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

Development of a new downscaling method for hydrologic assessment of climate change impacts in data scarce regions and its application in the Western Ghats, India

Climate change affects local and regional water resources. Especially in regions with water scarcity, high climate sensitivity, and dynamic socioeconomic development, an adaptation of water management strategies is needed. Our study aims at (i) testing a new downscaling approach to utilize climate model results in a meso-scale hydrologic model and at (ii) analyzing the impact of climate change on the water balance components in the Mula and Mutha Rivers catchment upstream of the city of Pune, India. The new downscaling approach relies on the inherent consistency of both, the climate model and the measured data. It allows to derive a representation of a future climate scenario (2009-2099) by rearranging past measurements (1988-2008). We found a good agreement of the monthly statistics of the rearranged and the original measured data in the baseline period. However, the downscaling method is limited by the range of measured values provided in the baseline period, which results in an underestimation of temperatures in the last 20 years of the scenario period. The downscaled weather data for IPCC emission scenario A1B were used in a hydrologic impact assessment with SWAT. The scenario resulted in higher evapotranspiration, particularly in the first months of the dry season and in repeated low water storages in the reservoirs at the end of rainy season. Consequently, local and downstream water users as well as rain-fed agriculture and semi-natural vegetation in the Western Ghats increasingly suffer from water stress

Evaluation of terrestrial carbon cycle models with atmospheric CO2 measurements: Results from transient simulations considering increasing CO2, climate, and land-use effects

An atmospheric transport model and observations of atmospheric CO2 are used to evaluate the performance of four Terrestrial Carbon Models (TCMs) in simulating the seasonal dynamics and interannual variability of atmospheric CO2 between 1980 and 1991. The TCMs were forced with time varying atmospheric CO2 concentrations, climate, and land use to simulate the net exchange of carbon between the terrestrial biosphere and the atmosphere. The monthly surface CO2 fluxes from the TCMs were used to drive the Model of Atmospheric Transport and Chemistry and the simulated seasonal cycles and concentration anomalies are compared with observations from several stations in the CMDL network. The TCMs underestimate the amplitude of the seasonal cycle and tend to simulate too early an uptake of CO2 during the spring by approximately one to two months. The model fluxes show an increase in amplitude as a result of land-use change, but that pattern is not so evident in the simulated atmospheric amplitudes, and the different models suggest different causes for the amplitude increase (i.e., CO2 fertilization, climate variability or land use change). The comparison of the modeled concentration anomalies with the observed anomalies indicates that either the TCMs underestimate interannual variability in the exchange of CO2 between the terrestrial biosphere and the atmosphere, or that either the variability in the ocean fluxes or the atmospheric transport may be key factors in the atmospheric interannual variability