Carbon source/sink information provided by column CO2 measurements from the Orbiting Carbon Observatory

© The Authors, 2010. This article is distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Atmospheric Chemistry and Physics 10 (2010): 4145-4165, doi:10.5194/acp-10-4145-2010.We quantify how well column-integrated CO2 measurements from the Orbiting Carbon Observatory (OCO) should be able to constrain surface CO2 fluxes, given the presence of various error sources. We use variational data assimilation to optimize weekly fluxes at a 2°×5° resolution (lat/lon) using simulated data averaged across each model grid box overflight (typically every ~33 s). Grid-scale simulations of this sort have been carried out before for OCO using simplified assumptions for the measurement error. Here, we more accurately describe the OCO measurements in two ways. First, we use new estimates of the single-sounding retrieval uncertainty and averaging kernel, both computed as a function of surface type, solar zenith angle, aerosol optical depth, and pointing mode (nadir vs. glint). Second, we collapse the information content of all valid retrievals from each grid box crossing into an equivalent multi-sounding measurement uncertainty, factoring in both time/space error correlations and data rejection due to clouds and thick aerosols. Finally, we examine the impact of three types of systematic errors: measurement biases due to aerosols, transport errors, and mistuning errors caused by assuming incorrect statistics. When only random measurement errors are considered, both nadir- and glint-mode data give error reductions over the land of ~45% for the weekly fluxes, and ~65% for seasonal fluxes. Systematic errors reduce both the magnitude and spatial extent of these improvements by about a factor of two, however. Improvements nearly as large are achieved over the ocean using glint-mode data, but are degraded even more by the systematic errors. Our ability to identify and remove systematic errors in both the column retrievals and atmospheric assimilations will thus be critical for maximizing the usefulness of the OCO data.SD and DB acknowledge support from NASA grant NNG06G127G. DB also acknowledges initial support from NOAA Grant NA16GP2935

Olive phenology as a sensitive indicator of future climatic warming in the Mediterranean

Experimental and modelling work suggests a strong dependence of olive flowering date on spring temperatures. Since airborne pollen concentrations reflect the flowering phenology of olive populations within a radius of 50 km, they may be a sensitive regional indicator of climatic warming. We assessed this potential sensitivity with phenology models fitted to flowering dates inferred from maximum airborne pollen data. Of four models tested, a thermal time model gave the best fit for Montpellier, France, and was the most effective at the regional scale, providing reasonable predictions for 10 sites in the western Mediterranean. This model was forced with replicated future temperature simulations for the western Mediterranean from a coupled ocean-atmosphere general circulation model (GCM). The GCM temperatures rose by 4·5 °C between 1990 and 2099 with a 1% per year increase in greenhouse gases, and modelled flowering date advanced at a rate of 6·2 d per °C. The results indicated that this long-term regional trend in phenology might be statistically significant as early as 2030, but with marked spatial variation in magnitude, with the calculated flowering date between the 1990s and 2030s advancing by 3–23 d. Future monitoring of airborne olive pollen may therefore provide an early biological indicator of climatic warming in the Mediterranean

Field Micrometeorological Measurements, Process-Level Studies and Modeling of Methane and Carbon Dioxide Fluxes in a Boreal Wetland Ecosystem

The main instrumentation platform consisted of eddy correlation sensors mounted on a scaffold tower at a height of 4.2 m above the peat surface. The sensors were attached to a boom assembly which could be rotated into the prevailing winds. The boom assembly was mounted on a movable sled which, when extended, allowed sensors to be up to 2 m away from the scaffolding structure to minimize flow distortion. When retracted, the sensors could easily be installed, serviced or rotated. An electronic level with linear actuators allowed the sensors to be remotely levelled once the sled was extended. Two instrument arrays were installed. A primary (fast-response) array consisted of a three-dimensional sonic anemometer, a methane sensor (tunable diode laser spectrometer), a carbon dioxide/water vapor sensor, a fine wire thermocouple and a backup one-dimensional sonic anemometer. The secondary array consisted of a one-dimensional sonic anemometer, a fine wire thermocouple and a Krypton hygrometer. Descriptions of these sensors may be found in other reports (e.g., Verma; Suyker and Verma). Slow-response sensors provided supporting measurements including mean air temperature and humidity, mean horizontal windspeed and direction, incoming and reflected solar radiation, net radiation, incoming and reflected photosynthetically active radiation (PAR), soil heat flux, peat temperature, water-table elevation and precipitation. A data acquisition system (consisting of an IBM compatible microcomputer, amplifiers and a 16 bit analog-to-digital converter), housed in a small trailer, was used to record the fast response signals. These signals were low-pass filtered (using 8-pole Butterworth active filters with a 12.5 Hz cutoff frequency) and sampled at 25 Hz. Slow-response signals were sampled every 5 s using a network of CR21X (Campbell Scientific, Inc., Logan Utah) data loggers installed in the fen. All signals were averaged over 30-minute periods (runs)

Climatic versus biotic constraints on carbon and water fluxes in seasonally drought-affected ponderosa pine ecosystems

We investigated the relative importance of climatic versus biotic controls on gross primary production (GPP) and water vapor fluxes in seasonally drought-affected ponderosa pine forests. The study was conducted in young (YS), mature (MS), and old stands (OS) over 4 years at the AmeriFlux Metolius sites. Model simulations showed that interannual variation of GPP did not follow the same trends as precipitation, and effects of climatic variation were smallest at the OS (50%), and intermediate at the YS (<20%). In the young, developing stand, interannual variation in leaf area has larger effects on fluxes than climate, although leaf area is a function of climate in that climate can interact with age-related shifts in carbon allocation and affect whole-tree hydraulic conductance. Older forests, with well-established root systems, appear to be better buffered from effects of seasonal drought and interannual climatic variation. Interannual variation of net ecosystem exchange (NEE) was also lowest at the OS, where NEE is controlled more by interannual variation of ecosystem respiration, 70% of which is from soil, than by the variation of GPP, whereas variation in GPP is the primary reason for interannual changes in NEE at the YS and MS. Across spatially heterogeneous landscapes with high frequency of younger stands resulting from natural and anthropogenic disturbances, interannual climatic variation and change in leaf area are likely to result in large interannual variation in GPP and NEE

Extracting ecological and biophysical information from AVHRR optical data: An integrated algorithm based on inverse modeling

Satellite remote sensing provides the only means of directly observing the entire surface of the Earth at regular spatial and temporal intervals

Extracting ecological and biophysical information from AVHRR optical data: An integrated algorithm based on inverse modeling

Satellite remote sensing provides the only means of directly observing the entire surface of the Earth at regular spatial and temporal intervals

The effects of CO2, climate and land-use on terrestrial carbon balance, 1920-1992: An analysis with four process-based ecosystem models

The concurrent effects of increasing atmospheric CO2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process-based terrestrial biosphere models. Over the long-term(1920–1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long-term analysis based on ice core and atmospheric CO2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO2. During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr−1, which is within the uncertainty of analysis based on CO2 and O2 budgets. Three of the four models indicated (in accordance with O2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long-term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Niño/Southern Oscillation (ENSO)-scale variability in the atmospheric CO2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO2 suggested that the observed trend may be a consequence of CO2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process-based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand-level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system