Search Results
The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: Results from a process-based model
2010, Thonicke, K., Spessa, A., Prentice, I.C., Harrison, S.P., Dong, L., Carmona-Moreno, C.
A process-based fire regime model (SPITFIRE) has been developed, coupled with ecosystem dynamics in the LPJ Dynamic Global Vegetation Model, and used to explore fire regimes and the current impact of fire on the terrestrial carbon cycle and associated emissions of trace atmospheric constituents. The model estimates an average release of 2.24 Pg C yr−1 as CO2 from biomass burning during the 1980s and 1990s. Comparison with observed active fire counts shows that the model reproduces where fire occurs and can mimic broad geographic patterns in the peak fire season, although the predicted peak is 1–2 months late in some regions. Modelled fire season length is generally overestimated by about one month, but shows a realistic pattern of differences among biomes. Comparisons with remotely sensed burnt-area products indicate that the model reproduces broad geographic patterns of annual fractional burnt area over most regions, including the boreal forest, although interannual variability in the boreal zone is underestimated.
Global observations of 2 day wave coupling to the diurnal tide in a high‐altitude forecast‐assimilation system
2017-4-18, Lieberman, R.S., Riggin, D.M., Nguyen, V., Palo, S.E., Siskind, D.E., Mitchell, N.J., Stober, G., Wilhelm, S., Livesey, N.J.
We examine wave components in a high-altitude forecast-assimilation system that arise from nonlinear interaction between the diurnal tide and the westward traveling quasi 2 day wave. The process yields a westward traveling “sum” wave with zonal wave number 4 and a period of 16 h, and an eastward traveling “difference” wave with zonal wave number 2 and a period of 2 days. While the eastward 2 day wave has been reported in satellite temperatures, the westward 16 h wave lies outside the Nyquist limits of resolution of twice daily local time satellite sampling. Hourly output from a high-altitude forecast-assimilation model is used to diagnose the nonlinear quadriad. A steady state primitive equation model forced by tide-2 day wave advection is used to intepret the nonlinear wave products. The westward 16 h wave maximizes in the midlatitude winter mesosphere and behaves like an inertia-gravity wave. The nonlinearly generated component of the eastward 2 day wave maximizes at high latitudes in the lower thermosphere, and only weakly penetrates to low latitudes. The 16 h and the eastward 2 day waves are of comparable amplitude and alias to the same apparent frequency when viewed from a satellite perspective.
Climate-driven interannual variability of water scarcity in food production potential: A global analysis
2014, Kummu, M., Gerten, D., Heinke, J., Konzmann, M., Varis, O.
Interannual climatic and hydrologic variability has been substantial during the past decades in many regions. While climate variability and its impacts on precipitation and soil moisture have been studied intensively, less is known on subsequent implications for global food production. In this paper we quantify effects of hydroclimatic variability on global "green" and "blue" water availability and demand in global agriculture, and thus complement former studies that have focused merely on long-term averages. Moreover, we assess some options to overcome chronic or sporadic water scarcity. The analysis is based on historical climate forcing data sets over the period 1977-2006, while demography, diet composition and land use are fixed to reference conditions (year 2000). In doing so, we isolate the effect of interannual hydroclimatic variability from other factors that drive food production. We analyse the potential of food production units (FPUs) to produce a reference diet for their inhabitants (3000 kcal cap-1 day -1, with 80% vegetal food and 20% animal products). We applied the LPJmL vegetation and hydrology model to calculate the variation in green-blue water availability and the water requirements to produce that very diet. An FPU was considered water scarce if its water availability was not sufficient to produce the diet (i.e. assuming food self-sufficiency to estimate dependency on trade from elsewhere). We found that 24% of the world's population lives in chronically water-scarce FPUs (i.e. water is scarce every year), while an additional 19% live under occasional water scarcity (water is scarce in some years). Among these 2.6 billion people altogether, 55% would have to rely on international trade to reach the reference diet, while for 24% domestic trade would be enough. For the remaining 21% of the population exposed to some degree of water scarcity, local food storage and/or intermittent trade would be enough to secure the reference diet over the occasional dry years.
