SMART Indicator Report: Sea Surface Temperature - Ocean Model
2 Indicator name
Sea Surface Temperature - Ocean Model
Includes variable(s): Fall-hindcast, forecast-1, forecast-10, forecast-2, forecast-3, forecast-4, forecast-5, forecast-6, forecast-7, forecast-8, forecast-9, forecast-Ensemble Mean, Spring-hindcast, Summer-hindcast, Winter-hindcast
3 Indicator brief description
The data presented here are seasonal sea surface temperature anomalies for the period 1993-2019 from the MOM6 hindcast ocean model for the Northwest Atlantic. Also shown here are 10-year forecasts of sea surface temperature anomalies (2023-2033) from the MOM6 decadal forecast ocean model for the Northwest Atlantic.
4 Indicator visualization
Here we show seasonal sea surface temperature anomalies in the Mid Atlantic Bight (MAB), Georges Bank (GB) and Gulf of Maine (GOM) EPUs. Data from 1993 through 2019 are from NWA MOM6 ([72]) with a base period for the climatology of 1993 through 2010. We do not compare these anomalies to those from observed OISST as the base period for that dataset is 1982-2010. We also show the 10-year forecast for annual sea surface temperature anomalies in the MAB, GB, and GOM. This forecast is from the decadal forecast of NWA MOM6 ([42]), which was initialized in 2022 and ran for 10 years. The forecast indicates a stagnation in surface temperature warming over the next ten years. Retrospective forecasts, where a forecast is initiated in the past and output is compared to observations, have shown that the NWA MOM6 decadal forecast is able to correctly predict periods of temperature stability and rapid warming in this region ([42]).
5 Indicator documentation
5.1 Are indicators available for others to use (data downloadable)?
## Yes
5.1.1 Where can indicators be found?
## Data: https://noaa-edab.github.io/ecodata/index.html
## Description: https://noaa-edab.github.io/catalog/surface_temp_mom6.html
## Technical documentation: https://noaa-edab.github.io/tech-doc/surface_temp_mom6.html
5.1.2 How often are they updated? Are future updates likely?
[need sequential look at datasets for update frequency. Future requires judgement]
5.1.3 Who is the contact?
Laura Gruenburg (laura.gruenburg@noaa.gov)
5.2 Gather indicator statistics
5.2.2 Length of time series, start and end date, periodicity
General overview: Winter (January, February, March), Spring (April, May, June), Summer (July, August, September), Fall (October, November, December), and Annual
Indicator specifics:
Indicator | EPU | StartYear | EndYear | NumYears | MissingYears |
---|---|---|---|---|---|
Fall-hindcast | GB | 1993 | 2019 | 27 | 0 |
Fall-hindcast | GOM | 1993 | 2019 | 27 | 0 |
Fall-hindcast | MAB | 1993 | 2019 | 27 | 0 |
forecast-1 | GB | 2023 | 2032 | 10 | 0 |
forecast-1 | GOM | 2023 | 2032 | 10 | 0 |
forecast-1 | MAB | 2023 | 2032 | 10 | 0 |
forecast-10 | GB | 2023 | 2032 | 10 | 0 |
forecast-10 | GOM | 2023 | 2032 | 10 | 0 |
forecast-10 | MAB | 2023 | 2032 | 10 | 0 |
forecast-2 | GB | 2023 | 2032 | 10 | 0 |
forecast-2 | GOM | 2023 | 2032 | 10 | 0 |
forecast-2 | MAB | 2023 | 2032 | 10 | 0 |
forecast-3 | GB | 2023 | 2032 | 10 | 0 |
forecast-3 | GOM | 2023 | 2032 | 10 | 0 |
forecast-3 | MAB | 2023 | 2032 | 10 | 0 |
forecast-4 | GB | 2023 | 2032 | 10 | 0 |
forecast-4 | GOM | 2023 | 2032 | 10 | 0 |
forecast-4 | MAB | 2023 | 2032 | 10 | 0 |
forecast-5 | GB | 2023 | 2032 | 10 | 0 |
forecast-5 | GOM | 2023 | 2032 | 10 | 0 |
forecast-5 | MAB | 2023 | 2032 | 10 | 0 |
forecast-6 | GB | 2023 | 2032 | 10 | 0 |
forecast-6 | GOM | 2023 | 2032 | 10 | 0 |
forecast-6 | MAB | 2023 | 2032 | 10 | 0 |
forecast-7 | GB | 2023 | 2032 | 10 | 0 |
forecast-7 | GOM | 2023 | 2032 | 10 | 0 |
forecast-7 | MAB | 2023 | 2032 | 10 | 0 |
forecast-8 | GB | 2023 | 2032 | 10 | 0 |
forecast-8 | GOM | 2023 | 2032 | 10 | 0 |
forecast-8 | MAB | 2023 | 2032 | 10 | 0 |
forecast-9 | GB | 2023 | 2032 | 10 | 0 |
forecast-9 | GOM | 2023 | 2032 | 10 | 0 |
forecast-9 | MAB | 2023 | 2032 | 10 | 0 |
forecast-Ensemble Mean | GB | 2023 | 2032 | 10 | 0 |
forecast-Ensemble Mean | GOM | 2023 | 2032 | 10 | 0 |
forecast-Ensemble Mean | MAB | 2023 | 2032 | 10 | 0 |
Spring-hindcast | GB | 1993 | 2019 | 27 | 0 |
Spring-hindcast | GOM | 1993 | 2019 | 27 | 0 |
Spring-hindcast | MAB | 1993 | 2019 | 27 | 0 |
Summer-hindcast | GB | 1993 | 2019 | 27 | 0 |
Summer-hindcast | GOM | 1993 | 2019 | 27 | 0 |
Summer-hindcast | MAB | 1993 | 2019 | 27 | 0 |
Winter-hindcast | GB | 1993 | 2019 | 27 | 0 |
Winter-hindcast | GOM | 1993 | 2019 | 27 | 0 |
Winter-hindcast | MAB | 1993 | 2019 | 27 | 0 |
5.2.3 Spatial location, scale and extent
General overview: The model data is on a roughly 1/12 degree grid. Here we show the data averaged by EPU.
