Climate Change and...
- Climate Variability
- Climate Models
Effects of Climate Change
Applications of Climate Models
Hirsch, A. I., Michalak, A. M., Bruhwiler, L. M., Peters, W., Dlugokencky, E. J., Tans, P. P. (2006). Inverse modeling estimates of the global nitrous oxide surface flux from 1998–2001. Global Biogeochemical Cycles 20 (GB1008): doi:10.1029/2004GB002443
ABSTRACT: Measurements of nitrous oxide in air samples from 48 sites in the Cooperative Global Air Sampling Network made by NOAA/ESRL GMD CCGG (the Carbon Cycle Greenhouse Gases group in the Global Monitoring Division at the NOAA Earth System Research Laboratory in Boulder, Colorado) and the three-dimensional chemical transport model TM3 were used to infer global nitrous oxide fluxes and their uncertainties from 1998–2001. Results are presented for four semihemispherical regions (90°S–30°S, 30°S to equator, equator to 30°N, 30°N–90°N) and six broad “super regions” (Southern Land, Southern Oceans, Tropical Land, Tropical Oceans, Northern Land, and Northern Oceans). We found that compared to our a priori estimate (from the International Geosphere-Biosphere Programme's Global Emissions Inventory Activity), the a posteriori flux was much lower from 90°S–30°S and substantially higher from equator to 30°N. Consistent with these results, the a posteriori flux from the Southern Oceans region was lower than the a priori estimate, while Tropical Land and Tropical Ocean estimates were higher. The ratio of Northern Hemisphere to Southern Hemisphere fluxes was found to range from 1.9 to 5.2 (depending on the model setup), which is higher than the a priori ratio (1.5) and at the high end of previous estimates. Globally, ocean emissions contributed 26–36% of the total flux (again depending on the model setup), consistent with the a priori estimate (29%), though somewhat higher than some other previous estimates.
ABSTRACT: This study addressed how different climate data sets influence simulations of the global terrestrial carbon cycle. For the period 1982–2001, we compared the results of simulations based on three climate data sets (NCEP/NCAR, NCEP/DOE AMIP-II and ERA40) employed in meteorological, ecological and biogeochemical studies and two different models (BEAMS and Sim-CYCLE). The models differed in their parameterizations of photosynthetic and phenological processes but used the same surface climate (e.g. shortwave radiation, temperature and precipitation), vegetation, soil and topography data. The three data sets give different climatic conditions, especially for shortwave radiation, in terms of long-term means, linear trends and interannual variability. Consequently, the simulation results for global net primary productivity varied by 16%–43% only from differences in the climate data sets, especially in these regions where the shortwave radiation data differed markedly: differences in the climate data set can strongly influence simulation results. The differences among the climate data set and between the two models resulted in slightly different spatial distribution and interannual variability in the net ecosystem carbon budget. To minimize uncertainty, we should pay attention to the specific climate data used. We recommend developing an accurate standard climate data set for simulation studies.
ABSTRACT: It is well known that expansion of agriculture into natural ecosystems can have important climatic consequences, but changes occurring within existing croplands also have the potential to effect local and global climate. To better understand the impacts of cropland management practices, we used the NCAR CAM3 general circulation model coupled to a slab-ocean model to simulate climate change under extreme scenarios of irrigation, tillage, and crop productivity. Compared to a control scenario, increases in irrigation and leaf area index and reductions in tillage all have a physical cooling effect by causing increases in planetary albedo. The cooling is most pronounced for irrigation, with simulated local cooling up to -8°C and global land surface cooling of 1.3°C. Increases in soil albedo through reduced tillage are found to have a global cooling effect (-0.2°C) comparable to the biogeochemical cooling from reported carbon sequestration potentials. By identifying the impacts of extreme scenarios at local and global scales, this study effectively shows the importance of considering different aspects of crop management in the development of climate models, analysis of observed climate trends, and design of policy intended to mitigate climate change.
Matthews, H. D., M. Eby, T. Ewen, P. Friedlingstein, B. J. Hawkins (2007). What determines the magnitude of carbon cycle-climate feedbacks?. Global Biogeochemical Cycles 21 (GB2012): doi:10.1029/2006GB002733
ABSTRACT: Positive feedbacks between climate change and the carbon cycle have the potential to amplify the growth of atmospheric carbon dioxide and accelerate future climate warming. However, both the magnitude of and the processes which drive future carbon cycle-climate feedbacks remain highly uncertain. In this study, we use a coupled climate-carbon model to investigate how the response of vegetation photosynthesis to climate change contributes to the overall strength of carbon cycle-climate feedbacks. We find that the feedback strength is particularly sensitive to the model representation of the photosynthesis-temperature response, with lesser sensitivity to the parameterization of soil moisture and nitrogen availability. In all simulations, large feedbacks are associated with a climatic suppression of terrestrial primary productivity and consequent reduction of terrestrial carbon uptake. This process is particularly evident in the tropics and can explain a large part of the range of carbon cycle-climate feedbacks simulated by different coupled climate-carbon models.
ABSTRACT: Carbon sequestered in biomass is not necessarily stored infinitely, but is exposed to human or natural disturbances. Storm is the most important natural disturbance agent in Swiss forests. Therefore, if forests are taken into account in the national carbon budget, the impact of windthrow on carbon pools and fluxes should be included. In this article the forest scenario model MASSIMO and the soil carbon model YASSO were applied to assess the effect of forest management and an increased storm activity on the carbon sequestration in Swiss forests. First, the soil model was adapted to Swiss conditions and validated. Second, carbon fluxes were assessed applying the two models under various forest management scenarios and storm frequencies. In particular, the influence of clearing after a storm event on the carbon budget was analyzed. The evaluation of the model results showed that the soil model reliably reproduces the amount of soil carbon at the test sites. The simulation results indicated that, within the simulated time period of 40 years, forest management has a strong influence on the carbon budget. However, forest soils only react slightly to changes in the above-ground biomass. The results also showed that a storm frequency increase of 30% has a small impact on the national carbon budget of forests. To develop effective mitigation strategies for forest management, however, longer time periods must be regarded.
