Software and Data for “Variations in Tropical Cyclone Size and Rainfall Patterns based on Synoptic-Scale Moisture Environments in the North Atlantic”

This is software and data to support the manuscript "Variations in Tropical Cyclone Size and Rainfall Patterns based on Synoptic-Scale Moisture Environments in the North Atlantic," which we are submitting to the journal, Journal of Geophysical Research Atmospheres.The MIT license applies to all source code and scripts published in this dataset.The software includes all code that is necessary to follow and evaluate the work. Public datasets include (1) the Atlantic hurricane database HURDAT2 (https://www.nhc.noaa.gov/data/#hurdat), (2) NASA’s Global Precipitation Measurement IMERG final precipitation (https://catalog.data.gov/dataset/gpm-imerg-final-precipitation-l3-half-hourly-0-1-degree-x-0-1-degree-v07-gpm-3imerghh-at-g), (3) the Tropical Cyclone Extended Best Track Dataset (https://rammb2.cira.colostate.edu/research/tropical-cyclones/tc_extended_best_track_dataset/), (4) the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5) (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5), and (5) the Statistical Hurricane Intensity Prediction Scheme (SHIPS) dataset (https://rammb.cira.colostate.edu/research/tropical_cyclones/ships/data/). We are also including four datasets generated by the code that will be helpful in evaluating the work. Lastly, we used the eofs software package, a python package for computing empirical orthogonal functions (EOFs), available publicly here: https://doi.org/10.5334/jors.122.All figures and tables in the manuscript are generated using Python, ArcGIS Pro, and GraphPad/Prism 10 Software:ArcGIS Pro used to make Figures 5GraphPad/Prism 10 Software used to make box plots in Figures 6-9Python used to make Figures 1-4, 10-11, and Tables 1-5Public Datasets:HURDAT2: Landsea, C. and Beven, J., 2019: The revised Atlantic hurricane database (HURDAT2). March 2022, https://www.aoml.noaa.gov/hrd/hurdat/hurdat2-format.pdfIMERG:NASA EarthData: GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V06. 9 December 2024, https://catalog.data.gov/dataset/gpm-imerg-final-precipitation-l3-half-hourly-0-1-degree-x-0-1-degree-v07-gpm-3imerghh-at-g. Note that this dataset is not longer publicly available, as it has been replaced with IMERG version 7: https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGHH_07/summary?keywords="IMERG final"Extended Best Track:Regional and Mesoscale Meteorology Branch, 2022: The Tropical Cyclone Extended Best Track Dataset (EBTRK). March 2022, https://rammb2.cira.colostate.edu/research/tropical-cyclones/tc_extended_best_track_dataset/ERA5: Guillory, A. (2022). ERA5. Ecmwf [Dataset]. https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5. (Accessed March 2, 2023). Also: Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146, 1999–2049, https://doi.org/10.1002/qj.3803SHIPS:Ships Predictor Files - Colorado State University (2022). Statistical Tropical Cyclone Intensity Forecast Technique Development. https://rammb.cira.colostate.edu/research/tropical_cyclones/ships/data/ships_predictor_file_2022.pdf. Also: DeMaria, M., and J. Kaplan, 1994: A Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic Basin. Weather and Forecasting, 9, 209–220, https://doi.org/10.1175/1520-0434(1994)009&lt;0209:ASHIPS&gt;2.0.CO;2.<br>Public Software: Dawson, A., 2016: eofs: A Library for EOF Analysis of Meteorological, Oceanographic, and Climate Data. JORS, 4, 14, https://doi.org/10.5334/jors.122.van der Walt, S., Schönberger, J. L., Nunez-Iglesias, J., Boulogne, F., Warner, J. D., Yager, N., et al. (2014). Scikit-image: Image processing in Python [Software]. PeerJ, 2, e453. https://doi.org/10.7717/peerj.453

