Projected Effects Of Climate Change Research Articles

Comparison of Hydrological Simulations of Climate Change Using Perturbation of Observations and Distribution‐Based Scaling

Projected climate change effects on groundwater and stream discharges were investigated through simulations with a distributed, physically based, surface water–groundwater model. Input to the hydrological model includes precipitation, reference evapotranspiration, and temperature data of the HIRHAM4 regional climate model (RCM). The aim of this study was to determine whether the choice of bias‐correction method, applied to the RCM data, affected the projected hydrological changes. One method consisted of perturbation of observed data (POD) using climate change signals derived from the RCM output, while the other consisted of distribution‐based scaling (DBS) of the RCM output. Distribution‐based scaling resulted in RCM control period data closely approaching the observed climate data and thereby considerably improved the simulation of recharge and stream discharges. When comparing the simulations using both methods, only small differences between the projected changes in hydrological variables for the scenario period were found. Mean annual recharge increased by 15% for the DBS method and 12% for POD, and drain flow increased by 24 and 19%, respectively, while the increases in base flow were similar (7%). For both methods, daily stream discharges up to and including the median showed little change, while increases occurred for the higher quantile values. This study showed that the choice of bias‐correction method did not have a significant influence on the projected changes of mean hydrological responses in this catchment, although further analysis is necessary to determine whether extremes are affected. Furthermore, the characteristics of the hydrological system likely reduced the sensitivity of the projected changes to the choice of method.

Projected climate change effects on water level of an oxbow

One of the most vulnerable regions in the Carpathian Basin is the Great Hungarian Plain, where small and shallow oxbows are endangered along river Tisza. The purpose of this paper is to determine how the global warming affects a typical oxbow, located on the floodplain of river Tisza, in Hungary. A coupled meteorological–hydraulic model is developed and applied for this oxbow. Results suggest that the monthly minimum water levels are expected to decrease, moreover, extreme drought events sometimes result temporary drying-up of the oxbow.

Applying Bayesian modelling to assess climate change effects on biofuel production

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 40:249-260 (2009) - DOI: https://doi.org/10.3354/cr00833 Applying Bayesian modelling to assess climate change effects on biofuel production Camaren Peter1,*, Willem de Lange2, Josephine K. Musango2, Kurt April3, Anet Potgieter1 1Ndibano: Intelligence in Systems, 245 Private Bag X18, Rondebosch 7701, Cape Town, South Africa 2CSIR Natural Resources and the Environment, PO Box 320, Stellenbosch 7599, South Africa 3Graduate School of Business, University of Cape Town, Private Bag X3, Rondebosch 7701, Cape Town, South Africa *Email: camarenpeter@hotmail.com ABSTRACT: Socioeconomic and ecological systems exhibit complex, interdependent behaviour which is often difficult to model and understand. This is due to the complex reorganisation of key sub-system processes involving nonlinear, cross-scale and cross-sector interactions in real time. Hence, predictive models of complex social–ecological systems are often subject to large uncertainties. We propose an approach for evaluating land-use adaptations for biofuel production, using Bayesian networks and integrating research on the food, water and energy sectors. The approach is intended to facilitate interdisciplinary consideration of cross-scale and intersector dependencies. We applied this approach to 2 examples of land-use strategies and show how the resilience of a strategy that meets the new South African national biofuel production target can be assessed in relation to climate change. Cross-disciplinary consideration of variables may be enhanced through the sensitivity analysis enabled by Bayesian networks, which is used to conceptualise the conditional causal dependencies between subsystem variables. We formulate and run a national scale South African model which links the impacts of projected climate change effects in southern Africa to irrigated agriculture, water storage planning and biofuel production. We demonstrate how the approach can be used to evaluate land-use changes in different projected climate change scenarios and land-use combinations, and how conflicting demands between water, food and biofuel energy sources may be preliminarily identified and assessed in an integrated probabilistic framework. Evaluating this problem in the context of climate change and water-related limits to growth enables research to support integrated analysis and planning for biofuel production and development. KEY WORDS: Bayesian networks · Climate change · Biofuels · Land-use change · Resilience · Cross-sector analysis Full text in pdf format PreviousCite this article as: Peter C, de Lange W, Musango JK, April K, Potgieter A (2009) Applying Bayesian modelling to assess climate change effects on biofuel production. Clim Res 40:249-260. https://doi.org/10.3354/cr00833 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 40, No. 2-3. Online publication date: December 10, 2009 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2009 Inter-Research.

