Efforts have been made by several investigators to produce a reliable global microwave snow algorithm to estimate snow depth or snow water equivalent (snow volume) and snow extent. Complications arise when trying to apply a global algorithm to specific regions where the climate, snowpack structure and vegetation vary. In forest regions, the microwave emission from dense coniferous forests may overwhelm the emission from the underlying snow-covered ground. As a result, algorithms employing microwave data tend to underestimate snow depths. Preliminary results indicate that the amount of underestimation can be minimized when the fraction of forest cover can be accounted for and used as an additional input in microwave algorithms. In the boreal forest of Saskatchewan, the standard error between the measured and the estimated snow water equivalent was reduced from 2.7 to 2.1 cm by using a generalized snow retrieval algorithm that includes the percentage of forest cover. However, perhaps as much as 25% of the boreal forest of North America and Eurasia is too dense to enable satisfactory snow water equivalent determination to be made using passive microwave techniques alone.Key words: brightness temperature, boreal forest, microwaves, radiometer, snowpack