Local temperature estimation under climate change

Summary A methodology to estimate the space-time distribution of daily mean temperature under climate change is developed and applied to a central Nebraska case study. The approach is based on the analysis of the Markov properties of atmospheric circulation pattern (CP) types, and a stochastic linkage between daily (here 500hPa) CP types and daily mean temperatures. Historical data and general circulation model (GCM) output of daily CP corresponding to 1 × CO₂ and 2 × CO₂ scenarios are considered. The relationship between spatially averaged geopotential height of the 500 hPa surface — within each CP type — and daily mean temperature is described by a nonparametric regression technique. Time series of daily mean temperatures corresponding to each of these cases are simulated and their statistical properties are compared. Under the climate of central Nebraska, the space-time response of daily mean temperature to global climate change is variable. In general, a warmer climate appears to cause about 5°C increase in the winter months, a smaller increase in other months with no change in July and August. The sensitivity of the results to the GCM utilized should be considered.On leave from the Department of Meteorology, Eötvós Loránd University, Budapest, Hungary.With 14 Figures     

PROJECTIONS OF CLIMATE CHANGE FOR THE CZECH REPUBLIC

The paper deals with a selection of the climatological baseline, GCM validity and construction of the climate change scenarios for an impact assessment in the Czech territory. The period of 1961–1990 has been selected as the climatological baseline. The corresponding database includes more than 50 monthly mean temperature and precipitation series, and 16 time series of daily meteorological data that contain also the solar radiation data. The 1× CO₂ outputs produced by four GCMs, provided by the CSMT (GISS, GFD30, GFD01, and CCCM), were compared with observed temperature and precipitation conditions in western and central Europe with a particular attention devoted to the Czech territory. The GCM ability to simulate annual cycles of temperature, precipitation and radiation was thoroughly examined. The GISS and CCCM were selected as a basis for constructing climate change scenarios as they simulated reasonably the observed patterns. According to the GISS variant, 2× CO₂ climate assumes a higher winter and lower summer warming, and an increase in annual precipitation amounts. A dangerous combination of the summer temperature increase and declining precipitation amounts is a specific feature of the CCCM scenario. An incremental scenario for temperature and precipitation is based on the combination of prescribed changes in both annual means and annual courses.     

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     

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.     

Constructing Site-Specific Climate Change Scenarios on a Monthly Scale Using Statistical Downscaling

Summary Monthly mean temperature and monthly precipitation totals in two small catchments in the Czech Republic are estimated from large-scale 500 hPa height and 1000/500 hPa thickness fields using statistical downscaling. The method used is multiple linear regression. Whereas precipitation can be determined from large-scale fields with some confidence in only a few months of the year, temperature can be determined successfully. Principal components calculated separately from the height and thickness anomalies are identified as the best predictor set. The method is most accurate if the regression is performed using seasons based on three months. The test on an independent sample, consisting of warm seasons, confirms that the method successfully reproduces the difference in mean temperature between two climatic states, which indicates that this downscaling method is applicable for constructing scenarios of a future climate change. The ECHAM3 GCM is used for scenario construction. The GCM is shown to simulate surface temperature and precipitation with low accuracy, whereas the large-scale atmospheric fields are reproduced well; this justifies the downscaling approach. The observed regression equations are applied to 2xCO₂ GCM output so that the model’s bias is eleminated. This procedure is then discussed and finally, temperature scenarios for the 2xCO₂ climate are constructed for the two catchments. Received December 3, 1998 Revised December 4, 1999     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

As carbon dioxide and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how derivative changes in climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using twelve scenarios derived from General Circulation Model (GCM) projections to drive biophysical impact models. These scenarios are described in this paper. The scenarios are first put into the context of recent work on climate-change by the IPCC for the 21st century and span two levels of global-mean temperature change and three sets of spatial patterns of change derived from GCM results. In addition, the effect of either the presence or absence of a CO₂ fertilization effect on vegetation is examined by using two levels of atmospheric CO₂ concentration as a proxy variable. Results from three GCM experiments were used to produce different regional patterns of climate change. The three regional patterns for the conterminous United States range from: an increase in temperature above the global-mean level along with a significant decline in precipitation; temperature increases in line with the global-mean with an average increase in precipitation; and, with a sulfate aerosol effect added to in the same model, temperature increases that are lower than the global-mean. The resulting set of scenarios span a wide range of potential climate changes and allows examination of the relative importance of global-mean temperature change, regional climate patterns, aerosol cooling, and CO₂ fertilization effects.     

