IMD’s monsoon heavy rain forecast accuracy has improved to 70% in three years

IMD and other teams from the MoES are working on the second phase of the monsoon mission that is focusing on extreme weather events and development of applications for various sectors

All four measures of weather forecast accuracy used to predict monsoon by India Meteorological Department (IMD) have shown a marked improvement over the past three years, while the probability of detection (POD) to forecast heavy rainfall has made significant progress, said M Rajeevan, secretary, Union Ministry of Earth Sciences (MoES) at an Indian Meteorological Society lecture on Wednesday.

Apart from an overall improvement in forecast reliability, IMD’s monsoon mission coupled forecast model has ensured that the authorities are able to make a short-range prediction of rain and associated weather for five days at present instead of three days, when the initiative was launched in 2012. (Sonu Mehta/HT PHoto)

POD accuracy went up from 45% from 2002-16 to 70% in 2017-19, the MoES secretary cited to buttress the IMD’s feat.

The National Oceanic and Atmospheric Administration describes POD to be the number of hits in forecast divided by the total number of events observed.

Similarly, the false alarm rate (FAR) has reduced from 42% to 32% over the corresponding period for heavy rain episodes during monsoon season.

Apart from an overall improvement in forecast reliability, IMD’s monsoon mission coupled forecast model has ensured that the authorities are able to make a short-range prediction of rain and associated weather for five days at present instead of three days, when the initiative was launched in 2012.

“We can forecast with the same accuracy, but for five days now, as far as the short-range forecast for monsoon season is concerned,” Rajeevan said during the virtual lecture, which was attended by scientists from across the country amid the raging coronavirus disease (Covid-19) outbreak.

The first phase of the monsoon mission was completed in 2017.

IMD and other teams from the MoES are working on the second phase of the monsoon mission that is focusing on extreme weather events and development of applications for various sectors such as renewable energy (solar and wind energy projects require accurate forecast); agriculture and hydrology.

MoES is working on topical issues and emerging problems of the future.

For example, Rajeevan said IMD has already developed a percentile-based forecast of extreme weather.

The 90th and 95th percentile forecast of rain (10% chance that rain will be higher than that) and wind provide a five-day lead time for a forecast.

Similarly, IMD is coming out with 550 new automatic weather stations for agromet services and state-of-the-art sensors for soil moisture and soil temperature detection. “These can help us understand landslides and help immensely with forecasts,” he added.

IMD has recently started impact-based forecasts. “I remember the 2013 Uttarakhand floods. We did forecast very heavy rain. But what does it mean for the common man? What action should he take when he has heavy or extremely heavy rain warning? The impact-based warning takes into account all these factors,” added Rajeevan.

The MoES secretary, however, conceded that though the 25 June lightning events in Bihar were predicted by the IMD and the Indian Institute of Tropical Meteorology (IITM) authorities, several people still died because of the natural disaster.

Independent experts, who spoke off the record, maintained that more long-term data is needed to measure improvements in making accurate predictions.

“These three years are not sufficient enough to judge improvement in forecast skill. There is a method called hindcast verification. Where you run the current model for earlier years and generate the skill score ...,” said a climate scientist on condition of anonymity.

But climate change is increasingly making a prediction of extreme rain and seasonal forecasts a difficult proposition.

In an article, co-authored by Rajeevan, published in Nature journal in 2015, titled: “Rethinking Indian monsoon rainfall prediction in the context of recent global warming,” the authors had said: “Despite enormous progress having been made in predicting ISMR (Indian summer monsoon rainfall) since 1886, the operational forecasts during recent decades (1989–2012) have little skill. Here we show, with both dynamical and physical–empirical models, that this recent failure is largely due to the models’ inability to capture new predictability sources emerging during recent global warming.”

Rajeevan responded to HT’s query on the challenges in seasonal predictions due to climate change. “Some extreme rain events pull up or down the average leading to deviation from the seasonal forecast. We have seen it happening,” the MoES secretary said.