Climatic change and the broad-scale distribution of terrestrial ecosystem complexes

The broad-scale distribution of terrestrial ecosystem complexes is determined in large part by climate and can be altered by climatic change due to natural causes or due to human activities such as those leading to increasing atmospheric CO₂ concentration. Classifications that recognize the dependence of natural vegetation on climate provide one means of constructing maps to display the impact of climatic change on the geography of major vegetation zones. A world map of the Holdridge Life-Zone Classification, developed from approximately 8,000 meteorological records, is compared with a Holdridge Map with average temperature increments simulated by a. model of climate under elevated atmospheric CO₂ concentration. The largest changes are indicated at high latitudes, where the simulated temperature increase is largest and the temperature intervals defining life zones are smallest. Boreal Forest Zones are replaced by either Cool Temperate Forest or Cool Temperate Steppe, depending on average precipitation. Changes in the tropics are smaller; however, in some regions, Subtropical Moist Forest is replaced by Tropical Dry Forest.Research supported by the National Science Foundation's Ecosystem Studies Program under Interagency Agreement Nos. DEB81-15316 and DEB83-15185.     

A Climate Change Scenario for the Tropics

This paper describes the construction of a climate change scenario for a region representing the extended Tropics – 30° N to 30° S – using a methodology that combines results from a simple climate model and a Global Climate Model (GCM) transient climate change experiment. The estimated date by which this climate change scenario might be realized ranges from as early as the end of the 2030s to as late as well into the 22nd century. The central estimate is for this scenario to describe the climate of the 2060s, which would represent a global warming rate of about 0.2 °C per decade, with associated atmospheric CO₂ concentrations estimated to be about 560 ppmv, 55% higher than 1990 levels. The role of anthropogenic aerosols in offsetting part of this future global warming and altering the regional character of the changes has not been considered. The paper presents changes in mean temperature; mean rainfall; rainfall seasonality, variability, frequency, and intensity and soil moisture. These patterns of change derive from only one GCM climate change experiment; different experiments would yield different patterns for the same global warming. There is also some discussion about possible changes in tropical cyclone (TC) activity, although since TCs remain poorly modelled in GCMs, the full range of possibilities (from reduced activity, through no change, to increased activity) should be considered in any impact assessment.     

A Climate Change Database for Biological Assessments in the Southeastern United States: Development and Case Study

A regional database containing historical time series and climate change scenarios for the Southeastern United States was developed for the U.S.D.A. Forest Service Southern Global Change Program (SGCP). Daily historical values of maximum temperature, minimum temperature and precipitation and empirically derived estimates of vapor pressure deficit and solar radiation across a uniform 1° latitude × 1° longitude grid were obtained. Climate change scenarios of temperature, precipitation, vapor pressure deficit and solar radiation were generated using semi-empirical techniques which combined historical time series and simulation field summaries from GISS, GFDL, OSU and UKMO General Circulation Model (GCM) experiments. An internally consistent 1° latitude × 1° longitude climate change scenario database was produced in which vapor pressure deficit and solar radiation conditions were driven by the GCM temperature projections, but were not constrained to agree with GCM calculated radiation and humidity fields. Some of the unique characteristics of the database were illustrated through a case study featuring growing season and annual potential evapotranspiration (ET_p) estimates. Overall, the unconstrained scenarios produced smaller median ET_p changes from historical baseline conditions, with a smaller range of outcomes than those driven by GCM-directed scenarios. Collectively, the range of annual and growing season ET changes from baseline estimates in response to the unconstrained climate scenarios was +10% to +40%. No outlier responses were identified. ET_p changes driven by GCM-directed (constrained) UKMO radiation and humidity scenarios were on the order of +100%, resulting in the identification of some ET_p responses as statistical outliers. These response differences were attributed to differences between the constrained and unconstrained humidity scenarios.     