ABSTRACT: Recent concern over the ecological effects of future trace-gas-induced climate change has accelerated efforts to understand and quantify climate-induced vegetation change1–9 . Here we discuss new and published climate-model results indicating that global warming favours increased rates of forest disturbance, as a result of weather more likely to cause forest fires (drought, wind and natural ignition sources), convective wind storms, coastal flooding and hurricanes. New sensitivity tests carried out with a vegetation model indicate that climate-induced increases in disturbance could, in turn, significantly alter the total biomass and compositional response of forests to future warming. An increase in disturbance frequency is also likely to increase the rate at which natural vegetation responds to future climate change. Our results reinforce the hypothesis6 that forests could be significantly altered by the first part of the next century. Our modelling also confirms the potential utility of selected time series of fossil pollen data for investigating the poorly understood natural patterns of century-scale climate variability.
Zhu, C., D.W. Pierce, T.P. Barnett, A.W. Wood, D.P. Lettenmaier (2004). Evaluation of hydrologically relevant PCM climate variables and large-scale variability over the western U.S.. Climatic Change 62 (1): 45-74
ABSTRACT: The ability of the Parallel Climate Model (PCM) to reproduce the mean and variability of hydrologically relevant climate variables was evaluated by comparing PCM historical climate runs with observations over temporal scales from sub-daily to annual. The domain was the continental U.S, and the model spatial resolution was T42 (about 2.8 degrees latitude by longitude). The climate variables evaluated include precipitation, surface air temperature, net surface solar radiation, soil moisture, and snow water equivalent. The results show that PCM has a winter dry bias in the Pacific Northwest and a summer wet bias in the central plains. The diurnal precipitation variation in summer is much stronger than observed, with an afternoon maximum in summer precipitation over much of the U.S. interior, in contrast with an observed nocturnal maximum in parts of the interior. PCM has a cold bias in annual mean temperature over most of the U.S., with deviations as large as –8 K. The PCM daily temperature range is lower than observed, especiallyin the central U.S. PCM generally overestimates the net solar radiation over most of the U.S, although the diurnal cycle is simulated well in spring, summer and winter. In autumn PCM has a pronounced noontime peak in solar radiation that differs by 5–10% from observations. PCM'ssimulated soil moisture is less variable than that of a sophisticated land-surface hydrology model, especially in the interior of the country. PCM simulates the wetter conditions over the southeastern U.S. and California during warm (El Niño) events, but shifts the drier conditions in the Pacific Northwest northward and underestimates their magnitude. The temperature response to the North Pacific Oscillation is generally captured by PCM, but the amplitude of this response is overestimated by a factor of about two.
ABSTRACT: General circulation models predict that freshwater discharge from the Mississippi River (USA) to the coastal ocean would increase 20% if atmospheric CO2 concentration doubles. Here we use a coupled physical-biological 2-box model to investigate the potential impacts of increased freshwater and nutrient inputs on the production and decay of organic matter in the coastal waters of the northern Gulf of Mexico. Model results for a doubled CO2 climate indicate that the annual net productivity of the upper water column (NP, 0 to 10 m) is likely to increase by 65 g C m-2 yr-1 , relative to a 1985-1992 average (122 g C m-2 yr-1 ). Interestingly, this projected increase is of the same magnitude as the one that has occurred slnce the 1940s due to the introduction of anthropogenlc nutrients. An increase in annual NP of 32 g C m-2 yr-1 was observed during the Great Mississippi River Flood of 1993, thus indicating the general validity of a doubled CO2 scenario. The total oxygen uptake in the lower water column (10 to 20 m), in contrast, is likely to remain at its present value of about 200 g O2 m-2 yr-1 . Thus, carbon export and burial, rather than in situ respiration, are likely to be the dominant processes balancing coastal carbon budgets, leading perhaps to an expanded extent of the hypoxic zone.
ABSTRACT: The signing of the UN Framework Convention on Climate Change in Rio de Janeiro in June 1992 by 160 nations has firmly identified global climate change due to human pollution as a pressing global environmental concern. Among the responsibilities that the nations which ratify the Convention will have are the drawing up of inventories of greenhouse gas sources and sinks and the formulation of national strategies to respond to climate change through adaptive and or preventive measures. One requirement for identifying appropriate response strategies will be the undertaking of regional assessments of climate change and its associated impacts.
This paper is concerned with climate change in the East Asian region, both over the last 100 years (using instrumental data) and also for the next 100 years (using results from climate model experiments). The juxtaposing of these two analyses, historical and future, enables a better interpretation of the significance of regional climate change to be made. Instrumental temperature and precipitation data for the East Asian region are analysed and compared with the observed global-scale trends in these two variables. Although the region has undoubtedly warmed over the last century, understanding the exact causes of the complex seasonal, diurnal, and spatial dimensions of this warming is difficult. We examine the role of increasing urbanization in inducing rising temperatures and suggest that, although substantial, urban warming cannot account for all of the observed temperature change. The paper also illustrates a flexible composite-model approach to regional climate change scenario construction that avoids the need for multiple transient GCM experiments, which can explicitly incorporate the effects of intermodel uncertainty, and is flexible enough to incorporate new scientific findings and results from new GCM experiments. The scenario presented here suggests that by 2050, mean conditions are expected to be warmer than the extremely warm seasonal anomalies that occurred during the most recent decade in East Asia. Precipitation is estimated to rise over most of the region in all seasons, although the uncertainty range attached to this estimate is much wider than for temperature.
