A toy model for estimating N2O emissions from natural soils

A model of N2O emissions from natural soils, whose ultimate objective is to evaluate what contribution natural ecosystems make to the global N2O budget and how the contribution would change with global change, is presented. Topics covered include carbon and nitrogen available in the soil, delivery of nitrifiable N, soil water and oxygen status, soil water budget model, effects of drainage, nitrification and denitrification potentials, soil fertility, N2O production, and a model evaluation. A major implication of the toy model is that the tropics account for more than 80 percent of global emission

The carbon cycle revisited

Discussions during the Global Change Institute indicated a need to present, in some detail and as accurately as possible, our present knowledge about the carbon cycle, the uncertainties in this knowledge, and the reasons for these uncertainties. We discuss basic issues of internal consistency within the carbon cycle, and end by summarizing the key unknowns

Rice cultivation and methane emission: Documentation of distributed geographic data sets

High-resolution global data bases on the geographic and seasonal distribution of rice cultivation and associated methane emission, compiled by Matthews et al., were archived for public use. In addition to the primary data sets identifying location, seasonality, and methane emission from rice cultivation, a series of supporting data sets is included, allowing users not only to replicate the work of Matthews et al. but to investigate alternative cultivation and emission scenarios. The suite of databases provided, at 1 latitude by 1 longitude resolution for the globe, includes (1) locations of rice cultivation, (2) monthly arrays of actively growing rice areas, (3) countries and political subdivisions, and (4) monthly arrays of methane emission from rice cultivation. Ancillary data include (1) a listing, by country, of harvested rice areas and seasonal distribution of crop cycles and (2) country names and codes. Summary tables of zonal/monthly distributions of actively growing rice areas and of methane emissions are presented. Users should consult original publications for complete discussion of the data bases. This short paper is designed only to document formats of the distributed information and briefly describe the contents of the data sets and their initial application to evaluating the role of rice cultivation in the methane budget

Changes in the Phase of the Annual Cycle of Surface Temperature

The annual cycle in the Earth's surface temperature is extremely large—comparable in magnitude to the glacial–interglacial cycles over most of the planet. Trends in the phase and the amplitude of the annual cycle have been observed, but the causes and significance of these changes remain poorly understood—in part because we lack an understanding of the natural variability. Here we show that the phase of the annual cycle of surface temperature over extratropical land shifted towards earlier seasons by 1.7 days between 1954 and 2007; this change is highly anomalous with respect to earlier variations, which we interpret as being indicative of the natural range. Significant changes in the amplitude of the annual cycle are also observed between 1954 and 2007. These shifts in the annual cycles appear to be related, in part, to changes in the northern annular mode of climate variability, although the land phase shift is significantly larger than that predicted by trends in the northern annular mode alone. Few of the climate models presented by the Intergovernmental Panel on Climate Change reproduce the observed decrease in amplitude and none reproduce the shift towards earlier seasons.Earth and Planetary Science

Natural variability in a stable, 1000-yr global coupled climate-carbon cycle simulation

Author Posting. © American Meteorological Society 2006. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 19 (2006): 3033–3054, doi:10.1175/JCLI3783.1.A new 3D global coupled carbon–climate model is presented in the framework of the Community Climate System Model (CSM-1.4). The biogeochemical module includes explicit land water–carbon coupling, dynamic carbon allocation to leaf, root, and wood, prognostic leaf phenology, multiple soil and detrital carbon pools, oceanic iron limitation, a full ocean iron cycle, and 3D atmospheric CO2 transport. A sequential spinup strategy is utilized to minimize the coupling shock and drifts in land and ocean carbon inventories. A stable, 1000-yr control simulation [global annual mean surface temperature ±0.10 K and atmospheric CO2 ± 1.2 ppm (1σ)] is presented with no flux adjustment in either physics or biogeochemistry. The control simulation compares reasonably well against observations for key annual mean and seasonal carbon cycle metrics; regional biases in coupled model physics, however, propagate clearly into biogeochemical error patterns. Simulated interannual-to-centennial variability in atmospheric CO2 is dominated by terrestrial carbon flux variability, ±0.69 Pg C yr−1 (1σ global net annual mean), which in turn reflects primarily regional changes in net primary production modulated by moisture stress. Power spectra of global CO2 fluxes are white on time scales beyond a few years, and thus most of the variance is concentrated at high frequencies (time scale 20 yr), global net ocean CO2 flux is strongly anticorrelated (0.7–0.95) with the net CO2 flux from land; the ocean tends to damp (20%–25%) slow variations in atmospheric CO2 generated by the terrestrial biosphere. The intrinsic, unforced natural variability in land and ocean carbon storage is the “noise” that complicates the detection and mechanistic attribution of contemporary anthropogenic carbon sinks.This work was supported by NCAR, NSF ATM-9987457, NASA EOS-IDS Grant NAG5-9514, NASA Carbon Cycle Program Grant NAG5-11200, Lawrence Berkeley National Laboratory LDRD, and the WHOI Ocean and Climate Change Institute

