Revisit Degree Days

[TLDR]The escalation of global temperatures, more frequent and severe winters, and summer heat waves may lead to changes in energy consumption and agricultural production. Typically, a series of temperature-dependent variables, specifically degree-day indicators, are calculated to consider the impact of climate on energy consumption (Christenson et al., 2006), agricultural production (Grigorieva et al., 2010), and crop phenology (Moriondo and Bindi, 2007).

Degree days offer a metric for both heating and cooling needs. The accumulation of degree days, beginning from a pertinent starting point, plays a crucial role in determining the best timing for crop planting and strategies related to pest management.

Historically, degree days, initially devised by US utility companies in the 1930s, serve as a climate statistic used to estimate the demand for coal and gas by gauging typical energy usage. According to the definition, degree days operate on the principle that an energy balance is attained when the heat inputs into a building are equivalent to the overall heat loss, leading to the absence of a latent load (McGilligan et al., 2011). Therefore, there is a balance point temperature (BPT) where the outdoor ambient temperature is high (or low) enough to eliminate the necessity for additional heating (or cooling). This BPT establishes the base temperature, a crucial component of the degree days methodology (American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE), 2001).

Three primary categories of degree days—cooling degree-days (CDD), heating degree-days (HDD), and growing degree-days (GDD)—are employed to gauge the energy needed for cooling or heating buildings and to assess the dynamics of the growing season.

• Cooling degree days (CDD) indicate the effect of outside air temperature on building energy consumption during a specified period. They represent the number of degrees and number of days that the outside air temperature at a specific location is higher than a specified base temperature (or balance point). This indicates how much cooling will be required in the building.
• Heating degree day (HDD) is a measurement designed to quantify the demand for energy needed to heat a building. HDD is derived from measurements of outside air temperature. The heating requirements for a given building at a specific location are directly proportional to the number of HDDs.
• Growing degree days (GDD) serve as a weather-dependent gauge for evaluating crop development. This calculation, employed by crop producers, measures heat accumulation to predict plant and pest development rates, including the date at which a crop attains maturity. GDD is credited to be first defined by Reaumur in 1735.

Degree days represent a simplified version of historical weather data, specifically focusing on outside air temperature data. The simplicity of the calculation makes it easily accessible and user-friendly, establishing it as the preferred choice among energy consultants and managers. This is particularly evident when contrasted with other types of historical weather data, like hourly temperature readings. The fundamental elements for calculating degree days are temperature data and appropriate base temperatures. Base temperature can be varied to consider local conditions. For example, In China, the base temperature for CDD is 26 degrees Celsius, while it is 18 degrees Celsius in Spain. Moreover, the base temperatures used for the HDD are frequently different from those used for the CDD.

Typically, HDD is determined by subtracting the daily mean temperature from a predefined base temperature and summing any positive values over a specified period. Likewise, CDD is computed by subtracting the base temperature from the mean daily temperature and summing only the positive values over a designated period (Sivak, 2008). The GDD is calculated similarly to the CDD (Project team ECA&D, 2013).

In certain instances, acquiring daily temperature data can be pretty challenging. Consequently, the calculation of extended degree-day records can be problematic; specifically, the absence of some daily temperature data points can hinder the computation of annual degree days. As a result, various methods have been devised to estimate degree days based on annual temperature profiles (McMaster and Wilhelm, 1997) or rely solely on monthly mean temperatures (e.g., Spinoni et al., 2015).

I typically use daily mean temperatures for computing Heating Degree Days (HDD) and Cooling Degree Days (CDD). However, I recently came across an approach employed by the European Environmental Agency (EEA) described by Spinoni et al. (2015). This method determines daily HDD and CDD by comparing the daily minimum and maximum air temperatures to a specified base temperature. This calculation considers the fluctuations of daily air temperature around the base temperature, along with the asymmetry between daily average temperature and diurnal temperature variations.

In my view, the approach outlined by Spinoni et al. (2015) appears to be more rational than depending solely on daily mean temperature. Regarding Cooling Degree Days (CDD), a straightforward comparison is conducted exclusively using daily mean temperature (i.e., CDD-Tmean) and the EEA method (CDD-EEA). The anomaly shows that the disparity between the two methods is not negligible.

Should temperature data with a more excellent temporal resolution (hourly or minutely) be accessible, we can compute degree days at an enhanced resolution, thereby acquiring more precise estimates.

References

https://en.wikipedia.org/wiki/Heating_degree_day

https://www.designingbuildings.co.uk/wiki/Cooling_degree_days

American Society of Heating, Refrigerating, and Air-Conditioning Engineers. 2001. Fundamentals Handbook. American Society of Heating, Refrigerating, and Air-Conditioning Engineers: Atlanta, GA.

Azevedo, J. A., Chapman, L., & Muller, C. L. (2015). Critique and suggested modifications of the degree days methodology to enable long-term electricity consumption assessments: a case study in Birmingham, UK. Meteorological Applications, 22(4), 789–796. doi:10.1002/met.1525

Christenson M, Manz H, Gyalistras D. 2006. Climate warming impact on degree-days and building energy demand in Switzerland. Energy Convers. Manage. 47(6): 671–686.

Ferchault de Réaumur, René Antoine (2023-02-06). "Observations du thermometre, faites a Paris pendant l'annees 1735, comparees a celles qui ont ete faites sous la ligne, a l'Isle de France, a Alger et en quelques-unes de nos isles de l'Amerique" (PDF). Mémoire de l'Académie royale des sciences.

Grigorieva EA, Matzarakis A, de Freitas CR. 2010. Analysis of growing degree-days as climate impact indicator in a region with extreme annual air temperature amplitude. Clim. Res. 42: 143–154

McMaster GS, Wilhelm W. 1997. Growing degree-days: one equation, two interpretations. Agric. For. Meteorol. 87(4): 291–300.

McGilligan C, Natarajan S, Nikolopoulou M. 2011. Adaptive comfort degree-days: a metric to compare adaptive comfort standards and estimate changes in energy consumption for future UK climates. Energy Build. 43: 2767–2778

Moriondo M, Bindi M. 2007. Impact of climate change on the phenology of typical Mediterranean crops. Ital. J. Agron. 3: 5–12

Project team ECA&D. 2013. Royal Netherlands Meteorological Institute (KNMI) - European Climate Assessment & Dataset (ECA&D) – Algorithm Theoretical Basis Document (ATBD) Version 10.7, Retrieved September 16, 2013. https://eca.knmi.nl/documents/atbd.pdf

Sivak M. 2008. Where to live in the United States: combined energy demand for heating and cooling in the 50 largest metropolitan areas. Cities 25: 396–398.

Spinoni J, Vogt JV, Barbosa P. 2015c. European degree-day climatologies and trends for the period 1951–2011. Int. J. Climatol. 35(1):25–36.

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