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

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

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

Sensitivity of Pan-Arctic Terrestrial Net Primary Productivity Simulations to Daily Surface Meterology From NCEP-NCAR and ERA-40 Reanalyses

We applied a terrestrial net primary production (NPP) model driven by satellite remote sensing observations of vegetation properties and daily surface meteorology from the 45-year ECMWF Re-Analysis (ERA-40) and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP-NCAR) reanalysis (NNR) to assess NPP spatial and temporal variability for the pan-Arctic basin and Alaska from 1982 to 2000. Sensitivity analysis of the production efficiency model (PEM) to uncertainties in surface meteorological inputs indicate that ERA-40 solar radiation and NNR solar radiation and surface temperatures are the primary sources of PEM-based NPP uncertainty for the region. Considerable positive bias in solar radiation inputs relative to surface observation networks resulted in overprediction of annual NPP by approximately 35.2 and 61.6% using ERA-40 and NNR inputs, respectively. Despite these uncertainties, both reanalysis products captured the major annual anomalies and trends in surface meteorology for the domain. The two reanalysis products also produced similar NPP spatial patterns for 74.7% of the domain, and similar annual anomalies and temporal trends, though there were significant regional differences particularly for Eurasia. A simple correction method based on a sensitivity experiment between reanalysis and surface station meteorological measurements produced generally consistent NPP results that were considerably smaller than PEM simulations derived from uncorrected reanalysis drivers. The results of this study identify major sources of uncertainty in reanalysis-based surface meteorology, and associated impacts on regional NPP simulations of the northern high latitudes

Satellite-based model detection of recent climate-driven changes in northern high-latitude vegetation productivity

We applied a satellite remote sensing based production efficiency model (PEM) using an integrated AVHRR and MODIS FPAR/LAI time series with a regionally corrected NCEP/NCAR reanalysis daily surface meteorology and NASA/GEWEX Surface Radiation Budget shortwave solar radiation inputs to assess annual terrestrial net primary productivity (NPP) for the pan-Arctic basin and Alaska from 1983 to 2005. Our results show that low temperature constraints on Boreal-Arctic NPP are decreasing by 0.43% per year (P \u3c 0.001), whereas a positive trend in vegetation moisture constraints of 0.49% per year (P = 0.04) are offsetting the potential benefits of longer growing seasons and contributing to recent disturbances in NPP. The PEM simulations of NPP seasonality, annual anomalies and trends are similar to stand inventory network measurements of boreal aspen stem growth (r = 0.56; P = 0.007) and atmospheric CO2 measurement based estimates of the timing of growing season onset (r = 0.78; P \u3c 0.001). Our results indicate that summer drought led to marked NPP decreases in much of the boreal forest region after the late-1990s. However, seasonal low temperatures are still a dominant limitation on regional NPP. Despite recent drought events, mean annual NPP for the pan-Arctic region showed a positive growth trend of 0.34% per year (20.27 TgC/a; P = 0.002) from 1983 to 2005. Drought induced NPP decreases may become more frequent and widespread as regional ecosystems adjust to a warmer, drier atmosphere, though the occurrence and severity of drought events will depend on future patterns of plant-available moisture

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

A satellite data driven biophysical modeling approach for estimating northern peatland and tundra CO\u3csub\u3e2\u3c/sub\u3e and CH\u3csub\u3e4\u3c/sub\u3e fluxes

The northern terrestrial net ecosystem carbon balance (NECB) is contingent on inputs from vegetation gross primary productivity (GPP) to offset the ecosystem respiration (Reco) of carbon dioxide (CO2) and methane (CH4) emissions, but an effective framework to monitor the regional Arctic NECB is lacking. We modified a terrestrial carbon flux (TCF) model developed for satellite remote sensing applications to evaluate wetland CO2 and CH4 fluxes over pan-Arctic eddy covariance (EC) flux tower sites. The TCF model estimates GPP, CO2 and CH4 emissions using in situ or remote sensing and reanalysis-based climate data as inputs. The TCF model simulations using in situ data explained \u3e70% of the r2 variability in the 8 day cumulative EC measured fluxes. Model simulations using coarser satellite (MODIS) and reanalysis (MERRA) records accounted for approximately 69% and 75% of the respective r2 variability in the tower CO2 and CH4 records, with corresponding RWSE uncertainties of 1.3 gCM-2 d-1 (CO2) and 18.2 mg Cm-2 d-1 (CH4). Although the estimated annual CH4 emissions were small (gCm-2 yr-1) relative to Reco (\u3e180 gCm-2 yr-1), they reduced the across-site NECB by 23%and contributed to a global warming potential of approximately 165±128 gCO2eqm−2 yr−1 when considered over a 100 year time span. This model evaluation indicates a strong potential for using the TCF model approach to document landscape-scale variability in CO2 and CH4 fluxes, and to estimate the NECB for northern peatland and tundra ecosystems

An assessment of the carbon balance of Arctic tundra:Comparisons among observations, process models, and atmospheric inversions

