Perhaps you have seen some version of the figure below. It illustrates the relative global average temperature since 1880 as compared to the average global temperature for the mid-twentieth century years of 1951-1980. The blue bars indicate cooler-than-average years; the red bars show warmer-than-average years. The data come from the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental information (NCEI). 

According to the NCEI in its Assessing the Global Climate in 2021 report:

  • Earth’s temperature has risen by 0.14° Fahrenheit (0.08° Celsius) per decade since 1880, but the rate of warming since 1981 is more than twice that: 0.32 °F (0.18 °C) per decade.
  • 2021 was the sixth-warmest year on record based on NOAA’s temperature data.
  • Averaged across land and ocean, the 2021 surface temperature was 1.51 °F (0.84 °C) warmer than the twentieth century average of 57.0 °F (13.9 °C) and 1.87 ˚F (1.04 ˚C) warmer than the pre-industrial period (1880-1900). 
  • The nine years from 2013 through 2021 rank among the ten warmest years on record.

 

Figure 1: Global average temperature compared to the middle of the 20th century. Data depicts July global land and ocean temperature anomalies. Data source: NOAA National Centers for Environmental information, Climate at a Glance: Global Time Series, published August 2022, retrieved on August 16, 2022 from https://www.ncei.noaa.gov/cag/

 

Using historical climate data

Despite such evidence of changing climate, in the United States it is still common for building project teams to reference U.S. Climate Normals derived from three consecutive decades of historic data for broad-based climate analyses and to utilize Typical Meteorological Year (TMY) datasets for building energy modeling exercises. All of these datasets reference historic climate information and, as a result of the climate change, are potentially inadequate to help building project teams design for the future. Rhetorically, why would we use the past 30 years of climate data to design for the next 60 years of a building?

To be certain, not all TMY datasets are equal. While some TMY datasets may be decades old, the most recent TMYx datasets offered by Climate.OneBuilding.Org are from 2007-2021 and provided in a variety of file formats. Given the uncertainty of climate projection data and the age of other climate datasets, some may reasonably contend that the latest TMYx datasets offer the best pathway toward using more appropriate climate data inputs in building energy modeling.

 

Nobody can predict the future

The Sixth Assessment Report (AR6) of the United Nations Intergovernmental Panel on Climate Change (IPCC) is the latest in a series of reports which assess scientific, technical, and socio-economic information concerning climate change. Amidst the rigors and technical depth of the research, the AR6 acknowledges the uncertainty in climate change projections. As a result, AR6 assesses a variety of outcomes for the climate based on a broad range of greenhouse gas (GHG) emissions futures. Among other aspects, AR6 offers potential changes in global mean temperature and potential patterns of change in near-surface air temperature, precipitation, and soil moisture. The range of scenarios brings with it inherent uncertainty and, therefore, perceived risk by many who may otherwise be inclined to design in anticipation of climate change. 

 

Climate data projections are available, so why don't we use them? 

I recently co-authored a policy analysis piece for Buildings & Cities with Parag Rastogi, Ariane Laxo, and L. DeWayne Cecil in which we addressed a variety of barriers to the broad adoption of projected climate data by building design professional. Climate data projections have been available from U.S. government websites and international resources for some time now (e.g. CORDEX, Cal-Adapt, and CMIP5 projections). However, the outputs from these sources are not formatted to a resolution, scale, or file type that is easily utilized in architectural or engineering design and analysis tools. 

Moreover, since projected data are modeled, the inherent uncertainties of forecasting are likely to impede their use by design professionals, especially if climate projection data are less accessible. 

In the policy analysis piece, we offer and expand on four primary technical and policy barriers to broad adoption of climate data projections - within which also lie solutions:

  • Lack of consensus on the methodology for creating climate data for buildings. Standardization will pave the road for practice and codification.
  • Lack of a publicly available platform for providing climate projections in a format suitable for building analysis. As with historic climate data, projection data must be freely available in formats used by building energy modeling tools. 
  • Lack of consensus on a standardized framework for communicating the results of simulation with long-term climate data projections. The use of a single ‘future typical’ file may create a false impression of certainty about future climate. Climate projections will continue to be a moving target. Updates to the data should be extremely clear and predictable.
  • Liability concerns with using projection data. A regulatory framework does not exist in the U.S. to guide building project teams using future climate data projections. As a result, there is inherent risk in making design decisions based on uncertain long-term forecasts. With risk comes liability concerns. One solution: take the decision out of the hands of building project team. If the practice of utilizing climate data projections is standardized and codified, building project teams may proceed with much greater confidence.

For read the policy analysis piece, please visit Building & Cities at journal-buildingscities.org