Amanambu, A. C., Obarein, O. A., Mossa, J., Li, L., Ayeni, S. S., Balogun, O., et al. (2020). Groundwater system and climate change: Present status and future considerations. Journal of Hydrology, 589.
Abstract: Climate change will impact every aspect of biophysical systems and society. However, unlike other components of the climate system, the impact of climate change on the groundwater system has only recently received attention. This focus is due to the realization that groundwater is a vital freshwater resource crucial to global food and water security, and is essential in sustaining ecosystems and human adaptation to climate variability and change. This paper synthesizes findings on the direct and indirect impacts of climate change on the entire groundwater system and each component. Also, we appraise the use of coupled groundwater-climate and land surface models in groundwater hydrology as a means of improving existing knowledge of climate change-groundwater interaction, finding that most models anticipate decreases in groundwater recharge, storage and levels, particularly in the arid/semi-arid tropics. Reducing uncertainties in future climate projections and improving our understanding of the physical processes underlying models to improve their simulation of real-world conditions remain a priority for climate and Earth scientists. Despite the enormous progress made, there are still few and inadequate local and regional aquifer studies, especially in less developed regions. The paper proposes two key considerations. First, physical basis: the need for a deeper grasp of complex physical processes and feedback mechanism with the use of more sophisticated models. Second, the need to understand the socioeconomic dimensions of climate-groundwater interaction through multidisciplinary synergy, leading to the development of better groundwater-climate change adaptation strategies and modeling
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Arruda, W., Zharkov, V., Deremble, B., Nof, D., & Chassignet, E. (2014). A New Model of Current Retroflection Applied to the Westward Protrusion of the Agulhas Current. J. Phys. Oceanogr., 44(12), 3118–3138.
Abstract: The dynamics of current retroflection and rings shedding are not yet fully understood. In this paper, the authors develop an analytical model of the Agulhas Current retroflection dynamics using three simple laws: conservation of volume, momentum balance, and Bernoulli’s principle. This study shows that, for a retroflecting current with a small Rossby number, this theoretical model is in good agreement with numerical simulations of a reduced-gravity isopycnal model. Otherwise, the retroflection position becomes unstable and quickly propagates upstream, leaving a chain of eddies in its path. On the basis of these findings, the authors hypothesize that the westward protrusion of the Agulhas retroflection and the local “zonalization” of the Agulhas Current after it passes the Agulhas Bank are stable only for small Rossby numbers. Otherwise, the retroflection shifts toward the eastern slope of the Agulhas Bank, where its position stabilizes due to the slanted configuration of the slope. This study shows that this scenario is in good agreement with several high-resolution numerical models.
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Balderacchi, M., Perego, A., Lazzari, G., Muñoz-Carpena, R., Acutis, M., Laini, A., et al. (2016). Avoiding social traps in the ecosystem stewardship: The Italian Fontanile lowland spring. Science of The Total Environment, 539, 526–535.
Abstract: Fontanile is a Po Valley (Italy) quasi-natural lowland spring built in the middle age. This paper identifies options for the conservation of the Fontanile water dependent ecosystem, using scenarios and simulations, and exploring different policy options. Three modeling analysis have been performed: the first was carried out for estimating groundwater contamination and recharge from above, the second for evaluating the function of vegetative filter strip on the surface water quality and the last one for testing pesticide drift reduction due to the vegetative filter strip. Uncertainty characterization included climate change projections. Despite the nitrate concentration in water could favorite the eutrophication phenomena, this not occurs because of the low phosphate concentration in water and of the presence of arboreal shade. Therefore, the protection strategies must focus on sustaining desirable water quantity conditions. Water saving and conservation technologies that improve the agricultural productivity but reduce the Fontanile water flow and large buffer strips that have a limited efficacy due to the Fontanile hydrological settings can be judged as ecological traps. Inefficient irrigation systems, good agricultural practices, integrated pest management and arboreal filter strip can preserve the quality of those ecosystems. (C) 2015 Elsevier B.V. All rights reserved.
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Boote, K. J., Jones, J. W., White, J. W., Asseng, S., & Lizaso, J. I. (2013). Putting mechanisms into crop production models: Putting mechanisms into crop production models. Plant Cell Environ, 36(9), 1658–1672.
