Global dust model intercomparison in AeroCom phase I

This study presents the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations related to desert dust aerosols, their direct radiative effect, and their impact on the biogeochemical cycle, i.e., aerosol optical depth (AOD) and dust deposition. Additional comparisons to Angström exponent (AE), coarse mode AOD and dust surface concentrations are included to extend the assessment of model performance and to identify common biases present in models. These data comprise a benchmark dataset that is proposed for model inspection and future dust model development. There are large differences among the global models that simulate the dust cycle and its impact on climate. In general, models simulate the climatology of vertically integrated parameters (AOD and AE) within a factor of two whereas the total deposition and surface concentration are reproduced within a factor of 10. In addition, smaller mean normalized bias and root mean square errors are obtained for the climatology of AOD and AE than for total deposition and surface concentration. Characteristics of the datasets used and their uncertainties may influence these differences. Large uncertainties still exist with respect to the deposition fluxes in the southern oceans. Further measurements and model studies are necessary to assess the general model performance to reproduce dust deposition in ocean regions sensible to iron contributions. Models overestimate the wet deposition in regions dominated by dry deposition. They generally simulate more realistic surface concentration at stations downwind of the main sources than at remote ones. Most models simulate the gradient in AOD and AE between the different dusty regions. However the seasonality and magnitude of both variables is better simulated at African stations than Middle East ones. The models simulate the offshore transport of West Africa throughout the year but they overestimate the AOD and they transport too fine particles. The models also reproduce the dust transport across the Atlantic in the summer in terms of both AOD and AE but not so well in winter-spring nor the southward displacement of the dust cloud that is responsible of the dust transport into South America. Based on the dependency of AOD on aerosol burden and size distribution we use model bias with respect to AOD and AE to infer the bias of the dust emissions in Africa and the Middle East. According to this analysis we suggest that a range of possible emissions for North Africa is 400 to 2200 Tg yr-1 and in the Middle East 26 to 526 Tg yr-1

Potential of using remote sensing techniques for global assessment of water footprint of crops

Remote sensing has long been a useful tool in global applications, since it provides physically-based, worldwide, and consistent spatial information. This paper discusses the potential of using these techniques in the research field of water management, particularly for ‘Water Footprint’ (WF) studies. The WF of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. In this paper evapotranspiration, precipitation, water storage, runoff and land use are identified as key variables to potentially be estimated by remote sensing and used for WF assessment. A mass water balance is proposed to calculate the volume of irrigation applied, and green and blue WF are obtained from the green and blue evapotranspiration components. The source of remote sensing data is described and a simplified example is included, which uses evapotranspiration estimates from the geostationary satellite Meteosat 9 and precipitation estimates obtained with the Climatic Prediction Center Morphing Technique (CMORPH). The combination of data in this approach brings several limitations with respect to discrepancies in spatial and temporal resolution and data availability, which are discussed in detail. This work provides new tools for global WF assessment and represents an innovative approach to global irrigation mapping, enabling the estimation of green and blue water use