ABSTRACT: The range of responses of alternate detailed models for the ocean and biosphere components of the global carbon cycle, cataloged in model intercomparison studies, are simulated by a reduced form Earth system model employing a range of model parameters. The reduced form model, parameterized in this way, allows the integration of these components of the carbon cycle with an energy balance climate model with a prescribed range of climate sensitivity. We use this model to construct ranges of: (1) past carbon budgets given past CO2 concentrations, fossil carbon emissions, and temperature records, (2) future CO2 concentrations and temperature for given emission scenarios, and (3) CO2 emissions and temperature for given trajectories of future CO2 concentrations leading to constant levels within the next several centuries. Carbon cycle is an additional contributor to uncertainty in climate projections that is calculated to expand the range of projected global temperature beyond that reported in the 2001 Intergovernmental Panel on Climate Change assessment.
ABSTRACT: Recent research has shown that decadal-to-multidecadal (D2M) climate variability is associated with environmental changes that have important consequences for human activities, such as public health, water availability, frequency of hurricanes, and so forth. As scientists, how do we convert these relationships into decision support products useful to water managers, insurance actuaries, and others, whose principal interest lies in knowing when future climate regime shifts will likely occur that affect long-horizon decisions? Unfortunately, numerical models are far from being able to make deterministic predictions for future D2M climate shifts. However, the recent development of paleoclimate reconstructions of the Atlantic Multidecadal Oscillation (AMO) (Gray et al., ) and Pacific Decadal Oscillation (PDO); (MacDonald and Case, ) give us a viable alternative: to estimate probability distribution functions from long climate index series that allow us to calculate the probability of future D2M regime shifts. In this paper, we show how probabilistic projections can be developed for a specific climate mode - the AMO as represented by the Gray et al. () tree-ring reconstruction. The methods are robust and can be applied to any D2M climate mode for which a sufficiently long index series exists, as well as to the growing body of paleo-proxy reconstructions that have become available. The target index need not be a paleo-proxy calibrated against a climate index; it may profitably be calibrated against a specific resource of interest, such as stream flow or lake levels.
ABSTRACT: By using a climate system model of intermediate complexity, we have simulated long-term natural climate changes occurring over the last 9000 years. The paleo-simulations in which the model is driven by orbital forcing only, i.e., by changes in insolation caused by changes in the Earth's orbit, are compared with sensitivity simulations in which various scenarios of increasing atmospheric CO2 concentration are prescribed. Focussing on climate and vegetation change in northern Africa, we recapture the strong greening of the Sahara in the early and mid-Holocene (some 9000–6000 years ago), and we show that some expansion of grasslandinto the Sahara is theoretically possible, if the atmospheric CO2 concentration increases well above pre-industrial values and if vegetation growth is not disturbed. Depending on the rate of CO2 increase, vegetation migration into the Sahara can be rapid, up to 1/10th of the Saharan area per decade, but could not exceed a coverage of 45%. In ourmodel, vegetation expansion into today's Sahara is triggered by an increase in summer precipitation which is amplified by a positive feedback between vegetation and precipitation. This is valid for simulations with orbital forcing and greenhouse-gas forcing. However, we argue that the mid-Holocene climate optimum some 9000 to 6000 years ago with its marked reduction of deserts in northern Africa is not a direct analogue for future greenhouse-gas induced climate change, as previously hypothesized. Not only does the global pattern of climate change differ between the mid-Holocene model experiments and the greenhouse-gas sensitivity experiments, but the relative role of mechanisms which lead to a reduction of the Sahara also changes. Moreover, the amplitude of simulated vegetation cover changes in northern Africa is less than is estimated for mid-Holocene climate.
ABSTRACT: We examined climate-carbon cycle feedback by performing a global warming experiment using MIROC-based coupled climate-carbon cycle model. The model showed that by the end of the 21st century, warming leads to a further increase in carbon dioxide (CO2 ) level of 123 ppm by volume (ppmv). This positive feedback can mostly be attributed to land-based soil-carbon dynamics. On a regional scale, Siberia experienced intense positive feedback, because the acceleration of microbial respiration due to warming causes a decrease in the soil carbon level. Amazonia also had positive feedback resulting from accelerated microbial respiration. On the other hand, some regions, such as western and central North America and South Australia, experienced negative feedback, because enhanced litterfall surpassed the increased respiration in soil carbon. The oceanic contribution to the feedback was much weaker than the land contribution on global scale, but the positive feedback in the northern North Atlantic was as strong as those in Amazonia and Siberia in our model. In the northern North Atlantic, the weakening of winter mixing caused a reduction of CO2 absorption at the surface. Moreover, weakening of the formation of North Atlantic Deep Water caused reduced CO2 subduction to the deep water. Understanding such regional-scale differences may help to explain disparities in coupled climate-carbon cycle model results.
ABSTRACT: Accurate simulation of ice-sheet surface mass balance requires higher spatial resolution than is afforded by typical atmosphere–ocean general circulation models (AOGCMs), owing, in particular, to the need to resolve the narrow and steep margins where the majority of precipitation and ablation occurs. We have developed a method for calculating mass-balance changes by combining ice-sheet average time-series from AOGCM projections for future centuries, both with information from high-resolution climate models run for short periods and with a 20 km ice-sheet mass-balance model. Antarctica contributes negatively to sea level on account of increased accumulation, while Greenland contributes positively because ablation increases more rapidly. The uncertainty in the results is about 20% for Antarctica and 35% for Greenland. Changes in ice-sheet topography and dynamics are not included, but we discuss their possible effects. For an annual- and area-average warming exceeding 4.5 ± 0.9 K in Greenland and 3.1 ± 0.8 K in the global average, the net surface mass balance of the Greenland ice sheet becomes negative, in which case it is likely that the ice sheet would eventually be eliminated, raising global-average sea level by 7m.
