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71.
Theodore G. Shepherd Emily Boyd Raphael A. Calel Sandra C. Chapman Suraje Dessai Ioana M. Dima-West Hayley J. Fowler Rachel James Douglas Maraun Olivia Martius Catherine A. Senior Adam H. Sobel David A. Stainforth Simon F. B. Tett Kevin E. Trenberth Bart J. J. M. van den Hurk Nicholas W. Watkins Dimitri A. Zenghelis 《Climatic change》2018,147(3-4):555-569
Investigating the relationships between climate extremes and crop yield can help us understand how unfavourable climatic conditions affect crop production. In this study, two statistical models, multiple linear regression and random forest, were used to identify rainfall extremes indices affecting wheat yield in three different regions of the New South Wales wheat belt. The results show that the random forest model explained 41–67% of the year-to-year yield variation, whereas the multiple linear regression model explained 34–58%. In the two models, 3-month timescale standardized precipitation index of Jun.–Aug. (SPIJJA), Sep.–Nov. (SPISON), and consecutive dry days (CDDs) were identified as the three most important indices which can explain yield variability for most of the wheat belt. Our results indicated that the inter-annual variability of rainfall in winter and spring was largely responsible for wheat yield variation, and pre-growing season rainfall played a secondary role. Frequent shortages of rainfall posed a greater threat to crop growth than excessive rainfall in eastern Australia. We concluded that the comparison between multiple linear regression and machine learning algorithm proposed in the present study would be useful to provide robust prediction of yields and new insights of the effects of various rainfall extremes, when suitable climate and yield datasets are available. 相似文献
72.
Rachel Mundeli Murekatete 《International journal of geographical information science》2018,32(11):2169-2188
Planners who are involved in locational decision-making often use raster-based geographic information systems to quantify the value of land in terms of suitability or cost for a certain use. From a computational point of view, this process can be seen as a transformation of one or more sets of values associated with a grid of cells into another set of such values through a function reflecting one or more criteria. While it is generally anticipated that different transformations lead to different ‘best’ locations, little has been known on how such differences arise (or do not arise). The paper attempts to answer this question in the context of path planning through a series of computational experiments using a number of random landscape grids with a variety of spatial and nonspatial structures. In the experiments, we generated least-cost paths on a number of cost grids transformed from the landscape grids using a variety of transformation parameters and analyzed the locations and (weighted) lengths of those paths. Results show that the same pair of terminal cells may well be connected by different least-cost paths on different cost grids though derived from the same landscape grid and that the variation among those paths is affected by how given values are distributed in the landscape grid as well as by how derived values are distributed in the cost grids. Most significantly, the variation tends to be smaller when the landscape grid contains more distinct patches of cells potentially attracting or distracting cost-saving passage or when the cost grid contains a smaller number of low-cost cells. 相似文献
73.
Panjai Prapaipong Colin W. Enssle Julie D. Morris Everett L. Shock Rachel E. Lindvall 《Applied Geochemistry》2008,23(8):2156-2170
To investigate Pb transport and cycling, soils from the forest floor and cores from White Oaks (Quercus alba L.) were collected near a Pb smelter in SE Missouri at varying depths from the surface and varying distances. Lead concentrations in soil samples at the surface drop dramatically with distance from approximately 1500 mg/kg at less than 2 km from the smelter to around 100 mg/kg at localities greater than 2 km from the smelter. Lead contents in tree rings are below 0.5 mg/kg in samples dated prior to 1970, and rapidly increase in 1975–1990 samples. Isotopic compositions of soils and tree rings exhibit systematic variations of Pb isotopic compositions with depth and tree ring age. Distinguishable isotopic signatures for Pb sources allowed quantification of the contribution of smelter Pb to the soils. At depths where Pb concentrations decreased and approached constant values (10–25 cm, 10–30 mg/kg), 50–90%, 40–50% and 10–50% of the Pb could be derived from the smelter for the samples at locations less than 2, 2–4 and over 4 km from the smelter, respectively. The remaining portion was attributable to automobile emission and bedrock sources. Because the smelter operated from 1963 to 2003 and samples were collected in 1999, it is estimated that smelter Pb infiltrates at rates of 1 cm/yr (30 cm in 30 yr). At distances less than 1.5 km from the smelter, even though Pb concentrations become asymptotic at a depth of 30 cm, isotopic evidence suggests that Pb has migrated below this depth, presumably through exchange with naturally occurring Pb in the soil matrix. This implies that soils heavily polluted by Pb can exceed their Pb carrying capacity, which could have potential impacts on shallow groundwater systems and risk further exposure to human and ecological receptors. 相似文献
74.
