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General Circulation Models (general + circulation_models)
Selected AbstractsA multimodel assessment of future climatological droughts in the United Kingdom,INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 14 2009Jean-Philippe Vidal Abstract This paper presents a detailed assessment of future rainfall drought patterns over the United Kingdom. Previously developed bias-corrected high-resolution gridded precipitation time series are aggregated to the scale relevant for water resources management, in order to provide 21st-century time series for 183 hydrologic areas, as computed by six General Circulation Models (GCMs) under two emissions scenarios. The control run data are used as a ,learning time series' to compute the Standardized Precipitation Index (SPI) at four different time scales. SPI values for three 30-year future time slices are computed with respect to these learning time series in order to assess the changes in drought frequency. Multimodel results under the A2 scenario show a dramatic increase in the frequency of short-term extreme drought class for most of the country. A decrease of long-term droughts is expected in Scotland, due to the projected increase in winter precipitation. The analysis for two catchment case studies also showed that changes under the B2 scenario are generally consistent with those of the A2 scenario, with a reduced magnitude in changes. The overall increase with time in the spread of individual GCM results demonstrates the utility of multimodel statistics when assessing the uncertainty in future drought indices to be used in long-term water resources planning. Copyright © 2009 Royal Meteorological Society [source] Estimated migration rates under scenarios of global climate changeJOURNAL OF BIOGEOGRAPHY, Issue 7 2002Jay R. Malcolm Aim Greenhouse-induced warming and resulting shifts in climatic zones may exceed the migration capabilities of some species. We used fourteen combinations of General Circulation Models (GCMs) and Global Vegetation Models (GVMs) to investigate possible migration rates required under CO2 -doubled climatic forcing. Location Global. Methods Migration distances were calculated between grid cells of future biome type x and nearest same-biome-type cells in the current climate. In `base-case' calculations, we assumed that 2 × CO2 climate forcing would occur in 100 years, we used ten biome types and we measured migration distances as straight-line distances ignoring water barriers and human development. In sensitivity analyses, we investigated different time periods of 2 × CO2 climate forcing, more narrowly defined biomes and barriers because of water bodies and human development. Results In the base-case calculations, average migration rates varied significantly according to the GVM used (BIOME3 vs. MAPSS), the age of the GCM (older- vs. newer-generation GCMs), and whether or not GCMs included sulphate cooling or CO2 fertilization effects. However, high migration rates (, 1000 m year,1) were relatively common in all models, consisting on average of 17% grid cells for BIOME3 and 21% for MAPSS. Migration rates were much higher in boreal and temperate biomes than in tropical biomes. Doubling of the time period of 2 × CO2 forcing reduced these areas of high migration rates to c. 12% of grid cells for both BIOME3 and MAPSS. However, to obtain migration rates in the Boreal biome that were similar in magnitude to those observed for spruce when it followed the retreating North American Glacier, a radical increase in the period of warming was required, from 100 to >1000 years. A reduction in biome area by an order of magnitude increased migration rates by one to three orders of magnitude, depending on the GVM. Large water bodies and human development had regionally important effects in increasing migration rates. Main conclusions In conclusion, evidence from coupled GCMs and GVMs suggests that global warming may require migration rates much faster than those observed during post-glacial times and hence has the potential to reduce biodiversity by selecting for highly mobile and opportunistic species. Several poorly understood factors that are expected to influence the magnitude of any such reduction are discussed, including intrinsic migrational capabilities, barriers to migration, the role of outlier populations in increasing migration rates, the role of climate in setting range limits and variation in species range sizes. [source] CLIMATE CHANGE IMPACTS ON WATER RESOURCES OF THE TSENGWEN CREEK WATERSHED IN TAIWAN,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 1 2001Ching-pin Tung ABSTRACT: This study presents a methodology to evaluate the vulnerability of water resources in the Tsengwen creek watershed, Taiwan. Tsengwen reservoir, located in the Tsengwen creek watershed, is a multipurpose reservoir with a primary function to supply water for the ChiaNan Irrigation District. A simulation procedure was developed to evaluate the impacts of climate change on the water resources system. The simulation procedure includes a streamflow model, a weather generation model, a sequent peak algorithm, and a risk assessment process. Three climate change scenarios were constructed based on the predictions of three General Circulation Models (CCCM, GFDL, and GISS). The impacts of climate change on streamflows were simulated, and, for each climate change scenario, the agricultural water demand was adjusted based