Implementation and Updating of Drift Forecasts (Simulation, Andlinkage of Monitoring and Simulation)

7/31/2019 Implementation and Updating of Drift Forecasts (Simulation, Andlinkage of Monitoring and Simulation)

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3.Implementation and updating of drift forecasts (simulation, andlinkage of monitoring and simulation)

3.1Eddy resolving resolution short-term forecastingAt first, the SEA-GEARN was run from March 12 to April 10 using the ocean currents

reproduced by MOVE-WNP and the winds by JCDAS. About 400,000 particles were released

from points off Aomori, Iwate, Miyagi, Fukushima and Ibaraki Prefectures during March. Three

kinds of prediction were then conducted from April 2011 to December 2011 making use of

independent ocean current and wind data as follows:

(1) ocean currents calculated by MOVE-NP and winds by JCDAS,

(2) ocean currents and winds by K7 and

(3) ocean currents calculated by MOVE-NP and winds by K7.

The particle trajectory experiment with ocean currents provided by MOVE-WNP and winds by

JCDAS shows that debris dispersal making up the debris fields to the east or southeast of Honshu

Island was greatly affected by the Kuroshio Current (Fig. 3.1.1). Three separate experiments

suggest that most of the debris was carried farther offshore during 2011, although the rate of

spreading is different among the three experiments (Fig. 3.1.2). It is possible that a part of the

debris field approached the coastal zone surrounding Japan along the path of the Kuroshio

Current.


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Fig. 3.1.1: Positions of marine debris on April 10, 2011 calculated by MOVE-WNP with JCDAS.


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Fig. 3.1.2: Positions of marine debris on December 15, 2011 calculated by MOVE-NP with JCDAS (upper panel), K7

(middle panel) and MOVE-NP with K7 wind (lower panel). Light gray shows a low concentration of marine

debris while dark gray shows a high concentration of marine debris.


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3.2Coupled atmosphere-ocean long-term forecastingA simulation in cases of 3 debris types (listed in Table 3.2) was conducted with the following 3 stages; first, particle diffusion is calculated by

MOVE-WNP with JCDAS data of currents and winds for the period immediately after the earthquake until 10 April 2011; second, adopting the

simulated particle distribution on 10 April 2011 as initial conditions, particle diffusion is calculated by MOVE-WP with JCDAS data of currents and

winds for 10 December 2011; third, adopting the simulated particle distribution on 10 December 2011 as initial conditions, drift forecast on the

atmosphere-ocean coupled fields was calculated by K7 (Fig. 3.2.1 (a) to (e)). Parameters in the model used for this calculation are optimized in

comparison with ship-visual information collected by Secretariat of Headquarters for Ocean Policy.

Subsurface type

(Specific gravity =1.0)

Lumber type


Float type


Most part is under water.

driftwood s, waterlogged lumbers, etc.

Less effect from westerlies

Nearly half is under water.

Lumbers derived from broken houses, flooded

vessels, etc.

A third is under water.Floats or buoys for fishery farm or fixed-netfisheries, unbroken floating vessels, etc.

Large effect from westerlies.

Table 3.2 Debris types classified for drift forecast.
http://ejje.weblio.jp/content/fixed-nethttp://ejje.weblio.jp/content/fisherieshttp://ejje.weblio.jp/content/fisherieshttp://ejje.weblio.jp/content/fixed-net


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Subsurface type Lumber type Float type

Dec. 2011

Feb. 2012

Fig. 3.2.1(a) Debris drift prediction for the 3 types. Gray scale refers to (particle number in 100 km x 100 km grid) / (total particle number) 100 (%)


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Apr. 2012

Jun. 2012

Fig. 3.2.1(b) Debris drift prediction for the 3 types. Gray scale refers to (particle number in 100 km x 100 km grid) / (total particle number) 100 (%)


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Aug. 2012

Oct. 2012

Fig. 3.2.1(c) Debris drift prediction for the 3 types. Gray scale refers to (particle number in 100 km x 100 km grid) / (total particle number) 100 (%)


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Dec. 2012

Feb. 2013

Fig. 3.2.1(d) Debris drift prediction for the 3 types. Gray scale refers to (particle number in 100 km x 100 km grid) / (total particle number) 100 (%)


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Apr. 2013

Jun. 2013

Fig. 3.2.1(e) Debris drift prediction for the 3 types. Gray scale refers to (particle number in 100 km x 100 km grid) / (total particle number) 100 (%)


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In this project, the atmospheric and oceanic fields were predicted up to 6 years ahead (to Sep, 2017)

with initial conditions set by assimilating data covering July to Sep, 2011. The prediction results for

sea-surface currents and sea-surface winds are shown in Fig 3.2.2.

Fig. 3.2.2 Predicted sea-surface currents (cm/s) and sea-surface winds for Dec., 2016

At the meeting with IPRC scientists on 10 Feb, 2012, it was pointed out that the California Current

has non-negligible inter-annual variations. Hence, in order to predict the locations at which debris

comes ashore, it is important for the model to have the capability to predict the inter-annual


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variability of the ocean currents. It was confirmed that the above-mentioned 6-year prediction of

ocean and atmosphere fields does not contradict existing knowledge, and it was confirmed that our

prediction model was suitable for predictions of more than 2 years in advance.

3.3 Repeat execution of simulation and monitoring

Before executing the above-mentioned prediction, the simulation method was optimized by

repeated simulation runs made under various conditions and by comparison with other

simulation results, visual information from vessels (4.1) and satellite observation (4.2).

(1) Observation results of outflow range and stagnation phenomena-near coasts, as obtainedfrom Daichi and foreign satellites, were reflected in the methods by which particles were

discharged.

(2) From experiments in which optimization of the diffusion factors was performed for eachregion in which the particle diffusion simulation was executed, it was found that the

Kuroshio Current extension was more influential than the eddy-diffusion terms. Therefore,

variations in the diffusion terms for each region were reflected by the following method:

when the majority of particles were present in the Kuroshio Current extension, particle

diffusion simulation was executed on the field obtained from the eddy-resolving model,

MOVE-WNP and MOVE-NP, whereas after these particles escaped from the Kuroshio

Current extension, particle diffusion simulation was executed with the coupled 4D-VAR

model, K7.

3.4 Automatization of data input and pre-processing of the data

assimilation system

To reduce the workload required to maintain the above prediction process on a regular

three-monthly basis after the 2012 fiscal year, automatization of updated-data input and

pre-processing (including quick QC for the data assimilation system) has been established within

this project.

The input data are the PREPBUFR dataset of NOAA/NCEP for atmosphere observation (wind

velocity vectors at designated altitude, temperature and humidity), DMSP satellites SSM/I

sea-surface wind together with wind directions from the NCEP/NCAR re-analysis data and

sea-surface temperature from OISST version2 ocean observations.

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Implementation and Updating of Drift Forecasts (Simulation, Andlinkage of Monitoring and Simulation)