
Alibaba DAMO Academy, the global research initiative by Alibaba Group, has unveiled a cloud-based Artificial Intelligence (AI)-powered nowcasting platform capable of predicting short-term weather conditions up to six hours in advance.
The Short-term AI Weather Forecasting Platform, now available to Alibaba Cloud’s clients in China, produces high-resolution imagery with one-kilometre grid spacing with updates available every 10 minutes. Capable of tracking rainfall, wind speed as well as severe weather conditions such as thunder and hailstorms, the platform promises to deliver tangible value to weather-dependent sectors, including agriculture, logistics, transportation and renewable energy.
For farmers, a timely and accurate weather forecast can minimise damage to crops and livestock. Couriers, on the other hand, can schedule their routes efficiently on rainy days, while photovoltaic power stations can use cloud formation predictions to better prepare their electricity trading plans.
“Nowcasting has proven a critical technology to help various sectors make informed weather-related decisions. Global technology players are working hard to develop technology-based services that utilise reliable climate data from their respective countries”, said Rong Jin, Head of the Machine Intelligence Lab at Alibaba DAMO Academy.
“Using our cutting-edge algorithms and cloud technologies, we have significantly advanced our nowcasting capabilities in China. By doing so, we aim to help businesses meet their climate-related challenges and mitigate the risks of unpredictable weather”, Jin added.
The AI-based forecast platform, co-developed by Alibaba DAMO Academy and the National Meteorological Center in China, incorporates a convolutional neural network (CNN) model to effectively extract features from radar reflectivity and meteorological satellite images.
A trained Machine-Learning model is capable of performing highly accurate and close-to real-time local weather forecasting in minutes, while Generative Adversarial Network (GAN) works to generate forecast images with exceptional clarity and detail. This AI-based prediction model outperforms the traditional physics-based model, for example the Global/Regional Assimilation and Prediction System (GRAPES), which requires hours to generate forecasting data, by increasing the speed and accuracy of reporting.
Alibaba is committed to using technology innovation to help solve the environmental challenges for industries that require actionable climate-related insights to support their daily operations. For example, grape farmers in Wuhan are using Alibaba Cloud’s IoT system to analyse data from the surrounding environment, including soil, humidity and sunlight, to better plan their water and fertiliser management, while pear farmers in Anhui province and pineapple farmers in Hainan province are benefitting from “modern digital farms”, powered by Alibaba’s latest cloud and AI technologies.


Archive
- October 2024(44)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)