on the change of potential evapotranspiration. Simulation results indicated that the climate change may increase the annual and seasonal streamflows in the Tsengwen creek watershed. The increase in streamflows during wet periods may result in serious flooding. In addition, despite the increase in streamflows, the risk of water deficit may still increase from between 4 and 7 percent to between 7 and 13 percent due to higher agricultural water demand. The simulation results suggest that the reservoir capacity may need to be expanded. In response to the climate change, four strategies are suggested: (1) strengthen flood mitigation measures, (2) enhance drought protection strategies, (3) develop new water resources technology, and (4) educate the public. [source] Prediction of sea surface temperature from the global historical climatology network dataENVIRONMETRICS, Issue 3 2004Samuel S. P. Shen Abstract This article describes a spatial prediction method that predicts the monthly sea surface temperature (SST) anomaly field from the land only data. The land data are from the Global Historical Climatology Network (GHCN). The prediction period is 1880,1999 and the prediction ocean domain extends from 60°S to 60°N with a spatial resolution 5°×5°. The prediction method is a regression over the basis of empirical orthogonal functions (EOFs). The EOFs are computed from the following data sets: (a) the Climate Prediction Center's optimally interpolated sea surface temperature (OI/SST) data (1982,1999); (b) the National Climatic Data Center's blended product of land-surface air temperature (1992,1999) produced from combining the Special Satellite Microwave Imager and GHCN; and (c) the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis data (1982,1999). The optimal prediction method minimizes the first- M -mode mean square error between the true and predicted anomalies over both land and ocean. In the optimization process, the data errors of the GHCN boxes are used, and their contribution to the prediction error is taken into account. The area-averaged root mean square error of prediction is calculated. Numerical experiments demonstrate that this EOF prediction method can accurately recover the global SST anomalies during some circulation patterns and add value to the SST bias correction in the early history of SST observations and the validation of general circulation models. Our results show that (i) the land only data can accurately predict the SST anomaly in the El Nino months when the temperature anomaly structure has very large correlation scales, and (ii) the predictions for La Nina, neutral, or transient months require more EOF modes because of the presence of the small scale structures in the anomaly field. Copyright © 2004 John Wiley & Sons, Ltd. [source] Will climate change be beneficial or detrimental to the invasive swede midge in North America?GLOBAL CHANGE BIOLOGY, Issue 8 2008Contrasting predictions using climate projections from different general circulation models Abstract Climate change may dramatically affect the distribution and abundance of organisms. With the world's population size expected to increase significantly during the next 100 years, we need to know how climate change might impact our food production systems. In particular, we need estimates of how future climate might alter the distribution of agricultural pests. We used the climate projections from two general circulation models (GCMs) of global climate, the Canadian Centre for Climate Modelling and Analysis GCM (CGCM2) and the Hadley Centre model (HadCM3), for the A2 and B2 scenarios from the Special Report on Emissions Scenarios in conjunction with a previously published bioclimatic envelope model (BEM) to predict the potential changes in distribution and abundance of the swede midge, Contarinia nasturtii, in North America. The BEM in conjunction with either GCM predicted that C. nasturtii would spread from its current initial invasion in southern Ontario and northwestern New York State into the Canadian prairies, northern Canada, and midwestern United States, but the magnitude of risk depended strongly on the GCM and the scenario used. When the CGCM2 projections were used, the BEM predicted an extensive shift in the location of the midges' climatic envelope through most of Ontario, Quebec, and the maritime and prairie provinces by the 2080s. In the United States, C. nasturtii was predicted to spread to all the Great Lake states, into midwestern states as far south as Colorado, and west into Washington State. When the HadCM3 was applied, southern Ontario, Saskatchewan, and Washington State were not as favourable for C. nasturtii by the 2080s. Indeed, when used with the HadCM3 climate projections, the BEM predicted the virtual disappearance of ,very favourable' regions for C. nasturtii. The CGCM2 projections generally caused the BEM to predict a small increase in the mean number of midge generations throughout the course of the century, whereas, the HadCM3 projections resulted in roughly the same mean number of generations but decreased variance. Predictions of the likely potential of C. nasturtii spatial spread are thus strongly dependent on the source of climate projections. This study illustrates the importance of using multiple GCMs in combination with multiple scenarios when studying the potential for spatial spread of an organism in response to climate change. [source] Downy mildew (Plasmopara viticola) epidemics on grapevine