,000 of the GHCN weather stations that have particularly high-quality measurements, with an average of 47 years of pre-1990 data per station.

IMWW使用大約6,000個GHCN氣象站的每日高溫，低溫和降水深度(相當于雨水和雪水)，這些氣象站的測量質量特別高，平均每個站1990年之前的數據為47年。

今天的天氣 (Today’s Weather)

IMWW current conditions and forecasts are provided by Aeris Weather, a professional-grade weather service trusted by industries including aviation, agriculture, and logistics.

IMWW的當前狀態和預報由Aeris Weather提供， Aeris Weather是航空，農業和物流等行業所信賴的專業級氣象服務。

IMWW uses the best data available for historic measurements and today’s weather.

IMWW使用最佳數據來進行歷史測量和今天的天氣。

方法 (The Method)

For more detail see the accompanying technical description (TBD).

有關更多詳細信息，請參見隨附的技術說明(TBD)。

1.計算每個站點的歷史天氣模式 (1. Calculate Historical Weather Patterns for each Station)

First we determine what weather looked like prior to 1990 for each day of the year at all of the 6,000 weather stations. We do this by lumping together all of the data, across all years, for a particular day of the year. In fact, we also lump in data from a few days before and after. This provides more data to work with for generating statistics, and it makes intuitive sense because typical weather doesn’t change much in very short timeframes. For instance, on average the weather March 15 isn’t much different than on March 16, or March 13. Seasonal changes in weather become more important on the timescale of weeks or longer.

首先，我們確定1990年之前的所有6000個氣象站的每一天的天氣情況。 為此，我們將一年中某一天的所有數據匯總在一起。 實際上，我們也會前后幾天收集數據。 這提供了更多可用于生成統計數據的數據，并且具有直覺上的意義，因為典型的天氣在很短的時間內變化不大。 例如，平均而言，3月15日的天氣與3月16日或3月13日的差別不大。在幾周或更長時間的時間范圍內，天氣的季節性變化變得更加重要。

This approach gives us around 600 days of historical measurements per day of the year, representing what the weather was like on (or near) that day in the past. Then, for each day, we analyze the distribution of measurements, which essentially means counting the number of times each weather type was a particular value — how many times the high temperature was 55, 56, 57, … 90, 91… etc — to determine what kind of weather was common and what was rare.

這種方法每年可以為我們提供約600天的歷史測量值，代表過去一天(或附近)的天氣情況。 然后，對于每一天，我們分析測量值的分布，這實際上意味著對每種天氣類型是特定值的次數進行計數，即高溫分別為55、56、57，……90、91…等的次數。確定哪種天氣是常見的，什么是罕見的。

2.將今天的天氣與車站的歷史模式進行比較 (2. Compare Today’s Weather with Historical Patterns at Stations)

We now have a description of historic weather patterns for each day of the year at each weather station. Next we grab today’s weather for any of those station locations, compare it to the historic pattern, and determine how weird the weather is at that location. This allows us to conclude things like, “A high temperature of 73 F on April 15 only happened 5% of the time at this station prior to 1990.”

現在，我們對每個氣象站一年中每一天的歷史天氣模式進行了描述。 接下來，我們獲取這些站點中任何一個站點的今日天氣，將其與歷史模式進行比較，并確定該站點的天氣有多怪異。 這使我們可以得出這樣的結論：“ 4月15日，在1990年之前，該站僅發生了5％的時間，發生了73 F的高溫。”

It’s again slightly more complex than this because we actually compare the current weather with a statistical fit to the historic data, using distribution forms that are suited for describing extreme values, i.e., the “tails” of the data.