Implications of CO2 global warming on great lakes ice cover

Statistical ice cover models were used to project daily mean basin ice cover and annual ice cover duration for Lakes Superior and Erie. Models were applied to a 1951–80 base period and to three 30-year steady double carbon dioxide (2 × CO₂) scenarios produced by the Geophysical Fluid Dynamics Laboratory (GFDL), the Goddard Institute of Space Studies (GISS), and the Oregon State University (OSU) general circulation models. Ice cover estimates were made for the West, Central, and East Basins of Lake Erie and for the West, East, and Whitefish Bay Basins of Lake Superior. Average ice cover duration for the 1951– 80 base period ranged from 13 to 16 weeks for individual lake basins. Reductions in average ice cover duration under the three 2 × CO₂ scenarios for individual lake basins ranged from 5 to 12 weeks for the OSU scenario, 8 to 13 weeks for the GISS scenario, and 11 to 13 weeks for GFDL scenario. Winters without ice formation become common for Lake Superior under the GFDL scenario and under all three 2 × CO₂ scenarios for the Central and East Basins of Lake Erie. During an average 2 × CO₂ winter, ice cover would be limited to the shallow areas of Lakes Erie and Superior. Because of uncertainties in the ice cover models, the results given here represent only a first approximation and are likely to represent an upper limit of the extent and duration of ice cover under the climate change projected by the three 2 × CO₂scenarios. Notwithstanding these limitations, ice cover projected by the 2 × CO₂ scenarios provides a preliminary assessment of the potential sensitivity of the Great Lakes ice cover to global warming. Potential environmental and socioeconomic impacts of a 2 × CO₂ warming include year-round navigation, change in abundance of some fish species in the Great Lakes, discontinuation or reduction of winter recreational activities, and an increase in winter lake evaporation.     

Climate Change and Forest Fire Potential in Russian and Canadian Boreal Forests

In this study outputs from four current General Circulation Models (GCMs) were used to project forest fire danger levels in Canada and Russia under a warmer climate. Temperature and precipitation anomalies between 1 × CO₂ and 2 × CO₂ runs were combined with baseline observed weather data for both countries for the 1980–1989 period. Forecast seasonal fire weather severity was similar for the four GCMs, indicating large increases in the areal extent of extreme fire danger in both countries under a 2 × CO₂ climate scenario. A monthly analysis, using the Canadian GCM, showed an earlier start to the fire season, and significant increases in the area experiencing high to extreme fire danger in both Canada and Russia, particularly during June and July. Climate change as forecast has serious implications for forest fire management in both countries. More severe fire weather, coupled with continued economic constraints and downsizing, mean more fire activity in the future is a virtual certainty. The likely response will be a restructuring of protection priorities to support more intensive protection of smaller, high-value areas, and a return to natural fire regimes over larger areas of both Canada and Russia, with resultant significant impacts on the carbon budget.     

Simulated Climate Change Effects on Year-Round Water Temperatures in Temperate Zone Lakes

A deterministic, one-dimensional model is presented to simulate daily water temperature profiles and associated ice and snow covers for dimictic and polymictic lakes of the temperate zone. The lake parameters required as model input are surface area (A_s), maximum depth (H_MAX), and Secchi depth (z_s), the latter, used as a measure of light attenuation and trophic state. The model is driven by daily weather data and operates year-round over multiple years. The model has been tested with extensive data (over 5,000 temperature points). Standard error between simulated and measured water temperatures is 1.4°C in the open water season and 0.5°C in the ice cover season. The model is applied to simulate the sensitivity of Minnesota lake water temperature characteristics to climate change. The projected climate changes due to a doubling of atmospheric CO₂ are obtained from the output of the Canadian Climate Center General Circulation Model (CCC GCM) and the Goddard Institute of Space Studies General Circulation Model (GISS GCM). Simulated lake temperature characteristics have been plotted in a coordinate system with a lake geometry ratio (A _s ^0.25 /H_MAX) on one axis and Secchi depth on the other. The lake geometry ratio expresses a lake's susceptibility to stratification. By interpolation, the sensitivity of lake temperature characteristics to changes of water depth and Secchi depth under the projected climate scenarios can therefore be obtained. Selected lake temperature characteristics simulated with past climate conditions (1961–1979) and with a projected 2 × CO₂ climate scenario as input are presented herein in graphical form. The simulation results show that under the 2 × CO₂ climate scenario ice formation is delayed and ice cover period is shortened. These changes cause water temperature modifications throughout the year.     

