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Meeus, Sofie. "Herbaria as Functional Trait Databases." Biodiversity Information Science and Standards 2 (July 4, 2018): e25766. http://dx.doi.org/10.3897/biss.2.25766.
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Although tropical rainforests play an important role in regulating the world’s climate, they are at the same time particularly vulnerable to changes in the climate. Intense and prolonged droughts, for instance, can lead to biomass loss which will further accelerate these changes. Especially for tree species it becomes problematic, due to their long lifespan, to quickly adapt to or evade unfavorable climatic conditions affecting the composition of the forest community as a whole and consequently the ecosystem services that the rainforests provide. A long-term drying trend currently threatens tropical regions worldwide but is especially strong in the central African rainforest, the second-largest rainforest on Earth. The impact of this decrease in precipitation on the vegetation is, however, still largely unknown due to the limited amount of historical eco-climatological data. Fortunately, these kind of data do exist albeit in a poorly accessible (analog) format in herbarium collections. To investigate if trees show changes in morphology and/or physiology invoked by climatic changes in the last century, the COBECORE team (Congo Basin Eco-Climatological Data Recovery and Valorization”) is exploring the usability of herbaria as potential sources of plant leaf functional trait data using established protocols adjusted to dried leaf material. Photosynthesis as well as gas exchange and transpiration are processes regulated by a plant’s leaves, and depend on the specific leaf area (SLA) and the number and size of the stomata. The less area the latter structures occupy on the leaf the less the plant will suffer from water losses which increases the resistance to drought of plants. We explored the recently digitized African Herbarium of the Botanic Garden Meise which contains over 1.2 million African specimens with a very good coverage of the Congo Basin, dating back to 1880. Currently, we obtained average SLA measurements for 833 herbarium specimens from 59 of the most common tree species of central African rainforests. Pictures for stomata counts and size measurements were taken from over one hundred specimens mainly focused on three Prioria species, giant tree species (up to 60 metres) currently suffering from overexploitation. The data generated in this project will be valuable to understand some lower-level vegetation responses such as plant water use needed to model and predict long-term climate change impacts on vegetation.
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Mafredas, Thomas, and George Malaperdas. "Archaeological Databases and GIS: Working with Databases." European Journal of Information Technologies and Computer Science 1, no. 3 (June 21, 2021): 1–6. http://dx.doi.org/10.24018/compute.2021.1.3.20.
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Digital databases are considered nowadays, necessary for the organization of a recent archeological project. Typically, one of the main issues at the stage of archaeological surface research preparation is the method of recording all the archaeological information that will emerge, which is directly dependent on two factors, the difference of each area in terms of its geomorphology, including the climate and general environmental conditions, and the different approach to the objectives to be achieved by the leading archaeologists. As a consequence of all of this, there is no such thing as a uniquely generated form that can act as a guideline. This paper provides some basic database knowledge as well as a case study with a database example.
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Kurian, Rosaliya, Kishor Sitaram Kulkarni, Prasanna Venkatesan Ramani, Chandan Swaroop Meena, Ashok Kumar, and Raffaello Cozzolino. "Estimation of Carbon Footprint of Residential Building in Warm Humid Climate of India through BIM." Energies 14, no. 14 (July 14, 2021): 4237. http://dx.doi.org/10.3390/en14144237.
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In recent years Asian Nations showed concern over the Life Cycle Assessment (LCA) of their civil infrastructure. This study presents a contextual investigation of a residential apartment complex in the territory of the southern part of India. The LCA is performed through Building Information Modelling (BIM) software embedded with Environmental Product Declarations (EPDs) of materials utilized in construction, transportation of materials and operational energy use throughout the building lifecycle. The results of the study illustrate that cement is the material that most contributes to carbon emissions among the other materials looked at in this study. The operational stage contributed the highest amount of carbon emissions. This study emphasizes variation in the LCA results based on the selection of a combination of definite software-database combinations and manual-database computations used. For this, three LCA databases were adopted (GaBi database and ecoinvent databases through One Click LCA software), and the ICE database was used for manual calculations. The ICE database showed realistic value comparing the GaBi and ecoinvent databases. The findings of this study are valuable for the policymakers and practitioners to accomplish optimization of Greenhouse Gas (GHG) emissions over the building life cycle.
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Hickcox, C. Woodbridge. "Using your Computer: Climate Databases for the Macintosh." Weatherwise 45, no. 6 (January 1993): 32–36. http://dx.doi.org/10.1080/00431672.1993.9931090.
