TOOCAN Database V2.08 – Tracking Of Organized Convection Algorithm using a 3-dimensional segmentation

TOOCAN is a cloud tracking algorithm, described in Fiolleau and Roca 2013, to detect and track Deep Convective Systems (DCSs) from the geostationary infrared observations. Here, the TOOCAN algorithm has been applied on the homogenized infrared observations from the fleet of multi-agencies meteorological geostationary satellites data (Fiolleau etal 2019) to monitor the entire tropical belt for the 2012-2020 period. Each geostationary platform permits the processing of a specific region (Eastern-Pacific, America, Africa, India, Western-Pacific). About 12×106 DCSs have been identified over the entire tropics for the 9-year period allowing the documentation of their morphological characteristics along their life cycles. A homogeneous level-2 database, called TOOCAN database, has then been built from this processing. It gives an access to the integrated morphological parameters of each DCS (Location and time of initiation and dissipation, lifetime duration, propagated distance, maximum extent…). DCSs are also described by their morphological characteristics at each 30min-step of their life cycles (Cold cloud surface at different level of brightness temperature thresholds, excentricity, instantaneous velocity… ).
The TOOCAN database is composed by two types of files:
• Regional segmented images at a 0.04° spatial resolution and a 30 minute temporal frequency (in NETCDF).
• Regional and monthly tracking files (in ASCII or in NETCDF) documenting the DCS integrated morphological parameters (lifetime duration, distance of propagation … ) and the evolution of the DCS parameters along their life cycles.

The TOOCAN version 2.08 differs from the previous version 2.06 (DOI) in several ways:

- The TOOCAN algorithm identifies convective systems by working in a spatio-temporal volume of infrared images. The first brightness temperature threshold is still set at 190K to detect the convective seeds in the volume of IR images, and the the iterative detection and dilation process is stopped when the 235K threshold is reached, corresponding to the high cold cloud shield boundaries. However, to improve the quality of convective system segmentation, the detection step has been reduced from 5K to 2K in the iterative detection and dilation process.
- New classifications of convective systems have been established, according to the definition of MCC, PECS, MβCCS, and MβECS defined in Jirak etal (2003) and Maddox (1981).
- Also, taking advantage of the IBTrACS database, convective systems located within a radius of 1000km from a cyclone have been flagged.
- The monthly tracking files have been saved in a NETCDF format in addition to the traditional ASCII format.
- The TOOCAN segmented images in a NETCDF format have been supplemented with the information on the scanning time of the geostationary satellites.

-Jirak, I. L., W. R. Cotton, and R. L. McAnelly, 2003: Satellite and Radar Survey of Mesoscale Convective System Development. Mon. Wea. Rev., 131, 2428–2449, https://doi.org/10.1175/1520-0493(2003)131<2428:SARSOM>2.0.CO;2
-Knapp, K. R., and Coauthors, 2011: Globally Gridded Satellite observations for climate studies. Bull Am Meteorol Soc, 92, 893–907, https://doi.org/10.1175/2011BAMS3039.1.
-Maddox, R. A., 1980: Mesoscale Convective Complexes. 1374–1387 pp.

References:
-Fiolleau, T. and R. Roca, 2013: An Algorithm for the Detection and Tracking of Tropical Mesoscale Convective Systems Using Infrared Images From Geostationary Satellite, IEEE Trans. Geosci. Remote Sens., vol. 51, no. 7, pp. 4302–4315. doi: 10.1109/TGRS.2012.2227762
-Fiolleau, T., R. Roca, S. Cloché, D. Bouniol, P. Raberanto, 2020: Homogenization of geostationary infrared imager channels for cold cloud studies using Megha-Tropiques/ScaRaB. IEEE Trans. Geosci. Remote Sens., vol 58, no. 9, pp. 6609-6622. doi: 10.1109/TGRS.2020.2978171

