Combining a Weather Forecast with a Stochastic Weather Generator

Posted by Jason Lillywhite

A couple of years ago, I blogged about the application of the GoldSim WGEN model for producing probabilistic time histories of precipitation and temperature data. WGEN is useful for modeling natural systems impacted by uncertain climate influences. This model can also be used for simulating future scenarios and forecasting.

Even though the results of a WGEN model are probabilistic and uncertain, they are based on historical observed records and tied to the latitude of the earth. This allows us to produce realistic future simulations. But if you plan to use WGEN for short-term forecasting (less than 6 months), it might be helpful to incorporate a weather forecast for the first part of the simulation. Read more to see how a web service forecast model is combined with WGEN to produce a more reasonable forecast for a specific location without having to manually download the forecast.

Building Blocks in GoldSim

Posted by Jason Lillywhite

One of the many strengths of GoldSim is its graphically enhanced user interface, which allows you to quickly build your model from reusable components. During a recent webinar, I built a reservoir operations model that receives water from a snowmelt driven watershed using 6 existing models found in our Model Library. Once I understood what my modeling requirements were, I was able to quickly compile a probabilistic system model that is powerful in demonstrating how to operate a dam that services changing water demands and climate scenarios, which protects against downstream flooding.

Applying the GoldSim WGEN Model to Generate Stochastic Weather Data

Posted by Jason Lillywhite

Now you can let GoldSim do all the heavy lifting for you when simulating weather for your next project. A new GoldSim model example in our library lets you quickly generate the input data required to run the WGEN model, which is a stochastic weather generator built in GoldSim that creates daily stochastic time series of precipitation, temperature, and solar radiation.

This model (called WGENprep) uses time series data to automatically generate the input file you need to run WGEN. The WGEN model requires a lot of statistical information in order to run it and it can be quite a project to develop these inputs. With WGENprep, you can simply input the time series, change the simulation start and end time to correspond to the time series and the model will automatically export all the WGEN input data to an Excel spreadsheet. All you have to do is start up the WGEN model and then copy and paste the data from Excel right into the WGEN dashboard. These models were recently put to the test using some observed historical time series data gathered from the Salt Lake City airport weather station, provided by the NOAA National Centers for Environmental Information website.