Rachel Whitsed Lisa T. Smallbone 《International journal of geographical information science》2017,31(4):717-737
Cellular automata (CA) models are commonly used to model vegetation dynamics, with the genetic algorithm (GA) being one method of calibration. This article investigates different GA settings, as well as the combination of a GA with a local optimiser to improve the calibration effort. The case study is a pattern-calibrated CA to model vegetation regrowth in central Victoria, Australia. We tested 16 GA models, varying population size, mutation rate, and level of allowable mutation. We also investigated the effect of applying a local optimiser, the Nelder?Mead Downhill Simplex (NMDS) at GA convergence. We found that using a decreasing mutation rate can reduce computational cost while avoiding premature GA convergence, while increasing population size does not make the GA more efficient. The hybrid GA-NMDS can also reduce computational cost compared to a GA alone, while also improving the calibration metric. We conclude that careful consideration of GA settings, including population size and mutation rate, and in particular the addition of a local optimiser, can positively impact the efficiency and success of the GA algorithm, which can in turn lead to improved simulations using a well-calibrated CA model. 相似文献
75.
Both statistical and dynamical downscaling methods are well established techniques to bridge the gap between the coarse information produced by global circulation models and the regional-to-local scales required by the climate change Impacts, Adaptation, and Vulnerability (IAV) communities. A number of studies have analyzed the relative merits of each technique by inter-comparing their performance in reproducing the observed climate, as given by a number of climatic indices (e.g. mean values, percentiles, spells). However, in this paper we stress that fair comparisons should be based on indices that are not affected by the calibration towards the observed climate used for some of the methods. We focus on precipitation (over continental Spain) and consider the output of eight Regional Climate Models (RCMs) from the EURO-CORDEX initiative at 0.44° resolution and five Statistical Downscaling Methods (SDMs) —analog resampling, weather typing and generalized linear models— trained using the Spain044 observational gridded dataset on exactly the same RCM grid. The performance of these models is inter-compared in terms of several standard indices —mean precipitation, 90th percentile on wet days, maximum precipitation amount and maximum number of consecutive dry days— taking into account the parameters involved in the SDM training phase. It is shown, that not only the directly affected indices should be carefully analyzed, but also those indirectly influenced (e.g. percentile-based indices for precipitation) which are more difficult to identify. We also analyze how simple transformations (e.g. linear scaling) could be applied to the outputs of the uncalibrated methods in order to put SDMs and RCMs on equal footing, and thus perform a fairer comparison. 相似文献
76.
77.
78.
