Modelling variable glacier lapse rates using ERA‐Interim reanalysis climatology: an evaluation at Vestari‐ Hagafellsjökull, Langjökull, Iceland

• Published in: International Journal of Climatology
• Main Authors: Hodgkins, R., Carr, S., Pálsson, F., Guðmundsson, S., Björnsson, H.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2012
• Subjects: Langjökull; glacier; Iceland
• Online Access: http://dx.doi.org/10.1002/joc.3440; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.3440; https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.3440

Abstract The near‐surface air temperature lapse rate is an important tool for spatially distributing temperatures in snow‐ and ice‐melt models, but is difficult to parameterize, as it is not simply correlated with boundary‐layer meteorological variables, such as temperature itself. This contribution quantifies spring‐autumn lapse rate variability over 5 years at Vestari‐Hagafellsjökull, a southerly outlet of Langjökull in Iceland. It is observed that summer lapse rates (0.57 °C 100 m −1 ) are significantly lower than non‐summer rates, and are also lower than the Saturated Adiabatic Lapse Rate (SALR), which is often adopted in melt models. This is consistent with reduced near‐surface temperature sensitivity to free‐atmosphere temperature change during the occurrence of melting. A Variable Lapse Rate (VLR) regression model is calibrated with standardized, 750 hPa temperature anomalies derived from ERA‐Interim climatology, which is shown to be highly significantly correlated with near‐surface temperatures. The modelled VLR overestimates cumulative June–September Positive Degree Days (PDDs) by 3% when used to extrapolate temperatures from 1100 to 500 m a.s.l. on the glacier, whereas the SALR overestimates cumulative PDDs by 14%. ERA‐Interim data therefore appear to offer a good representation of free‐atmosphere temperature variability over Vestari‐Hagafellsjökull, and the modelling approach offers a simple means of improving lapse rate parameterizations in melt models. Copyright © 2012 Royal Meteorological Society