TOOCAN是一款云追踪算法，由Fiolleau与Roca于2013年提出，用于从地球静止轨道红外观测数据中检测并追踪深对流系统（Deep Convective Systems, DCSs）。本研究将TOOCAN算法应用于多机构气象地球静止卫星集群的均一化红外观测数据（Fiolleau等，2019），以监测2012-2020年整个热带带的深对流系统。每个地球静止卫星平台可对特定区域开展处理，覆盖范围包括东太平洋、美洲、非洲、印度及西太平洋。在这9年的研究周期内，整个热带区域共识别出约1200万个深对流系统，得以完整记录其生命周期内的形态特征。研究团队由此构建了一套标准化二级数据库，即TOOCAN数据库，该库可获取每个深对流系统的综合形态参数，包括生成与消散的位置和时间、生命周期时长、移动距离、最大覆盖范围等。此外，数据库还记录了深对流系统在其生命周期每30分钟时间步上的形态特征，如不同亮温阈值下的冷云表面积、偏心率、瞬时移动速度等。
TOOCAN数据库包含两类文件：
• 空间分辨率0.04°、时间采样频率为30分钟的区域分割图像（格式为NETCDF）。
• 区域与月度追踪文件（格式为ASCII或NETCDF），用于记录深对流系统的综合形态参数（如生命周期时长、移动距离等）以及其生命周期内的参数演化过程。
TOOCAN 2.08版本相较于此前的2.06版本（DOI）存在多处改进：
- TOOCAN算法通过在红外图像的时空体域中识别对流系统。最初的亮温阈值仍设为190K，用于识别红外图像体域中的对流种子，而迭代检测与扩张过程会在达到235K阈值时停止，该阈值对应冷云罩的边界。为提升对流系统分割质量，本次更新将迭代检测与扩张过程中的检测步长从5K降至2K。
- 依据Jirak等（2003）与Maddox（1981）定义的中尺度对流复合体（Mesoscale Convective Complex, MCC）、行星尺度对流系统（Planetary-scale Convective Systems, PECS）、β中尺度对流复合体（MβCCS）及β中尺度对流系统（MβECS），建立了全新的对流系统分类体系。
- 此外，借助IBTrACS数据库，将距离气旋1000公里范围内的对流系统进行了标记。
- 除传统的ASCII格式外，月度追踪文件新增了NETCDF格式存储选项。
- NETCDF格式的TOOCAN分割图像补充了地球静止卫星的扫描时间信息。
——Jirak, I. L.、W. R. Cotton 与 R. L. McAnelly, 2003：中尺度对流系统发展的卫星与雷达观测研究，《气象月刊》，131卷，第2428-2449页，https://doi.org/10.1175/1520-0493(2003)131<2428:SARSOM>2.0.CO;2
——Knapp, K. R. 及合著者, 2011：用于气候研究的全球格点化卫星观测数据，《美国气象学会公报》，92卷，第893-907页，https://doi.org/10.1175/2011BAMS3039.1.
——Maddox, R. A., 1980：中尺度对流复合体，第1374-1387页。
参考文献：
——Fiolleau, T. 与 R. Roca, 2013：一种利用地球静止卫星红外图像检测与追踪热带中尺度对流系统的算法，IEEE 地球科学与遥感汇刊，第51卷第7期，第4302-4315页。doi: 10.1109/TGRS.2012.2227762
——Fiolleau, T.、R. Roca、S. Cloché、D. Bouniol 与 P. Raberanto, 2020：利用Megha-Tropiques/ScaRaB开展冷云研究的地球静止红外成像仪通道均一化方法，IEEE 地球科学与遥感汇刊，第58卷第9期，第6609-6622页。doi: 10.1109/TGRS.2020.2978171

搜集汇总

背景与挑战

背景概述

TOOCAN Database V2.08是一个专为热带深对流系统（DCSs）检测和跟踪设计的数据库，基于地球静止卫星的红外观测数据。它提供了对流系统的形态特征和生命周期参数的详细记录，覆盖2012-2020年整个热带地区，包含区域分割图像和跟踪文件，支持NETCDF和ASCII格式。