Source: NIWA – National Institute of Water and Atmospheric Research
The raw data is pulled down onto NIWA’s high-performance computer from NOAA every day. It is at a 50km resolution and a 31-member ensemble, which means that data is drawn from 31 different instances of the model.
This supplies 31 different scenarios for the forecast. When these scenarios agree, forecast confidence is generally higher, and when they diverge you’ve got lower confidence.
“Our initial review of model skill during summer 2021–22 showed that it picked up the extreme dryness that developed over New Zealand during January,” says Rampal.
As well as extending out to 35-day forecasts, NIWA35 projects conditions at a much higher resolution. It scales the ‘coarse’, global 50km input grid down to a 5km radius over New Zealand. This resolves the country’s complex topography far more effectively.
“It’s challenging to make decisions from something coarse and 50km is not representative of the wide diversity of our terrain in New Zealand,” says Rampal.
This is where data science and the power of deep learning really comes into play. Drawing on convolutional neural networks (CNN) to extract information, the model can extract far more complex relationships than principal component analysis.
“It’s different from dynamical downscaling because we’re not using physics. We’re trying to learn physics from what’s happened in the past,” says Rampal.
“It enables us to look at what’s happened in the past and fill in the gaps.”
This allows for judgements to be made over a smaller area and forecast down to a 5km radius, with the prospect of getting resolutions as low as a 1km radius.
Downscaling has been done before in the forecasting space, but deep learning adds speed of process. “We’re talking at least 1,000 times faster,” says Rampal.
In his media release earlier this year announcing MPI was partnering with NIWA to develop better drought forecasting systems, Agriculture Minister Damien O’Connor said the joint project was important to help farmers and growers get their businesses ready for future climate conditions.
“Knowing well in advance when dry conditions are heading your way means you can cut your cloth accordingly at critical times on-farm.”
“Improved forecasting will alleviate some of the financial and mental burden that drought puts on farmers and growers.”
“It will also make our primary industries more resilient, productive and sustainable.”
Over in Hawke’s Bay, Louis Beamish will welcome anything that helps landowners to be more proactive and manage their risk during those dry summer months.
“Any information on an extended forecast is useful,” he says.
For farmers like Reymer, NIWA35 would bring confidence about the length of the bridge.
“I could completely change my plan – forward contract palm kernel and silage, wean the calves in December, de-stock early, a number of things.”
He says during the summer of 2020, rain seemed to be predicted every week – but it didn’t turn up.
“We could see rain coming out of the tropics, but it kept getting pushed off. We need to know if the weather system is going to hit.”
And five kilometres changes so much. “We’re close to Mount Pirongia. They can get great rain and we still get none.
“Weather is the number one thing on your mind all of the time,” says Reymer.
This story forms part of Water and Atmosphere – December 2022, read more stories from this series.
