The optimal choice of residue management, crop rotations, and cost of carbon sequestration: empirical results in the Midwest US

This study investigates the cost of soil carbon sequestration in the Midwest US. The model addresses several missing components in earlier analyses: the link between the residue level choice and carbon payments, crop rotations, carbon loss when shifting from conservation to conventional tillage and the spatial pattern of carbon sequestration across different soil types. The results suggest that for $100 per metric ton of carbon, 1.5 million metric tons of carbon could be sequestered per year on the 19.9 million hectares of cropland in the study region. These estimates suggest less carbon potential than existing studies because the opportunity costs associated with conservation tillage are fairly high. Annual carbon rental payments are found to be more efficient, as expected, but for smaller programs, per hectare rental payments are not substantially more costly.     

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province,southern China

Rainfall erosivity, which shows a potential risk of soil loss caused by water erosion, is an important factor in soil erosion process. In consideration of the critical condition of soil erosion induced by rainfall in Guangdong Province of southern China, this study analyzed the spatial and temporal variations in rainfall erosivity based on daily rainfall data observed at 25 meteorological stations during the period of 1960–2011. The methods of global spatial autocorrelation, kriging interpolation, Mann–Kendall test, and continuous wavelet transform were used. Results revealed that the annual rainfall erosivity in Guangdong Province, which spatially varied with the maximum level observed in June, was classified as high erosivity with two peaks that occur in spring and summer. In the direction of south–north, mean annual rainfall erosivity, which showed significant relationships with mean annual rainfall and latitude, gradually decreased with the high values mainly distributed in the coastal area and the low values mainly occurring in the lowlands of northwestern Guangdong. Meanwhile, a significant positive spatial autocorrelation which implied a clustered pattern was observed for annual rainfall erosivity. The spatial distribution of seasonal rainfall erosivity exhibited clustering tendencies, except spring erosivity with Moran’s I and Z values of 0.1 and 1.04, respectively. The spatial distribution of monthly rainfall erosivity presented clustered patterns in January–March and July–October as well as random patterns in the remaining months. The temporal trend of mean rainfall erosivity in Guangdong Province showed no statistically significant trend at the annual, seasonal, and monthly scales. However, at each station, 1 out of 25 stations exhibited a statistically significant trend at the annual scale; 4 stations located around the Pearl River Delta presented significant trends in summer at the seasonal scale; significant trends were observed in March (increasing trends at 3 stations), June (increasing trends at 4 stations located in the Beijiang River Basin), and October (decreasing trends at 4 stations) at the monthly scale. In accordance with the mean annual rainfall over Guangdong Province, the mean annual rainfall erosivity showed two significant periodicities of 3–6 and 10–12 years at a confidence level of 95 %. In conclusion, the results of this study provide insights into the spatiotemporal variation in rainfall erosivity in Guangdong Province and support for agrolandscape planning and water and soil conservation efforts in this region.     

Multiple cropping systems of the world and the potential for increasing cropping intensity

Multiple cropping, defined as harvesting more than once a year, is a widespread land management strategy in tropical and subtropical agriculture. It is a way of intensifying agricultural production and diversifying the crop mix for economic and environmental benefits. Here we present the first global gridded data set of multiple cropping systems and quantify the physical area of more than 200 systems, the global multiple cropping area and the potential for increasing cropping intensity. We use national and sub-national data on monthly crop-specific growing areas around the year 2000 (1998–2002) for 26 crop groups, global cropland extent and crop harvested areas to identify sequential cropping systems of two or three crops with non-overlapping growing seasons. We find multiple cropping systems on 135 million hectares (12% of global cropland) with 85 million hectares in irrigated agriculture. 34%, 13% and 10% of the rice, wheat and maize area, respectively are under multiple cropping, demonstrating the importance of such cropping systems for cereal production. Harvesting currently single cropped areas a second time could increase global harvested areas by 87–395 million hectares, which is about 45% lower than previous estimates. Some scenarios of intensification indicate that it could be enough land to avoid expanding physical cropland into other land uses but attainable intensification will depend on the local context and the crop yields attainable in the second cycle and its related environmental costs.     

