The Analytical Objective Hysteresis Model (AnOHM v1.0): methodology to determine bulk storage heat flux coefficients

he net storage heat flux is not only a large part of the urban surface energy balance (SEB) but its determination remains a significant challenge. The diurnal hysteresis behaviour found between the net storage heat flux (ΔQS) and net all-wave radiation (Q*) has been captured in the Objective Hysteresis Model (OHM) parametrization of ΔQS. Although, successfully used in urban areas, the limited availability of coefficients for OHM hampers application. To facilitate use, and enhance physical interpretations of the OHM coefficients, an analytical solution of the 1-dimensional advection-diffusion equation of coupled heat and liquid water transport in conjunction with the SEB is conducted, allowing development of AnOHM (Analytical Objective Hysteresis Model). A sensitivity test of AnOHM to surface properties and hydrometeorological forcing is undertaken using a stochastic approach (the Subset Simulation). From this albedo, Bowen ratio and bulk transfer coefficient, solar radiation and wind speed are identified as being critical. AnOHM, driven by local meteorological conditions at five different land use areas, is shown to simulate the ΔQS flux well (RMSE values of ~30 W m−2). The intra-annual dynamics of OHM coefficients to are explored which offers significant potential to enhance modelling of the surface energy balance over a wider range of conditions

Increased CO₂ loss from vegetated drained lake tundra ecosystems due to flooding

Tundra ecosystems are especially sensitive to climate change, which is particularly rapid in high northern latitudes resulting in significant alterations in temperature and soil moisture. Numerous studies have demonstrated that soil drying increases the respiration loss from wet Arctic tundra. And, warming and drying of tundra soils are assumed to increase CO2 emissions from the Arctic. However, in this water table manipulation experiment (i.e., flooding experiment), we show that flooding of wet tundra can also lead to increased CO2 loss. Standing water increased heat conduction into the soil, leading to higher soil temperature, deeper thaw and, surprisingly, to higher CO2 loss in the most anaerobic of the experimental areas. The study site is located in a drained lake basin, and the soils are characterized by wetter conditions than upland tundra. In experimentally flooded areas, high wind speeds (greater than ~4 m s−1) increased CO2 emission rates, sometimes overwhelming the photosynthetic uptake, even during daytime. This suggests that CO2 efflux from C rich soils and surface waters can be limited by surface exchange processes. The comparison of the CO2 and CH4 emission in an anaerobic soil incubation experiment showed that in this ecosystem, CO2 production is an order of magnitude higher than CH4 production. Future increases in surface water ponding, linked to surface subsidence and thermokarst erosion, and concomitant increases in soil warming, can increase net C efflux from these arctic ecosystems

Microbial community structure and soil pH correspond to methane production in Arctic Alaska soils

While there is no doubt that biogenic methane production in the Arctic is an important aspect of global methane emissions, the relative roles of microbial community characteristics and soil environmental conditions in controlling Arctic methane emissions remains uncertain. Here, relevant methane‐cycling microbial groups were investigated at two remote Arctic sites with respect to soil potential methane production (PMP). Percent abundances of methanogens and iron‐reducing bacteria correlated with increased PMP, while methanotrophs correlated with decreased PMP. Interestingly, α‐diversity of the methanogens was positively correlated with PMP, while β‐diversity was unrelated to PMP. The β‐diversity of the entire microbial community, however, was related to PMP. Shannon diversity was a better correlate of PMP than Simpson diversity across analyses, while rarefied species richness was a weak correlate of PMP. These results demonstrate the following: first, soil pH and microbial community structure both probably control methane production in Arctic soils. Second, there may be high functional redundancy in the methanogens with regard to methane production. Third, iron‐reducing bacteria co‐occur with methanogens in Arctic soils, and iron‐reduction‐mediated effects on methanogenesis may be controlled by α‐ and β‐diversity. And finally, species evenness and rare species abundances may be driving relationships between microbial groups, influencing Arctic methane production

Temperature Response of Respiration Across the Heterogeneous Landscape of the Alaskan Arctic Tundra

AbstractPredictions of the response of ecosystem respiration to warming in the Arctic are not well constrained, partly due to the considerable spatial heterogeneity of these permafrost‐dominated areas. Accurate calculations of in situ temperature sensitivities of respiration (Q10) are vital for the prediction of future Arctic emissions. To understand the impact of spatial heterogeneity on respiration rates and Q10, we compared respiration measured from automated chambers across the main local polygonized landscape forms (high and low centers, polygon rims, polygon troughs) to estimates from the flux‐partitioned net ecosystem exchange collected in an adjacent eddy covariance tower. Microtopographic type appears to be the most important variable explaining the variability in respiration rates, and low‐center polygons and polygon troughs show the greatest cumulative respiration rates, possibly linked to their deeper thaw depth and higher plant biomass. Regardless of the differences in absolute respiration rates, Q10 is surprisingly similar across all microtopographic features, possibly indicating a similar temperature limitation to decomposition across the landscape. Q10 was higher during the colder early summer and lower during the warmer peak growing season, consistent with an elevated temperature sensitivity under colder conditions. The respiration measured by the chambers and the estimates from the daytime flux‐partitioned eddy covariance data were within uncertainties during early and peak seasons but overestimated respiration later in the growing season. Overall, this study suggests that it is possible to simplify estimates of the temperature sensitivity of respiration across heterogeneous landscapes but that seasonal changes in Q10 should be incorporated into model simulations

A yearlong comparison of plot‐scale and satellite footprint‐scale 19 and 37 GHz brightness of the Alaskan North Slope