Although Arctic tundra has been estimated to cover only 8% of the global land surface, the large and potentially labile carbon pools currently stored in tundra soils have the potential for large emissions of carbon (C) under a warming climate. These emissions as radiatively active greenhouse gases in the form of both CO<sub>2</sub> and CH<sub>4</sub> could amplify global warming. Given the potential sensitivity of these ecosystems to climate change and the expectation that the Arctic will experience appreciable warming over the next century, it is important to assess whether responses of C exchange in tundra regions are likely to enhance or mitigate warming. In this study we compared analyses of C exchange of Arctic tundra between 1990 and 2006 among observations, regional and global applications of process-based terrestrial biosphere models, and atmospheric inversion models. Syntheses of flux observations and inversion models indicate that the annual exchange of CO<sub>2</sub> between Arctic tundra and the atmosphere has large uncertainties that cannot be distinguished from neutral balance. The mean estimate from an ensemble of process-based model simulations suggests that Arctic tundra has acted as a sink for atmospheric CO<sub>2</sub> in recent decades, but based on the uncertainty estimates it cannot be determined with confidence whether these ecosystems represent a weak or a strong sink. Tundra was 0.6 °C warmer in the 2000s compared to the 1990s. The central estimates of the observations, process-based models, and inversion models each identify stronger sinks in the 2000s compared with the 1990s. Some of the process models indicate that this occurred because net primary production increased more in response to warming than heterotrophic respiration. Similarly, the observations and the applications of regional process-based models suggest that CH<sub>4</sub> emissions from Arctic tundra have increased from the 1990s to 2000s because of the sensitivity of CH<sub>4</sub> emissions to warmer temperatures. Based on our analyses of the estimates from observations, process-based models, and inversion models, we estimate that Arctic tundra was a sink for atmospheric CO<sub>2</sub> of 110 Tg C yr<sup>−1</sup> (uncertainty between a sink of 291 Tg C yr<sup>−1</sup> and a source of 80 Tg C yr<sup>−1</sup>) and a source of CH<sub>4</sub> to the atmosphere of 19 Tg C yr<sup>−1</sup> (uncertainty between sources of 8 and 29 Tg C yr<sup>−1</sup>). The suite of analyses conducted in this study indicate that it is important to reduce uncertainties in the observations, process-based models, and inversions in order to better understand the degree to which Arctic tundra is influencing atmospheric CO<sub>2</sub> and CH<sub>4</sub> concentrations. The reduction of uncertainties can be accomplished through (1) the strategic placement of more CO<sub>2</sub> and CH<sub>4</sub> monitoring stations to reduce uncertainties in inversions, (2) improved observation networks of ground-based measurements of CO<sub>2</sub> and CH<sub>4</sub> exchange to understand exchange in response to disturbance and across gradients of climatic and hydrological variability, and (3) the effective transfer of information from enhanced observation networks into process-based models to improve the simulation of CO<sub>2</sub> and CH<sub>4</sub> exchange from Arctic tundra to the atmosphere

Testing the applicability of neural networks as a gap-filling method using CH4 flux data from high latitude wetlands

Peer reviewe

Darkness visible: reflections on underground ecology

1 Soil science and ecology have developed independently, making it difficult for ecologists to contribute to urgent current debates on the destruction of the global soil resource and its key role in the global carbon cycle. Soils are believed to be exceptionally biodiverse parts of ecosystems, a view confirmed by recent data from the UK Soil Biodiversity Programme at Sourhope, Scotland, where high diversity was a characteristic of small organisms, but not of larger ones. Explaining this difference requires knowledge that we currently lack about the basic biology and biogeography of micro-organisms. 2 It seems inherently plausible that the high levels of biological diversity in soil play some part in determining the ability of soils to undertake ecosystem-level processes, such as carbon and mineral cycling. However, we lack conceptual models to address this issue, and debate about the role of biodiversity in ecosystem processes has centred around the concept of functional redundancy, and has consequently been largely semantic. More precise construction of our experimental questions is needed to advance understanding. 3 These issues are well illustrated by the fungi that form arbuscular mycorrhizas, the Glomeromycota. This ancient symbiosis of plants and fungi is responsible for phosphate uptake in most land plants, and the phylum is generally held to be species-poor and non-specific, with most members readily colonizing any plant species. Molecular techniques have shown both those assumptions to be unsafe, raising questions about what factors have promoted diversification in these fungi. One source of this genetic diversity may be functional diversity. 4 Specificity of the mycorrhizal interaction between plants and fungi would have important ecosystem consequences. One example would be in the control of invasiveness in introduced plant species: surprisingly, naturalized plant species in Britain are disproportionately from mycorrhizal families, suggesting that these fungi may play a role in assisting invasion. 5 What emerges from an attempt to relate biodiversity and ecosystem processes in soil is our extraordinary ignorance about the organisms involved. There are fundamental questions that are now answerable with new techniques and sufficient will, such as how biodiverse are natural soils? Do microbes have biogeography? Are there rare or even endangered microbes