Overestimated Biomass Carbon Pools of the Northern mid- and High Latitude Forests

The biomass carbon (C) stock of forests is one of key parameters for the study of regional and global carbon cycles. Literature reviews shows that inventory-based forest C stocks documented for major countries in the middle and high northern latitudes fall within a narrow range of 36–56 Mg C ha⁻¹ with an overall area-weighted mean of 43.6 Mg C ha⁻¹. These estimates are 0.40 to 0.71 times smaller than those (61–108 Mg C ha⁻¹) used in previous analysis of balancing the global carbon budget. A statistical analysis, using the global forest biomass database, implies that aboveground biomass per hectare is proportional to forest mean height [biomass in Mg/ha = 10.63 (height in m)] in closed-canopy forests in the study regions, indicating that forest height can be a proxy of regional biomass C stocks. The narrow range of C stocks is likely a result of similar forest height across the northern regions. The lower biomass C stock obtained in this study strongly suggests that the role of the northern forests in the global carbon cycle needs to be re-evaluated. Our findings also suggest that regional estimates of biomass could be readily made from the use of satellite methods such as lidar that can measure forest canopy height over large regions.     

Estimating the economic potential for agricultural soil carbon sequestration in the Central United States using an aggregate econometric-process simulation model

The purpose of this paper is to develop and apply a new method to assess economic potential for agricultural greenhouse gas mitigation. This method uses secondary economic data and conventional econometric production models, combined with estimates of soil carbon stocks derived from biophysical simulation models such as Century, to construct economic simulation models that estimate economic potential for carbon sequestration. Using this method, simulations for the central United States show that reduction in fallow and conservation tillage adoption in the wheat-pasture system could generate up to about 1.7 million MgC/yr, whereas increased adoption of conservation tillage in the corn–soy–feed system could generate up to about 6.2 million MgC/yr at a price of $200/MgC. About half of this potential could be achieved at relatively low carbon prices (in the range of $50 per ton). The model used in this analysis produced estimates of economic potential for soil carbon sequestration potential similar to results produced by much more data-intensive, field-scale models, suggesting that this simpler, aggregate modeling approach can produce credible estimates of soil carbon sequestration potential. Carbon rates were found to vary substantially over the region. Using average carbon rates for the region, the model produced carbon sequestration estimates within about 10% of those based on county-specific carbon rates, suggesting that effects of spatial heterogeneity in carbon rates may average out over a large region such as the central United States. However, the average carbon rates produced large prediction errors for individual counties, showing that estimates of carbon rates do need to be matched to the spatial scale of analysis. Transaction costs were found to have a potentially important impact on soil carbon supply at low carbon prices, particularly when carbon rates are low, but this effect diminishes as carbon prices increase. This research was supported in part by the Montana State Agricultural Experiment Station, by the EPA STAR Climate Change program and by the Consortium for the Agricultural Mitigation of Greenhouse Gases. Although the research described in this article has been funded wholly or in part by the United States Environmental Protection Agency through grant R-82874501-0 to Montana State University, it has not been subjected to the Agency’s required peer and policy review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.     

