Many processes and interactions in the atmosphere and the biosphere influence the rate of carbon dioxide exchange between these two systems. However, it is difficult to estimate the carbon dioxide flux over regions with diverse ecosystems and complex terrains, such as California. Traditional carbon dioxide measurements are sparse and limited to specific ecosystems. Therefore, accurately estimating carbon dioxide flux on a regional scale remains a major challenge.

In this study, we couple the Weather Research and Forecasting Model (WRF) with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model. Although WRF is a state-of-the-art regional atmospheric model with high spatial and temporal resolutions, the land surface schemes available in WRF lack the capability to simulate carbon dioxide. ACASA is a complex multilayer land surface model with interactive canopy physiology and full surface hydrological processes. It allows microenvironmental variables such as air and surface temperatures, wind speed, humidity, and carbon dioxide concentration to vary vertically. Carbon dioxide, sensible heat, water vapor, and momentum fluxes between the atmosphere and land surface are estimated in the ACASA model through turbulence equations with a third order closure scheme. It therefore permits counter-gradient transports that low-order turbulence closure models are unable to simulate.

A new CO₂ tracer module is introduced into the model framework to allow the atmospheric carbon dioxide concentration to vary according to terrestrial responses. In addition to the carbon dioxide simulation, the coupled WRF-ACASA model is also used to investigate the interactions of neighboring ecosystems in their response to atmospheric carbon dioxide concentration. The model simulations with and without the CO₂ tracer for WRF-ACASA are compared with surface observations from the AmeriFlux network.

In this study, we investigate possible future climate change over Northern Eurasia and its impact on extreme events. Northern Eurasia is a major player in the global carbon budget because of boreal forests and peatlands. Circumpolar boreal forests alone contain more than five times the amount of carbon of temperate forests and almost double the amount of carbon of the world’s tropical forests. Furthermore, severe permafrost degradation associated with climate change could result in peatlands releasing large amounts of carbon dioxide and methane. Meanwhile, changes in the frequency and magnitude of extreme events, such as extreme precipitation, heat waves or frost days are likely to have substantial impacts on Northern Eurasia ecosystems. For this reason, it is very important to quantify the possible climate change over Northern Eurasia under different emissions scenarios, while accounting for the uncertainty in the climate response and changes in extreme events.

For several decades, the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change has been investigating uncertainty in climate change using the MIT Integrated Global System Model (IGSM) framework, an integrated assessment model that couples an earth system model of intermediate complexity (with a 2D zonal-mean atmosphere) to a human activity model. In this study, regional change is investigated using the MIT IGSM-CAM framework that links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). New modules were developed and implemented in CAM to allow climate parameters to be changed to match those of the IGSM.

The simulations presented in this paper were carried out for two emission scenarios, a “business as usual” scenario and a 660 ppm of CO2-equivalent stabilization, which are similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios. Values of climate sensitivity and net aerosol forcing used in the simulations within the IGSM-CAM framework provide a good approximation for the median, and the lower and upper bound of 90% probability distribution of 21st century climate change. Five member ensembles were carried out for each choice of parameters using different initial conditions. With these simulations, we investigate the role of emissions scenarios (climate policies), the global climate response (climate sensitivity) and natural variability (initial conditions) on the uncertainty in future climate changes over Northern Eurasia. A particular emphasis is made on future changes in extreme events, including frost days, extreme summer temperature and extreme summer and winter precipitation.

Ethiopia is powering ahead with an energy development strategy that is highly reliant on abundant hydropower potential. A changing climate may pose a challenge to meeting expected targets. Bridging the modeling gaps between climate, energy, and economics, and effectively transforming climate changes into economic measures, is an emerging interdisciplinary field as nations attempt to position themselves for an uncertain future. Such a framework is adopted here to assess energy production and adaptation costs for four climate change scenarios over 2010–2049. Scenarios that favor a drying trend countrywide may lead to losses of 130–200 terawatt-hours over the 40-year period, translating to adaptation costs of US$2–4 billion, compared with a no climate change scenario. Even given these potential losses, energy development utilizing hydropower appears economically reasonable from this deterministic, sector-independent evaluation. This development is desperately needed, independent of future climate change trends, with the hope of appreciably reducing vulnerability to variability.

© 2012 Blackwell Publishing Ltd.

Long term response of the climate system to anthropogenic forcing was investigated with an Earth System Model of intermediate complexity (MIT IGSM). An ensemble of four hundred simulations was carried out for the period 1860-2005 using versions of the model with different values of climate sensitivity, the aerosol forcing, and the strength of ocean heat uptake using historical forcing. Then, a 400-member ensemble was carried out for each of four different RCP scenarios from the year 2006 to the year 3000. By the last decade of the 21st century, the ensemble mean of surface air temperature increases, relative to 1986-2005 period, by 0.88, 2.16, 2.68 and 4.0oC for RCP26, RCP4.5, RCP6.0 and RCP8.5 respectively. In spite of the forcing being fixed beyond year 2150 for RCP4.5 and RCP6.0 and beyond 2250 for RCP8.5, surface air temperature keeps rising until the end of 30th century under these scenarios. The upper bound of the 90% probability interval increases significantly more than the median. For the RCP4.5 scenario, the median value of possible SAT change increases by 1.07oC from the last decade of the 21st century to the end of 30th century, while the value of the 95th percentile increases by 2.88 oC. Corresponding numbers for RCP6.0 and RCP8.5 are 2.21 and 8.53oC for the medians and 5.36 and 14.65oC for the 95th percentiles, respectively. Such changes in the shape of probability distributions with time, indicate an increase in the probability that surface warming will exceed a given value. For example, the probability of exceeding 3oC warming under the RCP4.5 scenario increases from 4% at the end of 21st century to 37% and 57% at the end of 23d and 30th centuries, respectively. For the RCP2.6 scenario, in which radiative forcing peaks in the year 2070 before decreasing back to the 1990s level by the year 2300, the ensemble mean surface air temperature is still about 0.5oC above present at the end of the simulation.