Arctic climate change with a 2 ∘C global warming: Timing, climate patterns and vegetation change

The signatories to United Nations Framework Convention on Climate Change are charged with stabilizing the concentrations of greenhouse gases in the atmosphere at a level that prevents dangerous interference with the climate system. A number of nations, organizations and scientists have suggested that global mean temperature should not rise over 2 ^°C above preindustrial levels. However, even a relatively moderate target of 2 ^°C has serious implications for the Arctic, where temperatures are predicted to increase at least 1.5 to 2 times as fast as global temperatures. High latitude vegetation plays a significant role in the lives of humans and animals, and in the global energy balance and carbon budget. These ecosystems are expected to be among the most strongly impacted by climate change over the next century. To investigate the potential impact of stabilization of global temperature at 2 ^°C, we performed a study using data from six Global Climate Models (GCMs) forced by four greenhouse gas emissions scenarios, the BIOME4 biogeochemistry-biogeography model, and remote sensing data. GCM data were used to predict the timing and patterns of Arctic climate change under a global mean warming of 2 ^°C. A unified circumpolar classification recognizing five types of tundra and six forest biomes was used to develop a map of observed Arctic vegetation. BIOME4 was used to simulate the vegetation distributions over the Arctic at the present and for a range of 2 ^°C global warming scenarios. The GCMs simulations indicate that the earth will have warmed by 2 ^°C relative to preindustrial temperatures by between 2026 and 2060, by which stage the area-mean annual temperature over the Arctic (60–90^°N) will have increased by between 3.2 and 6.6 ^°C. Forest extent is predicted by BIOME4 to increase in the Arctic on the order of 3 × 10⁶ km² or 55% with a corresponding 42% reduction in tundra area. Tundra types generally also shift north with the largest reductions in the prostrate dwarf-shrub tundra, where nearly 60% of habitat is lost. Modeled shifts in the potential northern limit of trees reach up to 400 km from the present tree line, which may be limited by dispersion rates. Simulated physiological effects of the CO₂ increase (to ca. 475 ppm) at high latitudes were small compared with the effects of the change in climate. The increase in forest area of the Arctic could sequester 600 Pg of additional carbon, though this effect is unlikely to be realized over next century.     

Future changes of the terrestrial ecosystem based on a dynamic vegetation model driven with RCP8.5 climate projections from 19 GCMs

Future changes of terrestrial ecosystems due to changes in atmospheric CO₂ concentration and climate are subject to a large degree of uncertainty, especially for vegetation in the Tropics. Here, we evaluate the natural vegetation response to projected future changes using an improved version of a dynamic vegetation model (CLM-CN-DV) driven with climate change projections from 19 global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The simulated equilibrium vegetation distribution under historical climate (1981–2000) has been compared with that under the projected future climate (2081–2100) scenario for Representative Concentration Pathway 8.5 (RCP8.5) to qualitatively assess how natural potential vegetation might change in the future. With one outlier excluded, the ensemble average of vegetation changes corresponding to climates of 18 GCMs shows a poleward shift of forests in northern Eurasia and North America, which is consistent with findings from previous studies. It also shows a general “upgrade” of vegetation type in the Tropics and most of the temperate zones, in the form of deciduous trees and shrubs taking over C3 grass in Europe and broadleaf deciduous trees taking over C4 grasses in Central Africa and the Amazon. LAI and NPP are projected to increase in the high latitudes, southeastern Asia, southeastern North America, and Central Africa. This results from CO₂ fertilization, enhanced water use efficiency, and in the extra-tropics warming. However, both LAI and NPP are projected to decrease in the Amazon due to drought. The competing impacts of climate change and CO₂ fertilization lead to large uncertainties in the projection of future vegetation changes in the Tropics.     