Effects of simulated daily precipitation patterns on annual plant populations depend on life stage and climatic region

BackgroundTo improve the understanding of consequences of climate change for annual plant communities, I used a detailed, grid-based model that simulates the effect of daily rainfall variability on individual plants in five climatic regions on a gradient from 100 to 800 mm mean annual precipitation (MAP). The model explicitly considers moisture storage in the soil. I manipulated daily rainfall variability by changing the daily mean rain (DMR, rain volume on rainy days averaged across years for each day of the year) by ± 20%. At the same time I adjusted intervals appropriately between rainy days for keeping the mean annual volume constant. In factorial combination with changing DMR I also changed MAP by ± 20%.ResultsIncreasing MAP generally increased water availability, establishment, and peak shoot biomass. Increasing DMR increased the time that water was continuously available to plants in the upper 15 to 30 cm of the soil (longest wet period, LWP). The effect of DMR diminished with increasing humidity of the climate. An interaction between water availability and density-dependent germination increased the establishment of seedlings in the arid region, but in the more humid regions the establishment of seedlings decreased with increasing DMR. As plants matured, competition among individuals and their productivity increased, but the size of these effects decreased with the humidity of the regions. Therefore, peak shoot biomass generally increased with increasing DMR but the effect size diminished from the semiarid to the mesic Mediterranean region. Increasing DMR reduced via LWP the annual variability of biomass in the semiarid and dry Mediterranean regions.ConclusionMore rainstorms (greater DMR) increased the recharge of soil water reservoirs in more arid sites with consequences for germination, establishment, productivity, and population persistence. The order of magnitudes of DMR and MAP overlapped partially so that their combined effect is important for projections of climate change effects on annual vegetation.

Projected climate change effects on Rocky Mountain and Great Plains birds: generalities of biodiversity consequences

AbstractClimate change effects on biodiversity are already manifested, and yet no predictive knowledge characterizes the likely nature of these effects. Previous studies suggested an influence of topography on these effects, a possibility tested herein. Bird species with distributions restricted to montane (26 species) and Great Plains (19 species) regions of central and western North America were modeled, and climate change effects on their distributions compared: in general, plains species were more heavily influenced by climate change, with drastic area reductions (mode 35% of distributional area lost under assumption of no dispersal) and dramatic spatial movements (0–400 km shift of range centroid under assumption of no dispersal) of appropriate habitats. These results suggest an important generality regarding climate change effects on biodiversity, and provide useful guidelines for conservation planning.

RESEARCH: Projected Climate Change Effects on Winterkill in Shallow Lakes in the Northern United States.

/ Each winter, hundreds of ice-covered, shallow lakes in the northern United States are aerated to prevent winterkill, the death of fish due to oxygen depletion under the ice. How will the projected climate warming influence winterkill and the need to artificially aerate lakes? To answer this question, a deterministic, one-dimensional year-round water quality model, which simulates daily dissolved oxygen (DO) profiles and associated water temperatures as well as ice/snow covers on lakes, was applied. Past and projected climate scenarios were investigated. The lake parameters required as model input are surface area, maximum depth, and Secchi depth as a measure of radiation attenuation and trophic state. The model is driven by daily weather data. Weather records from 209 stations in the contiguous United States for the period 1961-1979 were used to represent past climate conditions. The projected climate change due to a doubling of atmospheric CO(2) was obtained from the output of the Canadian Climate Center General Circulation Model. To illustrate the effect of projected climate change on lake DO characteristics, we present herein DO information simulated, respectively, with inputs of past climate conditions (1961-1979) and with a projected 2 x CO(2) climate scenario, as well as differences of those values. Specific parameters obtained were minimum under-ice and lake bottom DO concentration in winter, duration of under-ice anoxic conditions (<0.1 mg/liter) and low DO conditions (<3 mg/liter), and percentage of anoxic and low DO lake volumes during the ice cover period. Under current climate conditions winterkill occurs typically in shallow eutrophic lakes of the northern contiguous United States. Climate warming is projected to eliminate winterkill in these lakes. This would be a positive effect of climate warming. Fish species under ice may still experience periods of stress and zero growth due to low DO (<3 mg/liter) conditions under projected climate warming.

Projections of Climate Change Effects on Water Temperature Characteristics of Small Lakes in the Contiguous U.S.

To simulate effects of projected climate change on water temperature characteristics of small lakes in the contiguous U.S., a deterministic, one-dimensional year-round water temperature model is applied. In cold regions the model simulates ice and snow cover on a lake. The lake parameters required as model input are surface area, maximum depth, and Secchi depth as a measure of radiation attenuation and trophic state. The model is driven by daily weather data. Weather records from 209 stations in the contiguous U.S. for the period 1961–1979 were used to represent present climate conditions. The projected climate change owing to a doubling of atmospheric CO2 was obtained from the output of the Canadian Climate Center General Circulation Model. The simulated water temperature and ice characteristics are related to the geometric and trophic state lake characteristics and to geographic location. By interpolation, the sensitivity of lake water temperature characteristics to latitude, longitude, lake geometry and trophic status can therefore be quantified for small lakes in the contiguous U.S. The 2× CO2 climate scenario is projected to increase maximum and minimum lake surface temperatures by up to 5.2°C. (Maximum surface water temperatures in lakes near the northern and the southern border of the contiguous U.S. currently differ by up to 13°C.) Maximum temperature differences between lake surface and lake bottom are projected to increase in average by only 1 to 2°C after climate warming. The duration of seasonal summer stratification is projected to be up to 66 days longer under a 2×CO2 climate scenario. Water temperatures of less than 8°C are projected to occur on lake bottoms during a period which is on the order of 50 days shorter under a 2×CO2 climate scenario. With water temperature change projected to be as high as 5.2°C, ecological impacts such as shifts in species distributions and in fish habitat are most likely. Ice covers on lakes of northern regions would also be changed strongly.