under climate changeGLOBAL CHANGE BIOLOGY, Issue 7 2006SALINARI FRANCESCA Abstract As climate is a key agro-ecosystem driving force, climate change could have a severe impact on agriculture. Many assessments have been carried out to date on the possible effects of climate change (temperature, precipitation and carbon dioxide concentration changes) on plant physiology. At present however, likely effects on plant pathogens have not been investigated deeply. The aim of this work was to simulate future scenarios of downy mildew (Plasmopara viticola) epidemics on grape under climate change, by combining a disease model to output from two general circulation models (GCMs). Model runs corresponding to the SRES-A2 emissions scenario, characterized by high projections of both population and greenhouse gas emissions from present to 2100, were chosen in order to investigate impacts of worst-case scenarios, among those currently available from IPCC. Three future decades were simulated (2030, 2050, 2080), using as baseline historical series of meteorological data collected from 1955 to 2001 in Acqui Terme, an important grape-growing area in the north-west of Italy. Both GCMs predicted increase of temperature and decrease of precipitation in this region. The simulations obtained by combining the disease model to the two GCM outputs predicted an increase of the disease pressure in each decade: more severe epidemics were a direct consequence of more favourable temperature conditions during the months of May and June. These negative effects of increasing temperatures more than counterbalanced the effects of precipitation reductions, which alone would have diminished disease pressure. Results suggested that, as adaptation response to future climate change, more attention would have to be paid in the management of early downy mildew infections; two more fungicide sprays were necessary under the most negative climate scenario, compared with present management regimes. At the same time, increased knowledge on the effects of climate change on host,pathogen interactions will be necessary to improve current predictions. [source] Applying climatically associated species pools to the modelling of compositional change in tropical montane forestsGLOBAL ECOLOGY, Issue 2 2008Duncan J. Golicher ABSTRACT Aim, Predictive species distribution modelling is a useful tool for extracting the maximum amount of information from biological collections and floristic inventories. However, in many tropical regions records are only available from a small number of sites. This can limit the application of predictive modelling, particularly in the case of rare and endangered species. We aim to address this problem by developing a methodology for defining and mapping species pools associated with climatic variables in order to investigate potential species turnover and regional species loss under climate change scenarios combined with anthropogenic disturbance. Location, The study covered an area of 6800 km2 in the highlands of Chiapas, southern Mexico. Methods, We derived climatically associated species pools from floristic inventory data using multivariate analysis combined with spatially explicit discriminant analysis. We then produced predictive maps of the distribution of tree species pools using data derived from 451 inventory plots. After validating the predictive power of potential distributions against an independent historical data set consisting of 3105 botanical collections, we investigated potential changes in the distribution of tree species resulting from forest disturbance and climate change. Results, Two species pools, associated with moist and cool climatic conditions, were identified as being particularly threatened by both climate change and ongoing anthropogenic disturbance. A change in climate consistent with low-emission scenarios of general circulation models was shown to be sufficient to cause major changes in equilibrium forest composition within 50 years. The same species pools were also found to be suffering the fastest current rates of deforestation and internal forest disturbance. Disturbance and deforestation, in combination with climate change, threaten the regional distributions of five tree species listed as endangered by the IUCN. These include the endemic species Magnolia sharpii Miranda and Wimmeria montana Lundell. Eleven vulnerable species and 34 species requiring late successional conditions for their regeneration could also be threatened. Main conclusions, Climatically associated species pools can be derived from floristic inventory data available for tropical regions using methods based on multivariate analysis even when data limitations prevent effective application of individual species modelling. Potential consequences of climate change and anthropogenic disturbance on the species diversity of montane tropical forests in our study region are clearly demonstrated by the method. [source] Effect of global atmospheric carbon dioxide on glacial,interglacial vegetation changeGLOBAL ECOLOGY, Issue 5 2000K. D. Bennett Abstract Global vegetation changes at the time-scale of the Earth's orbital variations (104,105 years) have been interpreted as a direct effect of consequential climatic changes, especially temperature. At mid- and high latitudes, the evidence from fossil data and general circulation models (GCMs) supporting this hypothesis is strong, but at low latitudes there is a major discrepancy. GCMs predict