From d22f64b6b750d381abf3fc88b07db69d09243f5c Mon Sep 17 00:00:00 2001 From: h-wilborn <153732478+h-wilborn@users.noreply.github.com> Date: Thu, 3 Oct 2024 09:29:02 +0200 Subject: [PATCH] Create abstract_wang.md --- assets/abstract_wang.md | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) create mode 100644 assets/abstract_wang.md diff --git a/assets/abstract_wang.md b/assets/abstract_wang.md new file mode 100644 index 000000000000..92a687bac853 --- /dev/null +++ b/assets/abstract_wang.md @@ -0,0 +1,18 @@ +--- +layout: minimal +--- + +## Impact of super resolution SIT data for seasonal sea ice predictions +### *Yiguo Wang* + +Accurate seasonal prediction of Sea Ice Extent (SIE) is critical for understanding Arctic climate dynamics and holds significant societal and environmental implications. +The Norwegian Climate Prediction Model (NorCPM) has previously demonstrated skill in predicting pan-Arctic SIE up to 12 months ahead, primarily using ocean data and coarse-resolution Sea Ice Concentration (SIC) and Sea Ice Thickness (SIT) data. +However, its capacity for regional SIE prediction remains limited to a few months, depending on season and region. + +This study aims to improve seasonal SIE prediction by incorporating high-resolution SIC and SIT data into NorCPM. +The high-resolution sea ice data are classed to SIC data in each category. NorCPM assimilates the category SIC data. +We assess the performance of this approach by conducting retrospective ensemble prediction for 2023. +The experiment is initialized in March and run for up to 13 months. +The prediction will be validated against observations and compared to the standard version of prediction using coarse-resolution sea ice data. + +[back to the Workshop page](https://nansencenter.github.io/superice-nersc/workshop/)