New Approach for Surface $n$ Factors

Air and surface freezing and thawing indexes and prediction of ground temperatures from air temperatures were investigated. A new method for applying $n$ factors on a daily basis to capture localized temperature extremes is presented and compared to conventional seasonal $n$ -factor analysis. Measured air temperatures from five locations and measured air and surface temperatures from one location were used. Freezing and thawing indexes were determined using daily and monthly average temperatures, different time frames, and seasonal and daily applications of $n$ factors. Air and surface freezing indexes ( $I_{\text{af}}$ and $I_{\text{sf}}$ ) varied more than air and surface thawing indexes ( $I_{\text{at}}$ and $I_{\text{st}}$ ). Significant variations were observed in air and surface indexes due to the length of the time period used (1, 10, and 30 years) and frequency of temperature data used (daily and monthly). The surface indexes from seasonal $n$ factors (using daily average temperatures) and daily $n$ factors were similar (within 4%) and higher than the indexes from seasonal $n$ factors (using monthly average temperatures). The average surface temperatures were within $2°\text{C}$ , whereas the maximum and minimum surface temperatures were significantly different (up to $26°\text{C}$ ) between the seasonal and daily $n$ factors. Maximum variations between consecutive daily maximum and minimum temperatures were significantly higher using daily $n$ factors (up to $52°\text{C}$ ) than seasonal $n$ factors (less than $1°\text{C}$ ). Surface indexes from seasonal (using daily average temperatures) and daily $n$ factors can be used interchangeably. Daily $n$ factors are recommended to obtain representative surface and near-surface temperature variations, diurnal extremes, representative timing for temperature change events, and localized freezing or thawing indexes during change-over months.