Indicator specifics:
Indicator | EPU |
---|---|
Fall-hindcast | GB |
Fall-hindcast | GOM |
Fall-hindcast | MAB |
forecast-1 | GB |
forecast-1 | GOM |
forecast-1 | MAB |
forecast-10 | GB |
forecast-10 | GOM |
forecast-10 | MAB |
forecast-2 | GB |
forecast-2 | GOM |
forecast-2 | MAB |
forecast-3 | GB |
forecast-3 | GOM |
forecast-3 | MAB |
forecast-4 | GB |
forecast-4 | GOM |
forecast-4 | MAB |
forecast-5 | GB |
forecast-5 | GOM |
forecast-5 | MAB |
forecast-6 | GB |
forecast-6 | GOM |
forecast-6 | MAB |
forecast-7 | GB |
forecast-7 | GOM |
forecast-7 | MAB |
forecast-8 | GB |
forecast-8 | GOM |
forecast-8 | MAB |
forecast-9 | GB |
forecast-9 | GOM |
forecast-9 | MAB |
forecast-Ensemble Mean | GB |
forecast-Ensemble Mean | GOM |
forecast-Ensemble Mean | MAB |
Spring-hindcast | GB |
Spring-hindcast | GOM |
Spring-hindcast | MAB |
Summer-hindcast | GB |
Summer-hindcast | GOM |
Summer-hindcast | MAB |
Winter-hindcast | GB |
Winter-hindcast | GOM |
Winter-hindcast | MAB |
5.3 Are methods clearly documented to obtain source data and calculate indicators?
## Yes
5.3.1 Can the indicator be calculated from current documentation?
[Build link to Tech-doc, look for current and previous methods]
5.4 Are indicator underlying source data linked or easy to find?
[Build link to Tech-doc, look for source, may require judgements]
5.4.1 Where are source data stored?
[Build link to Tech-doc, look for source, may require judgement]
6 Indicator analysis/testing or history of use
6.1 What decision or advice processes are the indicators currently used in?
This indicator shows seasonal sea surface temperature anomalies from a regional ocean model for the Northwest Atlantic based on the Modular Ocean Model Version 6 (NWA MOM6). The model is at roughly 1/12 a degree horizontal resolution with data from 1993-2019 from a hindcast simulation, which has no data assimilation. Investigating the ability of this model to reproduce key indicators can help us to develop confidence in the model as well as learn where improvements can be made. This indicator also shows 10-year forecasts of annual sea surface temperature anomalies from the decadal forecast of the MOM6 Northwest Atlantic regional ocean model. Understanding how temperatures might change in the future can help us anticipate potential shifts in marine communities.
6.2 What implications of the indicators are currently listed?
Sea surface temperature is important for many marine species that have specific thermal preferences and tolerances. When a region becomes too warm or cool, a species may respond in many ways including by shifting its range or changing its behavior. Understanding how surface temperature may vary in the future can help us anticipate changes to marine communities and living marine resources.
6.3 Do target, limit, or threshold values already exist for the indicator?
[Fill by hand; if not in key results or implications, likely does not exist]
6.4 Have the indicators been tested to ensure they respond proportionally to a change in the underlying process?
[Fill by hand; if not in introduction, key results, or implications, likely not tested]
7 Comments
[Fill below by hand once above data complete]
7.1 Additional potential links to management in addition to uses listed above
7.2 What additional work would be needed for the Council to use the indicator?
7.3 What issues are caused if there is a gap or delay in data underlying the indicator