Weather Prediction and Sustainability: The Role of BharatFS in Building Climate Resilience

Weather Prediction and Sustainability: The Role of BharatFS in Building Climate Resilience

Introduction 1

The Science Behind Numerical Weather Prediction (NWP) 2

BharatFS and the Triangular Cubic Octahedral (TCO) Grid 2

Sustainability Relevance of Weather Prediction 3

BharatFS in the Context of Climate Change 4

Collaboration and Indigenous Development 5

Conclusion 5

Key Takeaways 5

Introduction

Sustainability is no longer a choice but a necessity in the face of accelerating climate change, resource depletion, and environmental degradation. Among the many factors influencing sustainability, weather and climate prediction play a pivotal role. Accurate and reliable weather forecasts are crucial for sectors such as agriculture, water management, disaster preparedness, renewable energy, and urban planning—all of which are central pillars of sustainable development.

To address the challenges of climate variability, India has developed a new-generation weather prediction system called BharatFS, spearheaded by scientists at the Indian Institute of Tropical Meteorology (IITM), Pune. This high-resolution forecast model incorporates advanced grid structures, allowing for more accurate predictions of extreme events like heavy rainfall, heatwaves, and monsoons—phenomena directly tied to sustainability and resilience.

The Science Behind Numerical Weather Prediction (NWP)

Numerical Weather Prediction (NWP) models form the backbone of modern weather forecasting. These models solve the nonlinear partial differential equations governing atmospheric fluid motion using numerical techniques.

An NWP model has two essential components:

1. Dynamics – Captures the large-scale atmospheric motions that can be resolved on the model grid.
   
   

2. Physics – Represents smaller-scale processes (cloud microphysics, radiation, convection, turbulence) that occur at sub-grid levels.
   
   

While physics parameterizations ensure realism, the grid structure used in the dynamics component determines resolution, computational efficiency, and forecast accuracy.

BharatFS and the Triangular Cubic Octahedral (TCO) Grid

BharatFS marks a significant leap in India’s forecasting capabilities with a grid resolution of ~6 km, an improvement over the IMD-GFS model (~12 km). The key innovation lies in its Triangular Cubic Octahedral (TCO) grid, which replaces the conventional reduced Gaussian grid.

The TCO grid, based on a Collignon projection of a sphere onto an octahedron, offers several sustainability-linked advantages:

• Higher Resolution Near the Equator – Critical for accurate tropical weather and monsoon predictions, directly supporting agriculture and water management.
  
  

• Reduced Computational Cost – Lower energy requirements for simulations, aligning with sustainable use of supercomputing resources.
  
  

• Enhanced Orographic Representation – Better capture of terrain-induced rainfall, vital for flood management and hydropower planning.
  
  

• Improved Conservation Properties – Ensures realistic tracking of energy, momentum, and mass, essential for long-term climate projections.
  
  

This innovation not only improves forecasts but also makes them more resource-efficient, reducing computational waste and energy consumption.

Sustainability Relevance of Weather Prediction

Accurate weather and climate forecasting directly supports multiple Sustainable Development Goals (SDGs):

1. Agriculture & Food Security (SDG 2: Zero Hunger)
   Farmers rely on precise monsoon and rainfall forecasts to optimize sowing, irrigation, and harvesting, reducing crop losses and ensuring food security.
   
   

2. Disaster Risk Reduction (SDG 11 & 13: Sustainable Cities & Climate Action)
   Early warnings of floods, cyclones, and heatwaves help in evacuation planning, infrastructure resilience, and minimizing human and economic losses.
   
   

3. Water Resource Management (SDG 6: Clean Water & Sanitation)
   Hydrological models linked with weather forecasts guide dam operations, groundwater recharge, and drought management strategies.
   
   

4. Renewable Energy Optimization (SDG 7: Affordable & Clean Energy)
   Wind and solar energy forecasts, powered by high-resolution weather models, improve renewable integration into the national grid.
   
   

5. Health & Well-being (SDG 3: Good Health)
   Better forecasts of heatwaves, vector-borne disease risks, and air quality help public health authorities prepare preventive measures.
   
   

BharatFS in the Context of Climate Change

As climate change intensifies, extreme weather events are becoming more frequent and intense. Traditional coarse-resolution models struggle to capture small-scale events such as cloudbursts or localized heavy rainfall. BharatFS, with its enhanced resolution and improved grid design, enables India to:

• Anticipate micro-scale extreme weather that can devastate communities.
  
  

• Provide longer lead-time warnings for disaster preparedness.
  
  

• Optimize climate adaptation strategies by aligning policy with scientific forecasts.
  
  

Collaboration and Indigenous Development

While inspired by the European Centre for Medium-Range Weather Forecasts (ECMWF), BharatFS was developed indigenously, reflecting India’s growing self-reliance in climate science and technology. The TCO grid structure at its current truncation was developed in India, demonstrating scientific innovation that reduces dependence on external modeling systems.

All details of BharatFS, including development and results, were recently published in a peer-reviewed journal:

📖 Phani, M.K.R. et al. (2025). Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: An attempt to resolve the monsoon prediction deadlock. Geoscientific Model Development, 18, 1879–1894. https://doi.org/10.5194/gmd-18-1879-2025

Conclusion

The development of BharatFS represents a critical step in linking weather science with sustainability. By providing more accurate, high-resolution forecasts, India is better equipped to manage agriculture, energy, water, and disaster resilience. In the long run, such advancements will not only safeguard lives and livelihoods but also strengthen the country’s capacity to adapt to climate change—fulfilling the promise of sustainability for future generations.

Key Takeaways

• Weather forecasting is central to sustainability, influencing agriculture, energy, water, and disaster management.
  
  

• BharatFS introduces a new TCO grid, enhancing accuracy while reducing computational costs.
  
  

• High-resolution models are critical to capture extreme climate events, increasingly frequent in a warming world.
  
  

• Indigenous scientific innovation like BharatFS strengthens India’s resilience and global leadership in climate science.