它再次比這稍微復雜一點，因為我們實際上使用適合描述極值(即數據的“尾部”)的分布形式來比較當前天氣和對歷史數據的統計擬合。

3.計算所有位置的天氣怪異度 (3. Calculate Weather Weirdness for All Locations)

If you lived very close to one of these 6,000 weather stations we’d basically be done. But since most of us don’t live within a few miles of these locations, there is another step to take to determine weather weirdness for all locations and not just at these particular stations

如果您住在這6000個氣象站中的一個非常靠近，則基本上可以完成。 但是由于我們大多數人都不住在這些位置的幾英里內，因此需要采取另一步驟來確定所有位置而不是僅在這些特定站點的天氣怪異度

To do this we use a simple idea: if the weather is weird at point A, and it’s weird at point B, then it’s probably also weird in between, as long as A and B are not too far apart. To put this to practice, we first calculate weather weirdness today for each of our 6,000 weather stations. Then we use this information for every station to estimate weirdness for a nearly continuous map of the covered area, currently most of North America. We say nearly continuous because we can’t accurately calculate weirdness for places with no historic weather stations nearby, so we don’t return a result for those areas. This is also the reason we’re currently limited to North America, which has a particularly dense network of weather stations vs. other parts of the world.

為此，我們使用一個簡單的想法：如果A點的天氣很奇怪，而B點的天氣很奇怪，那么只要A和B的距離不太遠，它之間也可能很奇怪。 為了付諸實踐，我們首先為我們的6,000個氣象站中的每個氣象站計算今天的天氣怪異度。 然后，我們將這些信息用于每個站點，以估算覆蓋面(目前為北美大部分地區)幾乎連續的地圖的怪異度。 我們說幾乎是連續的，因為我們無法準確計算附近沒有歷史氣象站的地方的怪異度，因此我們不會為這些區域返回結果。 這也是我們目前僅限于北美的原因，北美與世界其他地區相比，氣象站網絡特別密集。

回顧 (Recap)

Is My Weather Weird?? is a weather app that provides a simple answer to a common question. We do this by comparing today’s weather with historic patterns, taking steps to ensure the best possible answers. We hope that this context about your daily experience of the weather is fun and thought provoking, and we’d love feedback at info@ismyweatherweird.com. Thanks!

是My Weather Weird？?是一款氣象應用程序，可為常見問題提供簡單的答案。 為此，我們將今天的天氣與歷史模式進行比較，并采取措施以確保獲得最佳答案。 我們希望您每天的天氣經歷有趣有趣，值得思考，我們希望能通過info@ismyweatherweird.com獲得反饋。 謝謝！

常問問題 (FAQ)

是否有“我的天氣怪獸”應用程序可供下載或購買？ (Is there an Is My Weather Weird? app for download or purchase?)

Not yet, but we’d like to do that soon. If you’re interested in this, or if you have ideas for features, let us know at app@ismyweatherweird.com

尚未，但我們希望盡快這樣做。 如果您對此感興趣，或者對功能有任何想法，請通過app@ismyweatherweird.com與我們聯系。

這是一個開源項目嗎？ (Is this an open source project?)

Not currently, but we’re open to the idea — it just takes quite a bit of effort to properly open source a project, and this is a side project for now.

目前還不行，但是我們對這個想法持開放態度-適當地開源項目只需要花費大量的精力，而現在這是一個附帶項目。

這個程序是否證明氣候變化是真實的？ (Does this app prove that climate change is real?)

The purpose of this app is to answer a simple question about today’s weather using the best available information. I hope you’ll find it interesting and fun, and it may also be concerning. Weird weather on any particular day is not by itself evidence of climate change, which is about long-term changes in weather. The long-term trends in our weather weirdness calculations show the same conclusions as other climate research, which is that since 1990 temperatures are increasing on average and that precipitation patterns are changing. A future version of the app will provide this climate analysis, so that you can see trends in your own hometown.

該應用程序的目的是使用最佳的可用信息來回答有關當今天氣的簡單問題。 希望您會發現它有趣而有趣，并且可能也有關系。 任何一天的奇怪天氣本身都不是氣候變化的證據，氣候變化是天氣的長期變化。 我們的天氣怪異度計算的長期趨勢與其他氣候研究得出的結論相同，即自1990年以來溫度平均在上升，而降水模式也在變化。 該應用程序的未來版本將提供此氣候分析，以便您可以查看自己家鄉的趨勢。

我可以為我的應用程序或數據分析獲取Weird Weather數據嗎？ (Can I get Weird Weather data for my app or data analysis?)

