Automated Author ProfileWatson, Peter
Watson, Peter
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.1 (sum of 6 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
TCPBench-Dataset is a tropical cyclone (TC) dataset designed for deep learning–based TC rainfall and track-related prediction tasks. It integrates historical observations, environmental reanalysis data, and future numerical weather prediction (NWP) information.The dataset is constructed following the settings described in our paper and is used by the TCPBench framework.The details could be checked at https://github.com/xiaochengfuhuo/TCPBench-Dataset
Authors
- Huang, Cheng ;
- Mu, Pan ;
- Cong, Bai ;
- Watson, Peter
TCPBench-Dataset is a tropical cyclone (TC) dataset designed for deep learning–based TC rainfall and track-related prediction tasks. It integrates historical observations, environmental reanalysis data, and future numerical weather prediction (NWP) information.The dataset is constructed following the settings described in our paper and is used by the TCPBench framework.The details could be checked at https://github.com/xiaochengfuhuo/TCPBench-Dataset
Authors
- Huang, Cheng ;
- Mu, Pan ;
- Cong, Bai ;
- Watson, Peter
spectroscopic dataset
Authors
- Mackenzie, Stuart ;
- Pearcy, Philip AJ ;
- Watson, Peter ;
- Meizyte, Gabriele ;
- Brewer, Edward I ;
- Haakansson, Christian ;
- Harington, Scott ;
- Doll, Matthew
No description available
Authors
- Peacock, Timothy ;
- Cooper, Jonathan ;
- Blyth, Christopher ;
- Watson, Peter ;
- Rapport, Michael
Large ensembles of global temperature are provided for three climate scenarios: historical (2006-16), 1.5 C and 2.0 C above pre-industrial levels. Each scenario has 700 members (70 runs per year for 10-year periods) of 6-hourly mean temperatures at a resolution of 0.833 degrees x 0.556 degrees (longitude x latitude). The data was generated using the climateprediction.net (CPDN) climate simulation environment, to run the Met Office HadAM4 Atmosphere-only General Circulation Model (AGCM) from the UK Met Office Hadley Centre. Biases in simulated temperature were identified and corrected using quantile mapping with reference temperature data from ERA5 reanalysis. Data were generated using the Met Office HadAM4 model at 6-hourly temporal resolution and 0.833 degrees x 0.556 degrees (longitude x latitude) over global domain. The data from each scenario is divided into 4 batches. Historic scenario (2006-2016): December-March data in Batch 889, April-May data in Batch 920, June-September data in Batch 901, October-November data in Batch 923. 1.5C scenario: December-March data in Batch 891, April-May data in Batch 921, June-September data in Batch 902, October-November data in Batch 924. 2.0C scenario: December-March data in Batch 895, April-May data in Batch 922, June-September data in Batch 903, October-November data in Batch 925.
Authors
- Lizana, Jesus ;
- Miranda, Nicole D ;
- Sparrow, Sarah ;
- Zachau-Walker, Miriam ;
- Watson, Peter ;
- Wallom, David C. H. ;
- McCulloch, Malcolm
No description available
Authors
- Peers, Polly ;
- Manly, Tom ;
- Murphy, Fionnuala ;
- Astle, Duncan ;
- Duncan, John ;
- Watson, Peter ;
- Bateman, Andrew ;
- Punton, Sarah ;
- Hampshire, Adam