Validation of the Diurnal Amplitude Variations for Freeze-Thaw (DAV-FT) algorithm with the National Ecological Observatory Network (NEON) soil temperature data

Knowing the Freeze-Thaw (FT) state/ice content/freezing front depth of the land surface is essential for many aspects of weather forecasting, climate, hydrology, and agriculture. Microwave L-band emission contains rather direct information about the FT-state because of its impact on the soil dielectric constant, which determines microwave emissivity and the optical depth profile. However, current L band-based FT algorithms need reference values to distinguish between frozen and thawed soil, which are often not well known. 

We present a series of new frozen soil detection algorithms based on the daily variation of the H-polarized brightness temperature. Exploiting the daily variation signal allows for a more reliable state detection, particularly during the transition periods, when the near-surface soil layer may freeze and thaw on sub-daily time scales. The new algorithms explore and prove that we can get the Freeze-Thaw (FT) state/ice content/freezing front depth of the land surface with a delicate analysis of the L-band passive brightness temperature signals. These studies are expected to extend L-band microwave remote sensing data for improved FT detection.