Yes, we offer the information from the app and much more via a programmatic API that can be integrated with your own weather app or data processing. Contact us at data@ismyweatherweird.com

是的，我們通過可與您自己的氣象應用程序或數據處理集成的程序化API提供來自應用程序的信息以及更多信息。 通過data@ismyweatherweird.com與我們聯系

不同類型的怪異天氣是什么意思？ 酷高點？ 溫暖的低點？ (What do the different types of weird weather mean? Cool Highs? Warm Lows?)

IMWW uses the three types of weather measurements that are broadly available with a long history of measurements:

IMWW使用三種類型的天氣測量方法，它們具有悠久的測量歷史，可廣泛使用：

• High Temperature: The daily high can be weirdly warm or weirdly cool. Warm highs are often more noticeable because they can make our days unbearably hot (in the summer) or perhaps pleasantly warm (in the winter). Cool highs can mean jackets when we expect to be wearing short sleeves, or bitter cold winter days when we prefer not to leave the house.

  高溫 ：每天的高溫可能很奇怪，也可能很奇怪。 溫暖的高處通常更引人注目，因為它們會使我們的日子令人難以置信的炎熱(夏季)或令人愉快的溫暖(冬季)。 當我們期望穿著短袖時，涼爽的高腰可能意味著穿夾克，或者當我們不愿離開家時，寒冷的寒冷冬季意味著我們會穿上夾克。

• Low Temperature: The daily low temperature can be weirdly warm or weirdly cool. Most of the time the low temperatures happen overnight, so warm lows might feel like a surprisingly pleasant autumn night. Cool lows might mean unexpected frost in the warm season, or dangerously cold winter nights.

  低溫 ：每天的低溫可能會異常溫暖或異常涼爽。 在大多數情況下，低溫會在一夜之間發生，因此溫暖的低壓可能會讓人感覺像是一個令人驚喜的秋天夜晚。 涼爽的低谷可能意味著在溫暖的季節出乎意料的霜凍，或者在危險的寒冷冬夜里。

• Precipitation: Weirdness is determined by total daily precipitation. For rainfall this is simply the depth of rain, while for snow this refers to snow water equivalent, which is the depth of water that would be left if you melted the snow that fell that day. Interestingly there are very few places on the entire planet where it is weird to have no precipitation on a given day. Even where daily rainfall is very common, such as the tropics during the wet season, it is statistically not that weird to have the occasional dry day. For this reason we only measure weirdly wet conditions.

  降水 ：怪異取決于每天的總降水量。 對于降雨，這僅僅是降雨的深度，而對于雪，則指的是雪水當量 ，即當您融化當天落下的雪時將剩下的水深。 有趣的是，整個星球上很少有地方在特定的一天沒有降雨。 即使在日常降雨非常普遍的地方，例如在雨季的熱帶地區，從統計上講，偶爾會有干日也不奇怪。 因此，我們僅測量奇怪的潮濕條件。

還有其他可計算的天氣怪異方面嗎？ (Are there other weird aspects of weather that can be calculated?)

Definitely. Even if we’re limited to temperature and precipitation measurements there are many other interesting and important aspects of weather weirdness that can be calculated. Examples include heat waves (consecutive days above a given temperature), cold spells, and dry spells or droughts. We’ll roll out more of these as soon as we can.

絕對是 即使我們僅限于溫度和降水測量，也可以計算出天氣怪異性的許多其他有趣且重要的方面。 例子包括熱浪(高于給定溫度的連續幾天)，寒冷季節，干旱季節或干旱。 我們將盡快推出更多此類產品。

翻譯自: https://medium.com/@thomas.c.moran/all-about-is-my-weather-weird-df913e6a0eec

女朋友天天氣我怎么辦

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