Forest law enforcement in the Brazilian Amazon: Costs and income effects

Despite recent success in reducing forest loss in the Brazilian Amazon, additional forest conservation efforts, for example, through ‘Reducing Emissions from Deforestation and Forest Degradation’ (REDD+), could significantly contribute to global climate-change mitigation. Economic incentives, such as payments for environmental services could promote conservation, but deforestation often occurs on land without crucial tenure-security prerequisites. Improving the enforcement of existing regulatory disincentives thus represents an important element of Brazil's anti-deforestation action plan. However, conservation law enforcement costs and benefits have been much less studied than for conditional payments. We develop a conceptual framework and a spatially explicit model to analyze field-based regulatory enforcement in the Brazilian Amazon. We validate our model, based on historical deforestation and enforcement mission data from 2003 to 2008. By simulating the current conservation law enforcement practice, we analyze the costs of liability establishment and legal coercion for alternative conservation targets, and evaluate corresponding income impacts. Our findings suggest that spatial patterns of both deforestation and inspection costs markedly influence enforcement patterns and their income effects. Field-based enforcement is a highly cost-effective forest conservation instrument from a regulator's point of view, but comes at high opportunity costs for land users. Payments for environmental services could compensate costs, but will increase budget outlays vis-à-vis a command-and-control dominated strategy. Both legal and institutional challenges have to be overcome to make conservation payments work at a larger scale. Decision-makers may have to innovatively combine incentive and disincentive-based policy instruments in order to make tropical forest conservation both financially viable and socially compatible.     

Climate change and global water resources

By 2025, it is estimated that around 5 billion people, out of a total population of around 8 billion, will be living in countries experiencing water stress (using more than 20% of their available resources). Climate change has the potential to impose additional pressures in some regions. This paper describes an assessment of the implications of climate change for global hydrological regimes and water resources. It uses climate change scenarios developed from Hadley Centre climate simulations (HadCM2 and HadCM3), and simulates global river flows at a spatial resolution of 0.5×0.5° using a macro-scale hydrological model. Changes in national water resources are calculated, including both internally generated runoff and upstream imports, and compared with national water use estimates developed for the United Nations Comprehensive Assessment of the Freshwater Resources of the World. Although there is variation between scenarios, the results suggest that average annual runoff will increase in high latitudes, in equatorial Africa and Asia, and southeast Asia, and will decrease in mid-latitudes and most subtropical regions. The HadCM3 scenario produces changes in runoff which are often similar to those from the HadCM2 scenarios — but there are important regional differences. The rise in temperature associated with climate change leads to a general reduction in the proportion of precipitation falling as snow, and a consequent reduction in many areas in the duration of snow cover. This has implications for the timing of streamflow in such regions, with a shift from spring snow melt to winter runoff. Under the HadCM2 ensemble mean scenario, the number of people living in countries with water stress would increase by 53 million by 2025 (relative to those who would be affected in the absence of climate change). Under the HadCM3 scenario, the number of people living in countries with water stress would rise by 113 million. However, by 2050 there would be a net reduction in populations in stressed countries under HadCM2 (of around 69 million), but an increase of 56 million under HadCM3. The study also showed that different indications of the impact of climate change on water resource stresses could be obtained using different projections of future water use. The paper emphasises the large range between estimates of “impact”, and also discusses the problems associated with the scale of analysis and the definition of indices of water resource impact.     

Estimating the world's potentially available cropland using a bottom-up approach

Previous estimates of the land area available for future cropland expansion relied on global-scale climate, soil and terrain data. They did not include a range of constraints and tradeoffs associated with land conversion. As a result, estimates of the global land reserve have been high. Here we adjust these estimates for the aforementioned constraints and tradeoffs. We define potentially available cropland as the moderately to highly productive land that could be used in the coming years for rainfed farming, with low to moderate capital investments, and that is not under intact mature forests, legally protected, or already intensively managed. This productive land is underutilized rather than unused as it has ecological or social functions. We also define potentially available cropland that accounts for trade-offs between gains in agricultural production and losses in ecosystem and social services from intensified agriculture, to include only the potentially available cropland that would entail low ecological and social costs with conversion to cropland. In contrast to previous studies, we adopt a “bottom-up” approach by analyzing detailed, fine scale observations with expert knowledge for six countries or regions that are often assumed to include most of potentially available cropland. We conclude first that there is substantially less potential additional cropland than is generally assumed once constraints and trade offs are taken into account, and secondly that converting land is always associated with significant social and ecological costs. Future expansion of agricultural production will encounter a complex landscape of competing demands and tradeoffs.     