Influence of dynamic vegetation on climate change arising from increasing CO<Subscript>2</Subscript>

A dynamic global vegetation model (DGVM) is coupled to an atmospheric general circulation model (AGCM) to investigate the influence of vegetation dynamics on climate change under conditions of global warming. The model results are largely in agreement with observations and the results of previous studies in terms of the present climate, present potential vegetation, present net primary productivity (NPP), and pre-industrial carbon budgets. The equilibrium state of climate properties are compared among pre-industrial, doubled, and quadrupled atmospheric CO₂ values using DGVM–AGCM and current AGCM with fixed vegetation to evaluate the influence of dynamic vegetation change. We also separated the contributions of temperature, precipitation and CO₂ fertilization on vegetation change. The results reveal an amplification of global warming climate sensitivity by 10% due to the inclusion of dynamic vegetation. The total effects of elevated CO₂ and climate change also lead to an increase in NPP and vegetation coverage globally. The reduction of albedo associated with this greening results in enhanced global warming. Our separation analysis indicates that temperature alters vegetation at high latitudes such as Siberia or Alaska, where there is a switch from tundra to forest. On the other hand, CO₂ fertilization provides the largest contribution to greening in arid/semi-arid region. Precipitation change did not cause any drastic vegetation shift.     

A projection of extreme climate events in the 21st century over east Asia using the community climate system model 3

A series of coupled atmosphere-ocean-land global climate model (GCM) simulations using the National Center for Atmospheric Research (NCAR) Community Climate System Model 3 (CCSM3) has been performed for the period 1870–2099 at a T85 horizontal resolution following the GCM experimental design suggested in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). First, a hindcast was performed using the atmospheric concentrations of three greenhouse gases (CO₂, CH₄, N₂O) specified annually and globally on the basis of observations for the period 1870–1999. The hindcast results were compared with observations to evaluate the GCM’s reliability in future climate simulations. Second, climate projections for a 100-year period (2000–2099) were made using six scenarios of the atmospheric concentrations of the three greenhouse gases according to the A1FI, A1T, A1B, A2, B1, and B2 emission profiles of the Special Report on Emissions Scenarios. The present CCSM simulations are found to be consistent with IPCC’s AR4 results in the temporal and spatial distributions for both the present-day and future periods. The GCM results were used to examine the changes in extreme temperatures and precipitation in East Asia and Korea. The extreme temperatures were categorized into warm and cold events: the former includes tropical nights, warm days, and heat waves during summer (June–July–August) and the latter includes frost days, cold days, and cold surges during winter (December–January–February). Focusing on Korea, the results predict more frequent heat waves in response to future emissions: the projected percentage changes between the present day and the late 2090s range from 294% to 583% depending on the emission scenario. The projected global warming is predicted to decrease the frequency of cold extreme events; however, the projected changes in cold surge frequency are not statistically significant. Whereas the number of cold surges in the A1FI emission profile decreases from the present-day value by up to 24%, the decrease in the B1 scenario is less than 1%. The frequency and intensity of extreme precipitation events year-round were examined. Both the frequency and the intensity of these events are predicted to increase in the region around Korea. The present results will be helpful for establishing an adaptation strategy for possible climate change nationwide, especially extreme climate events, associated with global warming.     

Vulnerability and adaptation assessments of agriculturalcrops under climate change in the Southeastern USA

Summary  It is expected that a change in climatic conditions due to global warming will directly impact agricultural production. Most climate change studies have been applied at very large scales, in which regions were represented by only one or two weather stations, which were mainly located at airports of major cities. The objective of this study was to determine the potential impact of climate change at a local level, taking into account weather data recorded at remote locations. Daily weather data for a 30-year period were obtained for more than 500 sites, representing the southeastern region of the USA. Climate change scenarios, using transient and equilibrium global circulation models (GCM), were defined, created and applied to the daily historical weather data. The modified temperature, precipitation and solar radiation databases corresponding to each of the climate change scenarios were used to run the CERES v.3.5 simulation model for maize and winter wheat and the CROPGRO v.3.5 model for soybean and peanut. The GCM scenarios projected a shorter duration of the crop-growing season. Under the current level of CO₂, the GCM scenarios projected a decrease of crop yields in the 2020s. When the direct effects of CO₂ were assumed in the study, the scenarios resulted in an increase in soybean and peanut yield. Under equilibrium , the GCM climate change scenarios projected a decrease of maize and winter wheat yield. The indirect effects of climate change also tended to decrease soybean and peanut yield. However, when the direct effects of CO₂ were included, most of the scenarios resulted in an increase in legume yields. Possible changes in sowing data, hybrids and cultivar selection, and fertilization were considered as adaptation options to mitigate the potential negative impact of potential warming. Received July 20, 1999/Revised April 18, 2000     

