Jennifer D. Watts

Cold season emissions dominate the Arctic tundra methane budget

Significance Arctic ecosystems are major global sources of methane. We report that emissions during the cold season (September to May) contribute ≥50% of annual sources of methane from Alaskan tundra, based on fluxes obtained from eddy covariance sites and from regional fluxes calculated from aircraft data. The largest emissions were observed at the driest site (<5% inundation). Emissions of methane in the cold season are linked to the extended “zero curtain” period, where soil temperatures are poised near 0 °C, indicating that total emissions are very sensitive to soil climate and related factors, such as snow depth. The dominance of late season emissions, sensitivity to soil conditions, and importance of dry tundra are not currently simulated in most global climate models. Arctic terrestrial ecosystems are major global sources of methane (CH4); hence, it is important to understand the seasonal and climatic controls on CH4 emissions from these systems. Here, we report year-round CH4 emissions from Alaskan Arctic tundra eddy flux sites and regional fluxes derived from aircraft data. We find that emissions during the cold season (September to May) account for ≥50% of the annual CH4 flux, with the highest emissions from noninundated upland tundra. A major fraction of cold season emissions occur during the “zero curtain” period, when subsurface soil temperatures are poised near 0 °C. The zero curtain may persist longer than the growing season, and CH4 emissions are enhanced when the duration is extended by a deep thawed layer as can occur with thick snow cover. Regional scale fluxes of CH4 derived from aircraft data demonstrate the large spatial extent of late season CH4 emissions. Scaled to the circumpolar Arctic, cold season fluxes from tundra total 12 ± 5 (95% confidence interval) Tg CH4 y−1, ∼25% of global emissions from extratropical wetlands, or ∼6% of total global wetland methane emissions. The dominance of late-season emissions, sensitivity to soil environmental conditions, and importance of dry tundra are not currently simulated in most global climate models. Because Arctic warming disproportionally impacts the cold season, our results suggest that higher cold-season CH4 emissions will result from observed and predicted increases in snow thickness, active layer depth, and soil temperature, representing important positive feedbacks on climate warming.

Surface water inundation in the boreal-Arctic: potential impacts on regional methane emissions

Northern wetlands may be vulnerable to increased carbon losses from methane (CH4), a potent greenhouse gas, under current warming trends. However, the dynamic nature of open water inundation and wetting/drying patterns may constrain regional emissions, offsetting the potential magnitude of methane release. Here we conduct a satellite data driven model investigation of the combined effects of surface warming and moisture variability on high northern latitude (⩾45° N) wetland CH4 emissions, by considering (1) sub-grid scale changes in fractional water inundation (Fw) at 15 day, monthly and annual intervals using 25km resolution satellite microwave retrievals, and (2) the impact of recent (2003–11) wetting/drying on northern CH4 emissions. The model simulations indicate mean summer contributions of 53 Tg CH4yr �1 from boreal-Arctic wetlands. Approximately 10% and 16% of the emissions originate from open water and landscapes with emergent vegetation, as determined from respective 15 day Fw means or maximums, and significant increases in regional CH4 efflux were observed when incorporating satellite observed inundated land fractions into the model simulations at monthly or annual time scales. The satellite Fw record reveals widespread wetting across the Arctic continuous permafrost zone, contrasting with surface drying in boreal Canada, Alaska and western Eurasia. Arctic wetting and summer warming increased wetland emissions by 0.56Tg CH4yr �1 compared to the 2003–11 mean, but this was mainly offset by decreasing emissions (�0.38Tg CH4yr �1 )i n sub-Arctic areas experiencing surface drying or cooling. These findings underscore the importance of monitoring changes in surface moisture and temperature when assessing the vulnerability of boreal-Arctic wetlands to enhanced greenhouse gas emissions under a shifting climate.