ABSTRACT: Terrestrial ecosystems and the climate system are closely coupled, particularly by cycling of carbon between vegetation, soils and the atmosphere. It has been suggested1,2 that changes in climate and in atmospheric carbon dioxide concentrations have modified the carbon cycle so as to render terrestrial ecosystems as substantial carbon sinks3,4 ; but direct evidence for this is very limited5,6 . Changes in ecosystem carbon stocks caused by shifts between stable climate states have been evaluated7,8 , but the dynamic responses of ecosystem carbon fluxes to transient climate changes are still poorly understood. Here we use a terrestrial biogeochemical model9 , forced by simulations of transient climate change with a general circulation model10 , to quantify the dynamic variations in ecosystem carbon fluxes induced by transient changes in atmospheric CO2 and climate from 1861 to 2070. We predict that these changes increase global net ecosystem production significantly, but that this response will decline as the CO2 fertilization effect becomes saturated and is diminished by changes in climatic factors. Thus terrestrial ecosystem carbon fluxes both respond to and strongly influence the atmospheric CO2 increase and climate change.
ABSTRACT: Climate models suggest that global warming could bring warmer, drier conditions to Mexico. Although precipitation increases are projected by some models, in most cases they do not compensate for increases in potential evaporation. Thus, soil moisture and water availability may decrease over much of Mexico with serious consequences for rainfed and irrigated agriculture, urban and industrial water supplies, hydropower and ecosystems. However, the assessment of global warming impacts in Mexico is an uncertain task because the projections of different models vary widely, particularly for precipitation, and because they perform poorly in reproducing the observed climate of Mexico.
C. M. Girod, G. C. Hurtt, S. Frolking, J. D. Aber, A. W. King (2007). The tension between fire risk and carbon storage: evaluating U.S. carbon and fire management strategies through ecosystem models. Earth Interactions 11 (2): 1-33
ABSTRACT: Fire risk and carbon storage are related environmental issues because fire reduction results in carbon storage through the buildup of woody vegetation, and stored carbon is a fuel for fires. The sustainability of the U.S. carbon sink and the extent of fire activity in the next 100 yr depend in part on the type and effectiveness of fire reduction employed. Previous studies have bracketed the range of dynamics from continued fire reduction to the complete failure of fire reduction activities. To improve these estimates, it is necessary to explicitly account for fire reduction in terrestrial models. A new fire reduction submodel that estimates the spatiotemporal pattern of reduction across the United States was developed using gridded data on biomass, climate, land-use, population, and economic factors. To the authors’ knowledge, it is the first large-scale, gridded fire model that explicitly accounts for fire reduction. The model was calibrated to 1° × 1° burned area statistics [Global Burnt Area 2000 Project (GBA-2000)] and compared favorably to three important diagnostics. The model was then implemented in a spatially explicit ecosystem model and used to analyze 1620 scenarios of future fire risk and fire reduction strategies. Under scenarios of climate change and urbanization, burned area and carbon emissions both increased in scenarios where fire reduction efforts were not adjusted to match new patterns of fire risk. Fuel reducing management strategies reduced burned area and fire risk, but also limited carbon storage. These results suggest that to promote carbon storage and minimize fire risk in the future, fire reduction efforts will need to be increased and spatially adjusted and will need to employ a mixture of fuel-reducing and non-fuel-reducing strategies.
ABSTRACT: The effects of changes in the landscape and climate over geological time are plain to see in the present hydrological regime. More recent anthropogenic changes may also have effects on our way of life. A prerequisite to predicting such effects is that we understand the interactions between climate, landscape and the hydrological regime. A semi-distributed hydrological model (SLURP) has been developed which can be used to investigate, in a simple way, the links between landscape, climate and hydrology for watersheds of various sizes. As well as using data from the observed climate network, the model has been used with data from atmospheric models to investigate possible changes in hydrology. A critical input to such a model is knowledge of the links between landscape and climate. While direct anthropogenic effects such as changes in forested area may presently be included, the indirect effects of climate on landscape and vice versa are not yet modeled well enough to be explicitly included. The development of models describing climate-landscape relationships such as regeneration, development and breakup, water and carbon fluxes at species, ecosystem and biome level is a necessarily step in understanding and predicting the effects of changes in climate on landscape and on water resources. Forest is the predominant land cover in Canada covering 453 Mha and productivity/succession models for major forest types should be included in an integrated climate-landscape-water simulation.
G. Parkin, G. O'Donnell, J. Ewen, J. C. Bathurst, P. E. O'Connell, J. Lavabre (1996). Validation of catchment models for predicting land-use and climate change impacts. 2. Case study for a Mediterranean catchment. Journal of Hydrology 175 (1-4): 595-613
ABSTRACT: Validation methods commonly used to test catchment models are not capable of demonstrating a model's fitness for making predictions for catchments where the catchment response is not known (including hypothetical catchments, and future conditions of existing catchments which are subject to land-use or climate change). This paper describes the first use of a new method of validation (Ewen and Parkin, 1996. J. Hydrol., 175: 583–594) designed to address these types of application; the method involves making `blind' predictions of selected hydrological responses which are considered important for a particular application. SHETRAN (a physically based, distributed catchment modelling system) is tested on a small Mediterranean catchment. The test involves quantification of the uncertainty in four predicted features of the catchment response (continuous hydrograph, peak discharge rates, monthly runoff, and total runoff), and comparison of observations with the predicted ranges for these features. The results of this test are considered encouraging.
Anderson, M.L., M. L. Kavvas, M. D. Mierzwa (2001). Probabilistic/ensemble forecasting: a case study using hydrologic response distributions associated with El Niño/Southern Oscillation (ENSO). Journal of Hydrology 249 (1-4): 134-147
ABSTRACT: Due to the non-linear processes and interactions of the hydroclimatic system, a given hydroclimatic event such as the El Niño/Southern Oscillation (ENSO) can lead to a range of possible hydrologic system responses described by a probability distribution. This probability distribution changes in space and time reflecting the non-stationary behavior of the hydroclimatic system. An initial approach in quantifying the evolving probability distributions of hydrologic system response utilizes a physically based hemispheric hydrologic model, PBHHM, that incorporates the salient physics of the hydroclimatic system for the midlatitudes of the Northern Hemisphere. The state variables of the model include atmospheric temperature, atmospheric water content, quasi-geostrophic potential vorticity, land hydrologic water storage, and land/sea surface temperature. The model is structured in such a way that characteristics (e.g. sea surface temperature, geopotential anomalies, etc.) of a hydroclimatic event such as ENSO can be incorporated into the model as a forcing event. The hydrologic system response probability distribution is quantified, via the land hydrologic water storage state variable.