中国土壤热通量的时空分布特征研究

利用中国生态系统研究网络(CERN)的17个野外台站2004～2007年的实测土壤表层热通量资料,分析了土壤表层热通量的季节和空间变化规律。土壤热通量从2月份开始由负值转变为正值,9月份左右开始由正值转变为负值,在3～8月份土壤热通量的值都为正值,12月至次年1月土壤热通量都为负值。空间分布上,东北地区和西北地区季节变化明显,年变幅比较大,长江流域地区夏季增加幅度小,年变化幅度也比较小,青藏高原地区四季都相对为低值地区,年变幅比较小,总的空间变化趋势是春夏季北高南低,秋冬季节南高北低。土壤热通量年合计值在东北黑土地地区、西北荒漠地区、黄土高原陕北地区和四川盆地地区是高值区,长江流域下游和黄河流域中下游冲积而成的区域为负值区。研究结果为进一步研究土壤的生态环境形成和变化提供了参考依据。     

Agroclimatic classification of the semi-arid tropics III. Characteristics of variables relevant to crop production potential

This paper presents the characteristics of agroclimatic variables identified in part II of this study as being relevant to crop production potential. A soil-water balance simulation and agronomic data for selected locations in India were used to assist in this analysis. Based on these observations the successful cropping systems and crop species for similar soil types were also discussed. Clearly, the cropping pattern is not only influenced by the mean effective rainy period but also by its variability, as well as the variability in the times at which the sowing rains commence. However, the crop varieties that are suitable for these cropping patterns differ significantly. They are associated more with soil type, and the wet and dry spells within the effective rainy period.     

Volatility modeling of rainfall time series

Networks of rain gauges can provide a better insight into the spatial and temporal variability of rainfall, but they tend to be too widely spaced for accurate estimates. A way to estimate the spatial variability of rainfall between gauge points is to interpolate between them. This paper evaluates the spatial autocorrelation of rainfall data in some locations in Peninsular Malaysia using geostatistical technique. The results give an insight on the spatial variability of rainfall in the area, as such, two rain gauges were selected for an in-depth study of the temporal dependence of the rainfall data-generating process. It could be shown that rainfall data are affected by nonlinear characteristics of the variance often referred to as variance clustering or volatility, where large changes tend to follow large changes and small changes tend to follow small changes. The autocorrelation structure of the residuals and the squared residuals derived from autoregressive integrated moving average (ARIMA) models were inspected, the residuals are uncorrelated but the squared residuals show autocorrelation, and the Ljung–Box test confirmed the results. A test based on the Lagrange multiplier principle was applied to the squared residuals from the ARIMA models. The results of this auxiliary test show a clear evidence to reject the null hypothesis of no autoregressive conditional heteroskedasticity (ARCH) effect. Hence, it indicates that generalized ARCH (GARCH) modeling is necessary. An ARIMA error model is proposed to capture the mean behavior and a GARCH model for modeling heteroskedasticity (variance behavior) of the residuals from the ARIMA model. Therefore, the composite ARIMA–GARCH model captures the dynamics of daily rainfall in the study area. On the other hand, seasonal ARIMA model became a suitable model for the monthly average rainfall series of the same locations treated.     

Considering the influence of sequestration duration and carbon saturation on estimates of soil carbon capacity

Rates of soil C sequestration have previously been estimated for a number of different land management activities, and these estimates continue to improve as more data become available. The time over which active sequestration occurs may be referred to as the sequestration duration. Integrating soil C sequestration rates with durations provides estimates of potential change in soil C capacity and more accurate estimates of the potential to sequester C. In agronomic systems, changing from conventional plow tillage to no-till can increase soil C by an estimated 16±3%, whereas increasing rotation intensity can increase soil C by an estimated 6±3%. The increase in soil C following a change in rotation intensity, however, may occur over a slightly longer period (26 yr) than that for tillage cessation (21 yr). Sequestration strategies for grasslands have, on average, longer sequestration durations (33 yr) than for croplands. Estimates for sequestration rates and durations are mean values and can differ greatly between individual sites and management practices. As the annual sequestration rate declines over the sequestration duration period, soil C approaches a new steady state. Sequestration duration is synonymous with the time to which soil C steady state is reached. However, soils could potentially sequester additional C following additional changes in management until the maximum soil C capacity, or soil C saturation, is achieved. Carbon saturation of the soil mineral fraction is not well understood, nor is it readily evident. We provide evidence of soil C saturation and we discuss how the steady state C level and the level of soil C saturation together influence the rate and duration of C sequestration associated with changes in land management.     