Abstract: Crop growth models dynamically simulate processes of C, N and water balance on daily or hourly time-steps to predict crop growth and development and at season-end, final yield. Their ability to integrate effects of genetics, environment and crop management have led to applications ranging from understanding gene function to predicting potential impacts of climate change. The history of crop models is reviewed briefly, and their level of mechanistic detail for assimilation and respiration, ranging from hourly leaf-to-canopy assimilation to daily radiation-use efficiency is discussed. Crop models have improved steadily over the past 30–40 years, but much work remains. Improvements are needed for the prediction of transpiration response to elevated CO2 and high temperature effects on phenology and reproductive fertility, and simulation of root growth and nutrient uptake under stressful edaphic conditions. Mechanistic improvements are needed to better connect crop growth to genetics and to soil fertility, soil waterlogging and pest damage. Because crop models integrate multiple processes and consider impacts of environment and management, they have excellent potential for linking research from genomics and allied disciplines to crop responses at the field scale, thus providing a valuable tool for deciphering genotype by environment by management effects.
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Boote, K. J., Prasad, V., Allen Jr., L. H., Singh, P., & Jones, J. W. (2018). Modeling sensitivity of grain yield to elevated temperature in the DSSAT crop models for peanut, soybean, dry bean, chickpea, sorghum, and millet. European Journal of Agronomy, 100, 99–109.
Abstract: Crop models are increasingly being used as tools to simulate climate change effects or effects of virtual heat-tolerant cultivars; therefore it is important that upper temperature thresholds for seed-set, seed growth, phenology, and other processes affecting yield be developed and parameterized from elevated temperature experiments whether field or controlled-environment chambers. In this paper, we describe the status of crop models for dry bean (Phaseolus vulgaris L.), peanut (Arachis hypogaea L.), soybean (Glycine max L.), chickpea (Cicer arietinum L.), sorghum (Sorghum bicolor (L.) Moench), and millet (Pennisetum glaucum L. (R.) Br) in the Decision Support System for Agrotechnology Transfer (DSSAT) for response to elevated temperature by comparison to observed data, and we review where changes have been made or where needed changes remain. Temperature functions for phenology and photosynthesis of the CROPGRO-Dry Bean model were modified in 2006 for DSSAT V4.5, based on observed growth and yield of Montcalm cultivar grown in sunlit, controlled-environment chambers. Temperature functions for soybean and peanut models were evaluated against growth and yield data in the same chambers and found to adequately predict growth and yield, thus have not been modified since 1998 release of V3.5. The temperature functions for the chickpea model were substantially modified for many processes, and are updated for V4.6. The millet model was re-coded and modified for its temperature sensitivities, with a new function to allow the 8–10 day period prior to anthesis to affect grain set, as parameterized from field observations. For the sorghum model, the temperature effect on grain growth rate was modified to improve yield and grain size response to elevated temperature by comparison to data in controlled-environment chambers. For reliable assessments of climate change impact, it is critically important to gather additional temperature response data and to update parameterization and code of all crop models including DSSAT.
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Conlon, K., Kintziger, K., Jagger, M., Stefanova, L., Uejio, C., & Konrad, C. (2016). Working with Climate Projections to Estimate Disease Burden: Perspectives from Public Health. Int. J. Environ. Res. Public Health, 13(8), 804.
Abstract: There is interest among agencies and public health practitioners in the United States (USA) to estimate the future burden of climate-related health outcomes. Calculating disease burden projections can be especially daunting, given the complexities of climate modeling and the multiple pathways by which climate influences public health. Interdisciplinary coordination between public health practitioners and climate scientists is necessary for scientifically derived estimates. We describe a unique partnership of state and regional climate scientists and public health practitioners assembled by the Florida Building Resilience Against Climate Effects (BRACE) program. We provide a background on climate modeling and projections that has been developed specifically for public health practitioners, describe methodologies for combining climate and health data to project disease burden, and demonstrate three examples of this process used in Florida.
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Drury, C., Paris, C. B., Kourafalou, V. H., & Lirman, D. (2018). Dispersal capacity and genetic relatedness in Acropora cervicornis on the Florida Reef Tract. Coral Reefs, 37(2), 585–596.
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Dzotsi, K. A., Basso, B., & Jones, J. W. (2013). Development, uncertainty and sensitivity analysis of the simple SALUS crop model in DSSAT. Ecological Modelling, 260, 62–76.
