IRI@AGU: Subseasonal Forecasting for the Indian Monsoon
Climate scientist Nachiketa Acharya is at the center of IRI’s efforts to develop a new seasonal forecasting system. He focuses on improving the skill and usability of climate forecasts for users in agriculture, water management and other sectors. Acharya is also actively involved in improving forecasting at the subseasonal scale. Recently, he and other IRI colleagues collaborated with the India Meteorology Department to implement real-time subseasonal forecasting in the northern state of Bihar. A new paper describes the experimental system and how it performed. Acharya will be also presenting this and other work at the AGU 2019 meeting. We delve into details in the Q&A below.
These experimental subseasonal forecasts focused on the 2018 monsoon in Bihar. Why the monsoon season and why Bihar?
Bihar, located in northern India bordering Nepal, is one of the most climate-sensitive states in the country due to its geographical setting, hydrometeorological uncertainties, dense rural population and high level of poverty. The Himalayan Mountains in the north have a significant bearing on the distribution of monsoon rainfall. The state is divided into four agroclimatic zones, with two zones north of the Ganges River prone to floods while the southern two zones are exposed to droughts.
Agriculture is the backbone of Bihar’s economy. It accounts for nearly a fifth of the state’s gross domestic product and provides employment to about 70% of the work force in rural areas–much higher than the national average.
Both irrigated and non-irrigated agriculture in Bihar is crucially dependent on rains that full during the monsoon, which account for 84% of Bihar’s total annual rainfall.
There are three crop seasons in Bihar: Kharif, Rabi and Zaid. The Kharif season is generally from June to September. Crops are usually sown at the beginning of the monsoon season around June and harvested by September or October. Onset of the monsoon toward the end of June or early July generally provides enough water for the rice, the main Kharif crop. Any aberration in rainfall during this period affects the prospect of good yield, so this motivated our concerted effort to study the potential usefulness of disseminating subseasonal forecast information to the rural commuintes of Bihar to improve climate resilience in agriculture.
For our case study, we included both the flood-prone northern districts of Darbhanga and East Champaran as well as the drought-prone southern districts, Nawada and Jehanabad.
The work was part of the International Research and Applications Project (IRAP), a joint effort led by researchers at IRI and the University of Arizona and funded by the National Oceanic and Atmospheric Administration.
What kind of information did the forecasts provide and how far in advance?
We provided subseasonal-to-seasonal rainfall forecasts throughout the 2018 Indian summer monsoon season. Two-week subseasonal forecasts were generated in real time every Thursday from June 7 to September 27, making 17 weekly issuances in all. We restricted the forecast lead time to about two weeks in advance because we found a lack of forecast strength and skill at longer lead times. The forecast maps were discussed each week with IMD, and displayed through a virtual maproom. A text summary was sent to Bihar’s State Agricultural Universities, which then forwarded them via a nongovernmental organization to disseminate to farmers.
What’s unique about this collaboration with the India Meteorology Department?
IRI has had a long relationship with IMD in terms of scientific collaboration. This particular work had a number of unique components. First, although IMD has recently begun issuing extended-range forecasts of monsoon rainfall up to 4 weeks ahead for every meteorological subdivision in India, access to timely and relevant climate information for rural communities at district-level is still very limited. IRI and IMD worked closely to develop subseasonal forecasts specifically at the district level.
Second, the two institutions also worked closely with government and nongovernmental institutions to improve dissemination of the forecasts, so that they reach rural communities. This also included capacity building for agricultural extension staff.
As part of the project, we helped develop and launch a virtual maproom that includes not only subseasonal forecasts, but also historical information, other forecasts and real-time monitoring. IMD provided its own high-resolution data to feed into the maproom. And finally, it’s great to see that even after the end of the project, IMD and its partners continue to send the S2S forecasts to farmers in Bihar. This is itself a huge success of the project.
In what ways is (or can) this information be useful for decision making? Are there plans to go beyond Bihar?
Farmers in the four districts used the forecasts for farm-level planning and decisions. For example, the 2018 monsoon reached Bihar on June 25–26, almost 16 days later than the average onset date of June 10 for the state. Rice farmers used this time-ahead knowledge to delay sowing and planting.
Because this experimental S2S forecast generated strong demand by the user community, our colleagues at IMD say they plan to extend the system for the entire country in the near future.
Here at IRI, we’re working on replicating the system for our partner countries in ACToday, the Columbia World Project we’re leading. For example, we’ve heard from both the meteorological department and the agriculture extension service of Bangladesh to implement S2S forecasts in the country as part of ACToday-Bangladesh.