Climate data from the R ocky M ountain B iological L aboratory (1975–2022)
Climate data from the R ocky M ountain B iological L aboratory (1975–2022)
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落基山生物实验室的气候数据（1975 年至 2022 年）
DOI：
10.1002/ecy.4153
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发表时间：
2023
期刊：
影响因子：
4.8
通讯作者：
Inouye, Brian D.
中科院分区：
文献类型：
--
作者：
Prather, Rebecca M.;Underwood, Nora;Dalton, Rebecca M.;barr, billy;Inouye, Brian D.
落基山生物实验室(RMBL；美国科罗拉多州)是许多研究项目的所在地，研究项目涵盖数十年、分类群和从生态学到进化生物学、水文学等多个研究领域。气候是这项工作的大部分重点，并为其余工作提供了重要的背景。在RMBL附近有五个主要的气候数据来源，每个来源都有独特的变量、格式和时间覆盖范围。这些数据来源包括(1)RMBL居民比利·巴尔、(2)美国国家海洋和大气管理局(NOAA)、(3)美国地质调查局(USGS)、(4)美国农业部(USDA)和(5)俄勒冈州立大学的PRISM气候小组。美国国家海洋和大气局和美国地质勘探局都在距离红树林约10 公里的科罗拉多州克雷斯特巴特设有自动气象站，而美国农业部在距离红树林约2.5 公里的斯诺德格拉斯山有一个自动化气象站。这些数据集中的每一个都有独特的时空覆盖范围和格式。尽管使用RMBL的数据在气候相关问题上做了大量工作，但之前的研究人员都必须访问和格式化自己的气候记录，做出处理缺失数据的决定，并重新创建数据摘要。在这里，我们提供了一个涵盖1975-2022年的每日观测的经过精选的气候数据集，其中融合了来自所有五个来源的信息，并包括记录处理数据的决定的带注释的脚本。这些综合的气候数据将促进未来的研究，减少重复工作，并提高我们比较不同研究结果的能力。数据集包括关于降水(水和雪)、融雪日期、温度、风速、土壤水分和温度以及水流的信息，所有这些信息都可以从多种来源公开获得。除了格式化的原始数据外，我们还提供了几个在生态分析中常用的新变量，包括生长度日、生长季长度、寒冷严重程度指数、严霜日数、厄尔尼诺-南方涛动指数和干旱(标准化降水蒸散指数)。这些新的变量是根据每天的天气记录计算出来的。在适当的情况下，数据还以最小值、最大值、平均值、残差和累积度量值的形式显示在各种时间尺度上，包括日、月、季和年。RMBL是一个全球研究中心。RMBL的现场科学家来自多个国家，每年出版约50份同行评议的出版物。来自世界各地的研究人员也经常使用RMBL的数据进行合成工作，美国各地的教育工作者也将RMBL的数据用于教学模块。这一经过整理和组合的数据集将对广大受众有用。除了合成的组合数据集，我们还包括原始数据和用于清理原始数据并创建月度和年度数据集的R代码，这有助于使用相同的标准化协议添加额外的年份或数据。使用此数据集不受版权或所有权限制；当数据用于出版物或科学活动时，请引用此数据文件。
The Rocky Mountain Biological Laboratory (RMBL; Colorado, USA) is the site for many research projects spanning decades, taxa, and research fields from ecology to evolutionary biology to hydrology and beyond. Climate is the focus of much of this work and provides important context for the rest. There are five major sources of data on climate in the RMBL vicinity, each with unique variables, formats, and temporal coverage. These data sources include (1) RMBL resident billy barr, (2) the National Oceanic and Atmospheric Administration (NOAA), (3) the United States Geological Survey (USGS), (4) the United States Department of Agriculture (USDA), and (5) Oregon State University's PRISM Climate Group. Both the NOAA and the USGS have automated meteorological stations in Crested Butte, CO, ~10 km from the RMBL, while the USDA has an automated meteorological station on Snodgrass Mountain, ~2.5 km from the RMBL. Each of these data sets has unique spatial and temporal coverage and formats. Despite the wealth of work on climate‐related questions using data from the RMBL, previous researchers have each had to access and format their own climate records, make decisions about handling missing data, and recreate data summaries. Here we provide a single curated climate data set of daily observations covering the years 1975–2022 that blends information from all five sources and includes annotated scripts documenting decisions for handling data. These synthesized climate data will facilitate future research, reduce duplication of effort, and increase our ability to compare results across studies. The data set includes information on precipitation (water and snow), snowmelt date, temperature, wind speed, soil moisture and temperature, and stream flows, all publicly available from a combination of sources. In addition to the formatted raw data, we provide several new variables that are commonly used in ecological analyses, including growing degree days, growing season length, a cold severity index, hard frost days, an index of El Niño‐Southern Oscillation, and aridity (standardized precipitation evapotranspiration index). These new variables are calculated from the daily weather records. As appropriate, data are also presented as minima, maxima, means, residuals, and cumulative measures for various time scales including days, months, seasons, and years. The RMBL is a global research hub. Scientists on site at the RMBL come from many countries and produce about 50 peer‐reviewed publications each year. Researchers from around the world also routinely use data from the RMBL for synthetic work, and educators around the United States use data from the RMBL for teaching modules. This curated and combined data set will be useful to a wide audience. Along with the synthesized combined data set we include the raw data and the R code for cleaning the raw data and creating the monthly and yearly data sets, which facilitate adding additional years or data using the same standardized protocols. No copyright or proprietary restrictions are associated with using this data set; please cite this data paper when the data are used in publications or scientific events.