temperature changes that are less than those inferred from palaeoclimatic data, including the plant fossil record. However, changes in atmospheric CO2 concentrations can account for a high proportion of the low-latitude vegetation change hitherto attributed to temperature change, and may thus explain the discrepancy. The implications of this finding are considerable for understanding patterns of macroevolution and ecosystem development throughout the geological record. [source] Assessment of climate-change impacts on alpine discharge regimes with climate model uncertaintyHYDROLOGICAL PROCESSES, Issue 10 2006Pascal Horton Abstract This study analyses the uncertainty induced by the use of different state-of-the-art climate models on the prediction of climate-change impacts on the runoff regimes of 11 mountainous catchments in the Swiss Alps having current proportions of glacier cover between 0 and 50%. The climate-change scenarios analysed are the result of 19 regional climate model (RCM) runs obtained for the period 2070,2099 based on two different greenhouse-gas emission scenarios (the A2 and B2 scenarios defined by the Intergovernmental Panel on Climate Change) and on three different coupled atmosphere-ocean general circulation models (AOGCMs), namely HadCM3, ECHAM4/OPYC3 and ARPEGE/OPA. The hydrological response of the study catchments to the climate scenarios is simulated through a conceptual reservoir-based precipitation-runoff transformation model called GSM-SOCONT. For the glacierized catchments, the glacier surface corresponding to these future scenarios is updated through a conceptual glacier surface evolution model. The results obtained show that all climate-change scenarios induce, in all catchments, an earlier start of the snowmelt period, leading to a shift of the hydrological regimes and of the maximum monthly discharges. The mean annual runoff decreases significantly in most cases. For the glacierized catchments, the simulated regime modifications are mainly due to an increase of the mean temperature and the corresponding impacts on the snow accumulation and melting processes. The hydrological regime of the catchments located at lower altitudes is more strongly affected by the changes of the seasonal precipitation. For a given emission scenario, the simulated regime modifications of all catchments are highly variable for the different RCM runs. This variability is induced by the driving AOGCM, but also in large part by the inter-RCM variability. The differences between the different RCM runs are so important that the predicted climate-change impacts for the two emission scenarios A2 and B2 are overlapping. Copyright © 2006 John Wiley & Sons, Ltd. [source] Statistical downscaling of daily precipitation from observed and modelled atmospheric fieldsHYDROLOGICAL PROCESSES, Issue 8 2004Stephen P. Charles Abstract Statistical downscaling techniques have been developed to address the spatial scale disparity between the horizontal computational grids of general circulation models (GCMs), typically 300,500 km, and point-scale meteorological observations. This has been driven, predominantly, by the need to determine how enhanced greenhouse projections of future climate may impact at regional and local scales. As point-scale precipitation is a common input to hydrological models, there is a need for techniques that reproduce the characteristics of multi-site, daily gauge precipitation. This paper investigates the ability of the extended nonhomogeneous hidden Markov model (extended-NHMM) to reproduce observed interannual and interdecadal precipitation variability when driven by observed and modelled atmospheric fields. Previous studies have shown that the extended-NHMM can successfully reproduce the at-site and intersite statistics of daily gauge precipitation, such as the frequency characteristics of wet days, dry- and wet-spell length distributions, amount distributions, and intersite correlations in occurrence and amounts. Here, the extended-NHMM, as fitted to 1978,92 observed ,winter' (May,October) daily precipitation and atmospheric data for 30 rain gauge sites in southwest Western Australia, is driven by atmospheric predictor sets extracted from National Centers for Environmental Prediction,National Center for Atmospheric Research reanalysis data for 1958,98 and an atmospheric GCM hindcast run forced by observed 1955,91 sea-surface temperatures (SSTs). Downscaling from the reanalysis-derived predictors reproduces the 1958,98 interannual and interdecadal variability of winter precipitation. Downscaling from the SST-forced GCM hindcast only reproduces the precipitation probabilities of the recent 1978,91 period, with poor performance for earlier periods attributed to inadequacies in the forcing SST data. Copyright © 2004 John Wiley & Sons, Ltd. [source] Predictions of future climate change in the caribbean region using global general circulation modelsINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 5 2007Moises E. Angeles Abstract Since the 1800s the global average CO2 mixing ratio has increased and has been related to increases in surface air temperature (0.6 ± 0.2 °C) and variations in precipitation patterns among other weather and climatic variables. The Small Island Developing States (SIDS), according to the 2001 report of the Intergovernmental Panel on Climate Change (IPCC), are likely to be among the most seriously impacted regions on Earth by global climate changes. In this work, three