Multidecadal trend analysis of in situ aerosol radiative properties around the world
2020, Collaud Coen, Martine, Andrews, Elisabeth, Alastuey, Andrés, Petkov Arsov, Todor, Backman, John, Brem, Benjamin T., Bukowiecki, Nicolas, Couret, Cédric, Eleftheriadis, Konstantinos, Flentje, Harald, Fiebig, Markus, Gysel-Beer, Martin, Hand, Jenny L., Hoffer, András, Hooda, Rakesh, Hueglin, Christoph, Joubert, Warren, Keywood, Melita, Eun Kim, Jeong, Kim, Sang-Woo, Labuschagne, Casper, Lin, Neng-Huei, Lin, Yong, Lund Myhre, Cathrine, Luoma, Krista, Lyamani, Hassan, Marinoni, Angela, Mayol-Bracero, Olga L., Mihalopoulos, Nikos, Pandolfi, Marco, Prats, Natalia, Prenni, Anthony J., Putaud, Jean-Philippe, Ries, Ludwig, Reisen, Fabienne, Sellegri, Karine, Sharma, Sangeeta, Sheridan, Patrick, Sherman, James Patrick, Sun, Junying, Titos, Gloria, Torres, Elvis, Tuch, Thomas, Weller, Rolf, Wiedensohler, Alfred, Zieger, Paul, Laj, Paolo
In order to assess the evolution of aerosol parameters affecting climate change, a long-term trend analysis of aerosol optical properties was performed on time series from 52 stations situated across five continents. The time series of measured scattering, backscattering and absorption coefficients as well as the derived single scattering albedo, backscattering fraction, scattering and absorption Ångström exponents covered at least 10 years and up to 40 years for some stations. The non-parametric seasonal Mann-Kendall (MK) statistical test associated with several pre-whitening methods and with Sen's slope was used as the main trend analysis method. Comparisons with general least mean square associated with autoregressive bootstrap (GLS/ARB) and with standard least mean square analysis (LMS) enabled confirmation of the detected MK statistically significant trends and the assessment of advantages and limitations of each method. Currently, scattering and backscattering coefficient trends are mostly decreasing in Europe and North America and are not statistically significant in Asia, while polar stations exhibit a mix of increasing and decreasing trends. A few increasing trends are also found at some stations in North America and Australia. Absorption coefficient time series also exhibit primarily decreasing trends. For single scattering albedo, 52 % of the sites exhibit statistically significant positive trends, mostly in Asia, eastern/northern Europe and the Arctic, 22 % of sites exhibit statistically significant negative trends, mostly in central Europe and central North America, while the remaining 26 % of sites have trends which are not statistically significant. In addition to evaluating trends for the overall time series, the evolution of the trends in sequential 10-year segments was also analyzed. For scattering and backscattering, statistically significant increasing 10-year trends are primarily found for earlier periods (10-year trends ending in 2010-2015) for polar stations and Mauna Loa. For most of the stations, the present-day statistically significant decreasing 10-year trends of the single scattering albedo were preceded by not statistically significant and statistically significant increasing 10-year trends. The effect of air pollution abatement policies in continental North America is very obvious in the 10-year trends of the scattering coefficient - there is a shift to statistically significant negative trends in 2009-2012 for all stations in the eastern and central USA. This long-term trend analysis of aerosol radiative properties with a broad spatial coverage provides insight into potential aerosol effects on climate changes. © 2020 Royal Society of Chemistry. All rights reserved.
The global technical potential of bio-energy in 2050 considering sustainability constraints
2010, Haberl, H., Beringer, T., Bhattacharya, S.C., Erb, K.-H., Hoogwijk, M.
Bio-energy, that is, energy produced from organic non-fossil material of biological origin, is promoted as a substitute for non-renewable (e.g., fossil) energy to reduce greenhouse gas (GHG) emissions and dependency on energy imports. At present, global bio-energy use amounts to approximately 50 EJ/yr, about 10% of humanity's primary energy supply. We here review recent literature on the amount of bio-energy that could be supplied globally in 2050, given current expectations on technology, food demand and environmental targets ('technical potential'). Recent studies span a large range of global bio-energy potentials from ≈30 to over 1000 EJ/yr. In our opinion, the high end of the range is implausible because of (1) overestimation of the area available for bio-energy crops due to insufficient consideration of constraints (e.g., area for food, feed or nature conservation) and (2) too high yield expectations resulting from extrapolation of plot-based studies to large, less productive areas. According to this review, the global technical primary bio-energy potential in 2050 is in the range of 160-270 EJ/yr if sustainability criteria are considered. The potential of bio-energy crops is at the lower end of previously published ranges, while residues from food production and forestry could provide significant amounts of energy based on an integrated optimization ('cascade utilization') of biomass flows. © 2010 Elsevier B.V.