Possible Impacts of Global Warming on the Hydrology of the Ogallala Aquifer Region

The Ogallala or High Plains aquifer provides water for about 20% of the irrigated land in the United States. About 20 km³ (16.6 million acre-feet) of water are withdrawn annually from this aquifer. In general, recharge has not compensated for withdrawals since major irrigation development began in this region in the 1940s. The mining of the Ogallala has been pictured as an analogue to climate change in that many GCMs predict a warmer and drier future for this region. In this paper we attempt to anticipate the possible impacts of climate change on the sustainability of the aquifer as a source of water for irrigation and other purposes in the region. We have applied HUMUS, the Hydrologic Unit Model of the U.S. to the Missouri and Arkansas-White-Red water resource regions that overlie the Ogallala. We have imposed three general circulation model (GISS, UKTR and BMRC) projections of future climate change on this region and simulated the changes that may be induced in water yields (runoff plus lateral flow) and ground water recharge. Each GCM was applied to HUMUS at three levels of global mean temperature (GMT) to represent increasing severity of climate change (a surrogate for time). HUMUS was also run at three levels of atmospheric CO₂ concentration (hereafter denoted by [CO₂]) in order to estimate the impacts of direct CO₂ effects on photosynthesis and evapotranspiration. Since the UKTR and GISS GCMs project increased precipitation in the Missouri basin, water yields increase there. The BMRC GCM predicts sharply decreased precipitation and, hence, reduced water yields. Precipitation reductions are even greater in the Arkansas basin under BMRC as are the consequent water yield losses. GISS and UKTR climates lead to only moderate yield losses in the Arkansas. CO₂-fertilization reverses these losses and yields increase slightly. CO₂ fertilization increases recharge in the base (no climate change) case in both basins. Recharge is reduced under all three GCMs and severities of climate change.     

Climate Scenarios for the Southeastern U.S. Based on GCM and Regional Model Simulations

We analyze the control runs and 2 × CO₂ projections (5-yearlengths) of the CSIRO Mk 2 GCM and the RegCM2 regional climate model, which was nested in the CSIRO GCM, over the Southeastern U.S.; and we present the development of climate scenarios for use in an integrated assessment of agriculture. The RegCM exhibits smaller biases in both maximum and minimum temperature compared to the CSIRO. Domain average precipitation biases are generally negative and relatively small in winter, spring, and fall, but both models produce large positive biases in summer, that of the RegCM being the larger. Spatial pattern correlations of the model control runs and observations show that the RegCM reproduces better than the CSIRO the spatial patterns of precipitation, minimum and maximum temperature in all seasons. Under climate change conditions, the most salient feature from the point of view of scenarios for agriculture is the large decreases in summer precipitation, about 20% in the CSIRO and 30% in the RegCM. Increases in springprecipitation are found in both models, about 35% in the CSIRO and 25% in theRegCM. Precipitation decreases of about 20% dominate in winter in the CSIRO,while a more complex pattern of increases and decreases is exhibited by the regional model. Temperature increases by 3 to 5 °C in the CSIRO, the higher values dominating in winter and spring. In the RegCM, temperature increases are much more spatially and temporally variable, ranging from 1 to 7 °C acrossall months and grids. In summer large increases (up to 7 °C) in maximum temperature are found in the northeastern part of the domain where maximum drying occurs.     