Colm Ó Cofaigh S. Louise Callard David H. Roberts Richard C. Chiverrell C. K. Ballantyne David J. A. Evans Margot Saher Katrien J. J. Van Landeghem Rachel Smedley Sara Benetti Matthew Burke Chris D. Clark Geoff A. T. Duller Derek Fabel Stephen J. Livingstone Stephen Mccarron Alicia Medialdea Steven G. Moreton Fabio Sacchetti 《第四纪科学杂志》2021,36(5):805-832
Understanding the pace and drivers of marine-based ice-sheet retreat relies upon the integration of numerical ice-sheet models with observations from contemporary polar ice sheets and well-constrained palaeo-glaciological reconstructions. This paper provides a reconstruction of the retreat of the last British–Irish Ice Sheet (BIIS) from the Atlantic shelf west of Ireland during and following the Last Glacial Maximum (LGM). It uses marine-geophysical data and sediment cores dated by radiocarbon, combined with terrestrial cosmogenic nuclide and optically stimulated luminescence dating of onshore ice-marginal landforms, to reconstruct the timing and rate of ice-sheet retreat from the continental shelf and across the adjoining coastline of Ireland, thus including the switch from a marine- to a terrestrially-based ice-sheet margin. Seafloor bathymetric data in the form of moraines and grounding-zone wedges on the continental shelf record an extensive ice sheet west of Ireland during the LGM which advanced to the outer shelf. This interpretation is supported by the presence of dated subglacial tills and overridden glacimarine sediments from across the Porcupine Bank, a westwards extension of the Irish continental shelf. The ice sheet was grounded on the outer shelf at ~26.8 ka cal bp with initial retreat underway by 25.9 ka cal bp. Retreat was not a continuous process but was punctuated by marginal oscillations until ~24.3 ka cal bp. The ice sheet thereafter retreated to the mid-shelf where it formed a large grounding-zone complex at ~23.7 ka cal bp. This retreat occurred in a glacimarine environment. The Aran Islands on the inner continental shelf were ice-free by ~19.5 ka bp and the ice sheet had become largely terrestrially based by 17.3 ka bp. This suggests that the Aran Islands acted to stabilize and slow overall ice-sheet retreat once the BIIS margin had reached the inner shelf. Our results constrain the timing of initial retreat of the BIIS from the outer shelf west of Ireland to the period of minimum global eustatic sea level. Initial retreat was driven, at least in part, by glacio-isostatically induced, high relative sea level. Net rates of ice-sheet retreat across the shelf were slow (62–19 m a−1) and reduced (8 m a−1) as the ice sheet vacated the inner shelf and moved onshore. A picture therefore emerges of an extensive BIIS on the Atlantic shelf west of Ireland, in which early, oscillatory retreat was followed by slow episodic retreat which decelerated further as the ice margin became terrestrially based. More broadly, this demonstrates the importance of localized controls, in particular bed topography, on modulating the retreat of marine-based sectors of ice sheets. 相似文献
79.
Laura T. Iraci Brent G. Riffel Carly B. Robinson Rebecca R. Michelsen Rachel M. Stephenson 《Journal of Atmospheric Chemistry》2007,58(3):253-266
The aqueous phase acid-catalyzed reaction of methanol (CH3OH) with nitric acid (HNO3) to yield methyl nitrate (CH3ONO2) under atmospheric conditions has been investigated using gas-phase infrared spectroscopy. Reactions were conducted in aqueous
sulfuric acid solutions (50.5–63.6 wt.%) with [CH3OH] = 0.00005–0.005 M and [HNO3] = 0.02–0.21 M, at 278.2–328.6 K. Methyl nitrate production rates increased linearly with CH3OH and HNO3 concentrations and exponentially with sulfuric acid weight percent within the regime studied. Rates increased linearly with
nitronium ion concentration, indicating that the reaction involves as the nitrating agent under these conditions. At 298 K, the rate of methyl nitrate production can be calculated from k
obs
[CH3OH][HNO3], where k
obs
= 2.337 × 10−13(exp(0.3198*wt.% H2SO4)) when the solubility of CH3ONO2 in acidic solution is approximated by H* for pure water. The temperature dependence of the rate coefficient is related to solution composition, with activation energies
of 59 and 49 kJ/mol at 51.1 and 63.6 wt.% H2SO4, respectively, when k is calculated from rate. The temperature dependence has also been parameterized for application to the atmosphere, but the small quantities of present in aerosol particles will result in methyl nitrate production rates too small to be of significance under most atmospheric
conditions.
An erratum to this article can be found at 相似文献
80.