climate change scenarios are investigated using the Parallel Climate Model (PCM) to study the impact of the global anthropogenic CO2 concentration increases on the Caribbean climate. A climatological analysis of the Caribbean seasonal climate variation was conducted employing the National Center for Environmental Prediction (NCEP) reanalysis data, the Xie,Arkin precipitation and the Reynolds,Smith Sea Surface Temperature (SST) observed data. The PCM is first evaluated to determine its ability to predict the present time Caribbean climatology. The PCM tends to under predict the SSTs, which along with the cold advection controls the rainfall variability. This seems to be a main source of bias considering the low model performance to predict rainfall activity over the Central and southern Caribbean. Future predictions indicate that feedback processes involving evolution of SST, cloud formation, and solar radiative interactions affect the rainfall annual variability simulated by PCM from 1996 to 2098. At the same time two large-scale indices, the Southern Oscillation Index (SOI) and the North Atlantic Oscillation (NAO) are strongly related with this rainfall annual variability. A future climatology from 2041 to 2058 is selected to observe the future Caribbean condition simulated by the PCM. It shows, during this climatology range, a future warming of approximately 1 °C (SSTs) along with an increase in the rain production during the Caribbean wet seasons (early and late rainfall seasons). Although the vertical wind shear is strengthened, it typically remains lower than 8 m/s, which along with SST > 26.5 °C provides favorable conditions for possible future increases in tropical storm frequency. Copyright © 2006 Royal Meteorological Society [source] Statistical correction of central Southwest Asia winter precipitation simulations,INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 12 2003Michael K. Tippett Abstract Severe drought is a notable feature of the hydrology of central Southwest (CSW) Asia. Although studies have linked the region's interannual precipitation variability to remote forcings that include East Asia jet stream variability and western Pacific tropical convection, atmospheric general circulation models (GCMs) forced by observed sea-surface temperatures demonstrate little skill in simulating interannual precipitation variability in this region. Here, statistical methods of correcting systematic errors in GCM simulations of CSW Asia precipitation are investigated. Canonical correlation analysis is used to identify model fields related to observed precipitation anomaly patterns. These relationships are then used to predict observed precipitation anomalies. This approach is applied to the ECHAM 4.5 GCM using regional precipitation, upper-level winds and western Pacific tropical precipitation as predictors of observed CSW Asia precipitation anomalies. The statistical corrections improve the GCM precipitation simulations, resulting in modest, but statistically significant, cross-validated skill in simulating CSW Asia precipitation anomalies. Applying the procedure to hindcasts with persisted sea-surface temperatures gives lower, but statistically significant, precipitation correlations in the region along the Hindu Kush mountain range. Copyright © 2003 Royal Meteorological Society [source] Intra-seasonal rainfall characteristics and their importance to the seasonal prediction problemINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 9 2002Warren J. Tennant Abstract Daily station rainfall data in South Africa from 1936 to 1999 are combined into homogeneous rainfall regions using Ward's clustering method. Various rainfall characteristics are calculated for the summer season, defined as December to February. These include seasonal rainfall total, region-average number of station rain days exceeding 1 and 20 mm, region-average of periods between rain days at stations >1 and >20 mm, region-average of wet spell length (sequential days of station rainfall >1 and >20 mm), correlation of daily station rainfall within a region and correlation of seasonal station rainfall anomalies within a region. Rank-ordered rainfall characteristic data generally form an s-shaped curve, and significance testing of discontinuities in these curves suggests that normal rainfall conditions in South Africa consist of a combined middle three quintiles separated from the outer quintiles, rather than the traditional middle tercile. The relationships between the various rainfall characteristics show that seasons with a high total rainfall generally have a higher number of heavy rain days (>20 mm) and not necessarily an increase in light rain days. The length of the period between rain days has a low correlation to season totals, demonstrating that seasons with a high total rainfall may still contain prolonged dry periods. These additional rainfall characteristics are important to end-users, and the analysis undertaken here offers a valuable starting point for seeking physical relationships between rainfall characteristics and the general circulation. Preliminary studies show that the vertical mean wind is related to rainfall characteristics in South Africa. Given that general circulation models capture this part of the circulation adequately, seasonal forecasts of rainfall characteristics become plausible. Copyright © 2002 Royal Meteorological Society. [source] Problems in evaluating regional and local trends in temperature: