落基山生物实验室(RMBL)(科罗拉多州,美国)是几十年来许多研究项目的所在地,taxa,和研究领域从生态学到进化生物学到水文学等等。气候是这项工作的重点,并为其他工作提供了重要的背景。人民币L附近有五个主要的气候数据来源,每个都有独特的变量,格式,和时间覆盖。这些数据来源包括1)人民币L居民比利巴尔,2)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管理局和美国地质勘探局都在凤头低地设有自动气象站,CO,距离RMBL约10公里,而美国农业部在斯诺德格拉斯山上有一个自动气象站,距离RMBL约2.5公里。这些数据集中的每一个具有独特的空间和时间覆盖和格式。尽管使用RMBL的数据在气候相关问题上做了大量工作,以前的研究人员都必须访问和格式化他们自己的气候记录,决定如何处理丢失的数据,并重新创建数据摘要。在这里,我们提供了涵盖1975年至2022年的每日观测数据集,该数据集融合了来自所有五个来源的信息,并包含注释脚本,记录了处理数据的决策。这些综合的气候数据将有助于未来的研究,减少重复劳动,并提高我们比较研究结果的能力。数据集包括降水信息(水和雪),融雪日期,温度,风速,土壤湿度和温度,和溪流流动,所有这些都可以从多种来源的组合中公开获得。除了格式化的原始数据,我们提供了生态分析中常用的几个新变量,包括学位日,生长季节长度,寒冷严重程度指数,硬霜天,厄尔尼诺-南方涛动指数,和干旱(标准化降水蒸散指数)。这些新变量是根据每日天气记录计算得出的。酌情,数据也以最小值表示,maxima,means,残差,和累积措施,对于各种时间尺度,包括天,月,季节,和几年。落基山生物实验室是全球研究中心。RMBL现场的科学家来自许多国家,每年产生约50种同行评审的出版物,来自世界各地的研究人员也经常利用RMBL的数据进行合成工作,美国各地的教育工作者将RMBL的数据用于教学模块。这个经过策划和组合的数据集将对广泛的受众有用。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。本数据集的使用没有版权或专有限制;当数据在出版物或科学活动中使用时,请引用本数据文件。
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.