A step-response approach for predicting and understanding non-linear precipitation changes

Future changes in precipitation represent one of the most important and uncertain possible effects of future climate change. We demonstrate a new approach based on idealised CO₂ step-change general circulation model (GCM) experiments, and test it using the HadCM3 GCM. The approach has two purposes: to help understand GCM projections, and to build and test a fast simple model for precipitation projections under a wide range of forcing scenarios. Overall, we find that the CO₂ step experiments contain much information that is relevant to transient projections, but that is more easily extracted due to the idealised experimental design. We find that the temporary acceleration of global-mean precipitation in this GCM following CO₂ ramp-down cannot be fully explained simply using linear responses to CO₂ and temperature. A more complete explanation can be achieved with an additional term representing interaction between CO₂ and temperature effects. Energy budget analysis of this term is dominated by clear-sky outgoing long-wave radiation (CSOLR) and sensible heating, but cloud and short-wave terms also contribute. The dominant CSOLR interaction is attributable to increased CO₂ raising the mean emission level to colder altitudes, which reduces the rate of increase of OLR with warming. This behaviour can be reproduced by our simple model. On regional scales, we compare our approach with linear ‘pattern-scaling’ (scaling regional responses by global-mean temperature change). In regions where our model predicts linear change, pattern-scaling works equally well. In some regions, however, substantial deviations from linear scaling with global-mean temperature are found, and our simple model provides more accurate projections. The idealised experiments reveal a complex pattern of non-linear behaviour. There are likely to be a range of controlling physical mechanisms, different from those dominating the global-mean response, requiring focussed investigation for individual regions, and in other GCMs.     

Regional Nested Model Simulations of Present Day and 2 × CO2 Climate over the Central Plains of the U.S.

A nested regional climate model is used to generate a scenario of climate change over the MINK region (Missouri, Iowa, Nebraska, Kansas) due to doubling of carbon dioxide concentration (2 × CO₂) for use in agricultural impact assessment studies. Five-year long present day (control) and 2 × CO₂ simulations are completed at a horizontal grid point spacing of 50 km. Monthly and seasonal precipitation and surface air temperature over the MINK region are reproduced well by the model in the control run, except for an underestimation of both variables during the spring months. The performance of the nested model in the control run is greatly improved compared to a similar experiment performed with a previous version of the nested modeling system by Giorgi et al. (1994). The nested model generally improves the simulation of spatial precipitation patterns compared to the driving general circulation model (GCM), especially during the summer. Seasonal surface warming of 4 to 6 K and seasonal precipitation increases of 6 to 24% are simulated in 2 × CO₂ conditions. The control run temperature biases are smaller than the simulated changes in all seasons, while the precipitation biases are of the same order of magnitude as the simulated changes. Although the large scale patterns of change in the driving GCM and nested RegCM model are similar, significant differences between the models, and substantial spatial variability, occur within the MINK region.     

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.     

21世纪黄河流域上中游地区气候变化趋势分析

 气候变化预估常用的全球气候模式（GCM）难以提供区域或更小尺度上可靠的逐日气候要素序列,针对这一问题,应用统计降尺度模型（statistical downscaling model,SDSM）将HadCM3的模拟数据（包括A2、B2两种情景）处理为具有较高可信度的逐日站点序列。以1961-1990年为基准期,分析了21世纪黄河流域上中游地区未来最高气温、最低气温与年降水量的变化。在A2、B2两种气候变化情景下,日最高气温、日最低气温均呈升高趋势;但A2的变化较显著,日最高气温的升高趋势在景泰站最明显,日最低气温的升高趋势在河曲站最显著。流域平均的年降水量变化范围为-18.2%～13.3%。A2情景下降水量增加和减少的面积基本相等,宝鸡站降水量增加最多;B2情景下大部分区域降水减少,西峰镇降水量减少最显著。     

21世纪黄河流域上中游地区气候变化趋势分析

气候变化预估常用的全球气候模式（GCM）难以提供区域或更小尺度上可靠的逐日气候要素序列,针对这一问题,应用统计降尺度模型（statistical downscaling model,SDSM）将HadCM3的模拟数据（包括A2、B2两种情景）处理为具有较高可信度的逐日站点序列。以1961-1990年为基准期,分析了21世纪黄河流域上中游地区未来最高气温、最低气温与年降水量的变化。在A2、B2两种气候变化情景下,日最高气温、日最低气温均呈升高趋势;但A2的变化较显著,日最高气温的升高趋势在景泰站最明显,日最低气温的升高趋势在河曲站最显著。流域平均的年降水量变化范围为-18.2%～13.3%。A2情景下降水量增加和减少的面积基本相等,宝鸡站降水量增加最多;B2情景下大部分区域降水减少,西峰镇降水量减少最显著。     