1961-2010年四川盆地霾气候特征及影响因子分析

利用1961-2010年四川盆地122个气象站观测资料,分析四川盆地年平均霾日数时空分布特征及霾日数季节和年变化趋势。探讨近50 a四川盆地大气干消光系数、风速、能源消耗和人口等因素与霾日数之间的关系。结果表明：1961-2010年四川盆地122个站年平均霾日数为62.5 d,最多的站可达100.0 d以上。霾日数有明显季节变化,四川盆地冬季霾日数最多（28.4 d）,春、秋季次之,夏季最少（5.9 d）。四川盆地有104个站霾日数年变化呈增加的趋势,其中有71个站通过了置信度99 %的检验,霾日数增加最多的是四川省内江地区的戚远,气候倾向率为42.0 d/10 a;霾日数增加最少的是成都市的新都,气候倾向率为0.4 d/10 a。四川盆地有18个站霾日数年变化呈下降趋势,仅7个站点通过了置信度99 %的信度检验,霾日数减少最多的是四川北部广元地区的南江,气候倾向率为-16.7 d/10 a。霾日数的年变化与大气干消光系数呈显著正相关,与风速呈显著负相关,与四川盆地的能源消耗和人口增长呈显著正相关。     

Spatial autocorrelation analysis of extreme precipitation in Iran

Spatial variations in extreme precipitation events make hydrological, climatological, social, environmental and agricultural effects on a country. This study presents the spatiotemporal autocorrelation analysis of extreme precipitation events over Iran using gridded data on daily precipitation for the period 1961–2010. The 95th percentile is considered as extreme precipitation factor. The spatial autocorrelation of extreme precipitation is examined by three commonly used spatial autocorrelation statistics, the G _i statistic index, Moran’s I global index, and Local Moran’s I (LISA) index, at the 95 and 99% significant confidence level. The results showed a strong significant spatial autocorrelation for extreme precipitation events with the highest Moran’s I value in January. The positive significant autocorrelation of extreme precipitation is observed over the southern parts of the Caspian Sea and Zagros Mountains ranges, while the negative significant autocorrelation is observed over the central and eastern parts of country. In spring and summer the positive autocorrelation cores displace from the Zagros Mountains ranges to the northwestern and southeastern parts.     

干旱区典型绿洲热场分布规律研究——以渭干河-库车河三角洲绿洲为例

利用Landsat7ETM＋遥感资料热红外波段定量反演晴空状态下夏季干旱区典型绿洲地表真实温度,运用影像叠加分析、直方图比对、缓冲区分析和空间自相关分析及剖面线分析等方法,分析其热场分布规律。结果表明：绿洲热场分布具有显著正空间自相关特性,Moran’s值为0．5489,Z值为48．44,同时呈现出显著的局部空间集聚现象;就局部而言,在相同热力环境下,由于盐碱地与裸地热容量不同,盐碱地温度低于周边裸地温度,盐碱地平均温度比周边300、900m和1500m缓冲区裸地的平均气温分别低0．59、0．44℃和0．26℃;然而盐碱地大多分布在裸地的高温区中心,且温度变化幅度小,在裸地低温区周围分布较少,所以就整体而言,裸地平均气温低于盐碱地温度,热场分布规律依次为水体温度21．65、耕地温度27．86、林草地温度35．59、城镇温度40．06℃、裸地温度42．07℃。水体、城镇、盐碱地、裸地的温度波动较小,热力景观单一,热场分布均匀,而耕地和林草地的温度梯度大,热力景观复杂多样,热场分布极不均匀,局部热场存在突变现象。绿洲荒漠交错带的面积较大,可以降低荒漠对绿洲的热力侵蚀,对保护绿洲有重要作用。     