本数据集为配套投稿于《地球物理研究杂志：大气科学分册》（*Journal of Geophysical Research Atmospheres*）的论文《基于北大西洋天气尺度水汽环境的热带气旋尺度与降水型变化》（*Variations in Tropical Cyclone Size and Rainfall Patterns based on Synoptic-Scale Moisture Environments in the North Atlantic*）的相关软件与数据。本数据集发布的所有源代码与脚本均适用MIT许可证。本软件包含复现并评估该研究工作所需的全部代码。公开数据集包括：(1) 大西洋飓风数据库HURDAT2（https://www.nhc.noaa.gov/data/#hurdat），(2) 美国国家航空航天局（NASA）全球降水测量IMERG最终降水产品（https://catalog.data.gov/dataset/gpm-imerg-final-precipitation-l3-half-hourly-0-1-degree-x-0-1-degree-v07-gpm-3imerghh-at-g），(3) 热带气旋扩展最佳路径数据集（https://rammb2.cira.colostate.edu/research/tropical-cyclones/tc_extended_best_track_dataset/），(4) 欧洲中期天气预报中心（ECMWF）大气再分析数据集ERA5（https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5），以及(5) 统计飓风强度预测方案（SHIPS）数据集（https://rammb.cira.colostate.edu/research/tropical_cyclones/ships/data/）。此外，本数据集还包含4组由本代码生成的辅助数据集，用于支撑该研究的评估工作。

本次研究还使用了公开的`eofs` Python软件包，该工具包用于计算经验正交函数（empirical orthogonal functions, EOFs），其公开DOI地址为：https://doi.org/10.5334/jors.122。

论文中所有图表与表格均通过以下软件生成：
- ArcGIS Pro：用于绘制图5
- GraphPad/Prism 10：用于绘制图6至图9中的箱线图
- Python：用于绘制图1至图4、图10至图11以及表1至表5

公开数据集引用详情如下：
1. **HURDAT2**：Landsea, C. 与 Beven, J., 2019：修订版大西洋飓风数据库（HURDAT2）。2022年3月，https://www.aoml.noaa.gov/hrd/hurdat/hurdat2-format.pdf
2. **IMERG**：NASA EarthData：GPM IMERG Final Precipitation L3 半小时分辨率0.1°×0.1° V06。2024年12月9日，https://catalog.data.gov/dataset/gpm-imerg-final-precipitation-l3-half-hourly-0-1-degree-x-0-1-degree-v07-gpm-3imerghh-at-g。注：该数据集已被IMERG第7版替代，目前已不再公开获取，新版地址为：https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGHH_07/summary?keywords="IMERG final"
3. **热带气旋扩展最佳路径数据集**：区域与中尺度气象分支，2022：热带气旋扩展最佳路径数据集（EBTRK）。2022年3月，https://rammb2.cira.colostate.edu/research/tropical-cyclones/tc_extended_best_track_dataset/
4. **ERA5**：Guillory, A. (2022). ERA5. Ecmwf [数据集]. https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5.（2023年3月2日访问）。另见：Hersbach, H. 及合作者, 2020：ERA5全球再分析数据集。《皇家气象学会季刊》, 146, 1999–2049, https://doi.org/10.1002/qj.3803
5. **SHIPS**：科罗拉多州立大学 (2022). 热带气旋强度统计预测技术开发：SHIPS预测文件。https://rammb.cira.colostate.edu/research/tropical_cyclones/ships/data/ships_predictor_file_2022.pdf. 另见：DeMaria, M. 与 J. Kaplan, 1994：大西洋盆地统计飓风强度预测方案（SHIPS）。《天气预报》, 9, 209–220, https://doi.org/10.1175/1520-0434(1994)009<0209:ASHIPS>2.0.CO;2

公开软件引用详情如下：
- Dawson, A., 2016：eofs：气象、海洋与气候数据EOF分析库。*Journal of Open Research Software*（JORS）, 4, 14, https://doi.org/10.5334/jors.122.
- van der Walt, S., Schönberger, J. L., Nunez-Iglesias, J., Boulogne, F., Warner, J. D., Yager, N. 等. (2014). Scikit-image：Python图像处理工具包 [软件]. *PeerJ*, 2, e453. https://doi.org/10.7717/peerj.453