an example from eastern Colorado, USAINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 4 2002R. A. Pielke SR Abstract We evaluated long-term trends in average maximum and minimum temperatures, threshold temperatures, and growing season in eastern Colorado, USA, to explore the potential shortcomings of many climate-change studies that either: (1) generalize regional patterns from single stations, single seasons, or a few parameters over short duration from averaging dissimilar stations; or (2) generalize an average regional pattern from coarse-scale general circulation models. Based on 11 weather stations, some trends were weakly regionally consistent with previous studies of night-time temperature warming. Long-term (80 + years) mean minimum temperatures increased significantly (P < 0.2) in about half the stations in winter, spring, and autumn and six stations had significant decreases in the number of days per year with temperatures , , 17.8 °C (,0 °F). However, spatial and temporal variation in the direction of change was enormous for all the other weather parameters tested, and, in the majority of tests, few stations showed significant trends (even at P < 0.2). In summer, four stations had significant increases and three stations had significant decreases in minimum temperatures, producing a strongly mixed regional signal. Trends in maximum temperature varied seasonally and geographically, as did trends in threshold temperature days ,32.2 °C (,90 °F) or days ,37.8 °C (,100 °F). There was evidence of a sub-regional cooling in autumn's maximum temperatures, with five stations showing significant decreasing trends. There were many geographic anomalies where neighbouring weather stations differed greatly in the magnitude of change or where they had significant and opposite trends. We conclude that sub-regional spatial and seasonal variation cannot be ignored when evaluating the direction and magnitude of climate change. It is unlikely that one or a few weather stations are representative of regional climate trends, and equally unlikely that regionally projected climate change from coarse-scale general circulation models will accurately portray trends at sub-regional scales. However, the assessment of a group of stations for consistent more qualitative trends (such as the number of days less than ,17.8 °C, such as we found) provides a reasonably robust procedure to evaluate climate trends and variability. Copyright © 2002 Royal Meteorological Society [source] Retro-active skill of multi-tiered forecasts of summer rainfall over southern AfricaINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 1 2001Willem A. Landman Abstract Sea-surface temperature (SST) variations of the oceans surrounding southern Africa are associated with seasonal rainfall variability, especially during austral summer when the tropical atmospheric circulation is dominant over the region. Because of instabilities in the linear association between summer rainfall over southern Africa and SSTs of the tropical Indian Ocean, the skilful prediction of seasonal rainfall may best be achieved using physically based models. A two-tiered retro-active forecast procedure for the December,February (DJF) season is employed over a 10-year period starting from 1987/1988. Rainfall forecasts are produced for a number of homogeneous regions over part of southern Africa. Categorized (below-normal, near-normal and above-normal) statistical DJF rainfall predictions are made for the region to form the baseline skill level that has to be outscored by more elaborate methods involving general circulation models (GCMs). The GCM used here is the Centre for Ocean,Land,Atmosphere Studies (COLA) T30, with predicted global SST fields as boundary forcing and initial conditions derived from the National Centres for Environmental Prediction (NCEP) reanalysis data. Bias-corrected GCM simulations of circulation and moisture at certain standard pressure levels are downscaled to produce rainfall forecasts at the regional level using the perfect prognosis approach. In the two-tiered forecasting system, SST predictions for the global oceans are made first. SST anomalies of the equatorial Pacific (NIÑO3.4) and Indian oceans are predicted skilfully at 1- and 3-month lead-times using a statistical model. These retro-active SST forecasts are accurate for pre-1990 conditions, but predictability seems to have weakened during the 1990s. Skilful multi-tiered rainfall forecasts are obtained when the amplitudes of large events in the global oceans (such as El Niño and La Niña episodes) are described adequately by the predicted SST fields. GCM simulations using persisted August SST anomalies instead of forecast SSTs produce skill levels similar to those of the baseline for longer lead-times. Given high-skill SST forecasts, the scheme has the potential to provide climate forecasts that outscore the baseline skill level substantially. Copyright © 2001 Royal Meteorological Society [source] Climate change scenarios and models yield conflicting predictions about the future risk of an invasive species in North AmericaAGRICULTURAL AND FOREST ENTOMOLOGY, Issue 3 2010Anna M. Mika 1The pea leafminer Liriomyza huidobrensis (Blanchard) (Diptera: Agromyzidae) is an invasive species in North America and a serious economic pest on a wide variety of crops. We developed a bioclimatic envelope model (BEM) for this species and examined the envelope's potential location in North America under various future climates. 