Adapting stochastic weather generation algorithms for climate change studies

While large-scale climate models (GCMs) are in principle the most appropriate tools for predicting climate changes, at present little confidence can be placed in the details of their projections. Use of tools such as crop simulation models for investigation of potential impacts of climatic change requires daily data pertaining to small spatial scales, not the monthly-averaged and large-scale information typically available from the GCMs. A method is presented to adapt stochastic weather generation models, describing daily weather variations in the present-day climate at particular locations, to generate synthetic daily time series consistent with assumed future climates. These assumed climates are specified in terms of the commonly available monthly means and variances of temperature and precipitation, including time-dependent (so-called transient) climate changes. Unlike the usual practice of applying assumed changes in mean values to historically observed data, simulation of meteorological time series also exhibiting changes in variability is possible. Considerable freedom in climate change scenario construction is allowed. The results are suitable for investigating agricultural and other impacts of a variety of hypothetical climate changes specified in terms of monthly-averaged statistics.     

Farm-Level Adaptation to Climatic Variability and Change: Crop Diversification in the Canadian Prairies

Among other foci, recent research on adaptation to climatic variability and change has sought to evaluate the merit of adaptation generally, as well as the suitability of particular adaptations. Additionally, there is a need to better understand the likely uptake of adaptations. For example, diversification is one adaptation that has been identified as a potential farm-level response to climatic variability and change, but its adoption by farmers for this reason is not well understood. This paper serves two purposes. The first is to document the adoption of crop diversification in Canadian prairie agriculture for the period 1994–2002, reflect upon its strengths and limitations for managing a variety of risks, including climatic ones, and gauge its likely adoption by producers in response to anticipated climate change. The second purpose is to draw on this case to refine our current understanding of climate change adaptation more generally. Based upon data from over 15 000 operations, it was determined that individual farms have become more specialized in their cropping patterns since 1994, and this trend is unlikely to change in the immediate future, notwithstanding anticipated climate change and the known risk-reducing benefits of crop diversification. More broadly, the analysis suggests that suitable and even possible climate change adaptations need to be more rigorously assessed in order to understand their wider strengths and limitations.     

Climate factors during key periods affect the comprehensive crop losses due to drought in Southern China

Southern China is a major grain-producing area, but has been suffering from increasingly serious droughts caused by global warming. As a result, crop losses have become serious. To provide insights into these losses, we obtained data to support a systematic and comprehensive analysis of how agricultural drought has caused crop losses from 1961 to 2011 and of the relationship between these changes and the climatic factors responsible for the losses. We found an obvious increase in the loss of crops due to agricultural drought in southern China, with the greatest increase in crop loss in the southwest and smaller increases in the south and southeast. Moreover, because each crop growth stage is affected differently by climatic factors and because the values of these factors show an uneven seasonal distribution, the losses were greatest when changes in various climatic factors occurred during key crop developmental periods. The fittings of the relationship between crop loss and various climatic factors was often strongest based on data from key developmental periods rather than based on data for the whole year. In addition, we found improved prediction of losses using multiple regression, and developed a model for assessing crop losses. Our results provide a scientific reference for developing methods to evaluate the losses caused by agricultural drought in southern China.

     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

PNNLs Agriculture and Land Use is used to demonstrate the impact of potential changes in climate on agricultural production and land use in the United States. AgLU simulates production of four crop types in several world regions, in 15-yr time steps from 1990 to 2095. Changes in yield of major field crops in the United States, for 12 climate scenarios, are obtained from simulations of the EPIC crop growth model. Results from the HUMUS model are used to constrain crop irrigation, and BIOME3 model is used to simulate productivity of unmanaged ecosystems. Assumptions about changes in agricultural productivity outside the United States are treated on a scenario basis, either responding in the same way as in the United States, or not responding to climate.     

Climatic change as a topic in the classical Greek and Roman literature

A search was made of the classical Greek and Roman literature for references to climatic change, irrespective whether facts of observation or views. It was found that several scholars/scientists of the classical antiquity made pronouncements on the subject and their statements are either summarized or quoted verbatim in this paper. From the Greek literature we quote Plato, Aristotle and Theophrastus; Herodotus is also quoted for an indirect reference to the topic. From the Roman literature we cite the agricultural writer Columella and the scientist Pliny the Elder; actually, Columella quotes the distinguished writers on husbandry, the Sasernas, father and son.Aristotle's statement is relevant to a degree to the Mycenaean drought (~ 1200 B.C.) problem. The Columella-Saserna pronouncement relates to the astronomical theory of climatic change, while Theophrastus discusses man-made climatic changes.Appendix I gives a statistics of storms, as gleaned from the classical literature, covering approximately the months April–October. Further, it lists some pointers to the relative coolness of the era 850/800–400/300 B.C. in some areas of the Mediterranean. Appendix II offers a few examples for the usefulness of the ancient literature from the point of view of environmental data or events.Now visiting with the Department of Meteorology, The University of Helsinki, Helsinki, Finland.     

