pfctdayelise + weatherforecasts   30

Ninjo Workstation: NinJo Workstation
The NinJo Workstation Software is an ultramodern meteorological workstation system
software  visualisation  weatherforecasts 
july 2013 by pfctdayelise
Old Weather - Our Weather's Past, the Climate's Future

Help scientists recover worldwide weather observations made by Royal Navy ships around the time of World War I. These transcriptions will contribute to climate model projections and improve a database of weather extremes. Historians will use your work to track past ship movements and the stories of the people on board.
weatherforecasts  science  data  history 
september 2011 by pfctdayelise
Model Spectrum
Great graphics!

One plot combining the NWS forecast with the output from multiple weather models.
weatherforecasts  flot  graphs 
august 2010 by pfctdayelise
My Own Hat: OSDC liveblogging: Natural language generation in weather forecasting
Yesterday, I was unwell so I didn't keep up with my presentation blogging. Here is my presentation on Natural language generation in weather forecasting.
NLG  BoM  GFE  weatherforecasts 
march 2010 by pfctdayelise
Standing Committee on Industry, Science and Innovation: Inquiry into long-term meteorological forecasting in Australia: report
On Monday, 23 November 2009, the Standing Committee on Industry, Science and Innovation tabled its report for the Inquiry into long-term meteorological forecasting in Australia, entitled: Seasonal forecasting in Australia.
weatherforecasts  australia  government 
january 2010 by pfctdayelise
Weather forecasting is evolving in a world characterized by accelerating scientific and technological change. This scientific and technological change has led to some confusion and concern about the role of humans in forecasting the weather. Therefore, this essay tries to find the proper perspective for understanding how humans contribute value to the prediction process.

Scientific weather forecasting proceeds by combining a diagnosis of the atmosphere's current state with a prognosis. It is argued that the diagnostic step involves both quantitative and qualitative knowledge of the meteorology, if the maximum possible understanding is to be gained. Since machines do not have access to qualitative information, they cannot provide as complete a diagnosis as humans. Further, in humans, the diagnostic and prognostic steps are blurred, allowing qualitative knowledge to influence the forecast as well.
december 2009 by pfctdayelise

Copy this bookmark: