Global Satellite Retrievals of the Near-Surface Atmospheric Vapor Pressure Deficit from AMSR-E and AMSR2

Stronger increases but greater variability in global mangrove productivity compared to that of adjacent terrestrial forests

Mangrove forests are a highly productive ecosystem with important potential to offset anthropogenic greenhouse gas emissions. Mangroves are expected to respond differently to climate change compared to terrestrial forests owing to their location in the tidal environment and unique ecophysiological characteristics, but the magnitude of difference remains uncertain at the global scale. Here we use satellite observations to examine mean trends and interannual variability in the productivity of global mangrove forests and nearby terrestrial evergreen broadleaf forests from 2001 to 2020. Although both types of ecosystem experienced significant recent increases in productivity, mangroves exhibited a stronger increasing trend and greater interannual variability in productivity than evergreen broadleaf forests on three-quarters of their co-occurring coasts. The difference in productivity trends is attributed to the stronger CO2 fertilization effect on mangrove photosynthesis, while the discrepancy in interannual variability is attributed to the higher sensitivities to variations in precipitation and sea level. Our results indicate that mangroves will have a faster increase in productivity than terrestrial forests in a CO2-rich future but may suffer more from deficits in water availability, highlighting a key difference between terrestrial and tidal ecosystems in their responses to climate change.

A calibration of cellulose isotopes in modern prostrate Nothofagus and its application to fossil material from Antarctica

Carbon and oxygen isotopes (δ¹³C and δ¹⁸O) in tree rings are widely used to reconstruct palaeoclimate variables such as temperature during the Holocene (12 thousand years ago - present), and are used increasingly in deeper time. However, their use is largely restricted to arboreal trees, which excludes potentially important data from prostrate trees and shrubs, which grow in high latitude and altitude end-member environments. Here, we calibrate the use of δ¹³C and δ¹⁸O as climatic archives in two modern species of southern beech (Nothofagus) from Tierra del Fuego, Chile, at the southern limit of their current range. We show that prostrate trees are potentially suitable archives for recording climatological means over longer periods (on the order of decades), which opens up these important environments for tree ring isotope analysis. We then apply our new understanding to a remarkable late Neogene (17-2.5 Ma) fossil Nothofagus assemblage from the Transantarctic Mountains, Antarctica, representative of a prostrate tundra shrub growing during a period of significant ice sheet retreat. The δ¹³C of the fossil cellulose was found to be ~4‰ enriched relative to that of the modern tress. This is likely to be due to a combination of a more positive δ¹³C of contemporaneous atmospheric CO₂ and enhanced water use efficiency at the fossil site. Using the cellulose-δ¹⁸O in the fossil wood, we are able to reconstruct precipitation oxygen isotopes over the Antarctic interior for the first time for this time period. The results show that δ¹⁸O_precip over Antarctica was -16.0 ± 4.2‰, around 12‰ enriched relative to today, suggesting changes in the hydrological cycle linked to warmer temperatures and a smaller ice sheet.

A Long-Term Passive Microwave Snowoff Record for the Alaska Region 1988–2016

Snowoff (SO) date—defined as the last day of observed seasonal snow cover—is an important governor of ecologic and hydrologic processes across Alaska and Arctic-Boreal landscapes; however, our understanding and capacity for the monitoring of spatial and temporal variability in the SO date is still lacking. In this study, we present a 6.25 km spatially gridded passive microwave (PMW) SO data record, complimenting current Alaskan SO records from Moderate Resolution Imaging Spectrometer (MODIS) and Landsat, but extending the SO record an additional 13 years. The PMW SO record was validated against in situ snow depth observations and showed favorable accuracy (0.66–0.92 mean correlations; 2–10 day mean absolute errors) for the major climate regions of Alaska. The PMW SO results were also within 10 days of finer spatial scale SO observational records, including Interactive Multisensor Snow and Ice Mapping System (IMS), MODIS, and Landsat, for a majority (75%) of Alaska. However, the PMW record showed a general SO delay at higher elevations and across the Alaska North Slope, and earlier SO in the Alaska interior and southwest regions relative to the other SO records. Overall, we assign an uncertainty +/−11 days to the PMW SO. The PMW SO record benefits from the near-daily temporal fidelity of underlying brightness temperature (Tb) observations and reveals a mean regional trend in earlier SO timing (−0.39 days yr−1), while significant (p < 0.1) SO trend areas encompassed 11% of the Alaska domain and ranged from −0.11 days yr−1 to −1.31 days yr−1 over the 29-year satellite record. The observed SO dates also showed anomalous early SO dates during markedly warm years. Our results clarify the pattern and rate of SO changes across Alaska, which are interactive with global warming and contributing to widespread permafrost degradation, changes in regional hydrology, ecosystems, and associated services. Our results also provide a robust means for SO monitoring from satellite PMW observations with similar precision as more traditional and finer scale observations.

Inter-Sensor Calibration between HY-2B and AMSR2 Passive Microwave Data in Land Surface and First Result for Snow Water Equivalent Retrieval

The self-designed HaiYang-2B (HY-2B) satellite was launched on 24 October 2018 in China at 22:57 UT in a 99.34° inclination sun-synchronous orbit. The Scanning Microwave Radiometer (SMR) on the core observatory has the capability to provide near-real-time multi-channel brightness temperature (Tb) observations, which are designed mainly for improving the level of marine forecasting and monitoring, serving the development and utilization of marine resources. After internal calibration and ocean calibration, the first effort to retrieve land surface snow parameters was performed in this study, which obtained extremely low accuracy both in snow extent and snow mass. Accordingly, land inter-sensor calibration was carried out between SMR and the Advanced Microwave Scanning Radiometer 2 (AMSR2) in order to broaden the research and application of SMR data on the Earth’s land surface. Finally, we evaluated the consistency of the snow extent and snow mass derived from the initial and land-calibrated SMR data. The results indicated that a systematic SMR cold deviation whose magnitude depends on the channel is present for all the compared channels. After intercalibration, the conformity of the snow extent and snow mass were substantially improved compared to before; the relative bias of the snow extent and snow mass decreased from −49.97% to 2.97% and from −51.71% to 3.01%, respectively.

Editorial for Special Issue “Remote Sensing Water Cycle: Theory, Sensors, Data, and Applications”

Global water cycle dynamics involve the exchange of water and energy matter among the atmosphere, hydrosphere, geosphere, cryosphere, and biosphere [...]