Lake ice records used to detect historical and future climatic changes

Historical ice records, such as freeze and breakup dates and the total duration of ice cover, can be used as a quantitative indicator of climatic change if long homogeneous records exist and if the records can be calibrated in terms of climatic changes. Lake Mendota, Wisconsin, has the longest uninterrupted ice records available for any lake in North America dating back to 1855. These records extend back prior to any reliable air temperature data in the midwestern region of the U.S. and demonstrate significant warming of approximately 1.5 °C in fall and early winter temperatures and 2.5 °C in winter and spring temperatures during the past 135 years. These changes are not completely monotonie, but rather appear as two shorter periods of climatic change in the longer record. The first change was between 1875 and 1890, when fall, winter, and spring air temperatures increased by approximately 1.5 °C. The second change, earlier ice breakup dates since 1979, was caused by a significant increase in winter and early spring air temperatures of approximately 1.3 °C. This change may be indicative of shifts in regional climatic patterns associated with global warming, possibly associated with the Greenhouse Effect.With the relationships between air temperature and freeze and break up dates, we can project how the ice cover of Lake Mendota should respond to future climatic changes. If warming occurs, the ice cover for Lake Mendota should decrease approximately 11 days per 1 °C increase. With a warming of 4 to 5 °C, years with no ice cover should occur in approximately 1 out of 15 to 30 years.     

Assessing climate persistence from climatic ‘noise’

Changes in climate are generally defined as differences between means. The autocorrelation usually encountered in geophysical series and the implied persistence, or reduced number of independent observations, tend to render significance tests of mean differences inconclusive until a considerable amount of data has accumulated, by which time a climatic change could be well under way. A more efficient alternative approach is provided by small-sample variances. Under slightly idealized conditions their frequency distribution is of the chi-square type with a number of degrees of freedom that measures the persistence in the series and can be monitored on a short time scale with a sequential sampling procedure.Also at homein CIRES, Campus Box 449, University of Colorado, Boulder, CO 80309, U.S.A.     

Glaciers and Climate in the Andes between the Equator and 30° S: What is Recorded under Extreme Environmental Conditions?

Sublimation and melt disturb the environmental information obtained from ice core records in the Andes. In two case studies we demonstrate to what extent these post-depositional processes may remove major parts of the accumulated snow cover. Dark ash layers from the Tungurahua eruption changed the albedo of surface snow on Chimborazo glacier (6268 m, 1°30 S,78°36 W, Ecuador) between two ice core drilling campaigns and forced substantial melt. Re-distribution and washout of the chemical constituents shifted the concentration profiles obtained in December 1999 as compared to an equivalent core drilled in December 2000. The stable isotope records showed that approximately the water equivalent (weq) of an annual layer had melted, and that the percolating melt water penetrated within the firn layer to a depth of at least 16.5 m without refreezing. In the second example, from a site on the dry axis between the tropical and extra-tropical precipitation belts, significant loss of accumulated snow layers occurred by sublimation. A surface experiment at Cerro Tapado glacier (5536 m, 30°08 S,69°55 W, Chile) revealed that losses of 2 mm weq (5 mm snow) per day occurred during the dry period following the 1997/98 El Niño. This loss generally included the entire surface layer enriched in stable isotopes, and thus caused minimal disturbance of the isotopic signature (and hence climatic information) of the net accumulation, yet chemical constituents again experienced considerable changes in concentration. From annual layer counting and direct dating it is obvious that the major part of the accumulated ice on both glaciers is younger than 100 years; however, isotopic and chemical variations at least in the basal ice from Cerro Tapado clearly point to climate conditions different from the recent centuries. This evidence is supported by mass balance considerations derived from a glacier-climate model. The possibility of a third type of disturbance aside from sublimation and melting – in this case a significant hiatus in the environmental chronology – also deserves consideration for other icecore records from this region. Potential disruptions or discontinuities need to be carefully evaluated given the profound changes in climatic and glaciological conditions since the Last Glacial Maximum throughout Holocene times.     