Abstract: Simplified approaches to modeling crop growth and development have recently received more attention due to increased interest in applying crop models at large scales for various agricultural assessments. In this study, we integrated the simple version of SALUS (System Approach to Land Use Sustainability) crop model in the widely-used Decision Support System for Agrotechnology Transfer (DSSAT) to enhance the capability of DSSAT to simulate additional crops without requiring detailed parameterization. An uncertainty and sensitivity analysis was conducted using the integrated DSSAT-simple SALUS model to assess the variability in model outputs and crop parameter ranking in response to uncertainties associated with crop parameters required by the model. The influence of year, production level, and location on the effect of crop parameter uncertainty was also investigated.
Parameter uncertainty resulted in a high variability in modeled outputs. Simulated potential aboveground biomass ranged from 1.2 t ha−1 to 38 t ha−1 for maize and 4 t ha−1 to 26.5 t ha−1 for peanut and cotton, all locations and years considered. The degree of variability was dependent upon the production level, the location, the year, and the crop. Ranking of crop parameters was not significantly affected by the year of study but was strongly related to the production level, location, and crop. The model was not sensitive to parameters related to prediction of the timing of germination and emergence. The most influential parameters were related to leaf area index growth, crop duration, and thermal time accumulation. Findings from this study contributed to understanding the effects of crop parameter uncertainty on the model's outputs under different environmental conditions.
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Erb, M. P., Broccoli, A. J., Graham, N. T., Clement, A. C., Wittenberg, A. T., & Vecchi, G. A. (2015). Response of the Equatorial Pacific Seasonal Cycle to Orbital Forcing. J. Climate, 28(23), 9258–9276.
Abstract: The response of the equatorial Pacific Ocean's seasonal cycle to orbital forcing is explored using idealized simulations with a coupled atmosphere-ocean GCM in which eccentricity, obliquity, and the longitude of perihelion are altered while other boundary conditions are maintained at preindustrial levels. The importance of ocean dynamics in the climate response is investigated using additional simulations with a slab ocean version of the model. Precession is found to substantially influence the equatorial Pacific seasonal cycle through both thermodynamic and dynamic mechanisms, while changes in obliquity have only a small effect. In the precession experiments, western equatorial Pacific SSTs respond in a direct thermodynamic manner to changes in insolation, while the eastern equatorial Pacific is first affected by the propagation of thermocline temperature anomalies from the west. These thermocline signals result from zonal wind anomalies associated with changes in the strength of subtropical anticyclones and shifts in the regions of convection in the western equatorial Pacific. The redistribution of heat from these thermocline signals, aided by the direct thermodynamic effect of insolation anomalies, results in large changes to the strength and timing of the eastern equatorial Pacific seasonal cycle. A comparison of 10 CMIP5 mid-Holocene experiments, in which the primary forcing is due to precession, shows that this response is relatively robust across models. Because equatorial Pacific SST anomalies have local climate impacts as well as nonlocal impacts through teleconnections, these results may be important to understanding paleoclimate variations both inside and outside of the tropical Pacific.
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Escobar, L. E., Ryan, S. J., Stewart-Ibarra, A. M., Finkelstein, J. L., King, C. A., Qiao, H., et al. (2015). A global map of suitability for coastal Vibrio cholerae under current and future climate conditions. Acta Tropica, 149, 202–211.
Abstract: Vibrio cholerae is a globally distributed water-borne pathogen that causes severe diarrheal disease and mortality, with current outbreaks as part of the seventh pandemic. Further understanding of the role of environmental factors in potential pathogen distribution and corresponding V. cholerae disease transmission over time and space is urgently needed to target surveillance of cholera and other climate and water-sensitive diseases. We used an ecological niche model (ENM) to identify environmental variables associated with V. cholerae presence in marine environments, to project a global model of V. cholerae distribution in ocean waters under current and future climate scenarios. We generated an ENM using published reports of V. cholerae in seawater and freely available remotely sensed imagery. Models indicated that factors associated with V. cholerae presence included chlorophyll-a, pH, and sea surface temperature (SST), with chlorophyll-a demonstrating the greatest explanatory power from variables selected for model calibration. We identified specific geographic areas for potential V. cholerae distribution. Coastal Bangladesh, where cholera is endemic, was found to be environmentally similar to coastal areas in Latin America. In a conservative climate change scenario, we observed a predicted increase in areas with environmental conditions suitable for V. cholerae. Findings highlight the potential for vulnerability maps to inform cholera surveillance, early warning systems, and disease prevention and control.