The modification of greenhouse gas warming by the direct effect of sulphate aerosols

 The Canadian Centre for Climate Modelling and Analysis (CCCma) second generation climate model (GCMII) consists of an atmospheric GCM coupled to mixed layer ocean. It is used to investigate the climate response to a doubling of the CO₂ concentration together with the direct effect of scattering by sulphate aerosols. As expected, the aerosols offset some of the greenhouse gas (GHG) warming; the global annual mean screen temperature change due to doubled CO₂ is 3.4 °C in this model and this is reduced to 2.7 °C when an estimate of the direct effect of anthropogenic sulphate aerosols is included. The pattern of climate response to the comparatively localized aerosol forcing is not itself localized, and it bears a striking resemblance to the response pattern that arises from the globally distributed change in GHG forcing. This “non-local” response to “localized” forcing indicates that the pattern of climate response is determined, to first order, by the overall magnitude of the change in forcing rather than its detailed nature or structure. Feedback processes operating in the system apparently determine this pattern by locally amplifying and suppressing the response to the magnitude of the change in forcing. The influence of the location of the change in forcing is relatively small. These “non-local” and “local” effects of aerosol forcing are characterized and displayed and some of their consequences discussed. Effects on the moisture budget and on the energetics of the global climate are also examined. Received: 10 June 1997 / Accepted: 8 January 1998     

Modeling the eco-hydrologic response of a Mediterranean type ecosystem to the combined impacts of projected climate change and altered fire frequencies

Global Climate Models (GCMs) project moderate warming along with increases in atmospheric CO₂ for California Mediterranean type ecosystems (MTEs). In water-limited ecosystems, vegetation acts as an important control on streamflow and responds to soil moisture availability. Fires are also key disturbances in semi-arid environments, and few studies have explored the potential interactions among changes in climate, vegetation dynamics, hydrology, elevated atmospheric CO2 concentrations and fire. We model ecosystem productivity, evapotranspiration, and summer streamflow under a range of temperature and precipitation scenarios using RHESSys, a spatially distributed model of carbon–water interactions. We examine the direct impacts of temperature and precipitation on vegetation productivity and impacts associated with higher water-use efficiency under elevated atmospheric CO2. Results suggest that for most climate scenarios, biomass in chaparral-dominated systems is likely to increase, leading to reductions in summer streamflow. However, within the range of GCM predictions, there are some scenarios in which vegetation may decrease, leading to higher summer streamflows. Changes due to increases in fire frequency will also impact summer streamflow but these will be small relative to changes due to vegetation productivity. Results suggest that monitoring vegetation responses to a changing climate should be a focus of climate change assessment for California MTEs.     

Annual and seasonal climate and climatic changes in the Canadian prairies simulated by the CCC GCM

Abstract

As part of a study on the effects of climatic variability and change on the sustainability of agriculture in Alberto, the modelling performance of the second‐generation Canadian Climate Centre GCM (general circulation model) is examined. For the region in general, the simulation of 1 × CO₂ mean temperature is generally better than that for mean precipitation, and summer is the season best modelled for each variable. At the scale of individual grid squares, DJF (December, January, February) (temperature) and JJA (June, July, August) (precipitation) are the seasons best modelled. The GCM‐simulated increases in mean annual temperature resulting from a doubling of CO₂ are of the order of 5 to 6°C in the Prairie region, with much of this increase resulting from substantial warming in the winter and spring. Increases in mean annual precipitation are of the order of 50 to 150 mm (changes of +5 to +15%), with the greatest changes again occurring in winter and spring. As far as the limited GCM run durations allow, temperature and precipitation variance generally show no significant changes from a 1 × CO₂ to a 2 × CO₂ climate. Increased precipitation in winter and spring does not result in greater snow accumulations owing to the magnitude of warming; and significant decreases in soil moisture content occur in summer and fall. The resulting effects on the growing season and moisture regime have the potential to affect agricultural practices in the area.     