长江中下游近百年气候冷暖变化对农业生态环境的影响

分别统计分析了上海、合肥、金华、武汉、长沙、南昌、吉安、衡阳等站生长季热量（﹥10 ℃积温及持续日数）和越冬期低温（﹤０℃负积温及极端最低气温）变化特征。运用谱分析方法，提出长江中下游地区气候冷暖变化的周期及长期波动趋势。同时，预测本世纪末，长江中下游地区气候冷暖波动对建立高产、优质、高效的现代农业可能是一种潜在威胁；指出在长江中下游地区农业生产过程中必须重视气候投入，突破传统农业经验，优化农业耕作轮作栽培制度，建设对气候变化具有强的调控功能的新的农业生态系统。     

USE OF A STOCHASTIC WEATHER GENERATOR IN THE DEVELOPMENT OF CLIMATE CHANGE SCENARIOS

Climate change scenarios with a high spatial and temporal resolution are required in the evaluation of the effects of climate change on agricultural potential and agricultural risk. Such scenarios should reproduce changes in mean weather characteristics as well as incorporate the changes in climate variability indicated by the global climate model (GCM) used. Recent work on the sensitivity of crop models and climatic extremes has clearly demonstrated that changes in variability can have more profound effects on crop yield and on the probability of extreme weather events than simple changes in the mean values. The construction of climate change scenarios based on spatial regression downscaling and on the use of a local stochastic weather generator is described. Regression downscaling translated the coarse resolution GCM grid-box predictions of climate change to site-specific values. These values were then used to perturb the parameters of the stochastic weather generator in order to simulate site-specific daily weather data. This approach permits the incorporation of changes in the mean and variability of climate in a consistent and computationally inexpensive way. The stochastic weather generator used in this study, LARS-WG, has been validated across Europe and has been shown to perform well in the simulation of different weather statistics, including those climatic extremes relevant to agriculture. The importance of downscaling and the incorporation of climate variability are demonstrated at two European sites where climate change scenarios were constructed using the UK Met. Office high resolution GCM equilibrium and transient experiments.     

Canadian vegetation sensitivity to projected climatic change at three organizational levels

The potential equilibrium response of Canadian vegetation under two doubled-CO₂ climatic scenarios was investigated at three levels in the vegetation mosaic using the rule-based, Canadian Climate-Vegetation Model (CCVM) and climatic response surfaces. The climatic parameters employed as model drivers (i.e., degree-days, minimum temperature, snowpack, actual evapotranspiration, and soil moisture deficit) have a more direct influence on the distribution of vegetation than those commonly used in equilibrium models. Under both scenarios, CCVM predicted reductions in the extent of the tundra and subarctic woodland formations, a northward shift and some expansion in the distributions of boreal and the temperate forest, and an expansion of the dry woodland and prairie formations that was especially pronounced under one of the scenarios. Results of the response surface analysis suggest the potential for significant changes in the probability of dominance for eight boreal tree species. A dissimilarity coefficient was used to identify forest-types under the future climatic scenarios that were analogous to boreal forest-types derived from cluster analysis of the current probabilities of species dominance. All of the current forest-types persisted under the doubled-CO₂ scenarios, but no-analog areas were also identified within which an empirically derived threshold of the distance coefficient was exceeded. Maps showing the highest level in the vegetation hierarchy where change was predicted suggest the relative impact of the response under the two climatic scenarios.     

Public expectation as an element of human perception of climate change

Human expectations regarding weather and climate sometimes lead to perceptions of climate change which are not supported by observational evidence. This paper analyses two very characteristic complaints about current climate in Switzerland, i.e., the lack of snow in winter and the lack of sunshine in summer, through a statistical investigation of climatological data. As one major problem of public perception of climate in mid-latitude regions is linked to the strong variability of the climatic parameters, the paper suggests means of presenting climatic data which include a measure of this variability. Such presentations would help overcome the common confusion between the terms weather and climate, and stress the fact that short-term extreme events are not necessarily indicative of a long-term shift in climate.     

The impact of climate change on the river rhine: A scenario study

This paper concerns the impact of human-induced global climate change on the River Rhine discharge. For this purpose a model for climate assessment, named ESCAPE, is coupled to a water balance model, named RHINEFLOW. From climate scenarios, changes in regional annual water availability and seasonal discharge in the River Rhine Basin are estimated. The climate scenarios are based on greenhouse gases emissions scenarios. An assessment is made for best guess seasonal discharge changes and for changes in frequencies of low and high discharges in the downstream reaches of the river. In addition, a quantitative estimation of the uncertainties associated with this guess is arrived at.The results show that the extent and range of uncertainty is large with respect to the best guess changes. The uncertainty range is 2–3 times larger for the Business-as-Usual than for the Accelerated Policies scenarios. This large range stems from the doubtful precipitation simulations from the present General Circulation Models. This scenario study showed the precipitation scenarios to be the key-elements within the present range of reliable climate change scenarios.For the River Rhine best guess changes for annual water availability are small according to both scenarios. The river changes from a present combined snow-melt-rain fed river to an almost entirely rain fed river. The difference between present-day large average discharge in winter and the small average discharge in autumn should increase for all scenarios. This trend is largest in the Alpine part of the basin. Here, winter discharges should increase even for scenarios forecasting annual precipitation decreases. Summer discharge should decrease. Best guess scenarios should lead to increased frequencies of both low and high flow events in the downstream (Dutch) part of the river. The results indicate changes could be larger than presently assumed in worst case scenarios used by the Dutch water management authorities.     

