Initial evaluations of a Gulf of Mexico/Caribbean ocean forecast system in the context of the Deepwater Horizon disaster

doi:10.1007/s11707-014-0508-x

Front. Earth Sci.

2015, Vol. 9

Issue (4) : 605-636 https://doi.org/10.1007/s11707-014-0508-x

RESEARCH ARTICLE

Initial evaluations of a Gulf of Mexico/Caribbean ocean forecast system in the context of the Deepwater Horizon disaster

Edward D. ZARON^1,^*(

),Patrick J. FITZPATRICK²,Scott L. CROSS³,John M. HARDING⁴,Frank L. BUB⁵,Jerry D. WIGGERT⁶,Dong S. KO⁷,Yee LAU²,Katharine WOODARD^2,⁶,Christopher N. K. MOOERS¹

1. Department of Civil and Environmental Engineering, Portland State University, Portland OR 97207, USA
2. Geosystems Research Institute, Mississippi State University, MSU Science & Technology Center, Stennis Space Center, MS 39529, USA
3. NOAA National Coastal Data Development Center, Stennis Space Center, MS 29412, USA
4. Northern Gulf Institute, Mississippi State University, MSU Science & Technology Center, Stennis Space Center, MS 39529, USA
5. unaffiliated, retired from the Naval Oceanographic Office, Stennis Space Center, MS 39522, USA
6. Department of Marine Science, University of Southern Mississippi, Stennis Space Center, MS 39529, USA
7. Oceanography Division, Naval Research Laboratory, Stennis Space Center, MS 39529, USA

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Abstract

In response to the Deepwater Horizon (DwH) oil spill event in 2010, the Naval Oceanographic Office deployed a nowcast-forecast system covering the Gulf of Mexico and adjacent Caribbean Sea that was designated Americas Seas, or AMSEAS, which is documented in this manuscript. The DwH disaster provided a challenge to the application of available ocean-forecast capabilities, and also generated a historically large observational dataset. AMSEAS was evaluated by four complementary efforts, each with somewhat different aims and approaches: a university research consortium within an Integrated Ocean Observing System (IOOS) testbed; a petroleum industry consortium, the Gulf of Mexico 3-D Operational Ocean Forecast System Pilot Prediction Project (GOMEX-PPP); a British Petroleum (BP) funded project at the Northern Gulf Institute in response to the oil spill; and the Navy itself. Validation metrics are presented in these different projects for water temperature and salinity profiles, sea surface wind, sea surface temperature, sea surface height, and volume transport, for different forecast time scales. The validation found certain geographic and time biases/errors, and small but systematic improvements relative to earlier regional and global modeling efforts. On the basis of these positive AMSEAS validation studies, an oil spill transport simulation was conducted using archived AMSEAS nowcasts to examine transport into the estuaries east of the Mississippi River. This effort captured the influences of Hurricane Alex and a non-tropical cyclone off the Louisiana coast, both of which pushed oil into the western Mississippi Sound, illustrating the importance of the atmospheric influence on oil spills such as DwH.

Keywords Gulf of Mexico Deepwater Horizon ocean forecasting skill assessment

Corresponding Author(s): Edward D. ZARON

Just Accepted Date: 27 November 2014 Online First Date: 02 February 2015 Issue Date: 30 October 2015

Cite this article:

Edward D. ZARON,Patrick J. FITZPATRICK,Scott L. CROSS, et al. Initial evaluations of a Gulf of Mexico/Caribbean ocean forecast system in the context of the Deepwater Horizon disaster[J]. Front. Earth Sci., 2015, 9(4): 605-636.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-014-0508-x
https://academic.hep.com.cn/fesci/EN/Y2015/V9/I4/605

Fig.1 AMSEAS domain with the insert outlining the Gulf of Mexico evaluation area. Depth scale in km.

Tab.1 Summary of general forecast model attributes for the operational GNCOM, and two regional models nested within GNCOM covering the Gulf of Mexico and Caribbean regions. One model is a research and development NCOM-based regional-scale prediction system called IASNFS with atmospheric forcing by NOGAPS. The second was operationally implemented as a response to the 2010 DwH oil spill event, designated as AMSEAS with atmospheric forcing by COAMPS. See text and references for details on these models and their data assimilation schemes.

