我正在尝试使用（T base -T a ）公式 T base 通常为65F， T a =（high_temp + low_temp）/ 2
（e.x）
high_temp = 96.5F low_temp=65.21F then
mean=(high_temp + low_temp)/2
result = mean - 65
65是平均室温
如果结果> 65，则冷却度日（cdd），否则加热度日（hdd）
我从两个API获取天气数据
在 weatherbit 中提供了cdd和hdd数据，但是在 darksky 中，我们需要使用上述公式（T base -T < sub> a ）
我的问题是两个api都显示不同的结果（e.x）
day的darksky json响应
{
"latitude": 47.552758,
"longitude": -122.150589,
"timezone": "America/Los_Angeles",
"daily": {
"data": [
{
"time": 1560927600,
"summary": "Light rain in the morning and overnight.",
"icon": "rain",
"sunriseTime": 1560946325,
"sunsetTime": 1561003835,
"moonPhase": 0.59,
"precipIntensity": 0.0057,
"precipIntensityMax": 0.0506,
"precipIntensityMaxTime": 1561010400,
"precipProbability": 0.62,
"precipType": "rain",
"temperatureHigh": 62.44,
"temperatureHighTime": 1560981600,
"temperatureLow": 48,
"temperatureLowTime": 1561028400,
"apparentTemperatureHigh": 62.44,
"apparentTemperatureHighTime": 1560981600,
"apparentTemperatureLow": 46.48,
"apparentTemperatureLowTime": 1561028400,
"dewPoint": 46.61,
"humidity": 0.75,
"pressure": 1021.81,
"windSpeed": 5.05,
"windGust": 8.36,
"windGustTime": 1560988800,
"windBearing": 149,
"cloudCover": 0.95,
"uvIndex": 4,
"uvIndexTime": 1560978000,
"visibility": 4.147,
"ozone": 380.8,
"temperatureMin": 49.42,
"temperatureMinTime": 1561010400,
"temperatureMax": 62.44,
"temperatureMaxTime": 1560981600,
"apparentTemperatureMin": 47.5,
"apparentTemperatureMinTime": 1561014000,
"apparentTemperatureMax": 62.44,
"apparentTemperatureMaxTime": 1560981600
}
]
},
"offset": -7
}
python计算
response = result.get("daily").get("data")[0]
low_temp = response.get("temperatureMin")
hi_temp = response.get("temperatureMax")
mean = (hi_temp + low_temp)/2
#65 is normal room temp
print(65-mean)
这里的平均值是6.509999999999998
65-平均值= 58.49
hdd为58.49 ，因此 cdd为0
weatherbit json响应中的相同日期是：
{
"threshold_units": "F",
"timezone": "America/Los_Angeles",
"threshold_value": 65,
"state_code": "WA",
"country_code": "US",
"city_name": "Newcastle",
"data": [
{
"rh": 68,
"wind_spd": 5.6,
"timestamp_utc": null,
"t_ghi": 8568.9,
"max_wind_spd": 11.4,
"cdd": 0.4,
"dewpt": 46.9,
"snow": 0,
"hdd": 6.7,
"timestamp_local": null,
"precip": 0.154,
"t_dni": 11290.6,
"temp_wetbulb": 53.1,
"t_dhi": 1413.9,
"date": "2019-06-20",
"temp": 58.6,
"sun_hours": 7.6,
"clouds": 58,
"wind_dir": 186
}
],
"end_date": "2019-06-21",
"station_id": "727934-94248",
"count": 1,
"start_date": "2019-06-20",
"city_id": 5804676
}
此处 hdd为6.7 和 cdd为0.4
您能解释一下他们如何获得此结果吗？
答案 0 :(得分：1)
您需要使用小时数据来计算HDD和CDD，然后将它们取平均值以获得每日价值。
此处有更多详细信息：https://www.weatherbit.io/blog/post/heating-and-cooling-degree-days-weather-api-release