MEAN AND VARIANCE CHANGE IN CLIMATE SCENARIOS: METHODS, AGRICULTURAL APPLICATIONS, AND MEASURES OF UNCERTAINTY

Our central goal is to determine the importance of including both mean and variability changes in climate change scenarios in an agricultural context. By adapting and applying a stochastic weather generator, we first tested the sensitivity of the CERES-Wheat model to combinations of mean and variability changes of temperature and precipitation for two locations in Kansas. With a 2°C increase in temperature with daily (and interannual) variance doubled, yields were further reduced compared to the mean only change. In contrast, the negative effects of the mean temperature increase were greatly ameliorated by variance decreased by one-half. Changes for precipitation are more complex, since change in variability naturally attends change in mean, and constraining the stochastic generator to mean change only is highly artificial. The crop model is sensitive to precipitation variance increases with increased mean and variance decreases with decreased mean. With increased mean precipitation and a further increase in variability Topeka (where wheat cropping is not very moisture limited) experiences decrease in yield after an initial increase from the 'mean change only case. At Goodland Kansas, a moisture-limited site where summer fallowing is practiced, yields are decreased with decreased precipitation, but are further decreased when variability is further reduced. The range of mean and variability changes to which the crop model is sensitive are within the range of changes found in regional climate modeling (RegCM) experiments for a CO₂ doubling (compared to a control run experiment). We then formed two types of climate change scenarios based on the changes in climate found in the control and doubled CO₂ experiments over the conterminous U. S. of RegCM: (1) one using only mean monthly changes in temperature, precipitation, and solar radiation; and (2) another that included these mean changes plus changes in daily (and interannual) variability. The scenarios were then applied to the CERES-Wheat model at four locations (Goodland, Topeka, Des Moines, Spokane) in the United States. Contrasting model responses to the two scenarios were found at three of the four sites. At Goodland, and Des Moines mean climate change increased mean yields and decreased yield variability, but the mean plus variance climate change reduced yields to levels closer to their base (unchanged) condition. At Spokane mean climate change increased yields, which were somewhat further increased with climate variability change. Three key aspects that contribute to crop response are identified: the marginality of the current climate for crop growth, the relative size of the mean and variance changes, and timing of these changes. Indices for quantifying uncertainty in the impact assessment were developed based on the nature of the climate scenario formed, and the magnitude of difference between model and observed values of relevant climate variables.     

Climate Change Effects on Plant Growth, Crop Yield and Livestock

A review is given of the state of knowledge in the field of assessing climate change impacts on agricultural crops and livestock. Starting from the basic processes controlling plant growth and development, the possible impacts and interactions of climatic and other biophysical variables in different agro-environments are highlighted. Qualitative and quantitative estimations of shifts in biomass production and water relations, inter-plant competition and crop species adaptability are discussed. Special attention is given to the problems encountered when scaling up physiological responses at the leaf- and plant level to yield estimates at regional to global levels by using crop simulation models in combination with geo-referenced, agro-ecological databases. Some non-linear crop responses to environmental changes and their relations to adaptability and vulnerability of agro-ecosystems are discussed.     

The effect of changing climate on Australian biomass production — a preliminary study

Increasing concentrations of carbon dioxide and other infrared absorbing gases are widely proposed as a mechanism for a global surface warming over the next several decades. Various methods have been used to anticipate the regional climatic changes which might result. In earlier papers Pittock has concluded that for Australia an increase in the extent of the summer rainfall regime is likely, with a decrease in winter rainfall. This is similar to a change which took place over much of Australia in the 1940's.In this paper a climate scenario, roughly corresponding to the climate which might be expected to occur by about the middle of the twenty-first century, has been used as the input into the Miami Model of net primary productivity due to Lieth. Results show that about half of Australia might experience productivity increases in excess of 20%. A small area in the extreme south-west of Australia shows a small decrease in productivity.The direct response of plants to higher ambient carbon dioxide concentrations, and many other possible effects such as changes in the incidence of plant diseases, pests, and soil erosion have not been assessed.Whether or not increasing carbon dioxide will lead to further climatic change in the next few decades, the results show that Australian primary productivity is quite sensitive to climatic variations within the range found in the historical records.     

