Ensemble forecast

Source: The Hindu

Gs3: Disaster Management

Context: India needs to shift to ensemble weather and flood forecast model to achieve better accuracy in flood forecasting.

What is the significance of using Ensemble forecast?

Deterministic forecast model Ensemble forecast
·         Deterministic forecast model merely indicates “Rising” or “Falling” above a water level at a river point. 

·         In this model,there is no idea of the area of inundation, its depth, and when the accuracy of the forecast decreases at 24 hours and beyond

 

 

·         It gives probability-based estimation as to different scenarios of water levels and regions of inundation. 

·         For example, it can indicate the probability like, the chances of the water level exceeding the danger level is 80%, with likely inundation of a village nearby at 20%.

 

·         It provides a lead time of just 24 hours ·         It provides a lead time of 7-10 days ahead. 

 

·         Since the end users (district administration, municipalities and disaster management authorities) receive such forecasts with very less “Lead time” and have to act quickly, flood forecast becomes less accurate. ·         It helps local administrations with better decision-making and helps them to get prepared better in advance. 

 

·         India has recently shifted towards -Deterministic forecast model ·         The United States, the European Union and Japan have shifted towards Ensemble flood forecasting along with “Inundation modelling”.

What are the shortcomings with India’s flood forecasting?

Multiple agencies:

  • The India Meteorological Department (IMD) issues meteorological or weather forecasts while the Central Water Commission (CWC) issues flood forecasts at various river points.
  • Therefore, the advancement of flood forecasting depends on how quickly rainfall is estimated and forecast by the IMD and how quickly the CWC integrates the rainfall forecast with flood forecast.
  • It also is linked to how fast the CWC disseminates this data to end user agencies.
  • This complicated arrangement reduces the “Lead time”.

Obsolete methods:

  • Most flood forecasts at several river points across India are based on outdated statistical methods that enable a lead time of less than 24 hours.
  • It renders the India’s flood forecast driven by Google’s most advanced Artificial Intelligence (AI) techniques ineffective.

Not uniform across India:

  • A recent study shows that, India has only recently moved to use hydrological or simply rainfall-runoff models not all, but in specific river basins.

Impact:

  • Therefore, outdated technologies and a lack of technological parity between multiple agencies and their poor water governance decrease crucial lead time.
  • Forecasting errors increase and the burden of interpretation shifts to incompetent end user agencies. The outcome is an increase in flood risk and disaster.

What is the way forward?

  • The IMD has already started testing and using ensemble models for weather forecast through its supercomputers (“Pratyush” and “Mihir”).
  • Yet, the forecasting agency has to adapt with advanced technology and need to achieve technological parity with the IMD in order to couple ensemble forecasts to its hydrological models.
  • The IMD has to modernise the telemetry infrastructure along with raising technological compatibility with river basin-specific hydrological, hydrodynamic and inundation modelling.
  • It also needs to trains its technical workforce to get well versed with ensemble models and capable of coupling the same with flood forecast models.
  • It is only then that India can look forward to probabilistic-based flood forecasts with a lead time of more than seven to 10 days that will place India on par with the developed world.
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