2We compared the future bioclimatic envelopes for L. huidobrensis using either simple scenarios comprising uniform changes in temperature/precipitation or climate projections from general circulation models (GCMs). Our simple scenarios were: (i) an increase of 0.1°C per degree in latitude with a 20% increase in summer precipitation and a 20% decrease in winter precipitation and (ii) an overall increase of 3°C everywhere, also with the same changes in precipitation. For GCM-modelled climate change, we used the Canadian Centre for Climate Modelling and Analysis GCM (CGCM2) and the Hadley Centre climate model (HadCM3), each in combination with two scenarios from the Special Report on Emissions Scenarios (A2 and B2). 3The BEM results using the simple scenarios were more similar to each other than to the results obtained using GCM projections. The results were also qualitatively different (i.e. spatially different and divergent) depending on which GCM-scenario combination was used. 4This modelling exercise illustrates that: (i) results using first approximation simple climate change scenarios can give predictions very different from those that use GCM-modelled climate projections (comprising a result that has worrying implications for empirical impact research) and that (ii) different GCM-models using the same scenario can give very different results (implying strong model dependency in projected biological impacts). [source] POTENTIAL IMPACTS OF CLIMATE CHANGE ON CALIFORNIA HYDROLOGY,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 4 2003Norman L. Miller ABSTRACT: Previous reports based on climate change scenarios have suggested that California will be subjected to increased wintertime and decreased summertime streamflow. Due to the uncertainty of projections in future climate, a new range of potential climatological future temperature shifts and precipitation ratios is applied to the Sacramento Soil Moisture Accounting Model and Anderson Snow Model in order to determine hydrologic sensitivities. Two general circulation models (GCMs) were used in this analysis: one that is warm and wet (HadCM2 run 1) and one that is cool and dry (PCM run B06.06), relative to the GCM projections for California that were part of the Third Assessment Report of the Intergovernmental Panel on Climate Change. A set of specified incremental temperature shifts from 1.5°C to 5.0°C and precipitation ratios from 0.70 to 1.30 were also used as input to the snow and soil moisture accounting models, providing for additional scenarios (e.g., warm/dry, cool/wet). Hydrologic calculations were performed for a set of California river basins that extend from the coastal mountains and Sierra Nevada northern region to the southern Sierra Nevada region; these were applied to a water allocation analysis in a companion paper. Results indicate that for all snow-producing cases, a larger proportion of the streamflow volume will occur earlier in the year. The amount and timing is dependent on the characteristics of each basin, particularly the elevation. Increased temperatures lead to a higher freezing line, therefore less snow accumulation and increased melting below the freezing height. The hydrologic response varies for each scenario, and the resulting solution set provides bounds to the range of possible change in streamflow, snowmelt, snow water equivalent, and the change in the magnitude of annual high flows. An important result that appears for all snowmelt driven runoff basins, is that late winter snow accumulation decreases by 50 percent toward the end of this century. [source] Joint projections of temperature and precipitation change from multiple climate models: a hierarchical Bayesian approachJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2009Claudia Tebaldi Summary., Posterior distributions for the joint projections of future temperature and precipitation trends and changes are derived by applying a Bayesian hierachical model to a rich data set of simulated climate from general circulation models. The simulations that are analysed here constitute the future projections on which the Intergovernmental Panel on Climate Change based its recent summary report on the future of our planet's climate, albeit without any sophisticated statistical handling of the data. Here we quantify the uncertainty that is represented by the variable results of the various models and their limited ability to represent the observed climate both at global and at regional scales. We do so in a Bayesian framework, by estimating posterior distributions of the climate change signals in terms of trends or differences between future and current periods, and we fully characterize the uncertain nature of a suite of other parameters, like biases, correlation terms and model-specific precisions. Besides presenting our results in terms of posterior distributions of the climate signals, we offer as an alternative representation of the uncertainties in climate change projections the use of the posterior predictive distribution of a new model's projections. The results from our analysis can find straightforward applications in impact studies, which necessitate not only best guesses but also a full representation of the uncertainty in climate change projections. For water resource and crop models, for example, it is vital to use joint projections of temperature and precipitation to represent the characteristics of future climate best, and our