Estimated annual regime of energy-balance components,evapotranspiration and soil moisture for a drainage basin in the case of a CO2 doubling

Assuming a doubling of the atmospheric CO₂ concentration, parameters of an empirical formula for calculating the daily net terrestrial radiation under the climatic conditions of Belgium are determined. The developed method takes into account information yielded by climate models about the CO₂ impacts. Annual regimes of the energy-balance components are calculated for a drainage basin in Belgium. A daily step conceptual hydrological model (developed at the Royal Meteorological Institute of Belgium) was run to estimate the effective evapotranspiration and the soil moisture in the 2 × CO₂ case; results of this simulation are compared with the present-day conditions.This research was supported by a Commission of the European Communities Grant [CLI-104B(RS)]     

Water Budgets of Two Watersheds in Different Climatic Zones under Projected Climate Warming

A deterministic monthly runoff model (MINRUN96)was applied to watersheds with substantially differentclimates. One watershed is in the north-central U.S.(Minnesota) and is heavily timbered. The other is inthe south-central U.S. (Oklahoma) and is mainlycovered with pastures and agricultural crops. Runoffwas simulated for past historical climate and twoprojected 2 × CO₂ climate scenarios. The output ofGeneral Circulation Models (GCMs) was used to specifythe two 2 × CO₂ climate scenarios. One GCM is theGoddard Institute of Space Studies (GISS) model andthe other is from the Canadian Center of ClimateModelling (CCC). In the northern watershed morerunoff is projected to occur in winter under a warmerclimate and less runoff in spring. About 80%increase in fall runoff and 20% decrease in soilmoisture in June and July is projected for thesouthern watershed. When runoff simulations for the2 × CO₂ climate scenarios were compared to pastrunoff, it was apparent that the change in runoffdepended on both the season and the magnitude of theprecipitation change. An increase in springprecipitation caused a significant increase in directrunoff, whereas an increase in fall precipitationcaused only a slight increase in total runoff. Alsothe runoff-precipitation relationship in the warm andseasonally dry southern watershed is very differentfrom that in the temperate and humid climate of thenorth. Therefore, runoff responses to projectedclimate change are substantially different in the tworegions.     

Circulation patterns, daily precipitation in Portugal and implications for climate change simulated by the second Hadley Centre GCM

Based on principal component analysis (PCA) and a k-means clustering algorithm, daily mean sea level pressure (MSLP) fields over the northeastern Atlantic and Western Europe, simulated by the Hadley Centre's second generation coupled ocean-atmosphere GCM (HADCM2) control run (HADCM2CON), are validated by comparison with the observed daily MSLP fields. It is clear that HADCM2 reproduces daily MSLP fields and its seasonal variability over the region very well, despite suffering from some deficiencies, such as the systematic displacement of the atmospheric centres of action. Four daily circulation patterns, previously identified from the observed daily MSLP fields over the area and well related to daily precipitation in Portugal, were also well classified from the daily MSLP fields simulated by HADCM2. The model can also simulate rather successfully the relationships between the four daily circulation patterns and daily precipitation in southern Portugal. However, compared with observations, daily precipitation intensities simulated by the model are too weak in southern Portugal. Nevertheless, HADCM2 represents a considerable improvement relative to the UKTR experiment. The results described here imply that it is doubtful whether regional precipitation scenarios provided by HADCM2 can be directly applied in impact studies and that a downscaling technique, based on daily circulation patterns, might be successful in reproducing local and regional precipitation characteristics. Moreover, the four circulation patterns can also be clearly identified in the two perturbed experiments, one under greenhouse gases forcing only (HADCM2GHG) and the other under additional forcing of sulphate aerosol (HADCM2SUL), although changes in the frequencies of occurrence of certain circulation patterns are found. Nevertheless, the observed links between regional precipitation in southern Portugal and large-scale atmospheric circulation seem likely to hold in the model's perturbed climate. It is therefore credible to use those links to downscale large-scale atmospheric circulation from GCM simulations to obtain future precipitation scenarios in southern Portugal. Received: 21 August 1998 / Accepted: 28 May 1999     

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.