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Wood, J. L., S. Harrison, L. Reinhardt, and F. E. Taylor. "Landslide databases for climate change detection and attribution." Geomorphology 355 (April 2020): 107061. http://dx.doi.org/10.1016/j.geomorph.2020.107061.
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Mínguez, R., A. Tomás, F. J. Méndez, and R. Medina. "Mixed extreme wave climate model for reanalysis databases." Stochastic Environmental Research and Risk Assessment 27, no. 4 (June 27, 2012): 757–68. http://dx.doi.org/10.1007/s00477-012-0604-y.
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Ziedan, Abubakr, Mbakisya Onyango, Weidong Wu, Sampson Udeh, Joseph Owino, and Ignatius Fomunung. "Comparative Analysis between Modern-Era Retrospective Analysis for Research and Applications and Updated Mechanistic-Empirical Pavement Design Guide Climate Database in the State of Tennessee." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 6 (May 16, 2019): 279–87. http://dx.doi.org/10.1177/0361198119844242.
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The Mechanistic-Empirical Pavement Design Guide addresses climate effects on pavement design in a comprehensive way, which allows for investigating the effect of climate on pavement performance. However, it requires detailed climate inputs, which might not be readily available for most of the state departments of transportation. The AASHTOWare Pavement Mechanistic-Empirical Design (PMED) version 2.3 (v2.3) climate database encompasses 12 weather stations in the state of Tennessee, which does not satisfactorily represent all climatic regions in the state. The terrain in Tennessee varies from flat in the west to mountainous in the east. To evaluate the effectiveness of the updated AASHTOWare PMED v2.3 climate data input, this study analyses the performance of selected pavements in the state of Tennessee using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and the AASHTOWare PMED v2.3 databases as sources of PMED climate data inputs. A comparative analysis of the two climate data sources is conducted using eight long-term pavement performance (LTPP) sites in the state of Tennessee. The study revealed that MERRA as a climate data source for the state of Tennessee offers better geographic coverage, and therefore provides more precise distress predictions than the AASHTOWare PMED v2.3 climate database.
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Cornick, S. M., P. C. Thomas, and D. K. Prasad. "Predicting the Effects of Changes in Thermal Envelope Characteristics on Energy Consumption: Application and Verification of a Simple Model for Australian and Canadian Climates." Energy & Environment 7, no. 1 (February 1996): 1–28. http://dx.doi.org/10.1177/0958305x9600700101.
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A simple energy model was used for determining thermal envelope characteristics and building envelope trade-off procedures for the new Canadian and Australian energy efficiency codes for new buildings. The model relates heating and cooling system loads to envelope thermal characteristics. It was developed from thousands of DOE2.1E simulation runs. Two separate databases, one containing 25 Canadian locations and the other containing 9 Australian locations were created. The heating and cooling models were developed from these databases. The model is shown to give consistent results although there are significant differences in climate, construction of the building envelope, building operational schedules and HVAC system configurations. This paper briefly describes the DOE2.1E models used for the study in each country, highlighting similarities and differences. The consistency of results predicted by the model is discussed for typical climatic locations in both countries. The methods for predicting heating and cooling system loads are shown to produce good results over a wide range of climates and for different system configurations. The paper also discusses the development of climate correlations to extend the range of the models to include locations not in the original databases.
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Labonnote, Nathalie, Åshild Lappegard Hauge, and Edvard Sivertsen. "A climate services perspective on Norwegian stormwater-related databases." Climate Services 13 (January 2019): 33–41. http://dx.doi.org/10.1016/j.cliser.2019.01.006.
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Sidău, Mugurel Raul, Adina-Eliza Croitoru, and Diana-Elena Alexandru. "Comparative Analysis between Daily Extreme Temperature and Precipitation Values Derived from Observations and Gridded Datasets in North-Western Romania." Atmosphere 12, no. 3 (March 9, 2021): 361. http://dx.doi.org/10.3390/atmos12030361.