Extreme events driving year-to-year differences in gross primary productivity across the US

Solar-Induced chlorophyll Fluorescence (SIF) has previously been shown to strongly correlate with gross primary productivity (GPP), however this relationship has not yet been quantified for the recently launched TROPOspheric Monitoring Instrument (TROPOMI). Here we use a Gaussian mixture model to develop a parsimonious relationship between SIF from TROPOMI and GPP from flux towers across the conterminous United States (CONUS). The mixture model indicates the SIF-GPP relationship can be characterized by a linear model with two terms. We then estimate GPP across CONUS at 500-m spatial resolution over a 16-day moving window. We find that CONUS GPP varies by less than 4% between 2018 and 2019. However, we observe four extreme precipitation events that induce regional GPP anomalies: drought in west Texas, flooding in the midwestern US, drought in South Dakota, and drought in California. Taken together, these events account for 28% of the year-to-year GPP differences across CONUS

Extreme events driving year-to-year differences in gross primary productivity across the US

Solar-Induced chlorophyll Fluorescence (SIF) has previously been shown to strongly correlate with gross primary productivity (GPP), however this relationship has not yet been quantified for the recently launched TROPOspheric Monitoring Instrument (TROPOMI). Here we use a Gaussian mixture model to develop a parsimonious relationship between SIF from TROPOMI and GPP from flux towers across the conterminous United States (CONUS). The mixture model indicates the SIF-GPP relationship can be characterized by a linear model with two terms. We then estimate GPP across CONUS at 500-m spatial resolution over a 16-day moving window. We find that CONUS GPP varies by less than 4% between 2018 and 2019. However, we observe four extreme precipitation events that induce regional GPP anomalies: drought in west Texas, flooding in the midwestern US, drought in South Dakota, and drought in California. Taken together, these events account for 28% of the year-to-year GPP differences across CONUS

A double peak in the seasonality of California's photosynthesis as observed from space

Solar-induced chlorophyll fluorescence (SIF) has been shown to be a powerful proxy for photosynthesis and gross primary productivity (GPP). The recently launched TROPOspheric Monitoring Instrument (TROPOMI) features the required spectral resolution and signal-to-noise ratio to retrieve SIF from space. Here, we present a downscaling method to obtain 500 m spatial resolution SIF over California. We report daily values based on a 14 d window. TROPOMI SIF data show a strong correspondence with daily GPP estimates at AmeriFlux sites across multiple ecosystems in California. We find a linear relationship between SIF and GPP that is largely invariant across ecosystems with an intercept that is not significantly different from zero. Measurements of SIF from TROPOMI agree with MODerate Resolution Imaging Spectroradiometer (MODIS) vegetation indices – the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near-infrared reflectance of vegetation index (NIR_v) – at annual timescales but indicate different temporal dynamics at monthly and daily timescales. TROPOMI SIF data show a double peak in the seasonality of photosynthesis, a feature that is not present in the MODIS vegetation indices. The different seasonality in the vegetation indices may be due to a clear-sky bias in the vegetation indices, whereas previous work has shown SIF to have a low sensitivity to clouds and to detect the downregulation of photosynthesis even when plants appear green. We further decompose the spatiotemporal patterns in the SIF data based on land cover. The double peak in the seasonality of California's photosynthesis is due to two processes that are out of phase: grasses, chaparral, and oak savanna ecosystems show an April maximum, while evergreen forests peak in June. An empirical orthogonal function (EOF) analysis corroborates the phase offset and spatial patterns driving the double peak. The EOF analysis further indicates that two spatiotemporal patterns explain 84 % of the variability in the SIF data. Results shown here are promising for obtaining global GPP at sub-kilometer spatial scales and identifying the processes driving carbon uptake