The GGCMI Phase 2 emulators: Global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0)
2020, Franke, James A., Müller, Christoph, Elliott, Joshua, Ruane, Alex C., Jägermeyr, Jonas, Snyder, Abigail, Dury, Marie, Falloon, Pete D., Folberth, Christian, François, Louis, Hank, Tobias, Izaurralde, R. Cesar, Jacquemin, Ingrid, Jones, Curtis, Li, Michelle, Liu, Wenfeng, Olin, Stefan, Phillips, Meridel, Pugh, Thomas A. M., Reddy, Ashwan, Williams, Karina, Wang, Ziwei, Zabel, Florian, Moyer, Elisabeth J.
Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: Atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: That growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts. © 2020 EDP Sciences. All rights reserved.
Reconstruction of global gridded monthly sectoral water withdrawals for 1971-2010 and analysis of their spatiotemporal patterns
2018, Huang, Z., Hejazi, M., Li, X., Tang, Q., Vernon, C., Leng, G., Liu, Y., Döll, P., Eisner, S., Gerten, D., Hanasaki, N., Wada, Y.
Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scales, due to a lack of observations at seasonal and local scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5°) sectoral water withdrawal dataset for the period 1971-2010, which distinguishes six water use sectors, i.e., irrigation, domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that total global water withdrawal has increased significantly during 1971-2010, mainly driven by the increase in irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of total annual irrigation water withdrawal in mid- and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual timescales. The reconstructed gridded water withdrawal dataset is open access, and can be used for examining issues related to water withdrawals at fine spatial, temporal, and sectoral scales.
Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6
2020, Hurtt, George C., Chini, Louise, Sahajpal, Ritvik, Frolking, Steve, Bodirsky, Benjamin L., Calvin, Katherine, Doelman, Jonathan C., Fisk, Justin, Fujimori, Shinichiro, Klein Goldewijk, Kees, Hasegawa, Tomoko, Havlik, Peter, Heinimann, Andreas, Humpenöder, Florian, Jungclaus, Johan, Kaplan, Jed O., Kennedy, Jennifer, Krisztin, Tamás, Lawrence, David, Lawrence, Peter, Ma, Lei, Mertz, Ole, Pongratz, Julia, Popp, Alexander, Poulter, Benjamin, Riahi, Keywan, Shevliakova, Elena, Stehfest, Elke, Thornton, Peter, Tubiello, Francesco N., van Vuuren, Detlef P., Zhang, Xin
Human land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth's surface, with consequences for climate and other ecosystem services. In the future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community has developed the next generation of advanced Earth system models (ESMs) to estimate the combined effects of human activities (e.g., land use and fossil fuel emissions) on the carbon–climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, is required as input for these models. With most ESM simulations for CMIP6 now completed, it is important to document the land use patterns used by those simulations. Here we present results from the Land-Use Harmonization 2 (LUH2) project, which smoothly connects updated historical reconstructions of land use with eight new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land use patterns, underlying land use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds on a similar effort from CMIP5 and is now provided at higher resolution (0.25∘×0.25∘) over a longer time domain (850–2100, with extensions to 2300) with more detail (including multiple crop and pasture types and associated management practices) using more input datasets (including Landsat remote sensing data) and updated algorithms (wood harvest and shifting cultivation); it is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5 and are designed to enable new and improved estimates of the combined effects of land use on the global carbon–climate system.
A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)
2017, Forkel, Matthias, Dorigo, Wouter, Lasslop, Gitta, Teubner, Irene, Chuvieco, Emilio, Thonicke, Kirsten
Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1). SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with data-driven modelling and model–data integration approaches can guide the future development of global process-oriented vegetation-fire models.
Water savings potentials of irrigation systems: Global simulation of processes and linkages
2015, Jägermeyr, J., Gerten, D., Heinke, J., Schaphoff, S., Kummu, M., Lucht, W.