The odds of foretelling rains: Why monsoon prediction is hard, and why it could soon improve
All current methods fail in predicting extreme events that cause droughts and floods, and predicting them is one of the real objectives of forecasting.
"During such experiments many scientists fall sick," says oceanographer and IISc professor PN Vinaychandran, who has done such trips before. "But they continue the measurements anyway."
Taking precise measurements underwater will help scientists understand the behaviour of the sea during the monsoon, and this understanding will eventually help develop better models to forecast the monsoon. Forecasting the Indian monsoon is difficult due to the complexity of the weather system. In fact, meteorologists consider the Indian monsoon to be the most complex weather system in the world.
Although scientists around the world study the monsoon, their research has not directly translated into accuracy of forecasts. But scientists think that forecasting accuracy will improve gradually, as new investments go into studying several aspects of the monsoon: collecting data from land and sea, understanding the impact of aerosols and clouds, improving models using this understanding, and using advanced technology for computing.
Chasing a breakthrough In the last decade, the India Meteorological Department (IMD), the country’s official weather forecaster, has been making improvements in their monsoon prediction, especially in the range and types of forecasts. IMD now gives three forecasts: a seasonal forecast, a short range forecast, and an (unofficial) medium-term (20 days) forecast. The official medium-term forecast is about to begin, and could make a big impact quickly.
"Farmers need two weeks to prepare for sowing," says M Rajeevan, secretary of the Ministry of Earth Sciences (MoES). "So the 20-day forecast will be a breakthrough."
IMD recently extended the short-range forecast to district levels, and is working on extending it further to block levels. It is a difficult exercise, and the department does not expect block-level forecasts to be operational before the year 2019. The scope of the seasonal forecasts has also been extended a decade ago, and they are now given for geographical regions separately.
However, in spite of all these improvements, the seasonal forecasts have not got more accurate over the last few decades. Many meteorologists are hoping that things will get better over the decade.
For IMD, the practice of giving a seasonal monsoon forecast is more than a century old. There were no computers in the 19th century, and no one even remotely understood the dynamics of the monsoon. So the forecasts were given based on just one parameter: Himalayan snow cover. Early in the twentieth century, Gilbert Walker, a British physicist with no experience in meteorology, came to India to head the IMD. Walker discovered the El Nino (warming of the Pacific), and developed a new statistical model to forecast the monsoon. This model was used for a long time, till IMD developed a new 16-parameter model in 1989.
But no matter what model was used, forecasts did not get better through the twentieth century when analysed over a period of time. They have begun to show improvements in recent years. "The models now give good results," says IISc professor and meteorologist Ravi Nanjundiah. "But all of them fail in predicting some extreme events." These extreme events cause droughts and floods, and predicting them is one of the real objectives of forecasting.
Now IMD is using a dynamical model along with a statistical model, and may soon switch completely to a dynamical model in the near future. A statistical model is based on parameters that are assumed to influence the monsoon. For example, increased Himalayan snow cover was seen to be associated with a strong monsoon, and El Nino was seen to influence the monsoon negatively. These correlations seem to match reality during some seasons and not match it during some other seasons.
For example, models show a strong negative influence of the El Nino on the monsoon, but in reality the influence is not always strong. Since statistics does not simulate reality, predictions were bound to go wrong. The Indian Institute of Tropical Meteorology (IITM ), a government-run research institution, has been working on developing dynamical models for some time, and IMD has been using it in recent times along with a statistical model. There are hints that forecast accuracy has improved by the combination.
A dynamical model simulates in the computer the actual conditions in the atmosphere that lead up to a monsoon season. Developing and using them involves understanding the physics of the monsoon well, developing mathematical equations that determine the behaviour of the atmosphere and the sea during the monsoon, measuring the initial conditions accurately over land and the sea, and making a computer calculate how these initial conditions evolve based on the equations.
In practice this is a hard task, and no dynamical model has been accurately able to predict all aspects of a monsoon season accurately. Scientists do not understand the physics well, data are hard to get, and simulating the evolution of a coupled ocean-atmosphere model is hard for the most powerful computers in the world so far. However, there have been improvements in all these aspects in recent times, and scientists expect more for some time.
Advances in computing power constitute the most immediate and noticeable improvement, and not just on seasonal forecast. For example, providing a short-range forecast at the block level requires data from each block level as well as enormous computing. Currently, the country has 800 observation stations; there is a programme to increase it to more than 6,000 over the next five years.
Data at this level of granularity would require a five-fold increase in computing power. IMD is increasing its computing resources from 1.2 petaflops to 10 petaflops by 2017, and this upgrade would have an immediate impact even with current data. An increase in computing power will improve medium-term and seasonal forecasts as well.
Medium-term forecasts are a new phenomenon for the country. The IITM has been using an atmosphere-ocean coupled model for providing an experimental 20-day forecast from the year 2001. Short-range forecasts are based only on the atmosphere. Coupled models are hard to simulate, but the accuracy and utility of the IITM forecasts were good enough for it to be taken over by the official forecaster from this year. "We found that this method is good for forecasting heat waves as well," says AK Sahai, IITM scientist. IMD used this model to provide forecasts for heat waves last year. It will start providing 20-day forecasts from next month.
Enter supercomputers Finally, the new supercomputers, made at an investment of Rs 400 crore, will impact the seasonal forecasts as well. IMD uses a statistical model, but also considers results from a dynamical model developed by IITM. The forecaster now wants to switch to a dynamic model in the next year or two, and a new supercomputer will make a difference here. Over the years, new experiments being performed on understanding the monsoon will make a difference as well.
The current Indo-UK programme is an example. The 8-million-pound project has scientists from the University of East Anglia, University of Reading, the Indian Institute of Science and the Indian Space Research Organisation, apart from expert support from a few more institutions. It has three components to study: the ocean, aerosols, and the land.
The aerosol experiments are being conducted over Bengaluru. The ocean experiments will start within a week. An extensive observation network has been established over land, and data from them will go into making models with better resolution. Together, these experiments are expected to generate enough data to improve our understanding of the monsoon.
The Indian Ocean plays an important role in the formation and behaviour of the monsoon, but it is not well understood as there are no data beyond a few hundred kilometers from the east coast of India. The current expedition, on the research ship Sindhu Sadhana, will use robots to gather data from below the surface.
Robots from the University of East Anglia have been used before in probing the Antarctic waters, and their inputs have helped scientists’ understanding of the south pole. Seven of them will dive deep into the ocean, and measure its temperature and salinity and other features.
In due course, data from the ship are expected to improve our understanding of the Indian Ocean and its impact on the monsoon, and this understanding will ultimately make its way to the coupled models. Similarly, the role of aerosols on the monsoon is poorly understood. Some scientists say aerosols improve the precipitation while others say they reduce precipitation.
The Indo-UK experiments could provide insights. In the long term, there is one aspect of the monsoon that is not understood at all: clouds. The monsoon is all about clouds. Its physics still has a long way to go.