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Farneti, R., Downes, S. M., Griffies, S. M., Marsland, S. J., Behrens, E., Bentsen, M., et al. (2015). An assessment of Antarctic Circumpolar Current and Southern Ocean meridional overturning circulation during 1958-2007 in a suite of interannual CORE-II simulations. Ocean Modelling, 93, 84–120.
Abstract: In the framework of the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II), we present an analysis of the representation of the Antarctic Circumpolar Current (ACC) and Southern Ocean meridional overturning circulation (MOC) in a suite of seventeen global ocean–sea ice models. We focus on the mean, variability and trends of both the ACC and MOC over the 1958–2007 period, and discuss their relationship with the surface forcing. We aim to quantify the degree of eddy saturation and eddy compensation in the models participating in CORE-II, and compare our results with available observations, previous fine-resolution numerical studies and theoretical constraints. Most models show weak ACC transport sensitivity to changes in forcing during the past five decades, and they can be considered to be in an eddy saturated regime. Larger contrasts arise when considering MOC trends, with a majority of models exhibiting significant strengthening of the MOC during the late 20th and early 21st century. Only a few models show a relatively small sensitivity to forcing changes, responding with an intensified eddy-induced circulation that provides some degree of eddy compensation, while still showing considerable decadal trends. Both ACC and MOC interannual variabilities are largely controlled by the Southern Annular Mode (SAM). Based on these results, models are clustered into two groups. Models with constant or two-dimensional (horizontal) specification of the eddy-induced advection coefficient κ show larger ocean interior decadal trends, larger ACC transport decadal trends and no eddy compensation in the MOC. Eddy-permitting models or models with a three-dimensional time varying κ show smaller changes in isopycnal slopes and associated ACC trends, and partial eddy compensation. As previously argued, a constant in time or space κ is responsible for a poor representation of mesoscale eddy effects and cannot properly simulate the sensitivity of the ACC and MOC to changing surface forcing. Evidence is given for a larger sensitivity of the MOC as compared to the ACC transport, even when approaching eddy saturation. Future process studies designed for disentangling the role of momentum and buoyancy forcing in driving the ACC and MOC are proposed.
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Feng, W., Liang, J., Hale, L. E., Jung, C. G., Chen, J., Zhou, J., et al. (2017). Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming. Glob Change Biol, 23(11), 4765–4776.
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Fleisher, D. H., Condori, B., Quiroz, R., Alva, A., Asseng, S., Barreda, C., et al. (2017). A potato model intercomparison across varying climates and productivity levels. Glob Change Biol, 23(3), 1258–1281.
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Flower, H., Rains, M., Carl Fitz, H., Orem, W., Newman, S., Osborne, T. Z., et al. (2019). Shifting Ground: Landscape-Scale Modeling of Biogeochemical Processes under Climate Change in the Florida Everglades. Environ Manage, 64(4), 416–435.
Abstract: Scenarios modeling can be a useful tool to plan for climate change. In this study, we help Everglades restoration planning to bolster climate change resiliency by simulating plausible ecosystem responses to three climate change scenarios: a Baseline scenario of 2010 climate, and two scenarios that both included 1.5 degrees C warming and 7% increase in evapotranspiration, and differed only by rainfall: either increase or decrease by 10%. In conjunction with output from a water-use management model, we used these scenarios to drive the Everglades Landscape Model to simulate changes in a suite of parameters that include both hydrologic drivers and changes to soil pattern and process. In this paper we focus on the freshwater wetlands; sea level rise is specifically addressed in prior work. The decreased rainfall scenario produced marked changes across the system in comparison to the Baseline scenario. Most notably, muck fire risk was elevated for 49% of the period of simulation in one of the three indicator regions. Surface water flow velocity slowed drastically across most of the system, which may impair soil processes related to maintaining landscape patterning. Due to lower flow volumes, this scenario produced decreases in parameters related to flow-loading, such as phosphorus accumulation in the soil, and methylmercury production risk. The increased rainfall scenario was hydrologically similar to the Baseline scenario due to existing water management rules. A key change was phosphorus accumulation in the soil, an effect of flow-loading due to higher inflow from water control structures in this scenario.
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Fujisaki, I., Mazzotti, F. J., Watling, J., Krysko, K. L., & Escribano, Y. (2015). Geographic risk assessment reveals spatial variation in invasion potential of exotic reptiles in an invasive species hotspot. Herpetological Conservation And Biology, 10(2), 621–632.