Use of general circulation model output in the creation of climate change scenarios for impact analysis

Many scientific studies warn of a rapid global climate change during the next century. These changes are understood with much less certainty on a regional scale than on a global scale, but effects on ecosystems and society will occur at local and regional scales. Consequently, in order to study the true impacts of climate change, regional scenarios of future climate are needed. One of the most important sources of information for creating scenarios is the output from general circulation models (GCMs) of the climate system. However, current state-of-the-art GCMs are unable to simulate accurately even the current seasonal cycle of climate on a regional basis. Thus the simple technique of adding the difference between 2 × CO₂ and 1 × CO₂ GCM simulations to current climatic time series cannot produce scenarios with appropriate spatial and temporal details without corrections for model deficiencies. In this study a technique is developed to allow the information from GCM simulations to be used, while accommodating for the deficiencies. GCM output is combined with knowledge of the regional climate to produce scenarios of the equilibrium climate response to a doubling of the atmospheric CO₂ concentration for three case study regions, China, Sub-Saharan Africa and Venezuela, for use in biological effects models. By combining the general climate change calculated with several GCMs with the observed patterns of interannual climate variability, reasonable scenarios of temperature and precipitation variations can be created. Generalizations of this procedure to other regions of the world are discussed.     

Improved methods for estimating equilibrium climate sensitivity from transient warming simulations

Climate Dynamics - Equilibrium climate sensitivity (ECS) refers to the total global warming caused by an instantaneous doubling of atmospheric CO2 from the pre-industrial level in a climate system....     

The potential effects of climate change on summer season dairy cattle milk production and reproduction

The potential direct effects of possible global warming on summer season dairy production and reproduction were evaluated for the United States and Europe. Algorithms used for milk production and conception rate were previously developed and validated. Three widely known global circulation models (GISS, GFDL, and UKMO) were used to represent possible scenarios of future climate. Milk production and conception rate declines were highest under the UKMO model scenario and lowest under the GISS model scenario. Predicted declines for the GCM scenarios are generally higher than either 1 year in 10 probability-based declines or declines based on the abnormally hot summer of 1980 in the United States. The greatest declines (about 10% for the GISS and GFDL scenarios, and about 20% for the UKMO scenario) in the United States are predicted to occur in the Southeast and the Southwest. Substantial declines (up to 35%) in conception rates were also predicted in many locations, particularly the eastern and southern United States. These areas correspond to areas of high dairy cattle concentration. They already have relatively large summer season milk production declines resulting from normally hot conditions. Thus, the actual impacts of increased production declines may be greater in other areas, which are not accustomed to large summer season declines and therefore may require more extensive mitigation measures.Published as Paper No. 9698 Journal Series, Nebraska Agricultural Research Division. The work reported here was conducted under Nebraska Agricultural Research Division Project 27–007.     

An analogue model to derive additional climate change scenarios from existing GCM simulations

 Changes in land surface driving variables, predicted by GCM transient climate change experiments, are confirmed to exhibit linearity in the global mean land temperature anomaly, ΔT _l . The associated constants of proportionality retain spatial and seasonal characteristics of the GCM output, whilst ΔT _l is related to radiative forcing anomalies. The resultant analogue model is shown to be robust between GCM runs and as such provides a computationally efficient technique of extending existing GCM experiments to a large range of climate change scenarios. As an example impacts study, the analogue model is used to drive a terrestrial ecosystem model, and predicted changes in terrestrial carbon are found to be similar to those when using GCM anomalies directly. Received: 4 January 1999 / Accepted: 11 December 1999     

