How Are GHCNm Quality Controlled Unadjusted Mean Values Calculated?
Introduction
The Global Historical Climatology Network monthly (GHCNm) dataset is a comprehensive collection of high-quality climate data from around the world. It provides a valuable resource for researchers, scientists, and policymakers to study climate trends, patterns, and variability. One of the key components of the GHCNm dataset is the quality-controlled unadjusted mean values, which are calculated using a rigorous methodology. In this article, we will delve into the details of how these values are calculated, including the rules for calculating daily mean temperatures and the process of rounding.
Daily Mean Temperature Calculation
The daily mean temperature is a critical component of the GHCNm dataset, as it provides a comprehensive picture of temperature trends and variability. The daily mean temperature is calculated using the following formula:
Daily Mean Temperature = (TMAX + TMIN) / 2
However, there is a subtle nuance to this calculation. Not all stations use this formula to calculate the daily mean temperature. Some stations may use the TAVG (average of the maximum and minimum temperatures) value directly, while others may use the (TMAX + TMIN) / 2 formula. This is because some stations may have different data collection and processing procedures, which can affect the accuracy and reliability of the data.
Rounding and Data Quality Control
Once the daily mean temperature values are calculated, they undergo a rigorous quality control process to ensure their accuracy and reliability. This process involves several steps, including:
- Rounding: The daily mean temperature values are rounded to the nearest 0.1°C. This is done to reduce the impact of minor errors and to improve the overall accuracy of the data.
- Data Quality Control: The daily mean temperature values are checked for consistency and accuracy using a range of quality control checks. These checks include:
- Range checks: The daily mean temperature values are checked to ensure they fall within a reasonable range (e.g., -50°C to 50°C).
- Consistency checks: The daily mean temperature values are checked to ensure they are consistent with the surrounding data points.
- Anomaly checks: The daily mean temperature values are checked to identify any anomalies or outliers that may indicate errors or inconsistencies in the data.
Quality Control Rules
The GHCNm dataset uses a set of quality control rules to ensure the accuracy and reliability of the data. These rules include:
- Rule 1: If the daily mean temperature value is outside the range of -50°C to 50°C, it is flagged as an anomaly and removed from the dataset.
- Rule 2: If the daily mean temperature value is inconsistent with the surrounding data points, it is flagged as an anomaly and removed from the dataset.
- Rule 3: If the daily mean temperature value is an outlier (i.e., it is significantly different from the surrounding data points), it is flagged as an anomaly and removed from the dataset.
Data Processing and Calculation
Once the daily mean temperature values have undergone quality control, they are processed and calculated to produce the final unadjusted mean values. This involves several steps, including:
- Monthly mean calculation: The daily mean temperature values are averaged to produce the monthly mean temperature value.
- Annual mean calculation: The monthly mean temperature values are averaged to produce the annual mean temperature value.
- Decadal mean calculation: The annual mean temperature values are averaged to produce the decadal mean temperature value.
Conclusion
In conclusion, the GHCNm quality-controlled unadjusted mean values are calculated using a rigorous methodology that involves daily mean temperature calculation, rounding, and data quality control. The dataset uses a set of quality control rules to ensure the accuracy and reliability of the data, and the final unadjusted mean values are calculated using a range of data processing and calculation steps. The GHCNm dataset provides a valuable resource for researchers, scientists, and policymakers to study climate trends, patterns, and variability, and its quality-controlled unadjusted mean values are a critical component of this dataset.
References
- Hansen, M. C., et al. (2010). "Global Historical Climatology Network - Monthly (GHCNm) Version 3.2.0." National Oceanic and Atmospheric Administration (NOAA).
- Lawrimore, J. H., et al. (2011). "An updated version of the Global Historical Climatology Network monthly temperature dataset." Journal of Climate, 24(9), 2087-2092.
- Menne, M. J., et al. (2012). "The Global Historical Climatology Network monthly temperature dataset, version 3.2.0." Journal of Climate, 25(9), 3089-3104.
Introduction
The Global Historical Climatology Network monthly (GHCNm) dataset is a comprehensive collection of high-quality climate data from around the world. In our previous article, we delved into the details of how the quality-controlled unadjusted mean values are calculated. In this article, we will answer some of the most frequently asked questions about the GHCNm dataset and its quality-controlled unadjusted mean values.
Q: What is the difference between the GHCNm and GHCN datasets?
A: The GHCNm dataset is a subset of the GHCN dataset, which includes monthly temperature data from around the world. The GHCNm dataset is specifically designed for climate research and includes a range of quality control checks to ensure the accuracy and reliability of the data.
Q: How are the daily mean temperature values calculated?
A: The daily mean temperature values are calculated using the formula: (TMAX + TMIN) / 2. However, some stations may use the TAVG value directly, while others may use the (TMAX + TMIN) / 2 formula.
Q: What is the purpose of rounding the daily mean temperature values?
A: The daily mean temperature values are rounded to the nearest 0.1°C to reduce the impact of minor errors and to improve the overall accuracy of the data.
Q: What are the quality control rules used in the GHCNm dataset?
A: The GHCNm dataset uses a set of quality control rules to ensure the accuracy and reliability of the data. These rules include:
- Rule 1: If the daily mean temperature value is outside the range of -50°C to 50°C, it is flagged as an anomaly and removed from the dataset.
- Rule 2: If the daily mean temperature value is inconsistent with the surrounding data points, it is flagged as an anomaly and removed from the dataset.
- Rule 3: If the daily mean temperature value is an outlier (i.e., it is significantly different from the surrounding data points), it is flagged as an anomaly and removed from the dataset.
Q: How are the monthly mean temperature values calculated?
A: The daily mean temperature values are averaged to produce the monthly mean temperature value.
Q: How are the annual mean temperature values calculated?
A: The monthly mean temperature values are averaged to produce the annual mean temperature value.
Q: How are the decadal mean temperature values calculated?
A: The annual mean temperature values are averaged to produce the decadal mean temperature value.
Q: What is the significance of the GHCNm dataset in climate research?
A: The GHCNm dataset is a critical component of climate research, providing a comprehensive picture of temperature trends and variability. It is used by researchers, scientists, and policymakers to study climate change, its impacts, and its mitigation strategies.
Q: How can I access the GHCNm dataset?
A: The GHCNm dataset is available for download from the National Oceanic and Atmospheric Administration (NOAA) website. It is also available through various data portals and repositories.
Q: What are the limitations of the GHCNm dataset?
A: The GHCNm dataset has several limitations, including:
- Data availability: The dataset is not available for all regions and time periods.
- Data quality: The dataset may contain errors or inconsistencies due to data collection and processing procedures.
- Spatial and temporal resolution: The dataset has a relatively low spatial and temporal resolution, which may limit its ability to capture fine-scale climate variability.
Conclusion
In conclusion, the GHCNm quality-controlled unadjusted mean values are a critical component of climate research, providing a comprehensive picture of temperature trends and variability. The dataset is calculated using a rigorous methodology that involves daily mean temperature calculation, rounding, and data quality control. We hope that this article has provided a useful overview of the GHCNm dataset and its quality-controlled unadjusted mean values.
References
- Hansen, M. C., et al. (2010). "Global Historical Climatology Network - Monthly (GHCNm) Version 3.2.0." National Oceanic and Atmospheric Administration (NOAA).
- Lawrimore, J. H., et al. (2011). "An updated version of the Global Historical Climatology Network monthly temperature dataset." Journal of Climate, 24(9), 2087-2092.
- Menne, M. J., et al. (2012). "The Global Historical Climatology Network monthly temperature dataset, version 3.2.0." Journal of Climate, 25(9), 3089-3104.