Arctic terrestrial ecosystems are major global sources of methane (CH 4 ); hence, it is important to understand the seasonal and climatic controls on CH 4 emissions from these systems. Here, we report year-round CH 4 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 CH 4 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 CH 4 emissions are enhanced when the duration is extended by a deep thawed layer as can occur with thick snow cover. Regional scale fluxes of CH 4 derived from aircraft data demonstrate the large spatial extent of late season CH 4 emissions. Scaled to the circumpolar Arctic, cold season fluxes from tundra total 12 ± 5 (95% confidence interval) Tg CH 4 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 CH 4 emissions will result from observed and predicted increases in snow thickness, active layer depth, and soil temperature, representing important positive feedbacks on climate warming.permafrost | aircraft | fall | winter | warming E missions of methane (CH 4 ) from Arctic terrestrial ecosystems could increase dramatically in response to climate change (1-3), a potentially significant positive feedback on climate warming. High latitudes have warmed at a rate almost two times faster than the Northern Hemisphere mean over the past century, with the most intense warming in the colder seasons (4) [up to 4°C in winter in 30 y (5)]. Poor understanding of controls on CH 4 emissions outside of the summer season (6-10) represents a large source of uncertainty for the Arctic CH 4 budget. Warmer air temperatures and increased snowfall can potentially increase soil temperatures and deepen the seasonal thawed layer, stimulating CH 4 and CO 2 emissions from the vast stores of labile organic matter in the Arctic (11). The overwhelming majority of prior studies of CH 4 fluxes in the Arctic have been carried out during the summer months (12-15). However, the fall, winter, and spring months represent 70-80% of the year in the Arctic and have been shown to have significant emissions of CO 2 (16-18). The few measurements of CH 4 fluxes in the Arctic that extend into the fall (6, 7, 9, 10) show complex patterns of CH 4 emissions, with a number indicating high fluxes (7, 10). Winter and early spring data appear to be absent in Arctic tundra over continuous permafrost.Beginning usually in late August or early September, the...

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We determined methane (CH 4 ) emissions from Alaska using airborne measurements from the Carbon Arctic Reservoirs Vulnerability Experiment (CARVE). Atmospheric sampling was conducted between May and September 2012 and analyzed using a customized version of the polar weather research and forecast model linked to a Lagrangian particle dispersion model (stochastic timeinverted Lagrangian transport model). We estimated growing season CH 4 fluxes of 8 ± 2 mg CH 4 ·m −2 ·d −1 averaged over all of Alaska, corresponding to fluxes from wetlands of 56·d −1 if we assumed that wetlands are the only source from the land surface (all uncertainties are 95% confidence intervals from a bootstrapping analysis). Fluxes roughly doubled from May to July, then decreased gradually in August and September. Integrated emissions totaled 2.1 ± 0.5 Tg CH 4 for Alaska from May to September 2012, close to the average (2.3; a range of 0.7 to 6 Tg CH 4 ) predicted by various land surface models and inversion analyses for the growing season. Methane emissions from boreal Alaska were larger than from the North Slope; the monthly regional flux estimates showed no evidence of enhanced emissions during early spring or late fall, although these bursts may be more localized in time and space than can be detected by our analysis. These results provide an important baseline to which future studies can be compared.

'1'hc smsitivitics of wind direction signals i)) ]Jassivc microwal'c brightness temperatures of sea surfaces to wind slwccl, incidcncc angle, polarization, and frequency are prwmted in this paper. '1'l)c cx]witncntal data were accluircd from ,a series of aircraft flights fro:n 1994 through 1996 by the Jet l'ropulsiorl Laboratory (JPL) using JP1i 19 and 37 G1lz polaritnetric radiometers (WINDRAI1). I'ouricr analysis of the data versus }vind dirwtiorl was carried out ancl the cocfficimts of Fourier scricx arc illustrated agaiust the wind speed at 45°, 55°, aud 65° incidmcc angles. Thm is a good agreement Mwccm the J1'L aimaft flight data and M'cntz's SSIVI/1 geophysical mode] fuuction for the vertically polarized brightnms tcmpcraturcs, but Wmtz's SSM/I wind direction model for horizontal polarization shows a significantly strollgcr upwind and clownwitld asymmetry than the aircraft flight data. Com~)ariso]l of the dual-frcqumcy WINI)RAIl data shows that, the wind direction signals arc similar at 19 and 37 GHz, although the 37 GIIz data have slightly strollgcr sigmds tllau the 19 GIIz data. in gmcral, tllc azimuthal variations of brightness tmn~m-aturcs irm-ease with increasing wind sped from low' to lllOdC1atC willds, thml ]c'w] off and decrease at ]ligh wiuds. Tllc only mcq)tion is the t] mcasure]nmlt,s at 65° iucidcnce angle, which haw a st rongm than expected sigllal at lo}v winds. An cxponcmtial function was ~)roposcd to model the scnwitivitics of wind direction signals to wind S] MWCIS. The coefflcicllts of the em~)irical model are j)rovidcd ill this pa]mr and am useful for the simulation of ocean bright]lms tcm]maturcs ancl for the clcve.lopmmt of gmphysical retrieval algorithms.