A reassessment of the economic effects of global climate change on U.S. agriculture

This study uses recent GCM forecasts, improved plant science and water supply data and refined economic modeling capabilities to reassess the economic consequences of long-term climate change on U.S. agriculture. Changes in crop yields, crop water demand and irrigation water arising from climate change result in changes in economic welfare. Economic consequences of the three GCM scenarios are mixed; GISS and GFDL-QFlux result in aggregate economic gains, UKMO implies losses. As in previous studies, the yield enhancing effects of atmospheric CO₂ are an important determinant of potential economic consequences. Inclusion of changes in world food production and associated export changes generally have a positive affect on U.S. agriculture. As with previous studies, the magnitude of economic effects estimated here are a small percentage of U.S. agricultural value.     

The potential effects of climate change on ecosystem processes and cattle production on U.S. rangelands

In spite of the uncertainties of potential climate change, a scientific consensus is emerging that increasing concentrations of atmospheric CO₂ could alter global temperatures and precipitation patterns. Changes in global climate as predicted by General Circulation Models (GCM) could therefore, have profound implications for global agriculture. The objective of this study was to assess the impacts of potential climate change on livestock and grassland production in the major producing regions of the United States. Simulation sites were selected for the study on the basis of the region's economic dependence on rangeland livestock production. Five thirty-year simulations were conducted on each site using the Simulation of Production and Utilization of Rangelands model and Colorado Beef Cattle Production Model. Climate change files were obtained by combining historic weather data from each site with predicted output from three GCM's. Results from nominal runs were compared with the three climate change scenarios and a doubled CO₂ run. The magnitude and direction of ecosystem response to climate change varied among the GCM's and by geographic region. Simulations demonstrated that changes in temperature and precipitation patterns caused an increase in above-ground net primary production for most sites. Increased decomposition rates were recorded for northern regions. Similarly, animal production in northern regions increased, implying an increase in economic survivability. However, because decreases in animal production indicators were recorded for the southern regions, economic survivability in southern regions is less certain.     

Uncertainty in the 2°C warming threshold related to climate sensitivity and climate feedback

Climate sensitivity is an important index that measures the relationship between the increase in greenhouse gases and the magnitude of global warming. Uncertainties in climate change projection and climate modeling are mostly related to the climate sensitivity. The climate sensitivities of coupled climate models determine the magnitudes of the projected global warming. In this paper, the authors thoroughly review the literature on climate sensitivity, and discuss issues related to climate feedback processes and the methods used in estimating the equilibrium climate sensitivity and transient climate response (TCR), including the TCR to cumulative CO₂ emissions. After presenting a summary of the sources that affect the uncertainty of climate sensitivity, the impact of climate sensitivity on climate change projection is discussed by addressing the uncertainties in 2°C warming. Challenges that call for further investigation in the research community, in particular the Chinese community, are discussed.     

Comparison of uncertainty sources for climate change impacts: flood frequency in England

This paper investigates the uncertainty in the impact of climate change on flood frequency in England, through the use of continuous simulation of river flows. Six different sources of uncertainty are discussed: future greenhouse gas emissions; Global Climate Model (GCM) structure; downscaling from GCMs (including Regional Climate Model structure); hydrological model structure; hydrological model parameters and the internal variability of the climate system (sampled by applying different GCM initial conditions). These sources of uncertainty are demonstrated (separately) for two example catchments in England, by propagation through to flood frequency impact. The results suggest that uncertainty from GCM structure is by far the largest source of uncertainty. However, this is due to the extremely large increases in winter rainfall predicted by one of the five GCMs used. Other sources of uncertainty become more significant if the results from this GCM are omitted, although uncertainty from sources relating to modelling of the future climate is generally still larger than that relating to emissions or hydrological modelling. It is also shown that understanding current and future natural variability is critical in assessing the importance of climate change impacts on hydrology.