Tab.2 Summary of each evaluation effort including the models evaluated; general locations of the evaluation; time period of each particular evaluation; variables that were compared; time and space scales of interest; and the specific purpose of each study. NAVOCEANO evaluation was part of the Navys formal operational testing. The second was part of IOOS Coastal Ocean Modeling Testbed (COMT). A third effort was associated with the Gulf of Mexico 3-D Operational Ocean Forecast System Pilot Prediction Project (GOMEX-PPP). Both the Navy and COMT efforts focused on Navy needs in the realm of nowcasts and few-day forecasts of temperature and salinity structure at representative depth levels over the shelves and deeper waters of the Gulf; an additional component of the COMT evaluated the synoptic-scale surface wind products used to force the Navy forecasts. The GOMEX-PPP work considered the seasonal-time-scale needs and mesoscale structures that are especially applicable to the offshore energy industry, concentrating on the location and energetic currents of the Loop Current and its Loop Current eddies. The fourth evaluation, funded by BP, examines the efficacy of using hindcast AMSEAS for oil spill modeling using a Lagrangian particle tracker.

Fig.2 Comparison of sea-surface height anomaly (SSHA) in AVISO hindcast ((a), (d), (g) – derived from satellite altimetry), IASNFS nowcast ((b), (e), (h)), and AMSEAS nowcast ((c), (f), (i)), for three dates in 2010. The solid contour represents the 500-m isobath.

Fig.3 Comparison of sea-surface temperature (SST) in NAVO GHRSST analysis ((a), (d), (g) – derived from multiple satellite measurements), IASNFS nowcast ((b), (e), (h)), and AMSEAS nowcast ((c), (f), (i)), for three dates in 2010. The solid contour represents the 500-m isobath.

Fig.4 Sea Surface Height (SSH) on June 10 2010. Three estimates of SSH (anomaly with respect to average sea level west of 90°W) are shown together with along-track data from the JASON-1 and 2 satellite altimeters. The AVISO hindcast (a) is produced in delayed mode from multiple satellite altimeters using objective analysis. The IASNFS (b) and AMSEAS (c) fields are nowcasts valid at 12 UTC on the given date. Observed minus model residuals along the ascending (gray) and descending (black) ground tracks during the 10-day window from 5 June to 15 June 2010 are projected perpendicular to, and northward of, the corresponding ground tracks.

Tab.3 Validation (with observation numbers) of COAMPS winds versus all buoys, moored buoys, and C-MAN stations for COAMPS winds analyses, 12-h forecast fields, and 24-h forecasts fields in the northern Gulf of Mexico during a summer and winter period. The summer dataset is in the period 0000 UTC 20 June 2010 to 0000 UTC 10 July 2010. The winter dataset is in the period 0000 01 December 2010 to 0000 15 January 2011. Bias is computed as COAMPS minus buoy observations.

Fig.5 Example of vector correlation squared, scaling factor (a) and rotation angle (c) based on methodology of Hanson et al. (1992) for COAMPS wind initialization and forecast interpolated to buoy 42003 during the period 0000 UTC 20 June 2010 to 0000 UTC 10 July 2010. The dashed line corresponds to the maximum possible squared correlation of 1. Time series of absolute errors for wind speed (b) and direction (d) for COAMPS at buoy 42003.

Fig.6 Example of scatterplots for COAMPS wind initialization as well as 12- and 24-h forecasts for speed (upper) and direction (lower) interpolated to buoy 42003 during the same period as Fig. 5. Wind speed plots also include ovals representing one standard deviation of each dataset; circular plots indicate both the model and buoys have the same data ranges and elliptic plots indicate one dataset has less range than the other.

Fig.7 Example of a plot for daily analyses for COAMPS initialization for 0000 UTC 22 June 2010. Observed buoy vectors, color shaded by wind speed (a). COAMPS wind vectors color shaded by wind speed (b). Color coded wind direction differences at the buoy locations (c). As on lower left but with buoy station direction difference within a 40° wind direction tolerance level shaded grey (d).

