How to Identify the typical Meteorological Year (TMY)

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Identifying the TMY (typical meteorological year) involves selecting a representative year that captures the average weather conditions of a specific location. In this article, we will outline the steps to effectively identify the TMY, enabling accurate analysis and simulation for various applications.

  1. Gather Historical Weather Data: Start by collecting long-term historical weather data for the location of interest. The dataset should ideally cover a period of 10 to 30 years, ensuring a robust representation of weather variability. Obtain data such as temperature, solar radiation, wind speed, humidity, and precipitation from reliable sources like meteorological stations, weather services, or climate databases.
  2. Filter and Clean the Data: Thoroughly examine the collected data to identify any anomalies, errors, or missing values. Remove or interpolate missing data points using appropriate techniques to ensure a complete dataset. Check for outliers or erroneous data that could skew the analysis. Filtering and cleaning the data is crucial to obtain reliable and accurate results.
  3. Calculate Statistical Metrics: Analyse the collected weather data by calculating statistical metrics such as mean, standard deviation, and percentiles for each weather parameter. These metrics provide insights into the typical weather patterns and variability at the location. Understanding the statistical distribution of the weather data is essential for identifying the TMY.
  4. Identify Representative Months: To identify the TMY, examine each month’s weather data to determine which months represent the typical weather conditions. Look for months with average values that closely match the long-term means and exhibit typical weather patterns. Consider both the mean values and the variability of weather parameters to capture the full range of conditions experienced throughout the year.
  5. Select the Typical Year: Based on the representative months identified in the previous step, select a typical year that best represents the average weather conditions. This selection can be done by examining the similarity between the chosen year’s monthly data and the long-term means. A typical year should encompass the range of weather conditions observed over the long-term dataset.
  6. Validate the TMY Selection: Validate the selected TMY by comparing it with additional observed weather data, if available. Compare the TMY data with independent measurements from the same location to ensure that the chosen year accurately represents the long-term averages. Validation provides confidence in the reliability and representativeness of the TMY selection.
  7. Document the TMY Characteristics: Document the characteristics and properties of the identified TMY, including the chosen year, its corresponding weather data, and any assumptions or limitations associated with the selection process. This documentation ensures transparency and enables reproducibility in future analyses or simulations that rely on the TMY.

 

 

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