TY - JOUR
T1 - Harnessing Land-Atmosphere Interactions to Enhance Subseasonal-to-Seasonal Predictability
AU - He, Cenlin
AU - Zhang, Lily N.
AU - Leung, L. Ruby
AU - Richter, Jadwiga H.
AU - Bassett, Christine
AU - Ferguson, Craig R.
AU - Kumar, Sanjiv
AU - Olsen, Mark A.
AU - Orr, Margaret
AU - Wang, Hailan
AU - Xue, Yan
AU - Attada, Raju
AU - Berner, Judith
AU - Draper, Clara
AU - El Afandi, Gamal
AU - Fowler, Megan D.
AU - Gerken, Tobias
AU - El Gharamti, Mohamad
AU - Hu, Aixue
AU - Huang, Min
AU - Kong, Xianghui
AU - Lu, Lixin
AU - Minallah, Samar
AU - Newman, Andrew
AU - Pu, Zhaoxia
AU - Raczka, Brett
AU - Ray, Pallav
AU - Singh, Manmeet
AU - Slinski, Kimberly
AU - Tang, Qi
AU - Tian, Shanru
AU - Wang, Lei
AU - Xue, Yongkang
AU - Zhang, Shixuan
AU - Zhang, Yongxin
PY - 2026/8
Y1 - 2026/8
N2 - 2025 Advancing Understanding of Land-Atmosphere Interactions and Processes on S2S Predictability Workshop What: 227 registered workshop participants gathered in person (43%) and online (57%) to discuss state-of-the-art scientific understanding and modeling of land-atmosphere interactions and related processes in the context of subseasonal-to-seasonal (S2S) predictability. Topics covered sources of S2S predictability, land model initialization methods, model diagnosis and evaluation metrics, AI/ML analysis and applications, and coordination of future community multimodel S2S forecast-focused experiments. To advance the science, this community workshop, organized by NSF NCAR, NOAA, NASA, and DOE, aimed to 1) identify process-and application-oriented metrics for assessing S2S prediction skill and 2) develop experimental protocols for coordinated experiments to isolate, quantify, and understand the role of land-atmosphere interactions in S2S predictability. When: 16-18 June 2025 Where: Boulder, Colorado and online
AB - 2025 Advancing Understanding of Land-Atmosphere Interactions and Processes on S2S Predictability Workshop What: 227 registered workshop participants gathered in person (43%) and online (57%) to discuss state-of-the-art scientific understanding and modeling of land-atmosphere interactions and related processes in the context of subseasonal-to-seasonal (S2S) predictability. Topics covered sources of S2S predictability, land model initialization methods, model diagnosis and evaluation metrics, AI/ML analysis and applications, and coordination of future community multimodel S2S forecast-focused experiments. To advance the science, this community workshop, organized by NSF NCAR, NOAA, NASA, and DOE, aimed to 1) identify process-and application-oriented metrics for assessing S2S prediction skill and 2) develop experimental protocols for coordinated experiments to isolate, quantify, and understand the role of land-atmosphere interactions in S2S predictability. When: 16-18 June 2025 Where: Boulder, Colorado and online
KW - Atmosphere-land interaction
KW - Data assimilation
KW - Forecast verification/skill
KW - Machine learning
KW - Seasonal forecasting
KW - Surface fluxes
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=ncarpurestagin&SrcAuth=WosAPI&KeyUT=WOS:001861591500001&DestLinkType=FullRecord&DestApp=WOS_CPL
U2 - 10.1175/BAMS-D-25-0255.1
DO - 10.1175/BAMS-D-25-0255.1
M3 - Article
SN - 0003-0007
VL - 107
SP - E1854-E1861
JO - Bulletin of the American Meteorological Society
JF - Bulletin of the American Meteorological Society
IS - 8
ER -