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Climate gridded datasets are highly needed and useful in conducting data analysis for research and practical purposes. They provide long-term information on various climatic variables for large areas worldwide, making them suitable for use at any spatial level. It is essential to assess the accuracy of gridded data by comparing the data to measured values, especially when they are used as input parameters for hydro-climatic models. From the multitude of databases available for North-western Romania, we selected three, particularly the European Climate Assessment and Dataset (E-OBS), the Romanian Climatic Dataset (ROCADA), and the Climate of the Carpathian Region (CARPATCLIM). In this paper, we analyse the extreme precipitation and temperature data derived from the above-mentioned datasets over a common 50-year period (1961–2010) and compare the data with raw values to estimate the degree of uncertainty for each set of data. The observation data, recorded at two meteorological stations located in a complex topography region, were compared to the output of the gridded datasets, by using descriptive statistics for the mean and extreme annual and seasonal temperature and precipitation data, and trend analyses. The main findings are: the high suitability of the ROCADA gridded database for climate trend analysis and of the E-OBS gridded database for extreme temperature and precipitation analysis.
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Sitko, R., J. Vido, J. Škvarenina, V. Pichler, L. Scheer, J. Škvareninová, and P. Nalevanková. "How different sources of climate databases influence assessment of growth response in dendroclimatic analyses – case study from Lapland." Earth System Dynamics Discussions 6, no. 2 (August 26, 2015): 1535–55. http://dx.doi.org/10.5194/esdd-6-1535-2015.
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Abstract. The paper deals with the comparison of the time series from different climate databases. We compared the measured data with the modelled data of monthly and seasonal temperature means and precipitation totals. Reliable and as long as possible time series of such data represent the basic starting point of dendroclimatic analyses. We evaluated the differences in the growth response of spruce derived using different databases of the stated climatic characteristics. The stem cores used to derive the cross-correlation function were taken from Hårås locality situated in the boreal zone of the Swedish part of Lapland. We compared the measured records from the nearest meteorological stations situated 18 and 40 km away from the locality with the interpolated values from CRU TS 3.21 climate database and with the reconstructed 502-year-long database. The spatial resolution of the modelled databases was 0.5° × 0.5° of latitude and longitude. We found a systematic error of different magnitudes in the modelled values, and we also quantified a random error and the overall accuracy of the data. The temperature model underestimated the data in comparison with the measured values, while the precipitation model overestimated the data. We also found that the radial increments of spruce correlated more strongly with the temperature than with the precipitation. Hence, in the conditions of the boreal zone, temperature is a more important factor affecting tree-ring formation. We found significantly higher correlations between the radial increment and the modelled precipitation data than with the data measured at the precipitation station situated 18 km from the locality of interest.
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Huggel, C., A. Raissig, M. Rohrer, G. Romero, A. Diaz, and N. Salzmann. "How useful and reliable are disaster databases in the context of climate and global change? A comparative case study analysis in Peru." Natural Hazards and Earth System Sciences 15, no. 3 (March 9, 2015): 475–85. http://dx.doi.org/10.5194/nhess-15-475-2015.
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Abstract. Damage caused by weather- and climate-related disasters have increased over the past decades, and growing exposure and wealth have been identified as main drivers of this increase. Disaster databases are a primary tool for the analysis of disaster characteristics and trends at global or national scales, and they support disaster risk reduction and climate change adaptation. However, the quality, consistency and completeness of different disaster databases are highly variable. Even though such variation critically influences the outcome of any study, comparative analyses of different databases are still rare to date. Furthermore, there is an unequal geographic distribution of current disaster trend studies, with developing countries being underrepresented. Here, we analyze three different disaster databases in the developing-country context of Peru: a global database (Emergency Events Database: EM-DAT), a multinational Latin American database (DesInventar) and a national database (Peruvian National Information System for the Prevention of Disasters: SINPAD). The analysis is performed across three dimensions: (1) spatial scales, from local to regional (provincial) and national scale; (2) timescales, from single events to decadal trends; and (3) disaster categories and metrics, including the number of single disaster event occurrence, or people killed and affected. Results show limited changes in disaster occurrence in the Cusco and ApurÍmac regions in southern Peru over the past four decades but strong positive trends in people affected at the national scale. We furthermore found large variations of the disaster metrics studied over different spatial and temporal scales, depending on the disaster database analyzed. We conclude and recommend that the type, method and source of documentation should be carefully evaluated for any analysis of disaster databases; reporting criteria should be improved and documentation efforts strengthened.
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Sitko, Roman, Jaroslav Vido, Jaroslav Škvarenina, Viliam Pichler, Ĺubomír Scheer, Jana Škvareninová, and Paulína Nalevanková. "Effect of various climate databases on the results of dendroclimatic analysis." Earth System Dynamics 7, no. 2 (April 26, 2016): 385–95. http://dx.doi.org/10.5194/esd-7-385-2016.
