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Skill assessment for an operational algal bloom forecast system - PubMed

  • ️Thu Jan 01 2009

Skill assessment for an operational algal bloom forecast system

Richard P Stumpf et al. J Mar Syst. 2009.

Abstract

An operational forecast system for harmful algal blooms (HABs) in southwest Florida is analyzed for forecasting skill. The HABs, caused by the toxic dinoflagellate, Karenia brevis, lead to shellfish toxicity and to respiratory irritation. In addition to predicting new blooms and their extent, HAB forecasts are made twice weekly during a bloom event, using a combination of satellite derived image products, wind predictions, and a rule-based model derived from previous observations and research. These forecasts include: identification, intensification, transport, extent, and impact; the latter being the most significant to the public. Identification involves identifying new blooms as HABs and is validated against an operational monitoring program involving water sampling. Intensification forecasts, which are much less frequently made, can only be evaluated with satellite data on mono-specific blooms. Extent and transport forecasts of HABs are also evaluated against the water samples. Due to the resolution of the forecasts and available validation data, skill cannot be resolved at scales finer than 30 km. Initially, respiratory irritation forecasts were analyzed using anecdotal information, the only available data, which had a bias toward major respiratory events leading to a forecast accuracy exceeding 90%. When a systematic program of twice-daily observations from lifeguards was implemented, the forecast could be meaningfully assessed. The results show that the forecasts identify the occurrence of respiratory events at all lifeguard beaches 70% of the time. However, a high rate (80%) of false positive forecasts occurred at any given beach. As the forecasts were made at half to whole county level, the resolution of the validation data was reduced to county level, reducing false positives to 22% (accuracy of 78%). The study indicates the importance of systematic sampling, even when using qualitative descriptors, the use of validation resolution to evaluate forecast capabilities, and the need to match forecast and validation resolutions.

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Figures

Fig. 1
Fig. 1

Map of the study area showing its location and the coastline from Pinellas County to Collier County, Florida, USA. Dashed lines show the extension of the county boundaries offshore, solid lines represent the boundaries for equidistant (61.4 km) segments along the coast (represented by solid black line). Circles represent the location of available K. brevis samples within 3 miles of the coast, from October 2004 to February 2007. These are coded dark or light to distinguish samples in adjacent equidistant segments. Inset shows the location of lifeguard beach stations.

Fig. 2
Fig. 2

SeaWiFS satellite image from November 21, 2004. Yellow areas indicate where the chlorophyll anomaly based on Stumpf et al. (2003) exceeded 1 µgL−1 cyan/green show anomalies between 0 and 1, blue indicates no positive anomaly. Red represents locations of K. brevis blooms based on the criteria listed in Table 1. The yellow areas failed the criteria in Table 1 and are not considered to be due to K. brevis.

Fig. 3
Fig. 3

Comparison of the number of cell counts samples per week to lifeguard reports by week from Sept. 2006 to March 2007. The lifeguard reports also show the distribution of impacts, both the Slight impacts and the combined Moderate and High impact reports.

Fig. 4
Fig. 4

Median number of cell count samples per week by segment and the equivalent resolution in km d−1 per sample for transport (or km per sample per day for extent). Results shown for 2005 and 2006, and segments identified in Fig. 1.

Fig. 5
Fig. 5

Distribution of octant wind directions as a function of time of day. Standard meteorological data from Venice Pier C-MAN Station (VENF1) from Sept. 2006 to March 2007.

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