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Simultaneous assimilation of SMOS soil moisture and atmospheric CO2 in-situ observations to constrain the global terrestrial carbon cycle

Author:
Scholze, M., Kaminski, T., Knorr, W., Blessing, S., Vossbeck, M., Grant, J.P., Scipal, K.
Source:
Remote sensing of environment 2016 v.180 pp. 334-345
ISSN:
0034-4257
Subject:
Soil Moisture and Ocean Salinity satellite, anthropogenic activities, biosphere, carbon, carbon cycle, carbon dioxide, carbon sinks, climate change, data collection, gas exchange, greenhouse gas emissions, greenhouse gases, hydrologic cycle, models, net ecosystem production, primary productivity, remote sensing, soil water, spatial distribution, uncertainty, value added
Abstract:
Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas contributing to about half of the total anthropogenic change in the Earth's radiation budget. And about half of the anthropogenic CO2 emissions stay in the atmosphere, the remainder is taken up by the biosphere. It is of paramount importance to better understand CO2 sources and sinks and their spatio-temporal distribution. In the context of climate change this information is needed to improve the projections of future trends in carbon sinks and sources. Since the terrestrial carbon and water cycles are tightly coupled by biological plant processes, i.e. through the stomatal gas exchange with the atmosphere, it is expected that information on the soil moisture state will help to constrain terrestrial carbon fluxes. In the present feasibility study we employ the Carbon Cycle Data Assimilation System CCDAS to pioneer the assimilation of the SMOS L3 soil moisture product together with another biophysical data set — in this case atmospheric CO2 flask samples. The two data streams are assimilated into a process-based model of the terrestrial carbon cycle over two years. CCDAS aims to optimise model process parameters and subsequently land surface CO2 exchange fluxes. We find that the assimilation of SMOS data improves the agreement with independent soil moisture data from the active ASCAT instrument. In both cases the assimilation also improves the fit of modelled atmospheric CO2 to the observations at flask sampling sites which have not been used in the assimilation. Reduction of uncertainty relative to the prior is generally high for both regional net ecosystem productivity and net primary productivity and considerably higher than for assimilating CO2 only, which quantifies the added value of SMOS observations as a constraint on the terrestrial carbon cycle. The study demonstrates a high potential for a SMOS L4 carbon flux product.
Agid:
5648529