Fig.8 Example of a plot for daily analyses for COAMPS initialization for 0000 UTC 22 June 2010. Observed buoy wind speeds, shaded by wind speed (a). Contours of COAMPS wind speed (b). Wind speed difference (c). Same as lower left with stations within the 2 m·s⁻¹ tolerance level shaded grey (d).

Fig.9 Location of mooring sites from which time series data were acquired from the NDBC website. Parameter(s) obtained from a given location are indicated in Table 4. All parameters are not available from all locations. Bottom topography obtained from the NOAA’s National Geophysical Data Center. Black dots represent station and buoy sites used in COAMPS evaluations. Black station numbers represent buoy overlap between COAMPS and oceanographic evaluations.

Tab.4 Moored sites accessed for assessment of AMSEAS model surface temperature and velocity. For each mooring, its NDBC ID and location are provided. The type of data obtained is indicated in the measurement column (T= Temperature, U, V= zonal, meridional velocity). Unless otherwise noted, the instrument depth is 1 m. The station caretaker and the sites water depth are provided.

Fig.10 Time series for the full AMSEAS-NDBC comparison period (June 2010 – October 2011) from two sites. The data shown are 1-m temperature at NDBC buoy site 42039 (a) and 1-m current speed at TABS site 42045 (b) for forecast day-1.

Fig.11 Scatter plots of model vs. data (AMSEAS vs. Mooring) for the March 2011 portion of the data shown in Fig. 10 at NDBC buoy 42039 for 1-m temperature (a) and at NDBC buoy 42045 for surface current speed (b). The one-one lines reveal the degree to which the modeled environment captures the natural system. The red ellipse on each plot represents the mean+/− one standard deviation around the mean value (center point of the ellipse) of the model (y-axis) and observations (x-axis). The tolerance limits, shown by the green lines, and used to determine the percentage of values above/below an acceptable linear error, are 0.5°C and 0.20 m·s⁻¹ for temperature and current speed, respectively. For these examples the mean and standard deviation of the model – data differences are (−0.32±0.53)°C for temperature and (0.039±0.13) m·s⁻¹ for current speed. The correlation coefficient, coefficient of determination and RMSD are 0.73, 0.54, 0.62 for temperature and 0.16, 0.026, 0.13 for current speed. These latter statistics are typically printed on the plots but omitted here for clarity.

Fig.12 Bar plot time series of 1-m temperature at NDBC buoy site 42039 showing the percentage of AMSEAS forecasts that are in the above/good/below tolerance bins for each month of all four forecast days over the full AMSEAS-NDBC buoy comparison period (June 2010 – October 2011). For forecast day-4, there is no June or July 2010 result since 4-day AMSEAS forecasts were not implemented until mid-July 2010. Green bars are within tolerance. Red bars are too high (model too warm); blue bars are too low (model too cold).

Fig.13 Time series showing the percentage of AMSEAS 1-m forecasts that are in the above, good, below tolerance bins for each month of forecast day-1 over the full AMSEAS-NDBC buoy comparison period (June 2010 – October 2011). Results are shown for all buoy sites listed in Table 4. Temperature tolerance limits set at ±0.5°C.

Fig.14 Time series showing the percentage of AMSEAS 1-m temperature forecasts that are in the above/good/below tolerance bins for each month of forecast day-4 over the full AMSEAS/buoy comparison period (August 2010 – October 2011). No comparisons are possible in June and July 2010 since the AMSEAS forecasts were not extended to 4 days until mid-July 2010. Results are shown for all buoy sites listed in Table 4. Temperature tolerance limits set at ±0.5°C.

Fig.15 Time series showing the percentage of AMSEAS 1-m temperature forecasts that are in the above/good/below tolerance bins for each month of forecast day-4 over the full AMSEAS/buoy comparison period (August 2010 – October 2011). No comparisons are possible in June and July 2010 since the AMSEAS forecasts were not extended to 4 days until mid-July 2010. Results are shown for all buoy sites listed in Table 4. Temperature tolerance limits set at ±0.5°C.

Fig.16 2010 Florida Current Transport: Observed (cable) and nowcast FC transport for IASNFS (left) and AMSEAS (right) indicates that the model transports are low by 4 to 5 Sv on average, but significantly larger error occurs during the June−September 2010 period. IASNFS and AMSEAS transports differ due to differences in atmospheric forcing, data assimilation, and other factors; although, the average transport and variability is similar in both models.

