Topoclimatic modeling of summer surface air temperature in the Canadian Arctic Archipelago.

Abstract

In the Canadian High Arctic general patterns of temperature are poorly resolved at the meso-scale. This project addressed this issue in three stages. In the first stage a data set of non-standard weather observations was assembled and quality controlled The data set possessed approximately 58000 observations, including dry-bulb temperature, wind, visibility and cloud cover, from the spring and summer seasons of the years 1974--1993. Up to 10% of the data were unusable due to erroneous station information. The second part of the project consisted of a principal components analysis (PCA) of daily temperature data in the Canadian Arctic Archipelago (CAA). The PCA (1) demonstrated how the timing and extent of synoptic events could be tracked, (2) identified the major regional controls of temperature in the CAA, and (3) showed that the non-standard data exhibited general coherency with regional patterns yet were able to reveal zones of coherency at the meso-scale in temperature patterns. In the third stage of the project a model to estimate surface air temperature at the meso-scale was constructed, It was based on a 1 km resolution digital elevation model of the CAA. The effects on temperature due to site elevation and coastal proximity were selected for parameterization. The change in temperature with elevation was implemented in the model using derived environmental lapse rates. Advection effects were handled using resultant winds combined with air temperature above the ocean. Lapse rates and resultant wind estimates were obtained from upper air ascents. Model results for 14-day runs were compared to observed data. Residuals (n = 385) possessed a mean absolute error of 1.5°C. The model was sensitive to steep surface inversions and to low-level warming. Sensitivity analyses were performed on the model to determine response to alterations in lapse rate calculation, sea surface temperature, and wind field generation. The model was most sensitive to lapse rate calculation. The lowest mean absolute error (0.2) was obtained using a moderate lapse rate calculation, moderate wind field and variable sea-surface temperature.