Lapse Rate Research

Motivation and History

Surface air temperature is a governing factor for many environmental processes, making it important to many fields of research, including hydrology, ecology, and the atmospheric sciences. Many hydrological and ecological models require accurate spatially distributed estimates of temperature to enhance their accuracy. Lapse rates have been increasingly applied to better interpolate near-surface air temperature at different elevations (Blandford et al. , 2008, Tercek et al. 2021). The commonly used globally-averaged, so-called ‘environmental lapse rate’ of 6.5°C/km has been shown by several studies to be different than in situ measured lapse rates near surfaces in many different locations, in addition to varying over daily, monthly, and seasonal time scales.

The Mount Washington Observatory has a dense network of surface weather stations adjacent to the Mount Washington Auto Road, with stations at 1600’, 2300’, 3300’, 4000’, 4300’, 5300’, in addition to the summit station which can be used to establish a NSLR for Mount Washington. This type of research can then be directly applied to model grids to generate more realistic temperature distributions within areas of mountainous terrain, which is critical to distinguishing precipitation type, delineating areas of snowmelt (Minder et al., 2010), and may affect precipitation and convective lift processes (Shadbolt, 2019). Minder et al., 2010 also noted the lack of high spatial and temporal resolution in past studies of NSLRs, which is characteristic of the Auto Road dataset. Additionally, ecological researchers in the alpine zone of the White Mountains region are interested in establishing a NSLR for future ecological modeling studies. By establishing a NSLR along the slope of Mount Washington, findings could then be cited in future ecological, meteorological, and climatological research and serve as a beginning to establishing a regional lapse for the White Mountains and the New England region.

Scope of Work

Average daily, monthly, seasonal, and annual NSLRs will be established for Mount Washington between 2016 and 2022 and findings will be presented in a report written by Karl Philippoff and Jay Broccolo. Weather Observer and Research Specialist (WORS) Jay Broccolo will serve as project manager for this investigation.

External Relevance

The establishment of a NSLR for Mount Washington will be the most comprehensive description of an NSLR in the White Mountains region, using high-quality data over an extended period of time. The need for understanding lapse rates has been identified as a critical component in understanding the future trends of not only precipitation, wind, and convective processes, but organisms that inhabit the White Mountains as well as mountain ranges further afield.


Blandford, T. R., Humes, K. S., Harshburger, B. J., Moore, B. C., Walden, V. P., & Ye, H. (2008). Seasonal and synoptic variations in near-surface air temperature lapse rates in a mountainous basin. Journal of Applied Meteorology and Climatology, 47(1), 249-261.

Lundquist, J. D., & Cayan, D. R. (2007). Surface temperature patterns in complex terrain: Daily variations and long‐term change in the central Sierra Nevada, California. Journal of Geophysical Research: Atmospheres, 112(D11).

Minder, J. R., Mote, P. W., & Lundquist, J. D. (2010). Surface temperature lapse rates over complex terrain: Lessons from the Cascade Mountains. Journal of Geophysical Research: Atmospheres, 115(D14).

Rolland, C. (2003). Spatial and seasonal variations of air temperature lapse rates in Alpine regions. Journal of Climate, 16(7), 1032-1046.

Shadbolt, R. P. (2019). Trends of Southern Appalachian Seasonal Air Temperature and Regional Lapse Rate Spanning 1969–2018. Southeastern Geographer, 59(4), 365-388.

Tercek, M. T., Rodman, A., Woolfolk, S., Wilson, Z., Thoma, D., & Gross, J. (2021). Correctly applying lapse rates in ecological studies: comparing temperature observations and gridded data in Yellowstone. Ecosphere, 12(3), e03451.

Karl Philippoff, Weather Observer & Research/IT Specialist