Evaluation of black carbon estimations in global aerosol models

We evaluate black carbon (BC) model predictions from the AeroCom model intercomparison project by considering the diversity among year 2000 model simulations and comparing model predictions with available measurements. These model-measurement intercomparisons include BC surface and aircraft concentrations, aerosol absorption optical depth (AAOD) retrievals from AERONET and Ozone Monitoring Instrument (OMI) and BC column estimations based on AERONET. In regions other than Asia, most models are biased high compared to surface concentration measurements. However compared with (column) AAOD or BC burden retreivals, the models are generally biased low. The average ratio of model to retrieved AAOD is less than 0.7 in South American and 0.6 in African biomass burning regions; both of these regions lack surface concentration measurements. In Asia the average model to observed ratio is 0.7 for AAOD and 0.5 for BC surface concentrations. Compared with aircraft measurements over the Americas at latitudes between 0 and 50N, the average model is a factor of 8 larger than observed, and most models exceed the measured BC standard deviation in the mid to upper troposphere. At higher latitudes the average model to aircraft BC ratio is 0.4 and models underestimate the observed BC loading in the lower and middle troposphere associated with springtime Arctic haze. Low model bias for AAOD but overestimation of surface and upper atmospheric BC concentrations at lower latitudes suggests that most models are underestimating BC absorption and should improve estimates for refractive index, particle size, and optical effects of BC coating. Retrieval uncertainties and/or differences with model diagnostic treatment may also contribute to the model-measurement disparity. Largest AeroCom model diversity occurred in northern Eurasia and the remote Arctic, regions influenced by anthropogenic sources. Changing emissions, aging, removal, or optical properties within a single model generated a smaller change in model predictions than the range represented by the full set of AeroCom models. Upper tropospheric concentrations of BC mass from the aircraft measurements are suggested to provide a unique new benchmark to test scavenging and vertical dispersion of BC in global models

Analysis of long-term terrestrial water storage variations in the Yangtze River basin

In this study, we analyze 32 yr of terrestrial water storage (TWS) data obtained from the Interim Reanalysis Data (ERA-Interim) and Noah model from the Global Land Data Assimilation System (GLDAS-Noah) for the period 1979 to 2010. The accuracy of these datasets is validated using 26 yr (1979–2004) of runoff data from the Yichang gauging station and comparing them with 32 yr of independent precipitation data obtained from the Global Precipitation Climatology Centre Full Data Reanalysis Version 6 (GPCC) and NOAA's PRECipitation REConstruction over Land (PREC/L). Spatial and temporal analysis of the TWS data shows that TWS in the Yangtze River basin has decreased significantly since the year 1998. The driest period in the basin occurred between 2005 and 2010, and particularly in the middle and lower Yangtze reaches. The TWS figures changed abruptly to persistently high negative anomalies in the middle and lower Yangtze reaches in 2004. The year 2006 is identified as major inflection point, at which the system starts exhibiting a persistent decrease in TWS. Comparing these TWS trends with independent precipitation datasets shows that the recent decrease in TWS can be attributed mainly to a decrease in the amount of precipitation. Our findings are based on observations and modeling datasets and confirm previous results based on gauging station datasets

Can crop residues provide fuel for future transport? Limited global residue bioethanol potentials and large associated land, water and carbon footprints

Bioethanol production from non-crop based lignocellulosic material has reached the commercial scale and is advocated as a possible solution to decarbonize the transport sector. This study evaluates how much presently used transport related fossil fuels can be replaced with lignocellulosic bioethanol using crop residues, calculates greenhouse gas emission savings, and determines lignocellulosic bioethanol's land, water, and carbon footprints. We estimate global bioethanol production potential from 123 crop residues in 192 countries and 20 territories under different environmental constraints (optimistic and realistic sustainable potentials) versus no constraints (theoretical potential) on residue availability. Previous studies on global bioethanol production potential from lignocellulosic material focused on one or few biomass feedstocks, and excluded (un)constrained residue availability scenarios. Our results suggest the global net lignocellulosic bioethanol output ranges from 7.1 to 34.0 EJ per annum replacing between 7% and 31% of oil products for transport yielding relative emission savings of 338 megatonne (Mt; 70%) to 1836 Mt (79%). Emission savings range from 4% to 23% of total transport emissions in the realistic sustainable versus theoretical potential. Land, water and carbon footprints of net bioethanol vary between potentials, countries/territories, and feedstocks, but overall exceed footprints of conventional bioethanol. Averaged footprints range between 0.14 and 0.24 m2 land per megajoule (MJ−1), 74–120 L water MJ−1, and 28–44 g CO2 equivalent MJ−1, with smaller footprints in the theoretical potential caused by the exclusion of secondary residues and low price of alternative biomass chains in the sustainable potential