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Abstract. The paper deals with the comparison of the time series drawn from different climate databases. We compared the observed data with the modeled data of monthly and seasonal temperature means and precipitation totals. Reliable and longest available time series of such data represent the basic starting point of dendroclimatic analyses. We evaluated the differences in the growth response of spruce derived using different databases of the considered climatic variables. The stem cores used to derive the cross-correlation function were taken from Hårås locality situated in the boreal zone of the Swedish part of Lapland. We compared the observed records from the nearest weather stations situated 18, 40, 70 and 110 km away from the locality with the interpolated data from four modeled temperature databases and four modeled precipitation databases generated by KNMI Climate Explorer. The spatial resolution of the modeled databases was 0.5° × 0.5° of latitude and longitude or 1° × 1° respectively. The evaluation revealed that in all modeled databases systematic errors of different magnitudes occurred. We also found that the radial increments of spruce correlated more tightly with the temperature than with the precipitation in the area of interest. Hence, in the conditions of the boreal zone, temperature could be a more important factor with regard to tree-ring formation. Because of higher spatial variability seen in precipitation data when compared to temperature data, we conclude that the nearest weather station is the most suitable for dendroclimatic analysis leaning on precipitation. Drawing on these results we recommend that the modeled precipitation and temperature databases examined in our study are used for dendroclimatic analyses within areas featuring a sparse network of weather stations.
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Bender, Fabiani Denise, and Paulo Cesar Sentelhas. "Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil." Advances in Meteorology 2018 (July 5, 2018): 1–15. http://dx.doi.org/10.1155/2018/6204382.
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The quantification of climate change impacts on several human activities depends on reliable weather data series, without gaps and long enough to build up future climate. Based on that, this study aimed to evaluate the performance of temperature-based models for estimating global solar radiation and gridded databases (AgCFSR, AgMERRA, NASA/POWER, and XAVIER) as alternative ways for filling gaps in historical weather series (1980–2009) in Brazil and to project climate change scenarios based on measured and gridded weather data. Projections for mid- and end-of-century periods (2040–2069 and 2070–2099), using seven global climate models from CMIP5 under intermediate (RCP4.5) and high (RCP8.5) emission scenarios, were performed. The Bristow–Campbell model was the one that best estimated solar radiation, whereas the XAVIER gridded database was the closest to observed weather data. Future climate projections, under RCP4.5 and RCP8.5 scenarios, as expected, showed warmer conditions for all scenarios over Brazil. On the contrary, rainfall projections are more uncertain. Despite that, the rainfall amounts will be reduced in the North-Northeast region and increased in Southern Brazil. No significant differences between projections using the observed and XAVIER gridded database were observed; therefore, such a database showed to be reliable for both to fill gaps and to generate climate change scenarios.
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Huggel, C., A. Raissig, M. Rohrer, G. Romero, A. Diaz, and N. Salzmann. "How useful and reliable are disaster databases in the context of climate and global change? A comparative case study analysis in Peru." Natural Hazards and Earth System Sciences Discussions 2, no. 6 (June 17, 2014): 4331–62. http://dx.doi.org/10.5194/nhessd-2-4331-2014.
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Abstract. Loss and damage caused by weather and climate related disasters have increased over the past decades, and growing exposure and wealth have been identified as main drivers of this increase. Disaster databases are a primary tool for the analysis of disaster characteristics and trends at global or national scales, and support disaster risk reduction and climate change adaptation. However, the quality, consistency and completeness of different disaster databases are highly variable. Even though such variation critically influences the outcome of any study, comparative analyses of different disaster databases are still rare to date. Furthermore, there is an unequal geographic distribution of current disaster trend studies, with developing countries being under-represented. Here, we analyze three different disaster databases for the developing country context of Peru; a global database (EM-DAT), a regional Latin American (DesInventar) and a national database (SINPAD). The analysis is performed across three dimensions, (1) spatial scales, from local to regional (provincial) and national scale; (2) time scales, from single events to decadal trends; and (3) disaster categories and metrics, including the number of disaster occurrence, and damage metrics such as people killed and affected. Results show limited changes in disaster occurrence in the Cusco and Apurímac regions in southern Peru over the past four decades, but strong trends in people affected at the national scale. We furthermore found large variations of the disaster parameters studied over different spatial and temporal scales, depending on the disaster database analyzed. We conclude and recommend that the type, method and source of documentation should be carefully evaluated for any analysis of disaster databases; reporting criteria should be improved and documentation efforts strengthened.