The use of general circulation models in the analysis of the ecosystem impacts of climatic change

The use of general circulation models in the estimation of the impact of climatic change on the global ecosystem is seen to depend primarily on their ability to reliably depict the seasonal and geographical distribution of the changes in surface climate variables. While present GCMs generally simulate the observed distribution of surface air temperature reasonably well, they show significantly different changes in the equilibrium temperature as a result of doubled CO₂, for example. These disagreements are attributed to differences in the model's resolution and parameterization of subgrid-scale processes. Such model-dependent errors notwithstanding, much more information of possible use in impact analysis can be extracted from general circulation model simulations than has generally been done so far. The completeness, consistency and experimental possibilities offered by simulated data sets permit the systematic extraction of a wide variety of statistics important to the surface ecosystem, such as the length of the growing season, the duration of rainless periods, and the surface moisture stress.Assuming further model improvements, the elements of a model-assisted methodology for climate impact analysis are seen to be: (1) the determination of the seasonal and geographical distribution of that portion of simulated climatic changes which are both statistically and physically significant; (2) the transformation of the (significant) large-scale climatic changes onto the local scale of impact (the climate inversion problem); and (3) the design of specific statistical parameters or functions relevant to local ecosystem impacts.     

Rainfall in the Garden of the United States Great Plains, 1870–1889

The recent accumulation of all published precipitation records from 1870–1889 in the central and northern Great Plains of the United States provides a renewed potential in analyzing climatic reality during early settlement, corresponding to a time when some written histories documented that the Rain followed the Plow. Growing season precipitation in the central and northern Great Plains from 1870–1889 were examined relative to modern climatic normals (1961–1990). Growing season totals mostly exhibit little changes in precipitation in the region as compared to today. Some wetter springs and summers occurred in the Dakotas during the late 1870s and early 1880s, subsequent to the drier early-mid 1870s and corresponding to the Great Dakota Boom. Wetter summers occurred over the central Plains in the mid-1880s, corresponding to increased migration in Nebraska and Kansas. Drier summers occurred during the early 1870s and inactive settlement in the early 1880s. Although increased rainfall may have been conducive for early settlement, in general the Rain did not follow the Plow, with extreme seasonal and monthly heavy precipitation events at the subregional scale perhaps playing important roles on settlers' climatic perceptions. The results of this study provide a framework in order to conduct historical climate impact analyses as well as information that can be applied towards understanding spatial climatic variations further back into time.     

Mechanisms of shrubland expansion: land use,climate or CO2?

Encroachment of trees and shrubs into grasslands and the thicketization of savannas has occurred worldwide over the past century. These changes in vegetation structure are potentially relevant to climatic change as they may be indicative of historical shifts in climate and as they may influence biophysical aspects of land surface-atmosphere interactions and alter carbon and nitrogen cycles. Traditional explanations offered to account for the historic displacement of grasses by woody plants in many arid and semi-arid ecosystems have centered around changes in climatic, livestock grazing and fire regimes. More recently, it has been suggested that the increase in atmospheric CO₂ since the industrial revolution has been the driving force. In this paper we evaluate the CO₂ enrichment hypotheses and argue that historic, positive correlations between woody plant expansion and atmospheric CO₂ are not cause and effect.Please direct all correspondence to the senior author.     

Impacts of a Ghg-Induced Climate Change on Crop Yields: Effects of Acceleration in Maturation, Moisture Stress and Optimal Temperature

The present study involves using the Canadian Climate Centre (CCC) climate change scenario to evaluate the impacts of a CO₂-induced climate change on agriculture in Québec and vicinity. Climate change using the CCC General Circulation Model (GCM) data are fed into a crop model (FAO) so as to gauge the changes in agroclimatic factors such as growing season length and growing degree days, and subsequently potential yield changes for a variety of cereal (C₃ and C₄), leguminous, oleaginous, vegetable and special crops, for twelve major agricultural regions in southern Québec. Our results show that depending upon the agricultural zone and crop type, yields may increase (ex. corn and sorghum by 20%) or decrease (ex. wheat and soybean by 20 to 30%). Also, these crop yield changes appear to be related to acceleration in maturation rates, mainly to change in moisture stress and to shifts in optimal thermal growth conditions. These possible shifts in agricultural production potentials would solicit the formulation of appropriate adaptation strategies.