The contribution of terrestrial sources and sinks to trends in the seasonal cycle of atmospheric carbon dioxide

We characterized decadal changes in the amplitude and shape of the seasonal cycle of atmospheric CO_2 with three kinds of analysis. First, we calculated the trends in the seasonal cycle of measured atmospheric CO_2 at observation stations in the National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostic Laboratory network. Second, we assessed the impact of terrestrial ecosystems in various localities on the mean seasonal cycle of CO_2 at observation stations using the Carnegie‐Ames‐Stanford Approach terrestrial biosphere model and the Goddard Institute for Space Studies (GISS) atmospheric tracer transport model. Third, we used the GISS tracer model to quantify the contribution of terrestrial sources and sinks to trends in the seasonal cycle of atmospheric CO_2 for the period 1961–1990, specifically examining the effects of biomass burning, emissions from fossil fuel combustion, and regional increases in net primary production (NPP). Our analysis supports results from previous studies that indicate a significant positive increase in the amplitude of the seasonal cycle of CO_2 at Arctic and subarctic observation stations. For stations north of 55°N the amplitude increased at a mean rate of 0.66% yr^(−1) from 1981 to 1995. From the analysis of ecosystem impacts on the mean seasonal cycle we find that tundra, boreal forest, and other northern ecosystems are responsible for most of the seasonal variation in CO_2 at stations north of 55°N. The effects of tropical biomass burning on trends in the seasonal cycle are minimal at these stations, probably because of strong vertical convection in equatorial regions. From 1981 to 1990, fossil fuel emissions contributed a trend of 0.20% yr^(−1) to the seasonal cycle amplitude at Mauna Loa and less than 0.10% yr^(−1) at stations north of 55°N. To match the observed amplitude increases at Arctic and subarctic stations with NPP increases, we find that north of 30°N a 1.7 Pg C yr^(−1) terrestrial sink would be required. In contrast, over regions south of 30°N, even large NPP increases and accompanying terrestrial sinks would be insufficient to account for the increase in high‐latitude amplitudes

Substrate limitations for heterotrophs: Implications for models that estimate the seasonal cycle of atmospheric CO_2

We examine the sensitivity of the seasonal cycle of heterotrophic respiration to model estimates of litterfall seasonality, herbivory, plant allocation, tissue chemistry, and land use. As a part of this analysis, we compare heterotrophic respiration models based solely on temperature and soil moisture controls (zero‐order models) with models that depend on available substrate as well (first‐order models). As indicators of regional and global CO_2 exchange, we use maps of monthly global net ecosystem production, growing season net flux (GSNF), and simulated atmospheric CO_2 concentrations from an atmospheric tracer transport model. In one first‐order model, CASA, variations on the representation of the seasonal flow of organic matter from plants to heterotrophs can increase global GSNF as much as 60% (5.7 Pg C yr^(−1)) above estimates obtained from a zero‐order model. Under a new first‐order scheme that includes separate seasonal dynamics for leaf litterfall, fine root mortality, coarse woody debris, and herbivory, we observe an increase in GSNF of 8% (0.7 Pg C yr^(−1)) over that predicted by the zero‐order model. The increase in seasonality of CO2 exchange in first‐order models reflects the dynamics of labile litter fractions; specifically, the rapid decomposition of a pulse of labile leaf and fine root litter that enters the heterotrophic community primarily from the middle to the end of the growing season shifts respiration outside the growing season. From the perspective of a first‐order model, we then explore the consequences of land use change and winter temperature anomalies on the amplitude of the seasonal cycle of atmospheric CO_2. Agricultural practices that accelerate decomposition may drive a long‐term increase in the amplitude, independent of human impacts on plant production. Consideration of first‐order litter decomposition dynamics may also help explain year‐to‐year variation in the amplitude