Actualização:
4 times per day, from 00:00, 06:00, 12:00 and 18:00 UTC
Disclaimer:
ECMWF does not accept any liability whatsoever for any error or omission in the data, their availability, or for any loss or damage arising from their use.
SST:
A daily, high-resolution, real-time, global, sea surface temperature (RTG_SST) analysis has been developed at the National Centers for Environmental Prediction/Marine Modeling and Analysis Branch (NCEP / MMAB). The analysis was implemented in the NCEP parallel production suite 16 August 2005. It became fully operational on September 27, 2005.
The daily sea surface temperature product is produced on a twelfth-degree (latitude, longitude) grid, with a two-dimensional variational interpolation analysis of the most recent 24-hours buoy and ship data, satellite-retrieved SST data, and SST's derived from satellite-observed sea-ice coverage. The algorithm employs the following data-handling and analysis techniques:
Satellite retrieved SST values are averaged within 1/12 o grid boxes with day and night 'superobs' created separately for each satellite;
Bias calculation and removal, for satellite retrieved SST, is the technique employed in the 7-day Reynolds-Smith climatological analysis;
Currently, the satellite SST retrievals are generated by a physically-based algorithm from the Joint Center for Satellite Data Assimilation. Retrievals are from NOAA-17 and NOAA-18 AVHRR data;
SST reports from individual ships and buoys are separately averaged within grid boxes;
The first-guess is the prior (un-smoothed) analysis with one-day's climate adjustment added;
Late-arriving data which did not make it into the previous SST analysis are accepted if they are less than 36 hours old;
Surface temperature is calculated for water where the ice cover exceeds 50%, using salinity climatology in Millero's formula for the freezing point of salt water:
t(S) = -0.0575 S + 0.0017 S3/2 - 0.0002 S2,
with S in psu.
An inhomogeneous correlation-scale-parameter l, for the correlation function: exp(-d2/l2) , is calculated from a climatological temperature gradient, as
l = min ( 450 , max( 2.25 / |grad T| , 100 )),
with d and l in kilometers. "grad T" is in oC / km
Evaluations of the analysis products have shown it to produce realistically tight gradients in the Gulf Stream regions of the Atlantic and the Kuroshio region of the Pacific, and to be in close agreement with SST reports from moored buoys in both oceans. Also, it has been shown to properly depict the wintertime colder shelf water -- a feature critical in getting an accurate model prediction for coastal winter storms.
NWP:
A previsão numérica do tempo usa o estado instantâneo da atmosfera como dados de entrada para modelos matemáticos da atmosfera, com vista à previsão do estado do tempo.
Apesar dos primeiros esforços para conseguir prever o tempo tivessem sido dados na década de 1920, foi apenas com o advento da era dos computadores que foi possível realizá-lo em tempo real. A manipulação de grandes conjuntos de dados e a realização de cálculos complexos para o conseguir com uma resolução suficientemente elevada para produzir resultados úteis requer o uso dos supercomputadores mais potentes do mundo. Um conjunto de modelos de previsão, quer à escala global quer à escala regional, são executados para criar previsões do tempo nacionais. O uso de previsões com modelos semelhantes ("model ensembles") ajuda a definir a incerteza da previsão e estender a previsão do tempo bastante mais no futuro, o que não seria possível conseguir de outro modo.
Contribuidores da Wikipédia, "Previsão numérica do tempo," Wikipédia, a enciclopédia livre,
http://pt.wikipedia.org/w/index.php?title=Previs%C3%A3o_num%C3%A9rica_do_tempo&oldid=17351675 (accessed fevereiro 9, 2010).