As a case study, the hydrologic system response probability distributions of the western continental United States to both the El Niño and La Niña phases of ENSO have been simulated. One hundred realizations were run for each phase using random initial conditions for the state variables in order to reflect differing hydroclimatic conditions during the initiation and evolution of the forcing event. The probability distributions of hydrologic system response and their evolution in space and time are described using relative frequency histograms, cumulative distribution functions, and contour plots of frequency histogram categories. Simulation results of the hydrologic system response probability distribution associated with each phase of the ENSO phenomenon are presented which show a distinct response that varies in space and time. The influence of the number of realizations upon these distributions will be discussed along with a means of incorporating the distributions into a water resources planning scheme.
ABSTRACT: Abrupt changes in climate, termed Dansgaard-Oeschger and Heinrich events, have punctuated the last glacial period (~100-10 kyr ago) but not the Holocene (the past 10 kyr). Here we use an intermediate-complexity climate model to investigate the stability of glacial climate, and we find that only one mode of Atlantic Ocean circulation is stable: a cold mode with deep water formation in the Atlantic Ocean south of Iceland. However, a 'warm' circulation mode similar to the present-day Atlantic Ocean is only marginally unstable, and temporary transitions to this warm mode can easily be triggered. This leads to abrupt warm events in the model which share many characteristics of the observed Dansgaard-Oeschger events. For a large freshwater input (such as a large release of icebergs), the model's deep water formation is temporarily switched off, causing no strong cooling in Greenland but warming in Antarctica, as is observed for Heinrich events. Our stability analysis provides an explanation why glacial climate is much more variable than Holocene climate.
M. D. Dettinger, D. R. Cayan, M. K. Meyer, A. E. Jeton (2004). Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900–2099. Climatic Change 62 (1-3): 283-317
ABSTRACT: Hydrologic responses of river basins in the Sierra Nevada of California to historical and future climate variations and changes are assessed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-yr period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th century until about 1975 when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st century with an attendant +2.5 °C warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. The various projected trends in the business-as-usual simulations become readily visible despite realistic simulated natural climatic and hydrologic variability by about 2025. In contrast to these changes that are mostly associated with streamflow timing, long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. A control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995 yields climate and streamflow timing conditions much like the 1980s and 1990s throughout its duration. The availability of continuous climate-change projection outputs and careful design of initial conditions and control experiments, like those utilized here, promise to improve the quality and usability of future climate-change impact assessments.
A. D. Ziegler, J. Sheffield, E. P. Maurer, B. Nijssen, E. F. Wood, D. P. Lettenmaier (2003). Detection of intensification in global- and continental-scale hydrological cycles: temporal scale of evaluation. Journal of Climate 16 (3): 535-547
ABSTRACT: Diagnostic studies of offline, global-scale Variable Infiltration Capacity (VIC) model simulations of terrestrial water budgets and simulations of the climate of the twenty-first century using the parallel climate model (PCM) are used to estimate the time required to detect plausible changes in precipitation (P), evaporation (E), and discharge (Q) if the global water cycle intensifies in response to global warming. Given the annual variability in these continental hydrological cycle components, several decades to perhaps more than a century of observations are needed to detect water cycle changes on the order of magnitude predicted by many global climate model studies simulating global warming scenarios. Global increases in precipitation, evaporation, and runoff of 0.6, 0.4, and 0.2 mm yr-1 require approximately 30–45, 25–35, and 50–60 yr, respectively, to detect with high confidence. These conservative detection time estimates are based on statistical error criteria (a = 0.05, ß = 0.10) that are associated with high statistical confidence, 1 - a (accept hypothesis of intensification when true, i.e., intensification is occurring), and high statistical power, 1 - ß (reject hypothesis of intensification when false, i.e., intensification is not occurring). If one is willing to accept a higher degree of risk in making a statistical error, the detection time estimates can be reduced substantially. Owing in part to greater variability, detection time of changes in continental P, E, and Q are longer than those for the globe. Similar calculations performed for three Global Energy and Water Experiment (GEWEX) basins reveal that minimum detection time for some of these basins may be longer than that for the corresponding continent as a whole, thereby calling into question the appropriateness of using continental-scale basins alone for rapid detection of changes in continental water cycles. A case is made for implementing networks of small-scale indicator basins, which collectively mimic the variability in continental P, E, and Q, to detect acceleration in the global water cycle.
Dolph, J., D. Marks, G.A. King, R.J. Naiman (1992). Sensitivity of the regional water balance in the Columbia River basin to climate variability: application of a spatially distributed water balance model. Springer-Verlag: 233-265
ABSTRACT: A one-dimensional water balance model was developed and used to simulate the water balance for the Columbia River Basin. The model was run over a 10 km digital elevation grid representing the U.S. portion of the basin. The regional water balance was calculated usign a monthly time step for a relatively wet year (1972 water year), a relatively dry year (1977 water year), and adouble (2xCO2 ) climate scenario. Input data, spatially distributed over the grid, included precipitation, maximum soil moisture storage capacity, potential evapotranspiration (PET) and threshold baseflow. The model output provides spatially distributed surfaces of actual evapotranspiration (ET), surface runoff, and soil storage. Model performance was assessed by comparing modelled ET and runoff with the input precipitation data, and by comparing modelled runoff with measured runoff. The model reasonably partitions incoming precipitation to evapotranspiration and runoff. However, modelled total annual runoff was significantly less than measured runoff, primarily because precipitation is underestimated by the network of measurement stations and because of limitations associated with the interpolation procedure used to distribute the precipitation across the grid. Estimated precipitation is less than measured runoff, a physical impossibility. Under warmer 2xCO2 climate conditions (January 4.0°K warmer, July 6.5°K warmer), the model predicts that PET increases by about 80%, ET increases, and runoff and soil moisture decrease. Under these climate conditions, the distribution and composition of forests in the region would change dramatically, and water resources would become more limited.
