A global satellite environmental data record derived from AMSR-E and AMSR2 microwave Earth observations

Abstract

Abstract. Spaceborne microwave remote sensing is widely used to monitor global environmental changes for understanding hydrological, ecological, and climate processes. A new global land parameter data record (LPDR) was generated using similar calibrated, multifrequency brightness temperature (T b ) retrievals from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2). The resulting LPDR provides a long-term (June 2002-December 2015 global record of key environmental observations at a 25 km grid cell resolution, including surface fractional open water (FW) cover, atmosphere precipitable water vapor (PWV), daily maximum and minimum surface air temperatures (T mx and T mn ), vegetation optical depth (VOD), and surface volumetric soil moisture (VSM). Global mapping of the land parameter climatology means and seasonal variability over the full-year records from AMSR-E (2003) and AMSR2 (2013 observation periods is consistent with characteristic global climate and vegetation patterns. Quantitative comparisons with independent observations indicated favorable LPDR performance for FW (R ≥ 0.75; RMSE ≤ 0.06), PWV (R ≥ 0.91; RMSE ≤ 4.94 mm), T mx and T mn (R ≥ 0.90; RMSE ≤ 3.48 • C), and VSM (0.63 ≤ R ≤ 0.84; bias-corrected RMSE ≤ 0.06 cm 3 cm −3 ). The LPDR-derived global VOD record is also proportional to satellite-observed NDVI (GIMMS3g) seasonality (R ≥ 0.88) due to the synergy between canopy biomass structure and photosynthetic greenness. Statistical analysis shows overall LPDR consistency but with small biases between AMSR-E and AMSR2 retrievals that should be considered when evaluating long-term environmental trends. The resulting LPDR and potential updates from continuing AMSR2 operations provide for effective global monitoring of environmental parameters related to vegetation activity, terrestrial water storage, and mobility and are suitable for climate and ecosystem studies. The LPDR dataset is publicly available at

Quantifying the effects of freeze-thaw transitions and snowpack melt on land surface albedo and energy exchange over Alaska and Western Canada

“…Surface air temperature and RH measurements from in situ weather stations were used to represent variations in seasonal climate for the different snow conditions in this study even though the AMSR FT retrieval is more directly sensitive to land surface dielectric changes due to FT related shifts in liquid water abundance (Du et al 2017). Alternatively, surface 'skin' temperatures from the MODIS (MYD11A1) land surface temperature (LST) record were analyzed for the same domain, period and snow (SCE) conditions (figure S4); the LST retrievals are a closer proxy of the energy state within the surface snow layer represented by the AMSR FT retrieval, while the LST results were consistent with the in situ air temperature assessment.…”

Rain-on-snow events in Alaska, their frequency and distribution from satellite observations

“…The AMSR orbital swath T data were spatially resampled to a 6 km resolution polar EASE-Grid (version 2) geographic projection, using an inverse distance squared weighting method (Brodzik et al 2012, Du et al 2017a. To ensure cross-sensor consistency, the gridded AMSR2 T data were empirically calibrated against the same AMSR-E frequencies using a double-differencing method and similar overlapping observations from the FY3B MWRI sensor record (Du et al 2017b, Du et al 2014. The new 6 km grid provided an intermediate resolution between the finer scale (500 m) MODIS SCE and the coarser resolution (∼12.5 km) AMSR T observations, while enabling enhanced assessment of terrain and land cover spatial heterogeneity.…”

Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis

“…We use the descending orbit as retrievals are generally more accurate when vertical temperature gradients are low (Liu et al, 2011). The retrieval specifically accounts for the effects of open water on the VOD and surface-soil moisture (Du et al, 2017b). The accompanying quality flags are used to remove all pixel values observed under non-favourable conditions with respect to frozen soils, snow, ice or large areas of open water on the surface, very dense vegetation, precipitation, radio frequency interference, or microwave signal saturation.…”

“…Accordingly, changes in species composition (Chapin et al, 1995) are observed and satellite records indicate a greening in large regions in the Arctic Verbyla, 2008). This is interpreted as increased growth (Stow et al, 2004;Elmendorf et al, 2012;Huemmrich et al, 2010a;Chapin et al, 1995) or even as a woody encroachment into tundra (Racine et al in Stow et al, 2004;Dass et al, 2016;Sturm et al, 2001). Yet, higher leaf mass and growth do not necessarily linearly translate into enhanced GPP in every case, as increased growth might also cause enhanced self-shading and lower nitrogen amounts per unit leaf area (Street et al, 2007;McFadden et al, 2003).…”