Manual on sea level measurement and ... - unesdoc - Unesco

Sea Level Measurement and Interpretation6. Quality Control of DataData recovered from a tide gauge always provide timeserieswith a particular sampling interval. Even analoguecharts are digitized to provide levels at regular points intime. Until recently, most data acquired this way havebeen archived and distributed by data assembly centres(DACs) in a quality controlled (QC) and fully documentedform. This results in ‘delayed mode’ data sets. Volume 3and earlier editions of this <strong>Manual</strong> dwelt at length onQC of data in delayed mode. Such QC methods are wellestablished and will not be repeated here.However, sea level data are required for many purposes,and in many applications there is no time to perform afull QC. For example, during the World Ocean CirculationExperiment (WOCE), the University of Hawaii Sea-LevelCentre (UHSLC) was established as the ‘fast delivery’DAC, with the British Oceanographic Data Centre(BODC) as the ‘delayed mode’ WOCE DAC. The UHSLCwas tasked with the assembly, quality control and distributionof sea level data from WOCE gauges withinseveral weeks, comparable to the delay, at the time, inthe delivery of satellite altimeter data. Meanwhile, BODChad the task to assemble and supply sea level data fromthe WOCE network to the full extent of quality controlwithin 18–24 months from data collection.More recently, there has been an emphasis on makingas many GLOSS gauges as possible deliver datain nearreal time, i.e. typically within an hour. Thisrequirement has arisen for several reasons. First, withreal-time data, it is immediately obvious when problemswith a gauge have occurred. Second, the databecome available for many other applications within‘operational oceanography’, e.g. for flood warningor for assimilation of sea level data into oceancirculation models. The data are also then useful fortsunami warning systems in certain areas. The GLOSSprogramme has defined the UHSLC as the ‘GLOSSReal-Time Centre’ in addition to the existing ‘FastCentre’ responsible for producing hourly values formonitoring and models.If sea level data are used in near-real-time applications,then the operational system has to be robustenough not to be perturbed when bad data arerecorded (e.g. data spikes). One way to guard againstbad data is to have continuous human oversight ofthe data stream (e.g. as occurs in the UK StormTide Forecasting Service for flood warning). Realtimequality control (RTQC) software is now beingdeveloped by several groups. For example, in Europethe Spanish Ports Authority (Puertos del Estado) hasdeveloped an automatic quality control of sea leveldata for detection of spikes, gaps, etc. before datais displayed on the public web-page and assimilatedinto a storm surge forecasting system. Informationabout this software and the algorithms for spikedetection can be obtained from Begoña Pérez.42IOC <strong>Manual</strong>s and Guides No 14 vol IV