ABSTRACT: Water plays a central role in nearly all Earth processes and in the evolution of the planet. However, despite the significance of water, our knowledge of it as part of the global system in meager. In fact, for paleoclimatology the primary focus on planetary evolution is centered on temperature variations and little attention is directed towards the role of the hydrologic cycle.
Model analyses presented here based on a series of simulations utilizing the Community Climate Model (CCM) at the National Center for Atmospheric Research demonstrate that the hydrologic cycle is highly sensitive to climate change and to climatic forcing factors such as changes in atmospheric carbon dioxide, plate tectonics, paleogeography, and orbital variations. The implications of the large sensitivity of the hydrologic cycle are of considerable importance. The role of water in explaining much of the Earth's record has probably been underestimated. The importance of water in global change in Earth history may also suggest that the hydrologic cycle should be of primary interest in studies of future global change.
ABSTRACT: Changes in the climatology of precipitation, evapotranspiration, and soil moisture lead also to changes in runoff and streamflow. The potential effects of global warming on the hydrology of 23 major rivers are investigated. The runoff simulated by the Canadian Centre for Climate Modeling and Analysis (CCCma) coupled climate model for the current climate is routed through the river system to the river mouth and compared with results for the warmer climate simulated to occur towards the end of the century. Changes in mean discharge, in the amplitude and phase of the annual streamflow cycle, in the annual maximum discharge (the flood) and its standard deviation, and in flow duration curves are all examined. Changes in flood magnitudes for different return periods are estimated using extreme value analysis. In the warmer climate, there is a general decrease in runoff and 15 out of the 23 rivers considered experience a reduction in annual mean discharge (with a median reduction of 32%). The changes in runoff are not uniform and discharge increases for 8 rivers (with a median increase of 13%). Middle- and high-latitude rivers typically show marked changes in the amplitude and phase of their annual cycle associated with a decrease in snowfall and an earlier spring melt in the warmer climate. Low-latitude rivers exhibit changes in mean discharge but modest changes in their annual cycle. The analysis of annual flood magnitudes show that 17 out of 23 rivers experience a reduction in mean annual flood (a median reduction of 20%). Changes in flow duration curves are used to characterize the different kinds of behavior exhibited by different groups of rivers. Differences in the regional distribution of simulated precipitation and runoff for the control simulation currently limit the application of the approach. The inferred hydrological changes are, nevertheless, plausible and consistent responses to simulated changes in precipitation and evapotranspiration and indicate the kinds of hydrological changes that could occur in a warmer climate.
Cooney, S.J., A. P. Covich, P.M. Lukacs, A. L. Harig, K.D. Fausch (2005). Modeling global warming scenarios in Greenback cutthroat trout (Oncorynchus clarki stomias ) streams: implications for species recovery. Western North American Naturalist 65 (3): 371-381
ABSTRACT: Changes in global climate may exacerbate other anthropogenic stressors, accelerating the decline in distribution and abundance of rare species throughout the world. We examined the potential effects of a warming climate on the greenback cutthroat trout (Oncorhynchus clarki stomias), a resident salmonid that inhabits headwater streams of the central Rocky Mountains. Greenbacks are outcompeted at lower elevations by nonnative species of trout and currently are restricted to upper-elevation habitats where barriers to upstream migration by nonnatives are or have been established. We used likelihood-based techniques and information theoretics to select models predicting stream temperature changes for 10 streams where greenback cutthroat trout have been translocated. These models showed high variability among responses by different streams, indicating the usefulness of a stream-specific approach. We used these models to project changes in stream temperatures based on 2 °C and 4 °C warming of average air temperatures. In these warming scenarios, spawning is predicted to begin from 2 to 3.3 weeks earlier than would be expected under baseline conditions. Of the 10 streams used in this assessment, 5 currently have less than a 50% chance of translocation success. Warming increased the probability of translocation success in these 5 streams by 11.2% and 21.8% in the 2 scenarios, respectively. Assuming barriers to upstream migration by nonnative competitors maintain their integrity, we conclude that an overall habitat improvement results because greenbacks have been restricted through competition with nonnatives to suboptimal habitats, which are generally too cold to be highly productive.
ABSTRACT: An artificial neural network (ANN) was used to evaluate the hydrological responses of two streams in the northeastern U.S. having different hydroclimatologies (rainfall and snow + rain) to hypothetical changes in precipitation and thermal regimes associated with climate change. For each stream, historic precipitation and temperature data were used as input to an ANN, which generated a synthetic daily hydrograph with high goodness-of-fit (r2 > 0.80). Four scenarios of climate change were used to evaluate stream responses to climate change: + 25% precipitation, -25% precipitation, 2x the coefficient of variation in precipitation regime, and +3°C average temperature. Responses were expressed in hydrological terms of ecological relevance, including flow variabilitiy, baseflow conditions, and frequency and predictability of floods. Increased average precipitation induced elevated runoff and more frequent high flow events, while decreased precipitation had the opposite effect. Elevated temperature reduced average runoff. Doubled precipitation variability had a large effect on many variables, including average runoff, variability of flow, flooding frequency, and baseflow stability. In general, the rainfall-dominated stream exhibited greater relative response to climate change scenarios than did the snowmelt stream.
