five

Temperature Severity Indicators

收藏
LOJIC Open Data Portal2026-03-21 收录
下载链接:
https://data.lojic.org/maps/56a1f80149ff4856944461e8958def4d
下载链接
链接失效反馈
官方服务:
资源简介:
<p><font size='3'>The Temperature Severity Indicator data identifies areas subject to extreme heat and cold events in the contiguous United States in an effort to inform temperature-related housing and planning research. The indicators, conveyed as a grid of 1-degree latitude by 1-degree longitude</font> cells, are created from observational data (Berkeley Earth Lab gridded daily maximum and minimum temperature ) and consider the frequency, intensity, and duration of extreme heat and extreme cold weather events that occurred in the US between 1913 and 2012.</p><p><b><br /></b></p><p><b>DEFINING EXTREME TEMPERATURE EVENTS</b></p><div> <p style='text-align:justify;'>For the purposes of this data, a daytime extreme heat event is defined as daily maximum temperature (tmax) that meets or exceeds the 90th percentile daily tmax for June, July, and August (JJA) during the reference period 1961-1990 and lasting for at least 3 consecutive days. A lower bound is set to 90 degrees Fahrenheit (F) to define the minimum temperature qualifying as a daytime heat event. Likewise, a night time extreme heat event is defined as daily minimum temperature (tmin) that meets or exceeds the 90th percentile daily tmin for JJA during the reference period 1961-1990 and lasting for at least 3 consecutive nights. A lower bound is set to 75 F to define the minimum temperature qualifying as a night time heat event.</p> <p style='text-align:justify;'>A daytime extreme cold event is defined as daily maximum temperature (tmax) that is at least 10 F less than the median daily climatological January tmax over the reference period 1961-1990 and lasting for at least 3 consecutive days. An upper bound is set at 32 F to define the maximum temperature qualifying as a daytime cold event, and a lower bound is set to -10 F, where any 3 or more consecutives days colder than this limit is considered a cold event. A night time extreme cold event is defined as daily minimum temperature (tmin) that is at least 10 F less than the median daily climatological January tmin over the reference period 1961-1990 and lasting for at least 3 consecutive days. An upper bound is set at 32 F to define the maximum temperature qualifying as a night time cold event, and a lower bound is set to -10 F, where any 3 or more consecutives nights colder than this limit is considered a cold event.</p><p style='text-align:justify;'><b><br /></b></p><p style='text-align:justify;'><b>CREATING EXTREME TEMPERATURE SEVERITY INDEXES</b></p> <p style='text-align:justify;'>The average annual event frequency (events/yr), average event intensity compared to a seasonally representative temperature (F), and the average event duration (days) are computed using the Berkeley Earth temperature observations as well as the above definitions for extreme heat and cold events. Results of those calculations are classified according to a quartile distribution of all values relative to attribute, and each cell receives a score according to its quartile class: 0 points for a cell value less than the 25th percentile, 1 point if between the 25th and 50th percentile, 2 points if between the 50th and 75th percentile, 3 points if greater than the 75th percentile. The index value represents the aggregation of quartile points awarded for each attribute of a particular cell.</p><p style='text-align:justify;'><b><br /></b></p><p style='text-align:justify;'><b>SUGGESTED USE OF DATA</b></p> <p>Fields ending with the suffix, “_INDX” provide spatially relevant severity indices for min/max cold snaps and heat waves. As described previously, the value for each index represents the summation of attributes scores determined by a quartile distribution of all values for each facet of analysis. Index scores for these fields range from 0 to 9 providing for a relatively smooth surface map illustrating spatial variability.</p><p> In contrast, fields ending with the suffix, “_IND” are binary attributes that indicate areas where the index values for both night-time (tmin) and day-time (tmax) is &gt;= 5 relative to each event type. Given the boolean nature of data in these fields they are best used to quickly identify areas of extreme temperature to answer policy related questions, and not necessarily for illustration or spatial analysis.</p><p><span style='font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size:16px;'>For questions about the spatial attribution of this dataset, please reach out to us at </span><a href='mailto:GISHelpdesk@hud.gov' style='color:rgb(0, 97, 155); text-decoration-line:none; font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size:16px;' target='_blank' rel='nofollow ugc noopener noreferrer'><b>GISHelpdesk@hud.gov</b></a><font face='Avenir Next W01, Avenir Next W00, Avenir Next, Avenir, Helvetica Neue, sans-serif'><span style='font-size:16px;'>. <br /></span></font><span style='font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size:medium;'>Data Dictionary: </span><a href='https://hud.maps.arcgis.com/sharing/rest/content/items/793b634a6a06495d80fb05779084601c/data' target='_blank' rel='nofollow ugc noopener noreferrer'>DD_Temperature Severity Index</a></p><p><span style='font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size:medium;'>Date of Coverage: 1913 - 2013</span><span style='font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size:medium;'> </span></p></div>
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作