Fig.17 Shoreline Cleanup and Assessment Technique (SCAT) data as tallied from 15 May to 20 September 2010. Shoreline oil pollution categories include designations for light, moderate, and heavy oiling; light, moderate, and heavy tarballs; and negligible tarballs. Plots are shown for Eastern Biloxi Marsh (region 1), Lake Borgne/Rigolets (region 2), North End of Barataria Bay (region 3), and the beach locations of Grand Isle/Fourchon (region 4).

Fig.18 Snapshot images of the DwH oil spill simulation from 0000 UTC 20 June 2010 to 0000 UTC 10 July 2010 in five-day increments. Note the inshore incursion into the Mississippi Sound and Lake Borgne regions starting in late June. Concentrations are computed as the ratio of parcels near a grid point divided by the number of parcels originally released at each point. In this simulation, each point has 25 releases at initialization, and then each trajectory is modified by a random number to mimic dispersion. Hence, concentrations in these runs are a fraction of 25. Concentration fields are shown from 0–100%, scaled from 0 to 1.

Fig.19 Hydrometeorological Prediction Center (HPC) North American surface analysis for 0000 UTC 25 June 2010, 1200 UTC 30 June 2010, 1200 UTC 2 July 2010, and 0000 UTC 5 July 2010 (available at http://www.hpc.ncep.noaa.gov/html/sfc_archive.shtml). HPC is part of the NOAA/National Weather Service National Centers for Environmental Prediction.

Fig.20 Observed water level (blue) and predicted water AMSEAS water level (red) for Shell Beach CMAN station in Lake Borgne, LA, during 0000 UTC 15 June to 0000 UTC 15 July 2010 relative to NAVD88. Above average water elevation associated with Hurricane Alex and the non- tropical low pressure system are apparent on 29 June−1 July and 3–7 July, respectively.

Fig.21 Monthly count of observed temperature data at 0-, 10-, 100-, and 500-m depths. Note vertical scale is logarithmic. The 10-month means plotted at the right are reflected in Column 2 of Table 5.

Tab.5 Means of 10-month evaluation statistics for the Gulf of Mexico area of the AMSEAS NCOM for forecast day-1, for water temperature (°C) and salinity (psu).

Fig.22 Month-by-month mean model minus observed bias for temperature (a) and salinity (b) at the surface, 10-, 100-, and 500-m depths, for 24-h forecasts. Dashed lines represent tolerance goals of ±0.5°C for temperature and ±0.20 psu for salinity. The 10-month (June 2010 – March 2011) means at the right are reflected in Column 7 of Table 5.

Fig.23 Month-by-month mean temperature (a) and salinity (b) root mean square differences (RMSD) at the surface, 10-, 100-, and 500-m depths. Dashed lines represent tolerance goals of ±0.5°C for temperature and ±0.20 psu for salinity. The 10-month (June 2010 – March 2011) means at the right are reflected in Column 10 of Table 5.

Fig.24 Month-by-month mean percent within tolerance for temperature (a) and salinity (b) at the surface, 10-, 100-, and 500-m depths. The 10-month (June 2010 – March 2011) means at the right are reflected in Column 11 of Table 5. Tolerance goals are ±0.5°C for temperature and ±0.20 psu for salinity.

Tab.6 Mean 1-, 2-, and 3-day model skills based on comparative tolerance and root-mean-squared differences averaged over 10 months for temperature (°C) and salinity (psu).

Fig.25 Monthly means of percent within tolerance limits for 100-m temperature (a) and 100-m salinity (b) and RMSD for 100-m temperature (c) and 100-m salinity (d) for forecast days one (red), two (green) and three (blue). Tolerance limits are ±0.5°C for temperature and ±0.20 psu for salinity. The 10-month (June 2010 – March 2011) means are plotted at right on each plot.

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[2]	Zhibin SUN, Lie-Yauw OEY, Yi-Hui ZHOU. Skill-assessments of statistical and Ensemble Kalman Filter data assimilative analyses using surface and deep observations in the Gulf of Mexico[J]. Front Earth Sci, 2013, 7(3): 271-281.

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