A Year‐Round Subseasonal‐to‐Seasonal Sea Ice Prediction Portal

Wayand, Nicholas E.; Bitz, Cecilia M.; Blanchard‐Wrigglesworth, Edward

doi:10.1029/2018gl081565

Cited by 34 publications

(38 citation statements)

References 23 publications

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“…The recently established database of the Subseasonal to Seasonal (S2S) Prediction Project (Vitart et al, , ) has proven to be valuable for evaluating the predictive skill of operational S2S ensemble forecast systems in the Arctic (Wayand et al, ; Zampieri et al, ). The availability of comprehensive sets of both reforecasts and real‐time forecasts allows for a robust assessment of the forecast skill over a relatively long time period (>10 years), covering the whole seasonal cycle.…”

Section: Introductionmentioning

confidence: 99%

Predictability of Antarctic Sea Ice Edge on Subseasonal Time Scales

Zampieri

Goessling

Jung

2019

Geophysical Research Letters

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Coupled subseasonal forecast systems with dynamical sea ice have the potential of providing important predictive information in polar regions. Here, we evaluate the ability of operational ensemble prediction systems to predict the location of the sea ice edge in Antarctica. Compared to the Arctic, Antarctica shows on average a 30% lower skill, with only one system remaining more skillful than a climatological benchmark up to ∼30 days ahead. Skill tends to be highest in the west Antarctic sector during the early freezing season. Most of the systems tend to overestimate the sea ice edge extent and fail to capture the onset of the melting season. All the forecast systems exhibit large initial errors. We conclude that subseasonal sea ice predictions could provide marginal support for decision‐making only in selected seasons and regions of the Southern Ocean. However, major progress is possible through investments in model development, forecast initialization and calibration.

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Section: Introductionmentioning

confidence: 99%

Predictability of Antarctic Sea Ice Edge on Subseasonal Time Scales

Zampieri

Goessling

Jung

2019

Geophysical Research Letters

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“…This effort spans research on potential predictability in dynamical models (e.g., Holland et al 2011;Blanchard-Wrigglesworth et al 2011), developing real-world forecasts using a range of dynamical and statistical models (e.g., Wang et al 2013;Merryfield et al 2013;Sigmond et al 2013;Msadek et al 2014;Yuan et al 2016), improving model simulation of polar-specific processes such as sea ice floe size distribution (e.g., Roach et al 2018), advances in sea ice data assimilation (e.g., Zhang et al 2018), and the deployment of observing networks and fieldwork campaigns [e.g., NASA's Operation Ice-Bridge and Ice, Cloud and Land Elevation Satellite-2 (IceSAT-2) platforms or the upcoming Multidisciplinary Drifting Observatory for the Study of Arctic Climate experiment]. Recent or current examples that characterize the growing momentum in polar predictability are the start of regular seasonal sea ice forecasts such as the sea ice outlook (Stroeve et al 2015), a year-round sea ice forecast portal (Wayand et al 2019), and the Year of Polar Prediction (YOPP) taking place over 2017-19 (Jung et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Tropical and Midlatitude Impact on Seasonal Polar Predictability in the Community Earth System Model

Blanchard‐Wrigglesworth

Ding

2019

Journal of Climate

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The impact on seasonal polar predictability from improved tropical and midlatitude forecasts is explored using a perfect-model experiment and applying a nudging approach in a GCM. We run three sets of 7-month long forecasts: a standard free-running forecast and two nudged forecasts in which atmospheric winds, temperature, and specific humidity (U, V, T, Q) are nudged toward one of the forecast runs from the free ensemble. The two nudged forecasts apply the nudging over different domains: the tropics (30°S–30°N) and the tropics and midlatitudes (55°S–55°N). We find that the tropics have modest impact on forecast skill in the Arctic or Antarctica both for sea ice and the atmosphere that is mainly confined to the North Pacific and Bellingshausen–Amundsen–Ross Seas, whereas the midlatitudes greatly improve Arctic winter and Antarctic year-round forecast skill. Arctic summer forecast skill from May initialization is not strongly improved in the nudged forecasts relative to the free forecast and is thus mostly a “local” problem. In the atmosphere, forecast skill improvement from midlatitude nudging tends to be largest in the polar stratospheres and decreases toward the surface.

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“…Here, we define the ice edge as 15% ice concentration. We also consider a Brier Skill Score (BSS) (Brier 1950) for ice concentration below 15% following Wayand et al (2019). The Brier Skill Score is the degree of improvement of the Brier Score (BS) of the Navy-ESPCENS forecast over the BS produced using a persisted analysis or climatology.…”

Section: Sea Ice Verificationmentioning

confidence: 99%

The Navy's Earth System Prediction Capability: A New Global Coupled Atmosphere‐Ocean‐Sea Ice Prediction System Designed for Daily to Subseasonal Forecasting

Barton¹,

Metzger

Reynolds³

et al. 2021

Earth and Space Science

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This paper describes the new global Navy Earth System Prediction Capability (Navy-ESPC) coupled atmosphere-ocean-sea ice prediction system developed at the Naval Research Laboratory (NRL) for operational forecasting for timescales of days to the subseasonal. Navy-ESPC will become operational in late 2020, and this system will be the first time the NRL operational partner, Fleet Numerical Meteorology and Oceanography Center, will provide global coupled atmosphere-ocean-sea ice forecasts, with atmospheric forecasts extending to 16 days, and ocean and sea ice ensemble forecasts. Two configurations of the system are validated: (1) a low-resolution 16-member ensemble system and (2) a highresolution deterministic system. A unique aspect of the Navy-ESPC is that the global ocean model is eddy resolving at 1/12° in the ensemble and at 1/25° in the deterministic configurations. The component models are current Navy operational systems: NAVy Global Environmental Model (NAVGEM) for the atmosphere; HYbrid Coordinate Ocean Model (HYCOM) for the ocean; and Community Ice CodE (CICE) for the sea ice. Physics updates to improve the simulation of equatorial phenomena, particularly the Madden Julian Oscillation (MJO) were introduced into NAVGEM. The low resolution ensemble configuration and highresolution deterministic configuration are evaluated based on analyses and forecasts from January 2017 to January 2018. Navy-ESPC ensemble forecast skill for large-scale atmospheric phenomena, such as the Madden-Julian Oscillation (MJO), North Atlantic Oscillation (NAO), Antarctic Oscillation (AAO), and other indices, is comparable to that of other numerical weather prediction (NWP) centers. Ensemble forecasts of ocean sea surface temperatures perform better than climatology in the tropics and mid-latitudes out to 60 days. In addition, the Navy-ESPC Pan-Arctic and Pan-Antarctic sea ice extent predictions perform better than climatology out to about 45 days, although the skill is dependent on season.

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A Year‐Round Subseasonal‐to‐Seasonal Sea Ice Prediction Portal

Cited by 34 publications

References 23 publications

Predictability of Antarctic Sea Ice Edge on Subseasonal Time Scales

Predictability of Antarctic Sea Ice Edge on Subseasonal Time Scales

Tropical and Midlatitude Impact on Seasonal Polar Predictability in the Community Earth System Model

The Navy's Earth System Prediction Capability: A New Global Coupled Atmosphere‐Ocean‐Sea Ice Prediction System Designed for Daily to Subseasonal Forecasting

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