Context Weather
收藏Snowflake2024-08-20 更新2024-08-21 收录
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https://app.snowflake.com/marketplace/listing/GZT0Z2BR4ACBG
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资源简介:
Context Weather is a series of climate scores derived from measuring and modeling climate data over time and across stratified geographies. The Context Weather product provides users with a series of detailed climate scores down to neighborhoods or ZIP Code boundaries.
Climate data reported by month and season:
- Average high and low temperatures
- Average precipitation
- Average snowfall
- Average sunny and cloudy days
- Average wind chill
- Average wind speed
- Average relative humidity
- Average Heat index
- Average heating and cooling degree days
Context Weather is available with the following Precisely polygon products:
- Neighborhood Boundaries
- Residential Boundaries
- ZIP Code Boundaries
Context Weather data and geographies are linked by IDs. A universal Context ID links to a Precisely polygon ID from its corresponding Precisely product. These other Precisely products are separately licensed and also available in Snowflake.
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This sample data set covers the San Francisco, CA area. This represents a subset of the full product’s geographic extent. The full commercial offering features geographic coverage of the entire United States. Contact snowflake.partnership@precisely.com for more information on licensing the product.
Context Weather是一套通过跨分层地理区域、随时间推移对气候数据开展测量与建模所衍生出的气候评分集。该产品可为用户提供细化至街区或邮政编码(ZIP Code)边界级别的一系列详细气候评分。
按月度与季度发布的气候数据涵盖以下类别:
- 平均最高与最低气温
- 平均降水量
- 平均降雪量
- 平均晴日与阴日数
- 平均风寒指数
- 平均风速
- 平均相对湿度
- 平均酷热指数(Heat index)
- 平均采暖度日数与降温度日数
Context Weather可搭配以下Precisely多边形产品使用:
- 街区边界
- 居住区域边界
- 邮政编码(ZIP Code)边界
Context Weather的数据与地理区域通过标识符(ID)建立关联。通用Context ID可关联至对应Precisely产品中的Precisely多边形标识符。其余Precisely产品需单独授权,且同样可在Snowflake平台获取。
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本示例数据集涵盖美国加利福尼亚州旧金山地区,仅为完整产品地理覆盖范围的子集。该商业产品的完整版本可覆盖美国全境。如需获取该产品的授权详情,请联系snowflake.partnership@precisely.com。
提供机构:
Precisely
创建时间:
2024-08-20
搜集汇总
数据集介绍

背景与挑战
背景概述
Context Weather是通过地理分层建模生成的气候评分数据集,提供包括温湿度、降水、风速等9类月度/季节性指标,可关联社区、住宅区及邮编边界。样本涵盖旧金山地区,完整版包含全美范围数据。
以上内容由遇见数据集搜集并总结生成



