Upscaling methane emission hotspots in boreal peatlands

Upscaling the properties and the effects of small-scale surface heterogeneities to larger scales is a challenging issue in land surface modeling. We developed a novel approach to upscale local methane emissions in a boreal peatland from the micro-topographic scale to the landscape-scale. We based this new parameterization on the analysis of the water table pattern generated by the Hummock–Hollow model, a micro-topography resolving model for peatland hydrology. We introduce this parameterization of methane hotspots in a global model-like version of the Hummock–Hollow model, that underestimates methane emissions. We tested the robustness of the parameterization by simulating methane emissions for the next century forcing the model with three different RCP scenarios. The Hotspot parameterization, despite being calibrated for the 1976–2005 climatology, mimics the output of the micro-topography resolving model for all the simulated scenarios. The new approach bridges the scale gap of methane emissions between this version of the model and the configuration explicitly resolving micro-topography

Bulk partitioning the growing season net ecosystem exchange of CO<sub>2</sub> in Siberian tundra reveals the seasonality of its carbon sequestration strength

This paper evaluates the relative contribution of light and temperature on net ecosystem CO2 uptake during the 2006 growing season in a polygonal tundra ecosystem in the Lena River Delta in Northern Siberia (72°22´ N, 126°30´ E). The occurrence and frequency of warm periods may be an important determinant of the magnitude of the ecosystem's carbon sink function, as they drive temperature-induced changes in respiration. Hot spells during the early portion of the growing season, when the photosynthetic apparatus of vascular plants is not fully developed, are shown to be more influential in creating positive mid-day surface-to-atmosphere net ecosystem CO2 exchange fluxes than those occurring later in the season. In this work we also develop and present a multi-step bulk flux partition model to better account for tundra plant physiology and the specific light conditions of the arctic region. These conditions preclude the successful use of traditional partition methods that derive a respiration–temperature relationship from all nighttime data or from other bulk approaches that are insensitive to temperature or light stress. Nighttime growing season measurements are rare during the arctic summer, however, so the new method allows for temporal variation in the parameters describing both ecosystem respiration and gross uptake by fitting both processes at the same time. Much of the apparent temperature sensitivity of respiration seen in the traditional partition method is revealed in the new method to reflect seasonal changes in basal respiration rates. Understanding and quantifying the flux partition is an essential precursor to describing links between assimilation and respiration at different timescales, as it allows a more confident evaluation of measured net exchange over a broader range of environmental conditions. The growing season CO2 sink estimated by this study is similar to those reported previously for this site, and is substantial enough to withstand the long, low-level respiratory CO2 release during the rest of the year to maintain the site's CO2 sink function on an annual basis

Substantial hysteresis in emergent temperature sensitivity of global wetland CH₄ emissions

Wetland methane (CH4) emissions (FCH4 ) are important in global carbon budgets and climate change assessments. Currently, FCH4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent FCH4 temperature dependence across spatial scales for use in models; however, sitelevel studies demonstrate that FCH4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between FCH4 and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between FCH4 and temperature, suggesting larger FCH4 sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.s

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4_{4} emissions

Wetland methane (CH$_{4}$) emissions (F$_{CH_{4}}$) are important in global carbon budgets and climate change assessments. Currently, F$_{CH_{4}}$ projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent F$_{CH_{4}}$ temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that F$_{CH_{4}}$ are often controlled by factors beyond temperature. Here, we evaluate the relationship between F$_{CH_{4}}$ and temperature using observations from the FLUXNET-CH$_{4}$ database. Measurements collected across the globe show substantial seasonal hysteresis between F$_{CH_{4}}$ and temperature, suggesting larger F$_{CH_{4}}$ sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH$_{4}$ production are thus needed to improve global CH$_{4}$ budget assessments

The biophysical climate mitigation potential of boreal peatlands during the growing season

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests-the dominant boreal forest type-and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a similar to 20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 degrees C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (similar to 45 degrees N) and decrease toward the northern limit of the boreal biome (similar to 70 degrees N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.Peer reviewe

Golden Rule of Forecasting: Be Conservative

This article proposes a unifying theory, or the Golden Rule, or forecasting. The Golden Rule of Forecasting is to be conservative. A conservative forecast is consistent with cumulative knowledge about the present and the past. To be conservative, forecasters must seek out and use all knowledge relevant to the problem, including knowledge of methods validated for the situation. Twenty-eight guidelines are logically deduced from the Golden Rule. A review of evidence identified 105 papers with experimental comparisons; 102 support the guidelines. Ignoring a single guideline increased forecast error by more than two-fifths on average. Ignoring the Golden Rule is likely to harm accuracy most when the situation is uncertain and complex, and when bias is likely. Non-experts who use the Golden Rule can identify dubious forecasts quickly and inexpensively. To date, ignorance of research findings, bias, sophisticated statistical procedures, and the proliferation of big data, have led forecasters to violate the Golden Rule. As a result, despite major advances in evidence-based forecasting methods, forecasting practice in many fields has failed to improve over the past half-century

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions

Wetland methane (CH4) emissions (FCH4) are important in global carbon budgets and climate change assessments. Currently, FCH4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent FCH4 temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that FCH4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between FCH4 and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between FCH4 and temperature, suggesting larger FCH4 sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments. Wetland methane emissions contribute to global warming, and are oversimplified in climate models. Here the authors use eddy covariance measurements from 48 global sites to demonstrate seasonal hysteresis in methane-temperature relationships and suggest the importance of microbial processes.Peer reviewe

FLUXNET-CH₄ synthesis activity: objectives, observations, and future directions

We describe a new coordination activity and initial results for a global synthesis of eddy covariance CH4 flux measurements