Rehfeldt, G.E., Crookston, N.L., Warwell, M.V., Evans, J.S. (2006). Empirical analyses of plant-climate relationships for the western United States. International Journal of Plant Sciences 167 (6): 1123-1150
ABSTRACT: The Random Forests multiple-regression tree was used to model climate profiles of 25 biotic communities of the western United States and nine of their constituent species. Analyses of the communities were based on a gridded sample of ca. 140,000 points, while those for the species used presence-absence data from ca. 120,000 locations. Independent variables included 35 simple expressions of temperature and precipitation and their interactions. Classification errors for community models averaged 19%, but the errors were reduced by half when adjusted for misalignment between geographic data sets. Errors of omission for species-specific models approached 0, while errors of commission were less than 9%. Mapped climate profiles of the species were in solid agreement with range maps. Climate variables of most importance for segregating the communities were those that generally differentiate maritime, continental, and monsoonal climates, while those of importance for predicting the occurrence of species varied among species but consistently implicated the periodicity of precipitation and temperature-precipitation interactions. Projections showed that unmitigated global warming should increase the abundance primarily of the montane forest and grassland community profiles at the expense largely of those of the subalpine, alpine, and tundra communities but also that of the arid woodlands. However, the climate of 47% of the future landscape may be extramural to contemporary community profiles. Effects projected on the spatial distribution of species-specific profiles were varied, but shifts in space and altitude would be extensive. Species-specific projections were not necessarily consistent with those of their communities.
ABSTRACT: Computer simulation models are increasingly being proposed as tools capable of giving water resource managers accurate predictions of the impact of changes in land-use and climate. Previous validation testing of catchment models is reviewed, and it is concluded that the methods used do not clearly test a model's fitness for such a purpose. A new generally applicable method is proposed. This involves the direct testing of fitness for purpose, uses established scientific techniques, and may be implemented within a quality assured programme of work. The new method is applied in Part 2 of this study (Parkin et al., J. Hydrol., 175:595–613, 1996).
ABSTRACT: Water availability on the continents is important for human health economic activity, ecosystem function and geophysical processes. Because the saturation vapour pressure of water in air is highly sensitive to temperature, perturbations in the global water cycle are expected to accompany climate warming. Regional patterns of warming-induced changes in surface hydroclimate are complex and less certain than those in temperature, however, with both regional increases and decreases expected in precipitation and runoff. Here we show that an ensemble of 12 climate models exhibits qualitative and statistically significant skill in simulating observed regional patterns of twentieth-century multidecadal changes in streamflow. These models project 10–40% increases in runoff in eastern equatorial Africa, the La Plata basin and high-latitude North America and Eurasia, and 10–30% decreases in runoff in southern Africa, southern Europe, the Middle East and mid-latitude western North America by the year 2050. Such changes in sustainable water availability would have considerable regional-scale consequences for economies as well as ecosystems.
ABSTRACT: The sensitivity of streamflow to climate change was investigated in the American, Carson, and Truckee River Basins, California and Nevada. Nine gaging stations were used to represent streamflow in the basins. Annual models were developed by regressing 1961-1991 streamflow data on temperature and precipitation. Climate-change scenarios were used as inputs to the models to determine streamflow sensitivities. Climate-change scenarios were generated from historical time series by modifying mean temperatures by a range of +4°C to -4°C and total precipitation by a range of +25 percent to -25 percent. Results show that streamflow on the warmer, lower west side of the Sierra Nevada generally is more sensitive to temperature and precipitation changes than is streamflow on the colder, higher east side. A 2°C rise in temperature and a 25-percent decrease in precipitation results in streamflow decreases of 56 percent on the American River and 25 percent on the Carson River. A 2°C decline in temperature and a 25-percent increase in precipitation results in streamflow increases of 102 percent on the American River and 22 percent on the Carson River.
ABSTRACT: Changes in regional temperature and precipitation expected to occur as a result of the accumulation of greenhouse gases may have significant impacts on water resources. We use a conceptual hydrologic model, developed and operated by the National Weather Service, to study the sensitivity of surface runoff in several sub-basins of the Colorado River to these changes. Increases in temperature of 2°C decrease mean annual runoff by 4–12%. A temperature increase of 4°C decreases mean annual runoff by 9–21%. Increases or decreases in annual precipitation of 10–20% result in corresponding changes in mean annual runoff of approximately 10–20%. For the range of scenarios studied, these results suggest that runoff in the basin is somewhat more sensitive to changes in precipitation than to changes in temperature. Seasonal changes were also observed, with peak runoff shifting from June to April or May. Fall and winter flows generally increase, whereas spring and summer flows decrease in most of the scenarios studied. These changes are attributed to an increase of the ratio of rain to snow and to a higher snowline. Although these results suggest that streamflow in the Colorado Basin is less sensitive to climatic changes than previous statistical studies have indicated, the magnitude of possible changes is nonetheless sufficiently great to have significant environmental, economic, and political implications.
ABSTRACT: The effects of changes in climate on aquifer storage and groundwater flow to rivers have been investigated using an idealized representation of the aquifer/river system. The generalized aquifer/river model can incorporate spatial variability in aquifer transmissivity and is applied with parameters characteristic of Chalk and Triassic sandstone aquifers in the United Kingdom, and is also applicable to other aquifers elsewhere. The model is run using historical time series of recharge, estimated from observed rainfall and potential evaporation data, and with climate inputs perturbed according to a number of climate change scenarios. Simulations of baseflow suggest large proportional reductions at low flows from Chalk under high evaporation change scenarios. Simulated baseflow from the slower responding Triassic sandstone aquifer shows more uniform and less severe reductions. The change in hydrological regime is less extreme for the low evaporation change scenario, but remains significant for the Chalk aquifer.