statistical analysis delivers just that. [source] Ensemble simulations of the cold European winter of 2005-2006THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 636 2008A. A. Scaife Abstract There is only limited understanding of the processes driving year-to-year variability in European winter climate and the skill of seasonal forecasts for Europe in winter is generally low. The winter of 2005-2006 is a useful case-study because it was the coldest winter in large parts of western Europe for over a decade, and the coldest in central England since 1995-1996. Here, we present results of experiments with a range of general circulation models to investigate the importance of both the Atlantic Ocean and stratospheric circulation in producing the unusually cold winter of 2005-2006. We use models with different combinations of horizontal and stratospheric vertical resolution, allowing the sensitivity of the response to model formulation to be tested. The response to Atlantic sea-surface temperature (SST) anomalies is improved in a more recent model with higher horizontal resolution. The results show that both Atlantic SSTs and the January 2006 sudden stratospheric warming are likely to have contributed to the cold 2005-2006 European winter. © Crown Copyright 2008. Reproduced with the permission of HMSO. Published by John Wiley & Sons Ltd. [source] Dynamical budgets of the Antarctic Circumpolar Current using ocean general-circulation modelsTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 607 2005A. Grezio Abstract Three general-circulation models (FRAM, OCCAM and POP) are used to investigate the dynamics of the Antarctic Circumpolar Current (ACC) at the latitudes of the Drake Passage where the ACC is unbounded. In these general circulation models, bottom form stress balances the wind stress in the momentum budgets. In the vorticity budgets, the main balance is between wind curl and bottom pressure torque in FRAM, OCCAM and POP. Moreover, in the ACC belt all topographic features are regions of nonlinearity and bottom pressure torque variations, with the Drake Passage playing the largest role. Transient eddy Reynolds stresses (TERSs) play a different role in the three models. In the upper levels, TERSs accelerate the flow in the POP and FRAM models, but decelerate the flow in OCCAM. The behaviour of TERSs change throughout the whole water column in the ACC belt and Reynolds stresses have a dragging effect on the flow below the levels where the topography starts to obstruct the flow. The total volume transport in three models is very different. Additionally, the different spatial resolution, which results in a different level of eddy kinetic energy, has a significant influence on the transport. Copyright © 2005 Royal Meteorological Society [source] Diagnosis of climate models in terms of transient climate response and feedback response timeATMOSPHERIC SCIENCE LETTERS, Issue 1 2008David G. Andrews Abstract Climate models have traditionally been characterised by their climate sensitivity (equilibrium response to a doubling of CO2) and their ocean heat uptake. Together these determine a third property: the transient climate response to a linear increase in radiative forcing. A fourth property, the feedback response time is introduced here and shown to provide a complementary diagnostic of climate model behaviour. In particular, it demonstrates that the discrepancy between recent climate observations and the general circulation models in the ,IPCC ensemble' primarily arises because the models are undersampling the range of transient climate responses consistent with recent attributable greenhouse warming. Copyright © 2007 Royal Meteorological Society [source] Simulation of the Asian summer monsoon in five European general circulation modelsATMOSPHERIC SCIENCE LETTERS, Issue 1 2000G. M. Martin Abstract A comparison is made of the mean monsoon climatology in five different general circulation models (GCMs) which have been used by the participants of a project, funded by the European Union, entitled Studies of the Influence, Hydrology and Variability of the Asian summer monsoon (SHIVA). The models differ considerably, in horizontal and vertical resolution, numerical schemes and physical parametrizations, so that it is impossible to isolate the cause of differences in their monsoon simulations. Instead, the purpose of this comparison is to document and compare the representation of the mean monsoon in models which are being used to investigate the characteristics of the monsoon, its variability and its response to different boundary forcings. All of the models produce a reasonable representation of the monsoon circulation, although there are regional variations in the magnitude and pattern of the flow at both 850 hPa and 200 hPa. Considerable differences between the models are seen in the amount and distribution of precipitation. The models all reproduce the basic monsoon seasonal variation, although the timing of the onset and retreat, and the maxima in the winds and precipitation during the established phase, differ between them. There are corresponding differences in the evolution of the atmospheric structure between the pre-monsoon season and its established phase. It is hoped that this study will set in context the investigations of the monsoon system and its impacts carried out using these models, both during SHIVA and in the future. Copyright © 2000 Royal Meteorological Society. [source] | |||||||||||||||||||