All  about Numerical Weather  Predicition

Numerical weather prediction (NWP) is a method which is based on mathematical models of the atmosphere and Earth's surface to anticipate future weather conditions. It entails predicting climatic factors including temperature, humidity, wind speed, and precipitation at different locations and periods using intricate mathematical equations and computer simulations. 

The numerical weather prediction models mimic the behaviour of the atmosphere throughout time once they are initialised. The mathematical equations that describe the physical processes driving atmospheric dynamics, thermodynamics, and moisture are solved by the models; these equations are referred to as the fundamental equations of fluid motion.

Model Integration

Data Collection

Gathering observational data from weather stations, satellites, radar systems, weather balloons, and other sources is the first step in the NWP process. These observations give us details about the present weather conditions at various sites across the world, including temperature, pressure, humidity, wind speed, and cloud cover.  


The numerical weather prediction models are initialised using the observational data. This entails incorporating the observational data into the model's beginning circumstances and modifying the state variables (such wind and temperature) to as nearly resemble the observed conditions as feasible. 

Time Stepping 

The models replicate the evolution of atmospheric variables at each grid point over short time intervals, usually on the scale of minutes to hours, by dividing the atmosphere into a three-dimensional grid of discrete points, or grid cells. Time stepping is the process of updating the atmospheric state variables according to the estimated variations in atmospheric conditions. 

Verification and Evaluation 

To determine the precision and dependability of the numerical weather prediction models, the forecast outputs are checked and compared to actual weather data. Meteorologists can uncover model biases, enhance model performance, and provide more precise and trustworthy weather forecasts with the use of this technique. 

Prediction Outputs 

Future weather conditions are forecasted by the model simulation as it goes along, with lead durations varying from a few hours to several days or more. At various locations and elevations, these forecasts offer data on temperature, precipitation, wind, pressure, and other meteorological characteristics. 

Weather prediction is inherently unpredictable because of the chaotic structure of the environment, Accuracy of forecasts declines with longer lead times especially in areas with complicated terrain or weather patterns.

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