{"id":11637,"date":"2024-04-16T10:00:00","date_gmt":"2024-04-16T10:00:00","guid":{"rendered":"https:\/\/modernsciences.org\/staging\/4414\/?p=11637"},"modified":"2024-04-12T04:32:24","modified_gmt":"2024-04-12T04:32:24","slug":"despite-what-you-might-hear-weather-prediction-is-getting-better-not-worse","status":"publish","type":"post","link":"https:\/\/modernsciences.org\/staging\/4414\/despite-what-you-might-hear-weather-prediction-is-getting-better-not-worse\/","title":{"rendered":"Despite what you might hear, weather prediction is getting better, not\u00a0worse"},"content":{"rendered":"\nAndrew King<\/a>, The University of Melbourne<\/a><\/em>; Kimberley Reid<\/a>, Monash University<\/a><\/em>; Michael Barnes<\/a>, Monash University<\/a><\/em>, and Nick Earl-Jones<\/a>, University of Tasmania<\/a><\/em><\/span>\n\n

Australia\u2019s weather bureau copped harsh criticism<\/a> after El Ni\u00f1o failed to deliver a much-vaunted dry summer in eastern Australia. Parts of northern Queensland in the path of Tropical Cyclone Jasper had a record wet December and areas of central Victoria had a record wet January. Overall, the summer was 19% wetter than average for Australia as a whole<\/a>.<\/p>\n\n

This led to debate<\/a> in the media and during senate estimates around the Bureau of Meteorology\u2019s ability to make accurate predictions as the climate changes. The value of seasonal forecasting in particular has been called into question. <\/p>\n\n

Weather prediction has actually improved in recent years. And there are exciting developments on the horizon<\/a> involving artificial intelligence. But the effect of future climate change on weather and seasonal prediction is not yet well understood. <\/p>\n\n

As climate scientists, we know 7\u201314-day forecasts and seasonal predictions stack up pretty well when it comes to the crunch. That\u2019s because agencies such as the Bureau check the success of their forecasts against reality<\/a> and make this information public. While it\u2019s possible climate change may pose challenges to weather and seasonal prediction in some regions, we believe improvements in forecasting far exceed any losses in accuracy.<\/p>\n\n\n\n

Advances in prediction<\/h2>\n\n

Ever since the UK physicist Lewis Fry Richardson<\/a> first envisaged the possibility in a 1922 book<\/a>, weather forecasting has been growing more accurate and powerful. <\/p>\n\n

The science of meteorology took a great leap forward with the boom in computing capability.<\/p>\n\n

Now, highly detailed satellite data and weather observations feed into multiple computer simulations. This makes 7-day forecasts pretty accurate<\/a> across the globe, although less so in poorer areas of the world. <\/p>\n\n

\n \"satellite<\/a>\n
\n Satellite data allows us to observe the weather far better than in the past. This image was captured by the Japanese Himawari-8 satellite on March 18, 2024.<\/span>\n The Bureau of Meteorology<\/span><\/span>\n <\/figcaption>\n <\/figure>\n\n

As we can never know the state of the atmosphere perfectly at any given time, it is beneficial to run many simulations<\/a> with slightly different starting conditions. This gives an idea of how the weather may change and how much confidence we have in those changes. <\/p>\n\n

The same principles that govern weather forecasting also support seasonal climate forecasting. Models representing the atmosphere and ocean are cast forward in time to give a three-month outlook.<\/p>\n\n

Beyond about ten days we\u2019re not able to say with certainty what the weather will be like for a precise location at a specific time. But we can give an indication of the chances the weather will be significantly hotter, cooler, drier or wetter than the seasonal average.<\/p>\n\n

Our ability to predict conditions over the coming season has greatly advanced in just the past 20 years. We now better understand how the various climate drivers influence our weather, and we have more computational power to run models. <\/p>\n\n

However model-based seasonal forecasting \u2013 providing location-specific guidance on likely rainfall and temperature compared to the long-term average for months at a time \u2013 is still relatively new. It has further to go to provide reliable, usable information to decision-makers. <\/p>\n\n

How do we measure how good a forecast is?<\/h2>\n\n

Meteorologists know whether their forecasts were right or wrong after the fact, because agencies such as the Bureau of Meteorology have entire teams dedicated to comparing their forecasts with what actually happened<\/a>.<\/p>\n\n