Adapting UAE’s Urban Planning for Extreme Rainfall and Flood Risks

This research data supports the findings presented in the manuscript titled "Adapting UAE’s Urban Planning for Extreme Rainfall and Flood Risks". It contains ERA5 reanalysis data, Python code, and outputs not fully included in the manuscript due to word and space limitations.

1. ERA5 Reanalysis Data (.nc Files):
The two NetCDF files are sourced from the Copernicus ERA5 reanalysis dataset and cover critical periods of extreme rainfall in the UAE, specifically:

April24.nc: Contains hourly climate data from April 1 to April 30, 2024.
July22.nc: Contains hourly climate data from July 1 to July 31, 2022.
The key variables extracted include total precipitation, wind speed (u10 and v10 components), and mean sea level pressure. These files enable a detailed analysis of the onset, progression, and impact of extreme rainfall events in the UAE. The coordinates corresponding to the geographical area extracted are as follows:

North: 32.25°
South: 12°
East: 70.4°
West: 41.92°

2. Analysis Code:
The Python code provided in this dataset is designed to process and analyze the ERA5 reanalysis data. The code can be accessed through the following Google Colab link: https://colab.research.google.com/drive/129bgvv6TEyLsxqfLkK0K5cixtjU8wajS?usp=sharing

The code performs the following functions:

Data Extraction: Parses the NetCDF files to extract relevant variables, including total precipitation, wind speed, and mean sea level pressure.
Wind Speed Calculation: Combines the u10 and v10 wind vector components to calculate the total wind speed.
Data Visualization: Generates time series plots to visualize the temporal evolution of key climatic variables for the selected regions (Abu Dhabi and East Coast). Additionally, the Cartopy library is used to create synoptic visualizations of the spatial distribution of precipitation and wind patterns over time.
3. Outputs (Hourly Snapshots and Videos):
Due to space constraints in the manuscript, some key visual outputs could not be fully included. The outputs, included in the accompanying ZIP files, provide detailed hourly snapshots and videos of the weather patterns during extreme rainfall events:

AbuDhabi_output.zip: Contains hourly snapshots of precipitation and wind vectors for the April 2024 event in Abu Dhabi. A time-lapse video combining these snapshots is also included to visually illustrate the progression of the weather system.
Fujairah_output.zip: Contains similar hourly snapshots and a time-lapse video for the July 2022 extreme rainfall event along the East Coast of the UAE.

本研究所提供的数据集支撑了题为《适应阿联酋城市规划以应对极端降雨和洪水风险》的论文中的发现。该数据集包含ERA5再分析数据、Python代码以及由于篇幅限制而未完全包含在论文中的输出。

1. ERA5再分析数据（.nc文件）:
这两个NetCDF文件源于Copernicus ERA5再分析数据集，覆盖了阿联酋极端降雨的关键时期，具体如下：

April24.nc：包含2024年4月1日至4月30日的每小时气候数据。
July22.nc：包含2022年7月1日至7月31日的每小时气候数据。
提取的关键变量包括总降水量、风速（u10和v10分量）以及平均海平面气压。这些文件使得对阿联酋极端降雨事件的起始、发展和影响进行详细分析成为可能。提取的地理区域坐标如下：

北纬：32.25°
南纬：12°
东经：70.4°
西经：41.92°

2. 分析代码：
本数据集中提供的Python代码旨在处理和分析ERA5再分析数据。代码可通过以下Google Colab链接访问：https://colab.research.google.com/drive/129bgvv6TEyLsxqfLkK0K5cixtjU8wajS?usp=sharing

该代码执行以下功能：

数据提取：解析NetCDF文件以提取相关变量，包括总降水量、风速和平均海平面气压。
风速计算：结合u10和v10风速向量分量以计算总风速。
数据可视化：生成时间序列图以可视化选定区域（阿布扎比和东海岸）的关键气候变量的时空演变。此外，使用Cartopy库创建降水和风速模式随时间变化的天气图。

3. 输出（每小时快照和视频）：
由于论文篇幅限制，一些关键可视化输出未能完全包含。附带ZIP文件中的输出提供了极端降雨事件期间天气模式的详细每小时快照和视频。

AbuDhabi_output.zip：包含阿布扎比2024年事件期间降水量和风速向量的每小时快照。还包括结合这些快照的时间流逝视频，以直观展示天气系统的演变过程。
Fujairah_output.zip：包含类似每小时快照和时间流逝视频，用于展示阿联酋东海岸2022年极端降雨事件。