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  • 1
    Publication Date: 2022-12-01
    Description: Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 103(6), (2022): E1502-E1521, https://doi.org/10.1175/bams-d-21-0227.1.
    Description: Climate observations inform about the past and present state of the climate system. They underpin climate science, feed into policies for adaptation and mitigation, and increase awareness of the impacts of climate change. The Global Climate Observing System (GCOS), a body of the World Meteorological Organization (WMO), assesses the maturity of the required observing system and gives guidance for its development. The Essential Climate Variables (ECVs) are central to GCOS, and the global community must monitor them with the highest standards in the form of Climate Data Records (CDR). Today, a single ECV—the sea ice ECV—encapsulates all aspects of the sea ice environment. In the early 1990s it was a single variable (sea ice concentration) but is today an umbrella for four variables (adding thickness, edge/extent, and drift). In this contribution, we argue that GCOS should from now on consider a set of seven ECVs (sea ice concentration, thickness, snow depth, surface temperature, surface albedo, age, and drift). These seven ECVs are critical and cost effective to monitor with existing satellite Earth observation capability. We advise against placing these new variables under the umbrella of the single sea ice ECV. To start a set of distinct ECVs is indeed critical to avoid adding to the suboptimal situation we experience today and to reconcile the sea ice variables with the practice in other ECV domains.
    Description: PH’s contribution was funded under the Australian Government’s Antarctic Science Collaboration Initiative program, and contributes to Project 6 of the Australian Antarctic Program Partnership (ASCI000002). PH acknowledges support through the Australian Antarctic Science Projects 4496 and 4506, and the International Space Science Institute (Bern, Switzerland) project #405.
    Description: 2022-12-01
    Keywords: Sea ice ; Climate change ; Climatology ; Climate records
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-12-20
    Description: In the Earth sciences, a transition is currently occurring in multiple fields towards an integrated Earth system approach, with applications including numerical weather prediction, hydrological forecasting, climate impact studies, ocean dynamics estimation and monitoring, and carbon cycle monitoring. These approaches rely on coupled modeling techniques using Earth system models that account for an increased level of complexity of the processes and interactions between atmosphere, ocean, sea ice, and terrestrial surfaces. A crucial component of Earth system approaches is the development of coupled data assimilation of satellite observations to ensure consistent initialization at the interface between the different subsystems. Going towards strongly coupled data assimilation involving all Earth system components is a subject of active research. A lot of progress is being made in the ocean–atmosphere domain, but also over land. As atmospheric models now tend to address subkilometric scales, assimilating high spatial resolution satellite data in the land surface models used in atmospheric models is critical. This evolution is also challenging for hydrological modeling. This book gathers papers reporting research on various aspects of coupled data assimilation in Earth system models. It includes contributions presenting recent progress in ocean–atmosphere, land–atmosphere, and soil–vegetation data assimilation.
    Keywords: Q1-390 ; land data assimilation system ; land data assimilation ; rainfall-runoff simulation ; 4D-Var data assimilation ; total water storage ; accuracy ; ocean–atmosphere assimilation ; precipitation ; Earth system models ; numerical weather prediction ; fluorescence ; GRACE ; MCA analysis ; weakly coupled data assimilation ; GPM IMERG ; atmospheric models ; rainfall correction ; remote sensing ; microwave remote sensing ; SMAP ; land surface modeling ; bending angle ; floods soil moisture ; vegetation ; GPSRO ; WRF ; merged CMORPH ; land surface model ; temperature ; 4D-Var ; data assimilation ; data-driven methods ; GSI ; radio occultation data ; rainfall ; soil moisture ; sea level anomaly ; total cloud cover ; land surface models ; Mediterranean basin ; interpolation ; sea surface height ; drought ; TRMM 3B42 ; analog data assimilation ; ocean models ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general
    Language: English
    Format: application/octet-stream
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