This binary dataset contains a specific customization of the National Center for Environmental Prediction (NCEP)/final analysis (FNL) data for ML applications, in which environmental conditions relevant for tropical cyclone (TC) formation during 1999-2023 are extracted for a range of forecast lead times (0-72 hours). The dataset is designed as multi-channel images centered on TC formation locations, with a positive and negative directory structure that can be readily input from any ML applications or common data interface. With its unique structure, this dataset provides users an opportunity to conduct ML application research on TC formation as well as related predictability at different forecast lead times. </p
Microwave remote sensing can be used to measure ocean surface winds, which can be used to detect tro...
Tropical cyclone ensemble prediction product in CXML format carrying position and center pressure of...
This is the official repository for the paper TCRIP-MIM: Rapid Intensification Prediction for Tropic...
LONG-TERM GOALS: The long-term goal is to improve the prediction of the intensity and structure of t...
This thesis documents advancements made during the 2021 season test of pre-formation tropical cyclon...
This study compared detection skill for tropical cyclone (TC) formation using models based on three ...
Concentric eyewalls (CEs) and associated eyewall replacements play key roles in tropical cyclone (TC...
The trained 600-member ensemble convolutional neural networks (CNNs) for seasonal tropical cyclone (...
About one hundred of tropical cyclones (TCs) annually influence human habitats, causing lots of soci...
This archive supports the submission of "Reducing a tropical cyclone weak intensity bias in a global...
Tropical cyclones (TC) are extreme weather phenomena that bring heavy disasters to humans. Existing ...
Regarded as one of the most dangerous types of natural disaster, tropical cyclones threaten the life...
Current numerical weather prediction models experience great difficulty in forecasting tropical cycl...
Tropical cyclones (TCs) are dangerous because they produce destructive winds, heavy rainfall with fl...
Tropical cyclone (TC) intensity change is controlled by both environmental conditions and internal s...
Microwave remote sensing can be used to measure ocean surface winds, which can be used to detect tro...
Tropical cyclone ensemble prediction product in CXML format carrying position and center pressure of...
This is the official repository for the paper TCRIP-MIM: Rapid Intensification Prediction for Tropic...
LONG-TERM GOALS: The long-term goal is to improve the prediction of the intensity and structure of t...
This thesis documents advancements made during the 2021 season test of pre-formation tropical cyclon...
This study compared detection skill for tropical cyclone (TC) formation using models based on three ...
Concentric eyewalls (CEs) and associated eyewall replacements play key roles in tropical cyclone (TC...
The trained 600-member ensemble convolutional neural networks (CNNs) for seasonal tropical cyclone (...
About one hundred of tropical cyclones (TCs) annually influence human habitats, causing lots of soci...
This archive supports the submission of "Reducing a tropical cyclone weak intensity bias in a global...
Tropical cyclones (TC) are extreme weather phenomena that bring heavy disasters to humans. Existing ...
Regarded as one of the most dangerous types of natural disaster, tropical cyclones threaten the life...
Current numerical weather prediction models experience great difficulty in forecasting tropical cycl...
Tropical cyclones (TCs) are dangerous because they produce destructive winds, heavy rainfall with fl...
Tropical cyclone (TC) intensity change is controlled by both environmental conditions and internal s...
Microwave remote sensing can be used to measure ocean surface winds, which can be used to detect tro...
Tropical cyclone ensemble prediction product in CXML format carrying position and center pressure of...
This is the official repository for the paper TCRIP-MIM: Rapid Intensification Prediction for Tropic...