J. Battin, M. W. Wiley, M.H. Ruckelshaus, R. N. Palmer, E. Korb, K. K. Bartz, H. Imaki (2007). Projected impacts of climate change on salmon habitat restoration. Proceedings of the National Academy of Sciences 104 (16): 6720-6725
ABSTRACT: Throughout the world, efforts are under way to restore watersheds, but restoration planning rarely accounts for future climate change. Using a series of linked models of climate, land cover, hydrology, and salmon population dynamics, we investigated the impacts of climate change on the effectiveness of proposed habitat restoration efforts designed to recover depleted Chinook salmon populations in a Pacific Northwest river basin. Model results indicate a large negative impact of climate change on freshwater salmon habitat. Habitat restoration and protection can help to mitigate these effects and may allow populations to increase in the face of climate change. The habitat deterioration associated with climate change will, however, make salmon recovery targets much more difficult to attain. Because the negative impacts of climate change in this basin are projected to be most pronounced in relatively pristine, high-elevation streams where little restoration is possible, climate change and habitat restoration together are likely to cause a spatial shift in salmon abundance. River basins that span the current snow line appear especially vulnerable to climate change, and salmon recovery plans that enhance lower-elevation habitats are likely to be more successful over the next 50 years than those that target the higher-elevation basins likely to experience the greatest snow–rain transition.
ABSTRACT: To evaluate the hydrologic and biogeochemical response of freshwater watersheds to climatic variability properly, a mathematical model with detailed parameterization in describing the hydrologic and thermal processes in a watershed is needed. For this purpose, the Enhanced Trickle Down model was modified to predict the hydrologic and thermal responses of freshwater watersheds to various climate change scenarios. Modifications of the model included the incorporation of an energy transfer submodel, an improved hydraulic conductivity scheme, and the coupling with a point source snowmelt model. The results of calibration and verification of the model using 8 years of field data collected at the Agricultural Research Service, W-3 watershed, located near Danville, Vermont, are presented.
Knowles, N., D. Cayan (2002). Potential effects of global warming on the Sacramento/San Joaquin watershed and the San Francisco estuary. Geophysical Research Letters 29 (18): 1891, doi:10.1029/2001GL014339
ABSTRACT: California's primary hydrologic system, the San Francisco estuary and its upstream watershed, is vulnerable to the regional hydrologic consequences of projected global climate change. Projected temperature anomalies from a global climate model are used to drive a combined model of watershed hydrology and estuarine dynamics. By 2090, a projected temperature increase of 2.1°C results in a loss of about half of the average April snowpack storage, with greatest losses in the northern headwaters. Consequently, spring runoff is reduced by 5.6 km3 (~20% of historical annual runoff), with associated increases in winter flood peaks. The smaller spring flows yield spring/summer salinity increases of up to 9 psu, with larger increases in wet years.
ABSTRACT: Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species’ bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate envelope models and discusses the implications of these criticisms for the different modelling strategies employed. It is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity. However, it is stressed that the spatial scale at which these models are applied is of fundamental importance, and that model results should not be interpreted without due consideration of the limitations involved. A hierarchical modelling framework is proposed through which some of these limitations can be addressed within a broader, scale-dependent context.
Payne, J.T., A. W. Wood, A. F. Hamlet, R. N. Palmer, D. P. Lettenmaier (2004). Mitigating the effects of climate change on the water resources of the Columbia River Basin. Climatic Change 62 (1-3): 233-256
ABSTRACT: Atmospheric Research Parallel Climate Model (DOE/NCAR PCM). This study focuses on three climate projections for the 21st century based on a `business as usual' (BAU) global emissions scenario, evaluated with respect to a control climate scenario based on static 1995 emissions. Time-varying monthly PCM temperature and precipitation changes were statistically downscaled and temporally disaggregated to produce daily forcings that drove a macro-scale hydrologic simulation model of the Columbia River basin at ¼-degree spatial resolution. For comparison with the direct statistical downscaling approach, a dynamical downscaling approach using a regional climate model (RCM) was also used to derive hydrologic model forcings for 20-year subsets from the PCM control climate (1995–2015) scenario and from the three BAU climate (2040–2060) projections. The statistically downscaled PCM scenario results were assessed for three analysis periods (denoted Periods 1–3: 2010–2039, 2040–2069, 2070–2098) in which changes in annual average temperature were +0.5, +1.3 and +2.1 °C, respectively, while critical winter season precipitation changes were –3, +5 and +1 percent. For RCM, the predicted temperature change for the 2040–2060 period was +1.2 °C and the average winter precipitation change was –3 percent, relative to the RCM control climate. Due to the modest changes in winter precipitation, temperature changes dominated the simulated hydrologic effects by reducing winter snow accumulation, thus shifting summer streamflow to the winter. The hydrologic changes caused increased competition for reservoir storage between firm hydropower and instream flow targets developed pursuant to the Endangered Species Act listing of Columbia River salmonids. We examined several alternative reservoir operating policies designed to mitigate reservoir system performance losses. In general, the combination of earlier reservoir refill with greater storage allocations for instream flow targets mitigated some of the negative impacts to flow, but only with significant losses in firm hydropower production (ranging from –9 percent in Period 1 to –35 percent for RCM). Simulated hydropower revenue changes were less than 5 percent for all scenarios, however, primarily due to small changes in annual runoff.
ABSTRACT: In this paper we present a comprehensive set of interpolated climate data for western Canada, including monthly data for the last century (1901–2006), future projections from general circulation models (68 scenario implementations from 5 GCMs), as well as decadal averages and multiple climate normals for the last century. For each of these time periods, we provide a large set of basic and derived biologically relevant climate variables, such as growing and chilling degree days, growing season length descriptors, frost free days, extreme minimum temperatures, etc. To balance file size versus accuracy for these approximately 15,000 climate surfaces, we provide a stand-alone software solution that adds or subtracts historical data and future projections as medium resolution anomalies (deviations) from the high resolution 1961–1990 baseline normal dataset. For a relative quality comparison between the original normal data generated with the Parameter Regression of Independent Slopes Model (PRISM) and derived historical data, we calculated the amount of variance explained (R2 ) in original weather station data for each year and month from 1901 to 2006. R2 values remained very high for most of the time period covered for most variables. Reduction in data quality was found for individual months (as opposed to annual, decadal or 30-year climate averages) and for the early decades of the last century. We discuss the limitations of the database and provide an overview of recent climate trends for western Canada.