Lakes have been highlighted as one of the largest natural sources of the greenhouse gas methane (CH₄) to the atmosphere. However, global estimates of lake CH₄ fluxes over the last 20 years exhibit widely different results ranging from 6 to 185 Tg CH₄ yr⁻¹, which is to a large extent driven by differences in lake areas and thaw season lengths used. This has generated uncertainty regarding both lake fluxes and the global CH₄ budget. This study constrains global lake water CH₄ emissions by using new information on lake area and distribution and CH₄ fluxes distinguished by major emission pathways; ecoclimatic lake type; satellite‐derived ice‐free emission period length; and diel‐ and temperature‐related seasonal flux corrections. We produced gridded data sets at 0.25° latitude × 0.25° longitude spatial resolution, representing daily emission estimates over a full annual climatological cycle, appropriate for use in global CH₄ budget estimates, climate and Earth System Models, bottom‐up biogeochemical models, and top‐down inverse model simulations. Global lake CH₄ fluxes are 41.6 ± 18.3 Tg CH₄ yr⁻¹ with approximately 50% of the flux contributed by tropical/subtropical lakes. Strong temperature‐dependent flux seasonality and satellite‐derived freeze/thaw dynamics limit emissions at high latitudes. The primary emission pathway for global annual lake fluxes is ebullition (23.4 Tg) followed by diffusion (14.1 Tg), ice‐out and spring water‐column turnover (3.1 Tg), and fall water‐column turnover (1.0 Tg). These results represent a major contribution to reconciling differences between bottom‐up and top‐town estimates of inland aquatic system emissions in the global CH₄ budget.

Inland aquatic systems, such as reservoirs, contribute substantially to global methane (CH₄) emissions; yet are among the most uncertain components of the total CH₄ budget. Reservoirs have received recent attention as they may generate high CH₄ fluxes. Improved quantification of these CH₄ fluxes, particularly their spatiotemporal distribution, is key to realistically incorporating them in CH₄ modeling and budget studies. Here we report on a new global, gridded (0.25° lat × 0.25° lon) study of reservoir CH₄ emissions, accounting for new knowledge regarding reservoir areal extent and distribution, and spatiotemporal emission patterns influenced by diurnal variability, temperature‐dependent seasonality, satellite‐derived freeze‐thaw dynamics, and eco‐climatic zone. The results of this new data set comprise daily CH₄ emissions throughout the full annual cycle and show that reservoirs cover 297 × 10³ km² globally and emit 10.1 Tg CH₄ yr⁻¹ (1σ uncertainty range of 7.2–12.9 Tg CH₄ yr⁻¹) from diffusive (1.2 Tg CH₄ yr⁻¹) and ebullitive (8.9 Tg CH₄ yr⁻¹) emission pathways. This analysis of reservoir CH₄ emission addresses multiple gaps and uncertainties in previous studies and represents an important contribution to studies of the global CH₄ budget. The new data sets and methodologies from this study provide a framework to better understand and model the current and future role of reservoirs in the global CH₄ budget and to guide efforts to mitigate reservoir‐related CH₄ emissions.

Methane (CH₄) is emitted from lakes by several processes: bubbles released from bottom sediments that reach the atmosphere (ebullition); spring release of CH₄ trapped in bubbles in and under the ice during fall freeze (bubble release), and diffusion of CH₄ from sediments to the surface. Each of these emission routes is highly variable over space and time, and episodic in the extreme, making reliable measurements difficult to carry out. However, lakes are receiving increasing interest for their important contribution to global CH₄ emissions. Their area, distribution and emissions respond to interannual and longer-term climate fluctuations and close to half the world’s lake area is in high northern latitudes that are experiencing rapidly-warming temperatures and lengthening thaw periods. We report on a new spatially-explicit data set of lakes > 50°N, classified with methane-relevant criteria. The seasonality of daily CH₄ fluxes is driven with satellite observations of thaw timing and duration. We found that observed thaw seasons are 10–30% shorter than those assumed in previous studies. The area of lakes is 1,095 × 10³ km² and total CH₄ emission is 13.8–17.7 Tg CH₄ year⁻¹: 11.2–14.4 Tg via diffusion and ebullition and 2.6–3.3 Tg from spring release of CH₄ stored in bubbles in winter lake ice. This novel suite of data and methodologies provides a unique framework to model CH₄ emission from lakes under current, past and future climates.

This study assesses the impact of different state of the art global biospheric CO₂ flux models, when applied as prior information, on inverse model “top-down” estimates of terrestrial CO₂ fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of observing system simulation experiments (OSSEs) using synthetic CO₂ column-average dry air mole fraction (XCO₂) retrievals sampled at the OCO-2 satellite spatiotemporal frequency. The OSSEs utilized a 4-D variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO₂ net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the “truth”. Results show that the assimilation of simulated XCO₂ retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce “true” NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in “bottom-up” NEE fluxes. Seasonally averaged posterior NEE estimates had standard deviations (SD) of ∼10 % to ∼50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥0.5 PgC yr⁻¹). On a global average, the seasonally averaged residual impact of the prior model NEE assumption on the posterior NEE spread is ∼10 %–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger than prior flux values in some regions/times in the tropics and Southern Hemisphere where sufficient OCO-2 data were available and large differences between the prior and truth were evident. Overall, even with the availability of spatiotemporally dense OCO-2 data, noticeable residual differences (up to ∼20 %–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.