  Long-range forecasting of heat/cold waves is a topical issue nowadays. High
computational complexity of the design of numerical and statistical models is a
bottleneck for the forecast process. In this work, Windows Server 2012 R2
virtual machines are used as a high-performance tool for the speed-up of the
computational process. Six D-series and one standard tier A-series virtual
machines were hosted in Microsoft Azure public cloud for this purpose.
Visualization of the forecasted data is based on the Google Earth Pro virtual
globe in ASP.NET web-site against http://gearth.azurewebsites.net (prototype),
where KMZ file represents geographic placemarks. The long-range predictions of
the heat/cold waves are computed for several specifically located places based
on nonanticipative analog algorithm. The arguments of forecast models are
datasets from around the world, which reflects the concept of teleconnections.
This methodology does not require the probability distribution to design the
forecast models and/or calculate the predictions. Heat weaves at Annaba
(Algeria) are discussed in detail. Up to 36.4% of heat waves are specifically
predicted. Up to 33.3% of cold waves are specifically predicted for other four
locations around the world. The proposed approach is 100% accurate if the signs
of predicted and actual values are compared according to climatological
baseline. These high-accuracy predictions were achieved due to the
interdisciplinary approach, but advanced computer science techniques, public
cloud computing and Google Earth Pro virtual globe mainly, form the major part
of the work.