Rural-urban connectivity and agricultural land management across the Global South

Research on how urbanization affects rural agriculture has typically focused on loss of farmland due to urban expansion. However, more distal pathways that could link urbanization to rural agriculture, including enhanced connectivity through rural-urban migration and market access, remain poorly understood. Here, we assess whether greater rural-urban connectivity is associated with changes in agricultural land management across the Global South. Such associations are complex, and thus difficult to measure at this scale. We therefore take a two-step approach to investigate these relationships. First, using a multivariate clustering approach, we define a series of rural-urban connectivity typologies from existing spatial data on land use, demographics, rural market access, and rural population change (as a proxy for outmigration). We examine the variation in key agricultural outcome variables (mean cereal crop yields, % of attainable yields met, and cropping frequency) within the typologies, which shows that greater overall connectivity (market access and population change) is associated with higher cereal yields, yield attainment, and cropping frequency. Second, building on these clustering results, we develop hypotheses about the relationship between rural-urban connectivity and agricultural land use intensity. We then use propensity score matching to test these hypotheses by comparing locations with similar sociodemographic and land use characteristics. When controlling for gross domestic product (GDP) per capita, agricultural land, and population density, rural locations with relatively high market access, negative population change, and greater built-up area have significantly higher mean nitrogen application rates, irrigated areas, and cereal yields across the Global South. Results vary by region, but greater rural-urban connectivity and urban extents are generally associated with higher overall agricultural inputs and yields, particularly in Asia. However, we find little support for a relationship between connectivity and either % attainable yields met or field size. Our findings stress the need to better understand the mechanisms that link urbanization processes and agricultural management at different spatiotemporal scales.     

环太湖地区气候变化特征研究

根据1971—2010年环太湖地区苏州、常州、长兴等9个气象台站日平均气温和日降水量资料,采用EOF正交经验分析法、线性倾向率法、小波分析法和Mann-Kendall检验法研究了环太湖地区近40 a来的气候变化特征。结果表明:1) 1971—2010年间,环太湖地区整体上呈增暖趋势,环太湖地区的季节性增暖存在空间差异,西北部的气温在春、夏季明显升高,而东南部则在秋、冬季明显增暖,1990年前后该地区的增暖率存在完全相反的空间分布。2)该40 a中,降水表现为北部增加,南部减少。整个环太湖地区的降水在冬季普遍呈现增加趋势,春、夏季降水的空间分布差异性大于秋、冬季。3) M orlet小波分析结果表明,环太湖地区年平均温度存在16～17 a和6 a、26 a左右的变化周期;年降水量存在15～16 a和24 a的强显著性变化周期,各地区在年均温、年降水量周期振荡的强度上存在一定的差异。4) Mann-Kendall突变检验显示,1971—2010年环太湖地区各站点均表现为气温由低向高的突变,突变发生在1992—1993年。     

Projected changes in drought occurrence under future global warming from multi-model,multi-scenario,IPCC AR4 simulations