Abstract: Invasive species are among the primary threats to biodiversity and risk assessment is one problem-solving approach that can prioritize and guide efforts to reduce the negative consequences of invasion. We used a niche-modeling framework to conduct a geographic risk assessment of exotic reptiles in the state of Florida, USA, a region with the highest density of invasive herpetofaunal species in the world. We then compared model predictions with observed records of exotic species across the state. We compiled georeferenced native occurrence locations of exotic reptile species found in Florida and used maximum entropy modeling with global-scale environmental data as inputs. The predicted number of species with suitable habitat was variable across the state and by management units, and it generally decreased with increasing latitude. These predictions were supported by observed richness of exotic species in the lower latitude and the known problem of exotic reptiles in southern Florida. Overall, minimum temperature made the greatest contributions in model predictions, but the level of each variable's contributions varied by species. The overall omission rate with the test data was small, but it was largely variable by species when we used the occurrence locations in Florida. Our use of a niche-modeling for geographic risk assessment of an assemblage of exotic reptile species can be applied cost-effectively to identify areas most susceptible to invasion. The observed large geographic variability in number of potential exotic reptiles suggests that local-scale environmental data can be employed to enhance management applications.
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Gbegbelegbe, S., Cammarano, D., Asseng, S., Robertson, R., Chung, U., Adam, M., et al. (2017). Baseline simulation for global wheat production with CIMMYT mega-environment specific cultivars. Field Crops Research, 202, 122–135.
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Glazer, R. H., & Misra, V. (2018). Ice versus liquid water saturation in simulations of the Indian summer monsoon. Climate Dynamics, .
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Goly, A., Teegavarapu, R. S. V., & Mondal, A. (2014). Development and Evaluation of Statistical Downscaling Models for Monthly Precipitation. Earth Interact., 18(18), 1–28.
Abstract: Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001–10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.
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Gonzalez-Benecke, C. A., Teskey, R. O., Martin, T. A., Jokela, E. J., Fox, T. R., Kane, M. B., et al. (2016). Regional validation and improved parameterization of the 3-PG model for Pinus taeda stands. Forest Ecology and Management, 361, 237–256.
Abstract: The forest simulation model, 3-PG, has the capability to estimate the effects of climate, site and management practices on many stand attributes using easily available data. The model, once calibrated, has been widely applied as a useful tool for estimating growth of forest species in many countries. Currently, there is an increasing interest in estimating biomass and assessing the potential impact of climate change on loblolly pine (Pinus taeda L.), the most important commercial tree species in the southeastern U.S. This paper reports a new set of 3-PG parameter estimates for loblolly pine, and describe new methodologies to determine important estimates. Using data from the literature and long-term productivity studies, we parameterized 3-PG for loblolly pine stands, and developed new functions for estimating NPP allocation dynamics, biomass pools at variable starting ages, canopy cover dynamics, effects of frost on production, density-independent and density-dependent tree mortality and the fertility rating. The model was tested against data from replicated experimental measurement plots covering a wide range of stand characteristics, distributed across the southeastern U.S. and also beyond the natural range of the species, using stands in Uruguay, South America. We used the largest validation dataset for 3-PG, and the most geographically extensive within and beyond a species' native range. Comparison of modeled to measured data showed robust agreement across the natural range in the U.S., as well as in South America, where the species is grown as an exotic. Across all tested sites, estimations of survival, basal area, height, quadratic mean diameter, bole volume and above-ground biomass agreed well with measured values, with R-2 values ranging between 0.71 for bole volume, and 0.95 for survival. The levels of bias were small and generally less than 13%. LAI estimations performed well, predicting monthly values within the range of observed LAI. The results provided strong evidence that 3-PG could be applied over a wide geographical range using one set of parameters for loblolly pine. The model can also be applied to estimate the impact of climate change on stands growing across a wide range of ages and stand characteristics.
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Goodwin, W. M. (2015). Global Climate Modeling as Applied Science. J Gen Philos Sci, 46(2), 339–350.
Abstract: In this paper I argue that the appropriate analogy for "understanding what makes simulation results reliable" in global climate modeling is not with scientific experimentation or measurement, but-at least in the case of the use of global climate models for policy development-with the applications of science in applied design problems. The prospects for using this analogy to argue for the quantitative reliability of GCMs are assessed and compared with other potential strategies.
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