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Monitoring of surface soil moisture (SM) through microwave radiometry typically relies on the inversion of a radiative transfer model. Conventional inversion algorithms require proper calibration of surface roughness and radiometric parameters of the overlying canopy, including the scattering albedo and optical depth. However, uncertainty in global characterization of these parameters is one of the main sources of error in satellite SM retrievals. To cope with this uncertainty, this paper presents a new algorithm, called "temporal polarization ratio algorithm" (TPRA), that enables retrieval of SM independent of surface roughness and vegetation parameters. This approach uses the temporal differences of polarized emissivity observations assuming that the surface roughness and vegetation parameters are invariant over a window of time. Unlike the classical dual channel algorithms (DCA), TPRA is not only free of surface calibration but also robust to systematical errors arising from surface soil temperature errors. One caveat is that the algorithm is unable to retrieve SM when surface emissivity does not change appreciably in time. The performance of TPRA is evaluated through several controlled numerical experiments and validated using the Soil Moisture Active Passive (SMAP) satellite retrievals as well as in-situ SM measurements over Australia. The results show improved SM retrievals compared with the DCA and SMAP official products as long as the surface emissivity changes sufficiently over the retrieval time period. • A new algorithm is designed for the retrieval of soil moisture at L-band. • Soil moisture retrievals are independent of surface roughness. • Soil moisture retrievals are independent of vegetation parameters. • Soil moisture retrievals are robust to systematical errors in soil temperature. [ABSTRACT FROM AUTHOR]