Recent and potential future increases in global temperatures are likely to be associated with impacts on the hydrologic cycle, including changes to precipitation and increases in extreme events such as droughts. We analyze changes in drought occurrence using soil moisture data for the SRES B1, A1B and A2 future climate scenarios relative to the PICNTRL pre-industrial control and 20C3M twentieth century simulations from eight AOGCMs that participated in the IPCC AR4. Comparison with observation forced land surface model estimates indicates that the models do reasonably well at replicating our best estimates of twentieth century, large scale drought occurrence, although the frequency of long-term (more than 12-month duration) droughts are over-estimated. Under the future projections, the models show decreases in soil moisture globally for all scenarios with a corresponding doubling of the spatial extent of severe soil moisture deficits and frequency of short-term (4–6-month duration) droughts from the mid-twentieth century to the end of the twenty-first. Long-term droughts become three times more common. Regionally, the Mediterranean, west African, central Asian and central American regions show large increases most notably for long-term frequencies as do mid-latitude North American regions but with larger variation between scenarios. In general, changes under the higher emission scenarios, A1B and A2 are the greatest, and despite following a reduced emissions pathway relative to the present day, the B1 scenario shows smaller but still substantial increases in drought, globally and for most regions. Increases in drought are driven primarily by reductions in precipitation with increased evaporation from higher temperatures modulating the changes. In some regions, increases in precipitation are offset by increased evaporation. Although the predicted future changes in drought occurrence are essentially monotonic increasing globally and in many regions, they are generally not statistically different from contemporary climate (as estimated from the 1961–1990 period of the 20C3M simulations) or natural variability (as estimated from the PICNTRL simulations) for multiple decades, in contrast to primary climate variables, such as global mean surface air temperature and precipitation. On the other hand, changes in annual and seasonal means of terrestrial hydrologic variables, such as evaporation and soil moisture, are essentially undetectable within the twenty-first century. Changes in the extremes of climate and their hydrological impacts may therefore be more detectable than changes in their means.     

GCM-based regional temperature and precipitation change estimates for Europe under four SRES scenarios applying a super-ensemble pattern-scaling method

Seasonal GCM-based temperature and precipitation projections for the end of the 21st century are presented for five European regions; projections are compared with corresponding estimates given by the PRUDENCE RCMs. For most of the six global GCMs studied, only responses to the SRES A2 and B2 forcing scenarios are available. To formulate projections for the A1FI and B1 forcing scenarios, a super-ensemble pattern-scaling technique has been developed. This method uses linear regression to represent the relationship between the local GCM-simulated response and the global mean temperature change simulated by a simple climate model. The method has several advantages: e.g., the noise caused by internal variability is reduced, and the information provided by GCM runs performed with various forcing scenarios is utilized effectively. The super-ensemble method proved especially useful when only one A2 and one B2 simulation is available for an individual GCM. Next, 95% probability intervals were constructed for regional temperature and precipitation change, separately for the four forcing scenarios, by fitting a normal distribution to the set of projections calculated by the GCMs. For the high-end of the A1FI uncertainty interval, temperature increases close to 10°C could be expected in the southern European summer and northern European winter. Conversely, the low-end warming estimates for the B1 scenario are ~ 1°C. The uncertainty intervals of precipitation change are quite broad, but the mean estimate is one of a marked increase in the north in winter and a drastic reduction in the south in summer. In the RCM simulations driven by a single global model, the spread of the temperature and precipitation projections tends to be smaller than that in the GCM simulations, but it is possible to reduce this disparity by employing several driving models for all RCMs. In the present suite of simulations, the difference between the mean GCM and RCM projections is fairly small, regardless of the number or driving models applied.     

Stochastic interpolation as a means to estimate oceanic fields

Abstract

The method of stochastic interpolation (conditional simulation) is introduced as a means to interpolate / extrapolate a scalar or vector field of an oceanic variable, e.g. currents. Conditional simulation produces the synthesis of a random field that is forced to agree with simultaneous measurements in the same time interval and area where the input data are being synthesized. The conditional simulation is applied to the vector field for two California current measurement programs (Coastal Ocean Dynamics Experiment (CODE) and Central California Coastal Circulation Study fccccsj, north and south of San Francisco, respectively). These field programs covered different areas and were characterized by different instrument spacings. The influence of these spatial factors shows up in the quality of the conditional simulations, i.e. a smaller area and a tighter mooring array led to more physically reasonable flow realizations. The various realizations provided by a series of conditional simulations allow confidence intervals to be defined. Other uses for this technique include optimization of current‐meter (or other sensor) placement and the specification of initial or boundary conditions for numerical models. This latter function could be invoked when real data are sparse or when the data that are available are overly smooth and do not contain enough of the variability of the natural system.