Seasonal tropical cyclone(TC)forecasting has evolved substantially since its commencement in the early 1980s.However,present operational seasonal TC forecasting services still do not meet the requirements of society a...Seasonal tropical cyclone(TC)forecasting has evolved substantially since its commencement in the early 1980s.However,present operational seasonal TC forecasting services still do not meet the requirements of society and stakeholders:current operational products are mainly basin-scale information,while more detailed sub-basin scale information such as potential risks of TC landfall is anticipated for decision making.To fill this gap and make the TC science and services move forward,this paper reviews recent research and development in seasonal tropical cyclone(TC)forecasting.In particular,this paper features new research topics on seasonal TC predictability in neutral conditions of El Ni˜no–Southern Oscillation(ENSO),emerging forecasting techniques of seasonal TC activity including Machine Learning/Artificial Intelligence,and multi-annual TC predictions.We also review the skill of forecast systems at predicting landfalling statistics for certain regions of the North Atlantic,Western North Pacific and South Indian oceans and discuss the gap that remains between current products and potential user's expectations.New knowledge and advanced forecasting techniques are expected to further enhance the capability of seasonal TC forecasting and lead to more actionable and fit-for-purpose products.展开更多
Cloud-based services introduce a paradigm shift in how users access,process and analyse Big Earth data.A key challenge is to align the current state of how users access,process and analyse the data with trends and roa...Cloud-based services introduce a paradigm shift in how users access,process and analyse Big Earth data.A key challenge is to align the current state of how users access,process and analyse the data with trends and roadmaps large data organisations layout.In addition,due to the increased availability of open data,a more diverse user base wants to take advantage of Earth science data leading to new user requirements.We run a web-based survey among Big Earth data users to better understand the motivation to migrate to cloud-based services as well as the challenges and opportunities that might arise.Results show an overall interest in moving to cloud-based services but air an insufficient literacy in cloud systems and a lack of trust due to security concerns and opacity of emerging costs.These gaps demand efforts on three levels.First,cloud services shall be targeted at intermediate users instead of policy-and decision-makers and over-engineered systems with a high level of abstraction should be avoided.Second,more substantial capacity-building efforts are required to decrease the existing gap in cloud skills and uptake.Third,a cloud certification mechanism could help in building up overall trust in cloud-based services.展开更多
基金support of the MEXT program for the advanced studies of climate change projection(SENTAN),Grant Numbers JPMXD0722680395 and JPMXD0722680734Julia Lockwood would like to acknowledge funding from the C3S_34c contract(number:ECMWF/COPERNICUS/2019/C3S_34c_DWD)of the Copernicus Climate Change Service operated by ECMWF.
文摘Seasonal tropical cyclone(TC)forecasting has evolved substantially since its commencement in the early 1980s.However,present operational seasonal TC forecasting services still do not meet the requirements of society and stakeholders:current operational products are mainly basin-scale information,while more detailed sub-basin scale information such as potential risks of TC landfall is anticipated for decision making.To fill this gap and make the TC science and services move forward,this paper reviews recent research and development in seasonal tropical cyclone(TC)forecasting.In particular,this paper features new research topics on seasonal TC predictability in neutral conditions of El Ni˜no–Southern Oscillation(ENSO),emerging forecasting techniques of seasonal TC activity including Machine Learning/Artificial Intelligence,and multi-annual TC predictions.We also review the skill of forecast systems at predicting landfalling statistics for certain regions of the North Atlantic,Western North Pacific and South Indian oceans and discuss the gap that remains between current products and potential user's expectations.New knowledge and advanced forecasting techniques are expected to further enhance the capability of seasonal TC forecasting and lead to more actionable and fit-for-purpose products.
文摘Cloud-based services introduce a paradigm shift in how users access,process and analyse Big Earth data.A key challenge is to align the current state of how users access,process and analyse the data with trends and roadmaps large data organisations layout.In addition,due to the increased availability of open data,a more diverse user base wants to take advantage of Earth science data leading to new user requirements.We run a web-based survey among Big Earth data users to better understand the motivation to migrate to cloud-based services as well as the challenges and opportunities that might arise.Results show an overall interest in moving to cloud-based services but air an insufficient literacy in cloud systems and a lack of trust due to security concerns and opacity of emerging costs.These gaps demand efforts on three levels.First,cloud services shall be targeted at intermediate users instead of policy-and decision-makers and over-engineered systems with a high level of abstraction should be avoided.Second,more substantial capacity-building efforts are required to decrease the existing gap in cloud skills and uptake.Third,a cloud certification mechanism could help in building up overall trust in cloud-based services.
