Pacific ENSO Update3rd Quarter, 2005 Vol. 11 No. 3 |
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NEW - Experimental Sea level Forecasts
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Tide Gauge Station | Jan | Feb | Mar |
Marianas, Guam | +9.4 (3.7) | +10.9 (3.9) | +12.0 (3.6) |
Saipan, CNMI | N/A(3.2) | N/A(2.9) | N/A(2.8) |
Malakal, R. Palau | -2.7 (4.6) | -.3 (4.6) | 0 (4.2) |
Yap, FSM | -1.7(3.9) | +3.9 (3.4) | +5.9 (4.1) |
Pohnpei, FSM | +4.5 (2.0) | +4.4 (2.4) | +4.4( 2.8) |
Kapingamar, FSM | +3.2 (3.0) | +1.4 (2.9) | +.2 (2.6) |
Majuro, Marshalls | +2.0 (2.0) | +3.0 (2.0) | +.7 (2.1) |
Kwajalein, Marshalls | +3.9 (2.0) | +5.7 (2.5) | +3.8 (2.2) |
Pago-Pago, A Samoa | -1.6 (3.6) | +0.0 (4.2) | +2.1 (3.6) |
Note: - indicate negative deviations (fall of sea-level from the mean), and + indicate positive deviations (rise of sea-level from the mean), n/a: data not available, Figures in parenthesis are year-to-year SD (standard deviations) for the month. For the forecasted values of sea level deviations, please refer to our previous issue of this newsletter (2 nd Quarter 2005, Vol. 11, No. 2). |
In the 1st quarter (JFM) of 2005, the average sea level deviations in most of the northwestern Pacific Island stations displayed negative deviations, the 2nd quarter provides a tendency towards enhanced positive deviations (Table 1; Fig. 3). This agrees with the AMJ forecast in the last newsletter (Fig. 3 dotted line). Both the low latitude station (Kapingamarangi) and the central Pacific Island stations ( Kwajalein and Majuro) continued to show rising trends in this quarter. On the contrary, the South Pacific Island station ( Pago Pago ), which displayed negative deviation in the last quarter, tended to show a positive deviation in this quarter. This is somewhat expected pattern for American Samoa . Following a weak El Niño year, American Samoa has been found not to experience any pronounced variation in sea level from July to December (see Pacific ENSO Update, 4th Quarter 2004, Vol. 10, No. 4).
Seasonal Sea Level Forecast for JAS, ASO, and SON, 2005
Forecasts of the sea level anomalies in the USAPI are presented here using CCA statistical model. Based on the independent SST values in JFM 2005, the resulting CCA model was used to forecast the sea level of moving-average season of three consecutive months: Jul-Aug-Sep (JAS), Aug-Sep-Oct (ASO), and Oct-Nov-Dec (OND) (Table 2). 1-season ahead of CCA cross-validation forecast skills (cross-validation is conducted to evaluate the overall forecasting skill of the CCA model) are also presented (Fig. 4). A short summary of qualitative forecast quality is presented (Table 2).
Table 2 : Forecasts of sea level deviation in inches (JAS: Jul-Aug-Sep, ASO: Aug-Sep-Oct, and SON: Sep-Oct-Nov )
Tide Gauge Station | JAS | ASO | SON | *Forcst. quality | * Forecast quality is a measure of the expected CCA cross-validation skill. In general terms, these kinds of forecasts are thought to be of useful skill (or at least fair skill) if the CCA cross-validation value is greater than 0.3 (Fig.4). Higher skills correspond to greater expected accuracy of the forecasts. Skill levels greater than 0.5 are thought to be good, while skill levels greater than 0.6 are thought to be high. |
Guam | +4 | +3 | +2 | Good | |
Saipan | +3 | +3 | * | Fair | |
Malakal | +5 | +5 | +4 | Good | |
Yap | +5 | +4 | +3 | Good | |
Pohnpei | +2 | +2 | +3 | High | |
Kapingamari | * | * | +2 | Moderate | |
Majuro | +1 | +2 | +3 | Moderate | |
Kwajalein | +2 | +2 | +2 | Moderate | |
Pago Pago | * | +1 | +1 | Good | |
Note: For +/-, see notes in Table 1. Any deviations between (0~ ±1) inch is considered as negligible and denoted by * |
From Table 2, it has been found that forecast skill for most of the tide gauge stations varies from moderate-to-good. Pohnpei provided high skill while CNMI at Saipan displayed fair skills (Fig. 3). Other than CNMI, the cross-validation correlation skills for the 3-moving seasons (at 1-season lead time) are reasonably well predicted with a mean skill greater than 0.40 for all the tide gauge stations.
The sea level forecast in JAS, which is based on spring SSTs (AMJ), is slightly less skillful than previous seasons. Climatologists refer to this period as the spring barrier because of the difficulty in predicting SST during the spring. As the year advances, the skill gradually increases until the next spring. For rainfall prediction, this spring barrier has a pronounced effect; however it appears to be a relativily weaker obstacle for SST based sea level predictions. As a result this season has slightly weaker yet still useful skill values for the upcoming seasons (Fig 3).