Mapping Arctic Tundra Vegetation Communities Using Field Spectroscopy and Multispectral Satellite Data in North Alaska, USA

The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ~1 m chamber flux) and those encompassing multiple vegetation communities (e.g., ~300 m eddy covariance measurements). The objectives of this study were: (1) to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2) to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450–510 nm, 630–690 nm and 705–745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450–510 nm and 630–690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using linear discriminant analysis with raw and rescaled spectroscopy reflectance data and derived vegetation indices. However, lower classification accuracies (~70%) resulted when using the coarser 2.0 m WorldView-2 data inputs. The results from this study suggest that tundra vegetation communities are separable using plot-level spectroscopy with hand-held sensors. These results also show that tundra vegetation mapping can be scaled from the plot level (<1 m) to patch level (<500 m) using spectroscopy data rescaled to match the wavebands of the multispectral satellite remote sensing. We find that developing a consistent method for classification of vegetation communities across the flux tower sites is a challenging process, given the spatial variability in vegetation communities and the need for detailed vegetation survey data for training and validating classification algorithms. This study highlights the benefits of using fine-scale field spectroscopy measurements to obtain tundra vegetation classifications for landscape analyses and use in carbon flux scaling studies. Improved understanding of tundra vegetation distributions will also provide necessary insight into the ecological processes driving plant community assemblages in Arctic environments.

Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat

A method to assess global land surface water (fw) inundation dynamics was developed by exploiting the enhanced fw sensitivity of L-band (1.4 GHz) passive microwave observations from the Soil Moisture Active Passive (SMAP) mission. The L-band fw (fwLBand ) retrievals were derived using SMAP H-polarization brightness temperature (Tb ) observations and predefined L-band reference microwave emissivities for water and land endmembers. Potential soil moisture and vegetation contributions to the microwave signal were represented from overlapping higher frequency Tb observations from AMSR2. The resulting fwLBand global record has high temporal sampling (1-3 days) and 36-km spatial resolution. The fwLBand annual averages corresponded favourably (R=0.85, p-value<0.001) with a 250-m resolution static global water map (MOD44W) aggregated at the same spatial scale, while capturing significant inundation variations worldwide. The monthly fwLBand averages also showed seasonal inundation changes consistent with river discharge records within six major US river basins. An uncertainty analysis indicated generally reliable fwLBand performance for major land cover areas and under low to moderate vegetation cover, but with lower accuracy for detecting water bodies covered by dense vegetation. Finer resolution (30-m) fwLBand results were obtained for three sub-regions in North America using an empirical downscaling approach and ancillary global Water Occurrence Dataset (WOD) derived from the historical Landsat record. The resulting 30-m fwLBand retrievals showed favourable spatial accuracy for water (commission error 31.46%, omission error 30.20%) and land (commission error 0.87%, omission error 0.96%) classifications and seasonal wet and dry periods when compared to independent water maps derived from Landsat-8 imagery. The new fwLBand algorithms and continuing SMAP and AMSR2 operations provide for near real-time, multi-scale monitoring of global surface water inundation dynamics and potential flood risk.

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

Near-surface atmospheric Vapor Pressure Deficit (VPD) is a key environmental variable affecting vegetation water stress, evapotranspiration, and atmospheric moisture demand. Although VPD is readily derived from in situ standard weather station measurements, more spatially continuous global observations for regional monitoring of VPD are lacking. Here, we document a new method to estimate daily (both a.m. and p.m.) global land surface VPD at a 25-km resolution using a satellite passive microwave remotely sensed Land Parameter Data Record (LPDR) derived from the Advanced Microwave Scanning Radiometer (AMSR) sensors. The AMSR-derived VPD record shows strong correspondence (correlation coefficient ≥ 0.80, p-value < 0.001) and overall good performance (0.48 kPa ≤ Root Mean Square Error ≤ 0.69 kPa) against independent VPD observations from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data. The estimated AMSR VPD retrieval uncertainties vary with land cover type, satellite observation time, and underlying LPDR data quality. These results provide new satellite capabilities for global mapping and monitoring of land surface VPD dynamics from ongoing AMSR2 operations. Overall good accuracy and similar observations from both AMSR2 and AMSR-E allow for the development of climate data records documenting recent (from 2002) VPD trends and potential impacts on vegetation, land surface evaporation, and energy budgets.