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95289/1/jgrd9836.pd

Tundra water budget and implications of precipitation underestimation

Difficulties in obtaining accurate precipitation measurements have limited meaningful hydrologic assessment for over a century due to performance challenges of conventional snowfall and rainfall gauges in windy environments. Here, we compare snowfall observations and bias adjusted snowfall to end-of-winter snow accumulation measurements on the ground for 16 years (1999–2014) and assess the implication of precipitation underestimation on the water balance for a low-gradient tundra wetland near Utqiagvik (formerly Barrow), Alaska (2007–2009). In agreement with other studies, and not accounting for sublimation, conventional snowfall gauges captured 23–56% of end-of-winter snow accumulation. Once snowfall and rainfall are bias adjusted, long-term annual precipitation estimates more than double (from 123 to 274 mm), highlighting the risk of studies using conventional or unadjusted precipitation that dramatically under-represent water balance components. Applying conventional precipitation information to the water balance analysis produced consistent storage deficits (79 to 152 mm) that were all larger than the largest actual deficit (75 mm), which was observed in the unusually low rainfall summer of 2007. Year-to-year variability in adjusted rainfall (±33 mm) was larger than evapotranspiration (±13 mm). Measured interannual variability in partitioning of snow into runoff (29% in 2008 to 68% in 2009) in years with similar end-of-winter snow accumulation (180 and 164 mm, respectively) highlights the importance of the previous summer's rainfall (25 and 60 mm, respectively) on spring runoff production. Incorrect representation of precipitation can therefore have major implications for Arctic water budget descriptions that in turn can alter estimates of carbon and energy fluxes

Methane fluxes during the initiation of a large-scale water table manipulation experiment in the Alaskan Arctic tundra

Much of the 191.8 Pg C in the upper 1 m of Arctic soil of Arctic soil organic mater is, or is at risk of, being released to the atmosphere as CO2 and/or CH4. Global warming will further alter the rate of emission of these gases to the atmosphere. Here we quantify the effect of major environmental variables affected by global climate change on CH4 fluxes in the Alaskan Arctic. Soil temperature best predicts CH4 fluxes and explained 89% of the variability in CH4 emissions. Water table depth has a nonlinear impact on CH4 efflux. Increasing water table height above the surface retards CH4 efflux. Decreasing water table depth below the surface has a minor effect on CH4 release once an aerobic layer is formed at the surface. In contrast with several other studies, we found that CH4 emissions are not driven by net ecosystem exchange (NEE) and are not limited by labile carbon supply

Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling

The Arctic is warming at twice the rate of the global mean. This warming could further stimulate methane (CH4) emissions from northern wetlands and enhance the greenhouse impact of this region. Arctic wetlands are extremely heterogeneous in terms of geochemistry, vegetation, microtopography, and hydrology, and therefore CH4 fluxes can differ dramatically within the metre scale. Eddy covariance (EC) is one of the most useful methods for estimating CH4 fluxes in remote areas over long periods of time. However, when the areas sampled by these EC towers (i.e. tower footprints) are by definition very heterogeneous, due to encompassing a variety of environmental conditions and vegetation types, modelling environmental controls of CH4 emissions becomes even more challenging, confounding efforts to reduce uncertainty in baseline CH4 emissions from these landscapes. In this study, we evaluated the effect of footprint variability on CH4 fluxes from two EC towers located in wetlands on the North Slope of Alaska. The local domain of each of these sites contains well developed polygonal tundra as well as a drained thermokarst lake basin. We found that the spatiotemporal variability of the footprint, has a significant influence on the observed CH4 fluxes, contributing between 3% and 33% of the variance, depending on site, time period, and modelling method. Multiple indices were used to define spatial heterogeneity, and their explanatory power varied depending on site and season. Overall, the normalised difference water index had the most consistent explanatory power on CH4 fluxes, though generally only when used in concert with at least one other spatial index. The spatial bias (defined here as the difference between the mean for the 0.36 km2 domain around the tower and the footprint-weighted mean) was between mid51mid% and mid18mid% depending on the index. This study highlights the need for footprint modelling to infer the representativeness of the carbon fluxes measured by EC towers in these highly heterogeneous tundra ecosystems, and the need to evaluate spatial variability when upscaling EC site-level data to a larger domain

Effect of thaw depth on fluxes of CO2 and CH4 in manipulated Arctic coastal tundra of Barrow, Alaska

The manipulation treatment consisted of draining, controlling, and flooding treated sections by adjusting standing water. Inundation increased CH4 emission by a factor of 4.3 compared to non-flooded sections. This may be due to the decomposition of organic matter under a limited oxygen environment by saturated standing water. On the other hand, CO2 emission in the dry section was 3.9-fold higher than in others. CH4 emission tends to increase with deeper thaw depth, which strongly depends on the water table; however, CO2 emission is not related to thaw depth. Quotients of global warming potential (GWPCO2) (dry/control) and GWPCH4 (wet/control) increased by 464 and 148 %, respectively, and GWPCH4 (dry/control) declined by 66 %. This suggests that CO2 emission in a drained section is enhanced by soil and ecosystem respiration, and CH4 emission in a flooded area is likely stimulated under an anoxic environment by inundated standing water. The findings of this manipulation experiment during the autumn period demonstrate the different production processes of CO2 and CH4, as well as different global warming potentials, coupled with change in thaw depth. Thus the outcomes imply that the expansion of tundra lakes leads the enhancement of CH4 release, and the disappearance of the lakes causes the stimulated CO2 production in response to the Arctic climate change.This research was conducted under the JAMSTEC-IARC Collaboration Study with funding provided by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) under a grant to the International Arctic Research Center (IARC)

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 thespatial 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