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Santos-Gómez, José David, Juan Sebastián Fontalvo-García, and Juan Diego Giraldo Osorio. "Validating the University of Delaware’s precipitation and temperature database for northern South America." DYNA 82, no. 194 (December 21, 2015): 86–95. http://dx.doi.org/10.15446/dyna.v82n194.46160.
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Vast sections of the planet face either a dearth of ground-based weather stations or are hampered by the poor quality of those in service. In response, researchers are forced to turn to climate field databases, as they constitute a source of reliable information for local studies. Insofar as the Amazon region, these databases prove to be valuable given their open-access platform and the fact that this expansive region possesses few quality stations (coupled with insufficient temporal coverage). However, before basing research on such archives, this information should be compared against in situ station measurements. Then, the present study assesses the validity of temperature and precipitation information furnished by University of Delaware’s database (UD-ATP) by means of a comparison with the open-access information available from Climate Explorer project (CLIMEXP). Results show that UD-ATP database offers better precipitation data representation, especially on Brazil, which is perhaps the effect of higher-quality and larger-quantity observed data.
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Maycock, Amanda C., Katja Matthes, Susann Tegtmeier, Hauke Schmidt, Rémi Thiéblemont, Lon Hood, Hideharu Akiyoshi, et al. "The representation of solar cycle signals in stratospheric ozone – Part 2: Analysis of global models." Atmospheric Chemistry and Physics 18, no. 15 (August 13, 2018): 11323–43. http://dx.doi.org/10.5194/acp-18-11323-2018.
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Abstract. The impact of changes in incoming solar irradiance on stratospheric ozone abundances should be included in climate simulations to aid in capturing the atmospheric response to solar cycle variability. This study presents the first systematic comparison of the representation of the 11-year solar cycle ozone response (SOR) in chemistry–climate models (CCMs) and in pre-calculated ozone databases specified in climate models that do not include chemistry, with a special focus on comparing the recommended protocols for the Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5 and CMIP6). We analyse the SOR in eight CCMs from the Chemistry–Climate Model Initiative (CCMI-1) and compare these with results from three ozone databases for climate models: the Bodeker Scientific ozone database, the SPARC/Atmospheric Chemistry and Climate (AC&C) ozone database for CMIP5 and the SPARC/CCMI ozone database for CMIP6. The peak amplitude of the annual mean SOR in the tropical upper stratosphere (1–5 hPa) decreases by more than a factor of 2, from around 5 to 2 %, between the CMIP5 and CMIP6 ozone databases. This substantial decrease can be traced to the CMIP5 ozone database being constructed from a regression model fit to satellite and ozonesonde measurements, while the CMIP6 database is constructed from CCM simulations. The SOR in the CMIP6 ozone database therefore implicitly resembles the SOR in the CCMI-1 models. The structure in latitude of the SOR in the CMIP6 ozone database and CCMI-1 models is considerably smoother than in the CMIP5 database, which shows unrealistic sharp gradients in the SOR across the middle latitudes owing to the paucity of long-term ozone measurements in polar regions. The SORs in the CMIP6 ozone database and the CCMI-1 models show a seasonal dependence with enhanced meridional gradients at mid- to high latitudes in the winter hemisphere. The CMIP5 ozone database does not account for seasonal variations in the SOR, which is unrealistic. Sensitivity experiments with a global atmospheric model without chemistry (ECHAM6.3) are performed to assess the atmospheric impacts of changes in the representation of the SOR and solar spectral irradiance (SSI) forcing between CMIP5 and CMIP6. The larger amplitude of the SOR in the CMIP5 ozone database compared to CMIP6 causes a likely overestimation of the modelled tropical stratospheric temperature response between 11-year solar cycle minimum and maximum by up to 0.55 K, or around 80 % of the total amplitude. This effect is substantially larger than the change in temperature response due to differences in SSI forcing between CMIP5 and CMIP6. The results emphasize the importance of adequately representing the SOR in global models to capture the impact of the 11-year solar cycle on the atmosphere. Since a number of limitations in the representation of the SOR in the CMIP5 ozone database have been identified, we recommend that CMIP6 models without chemistry use the CMIP6 ozone database and the CMIP6 SSI dataset to better capture the climate impacts of solar variability. The SOR coefficients from the CMIP6 ozone database are published with this paper.
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MacDonald, G. M., K. D. Bennett, S. T. Jackson, L. Parducci, F. A. Smith, J. P. Smol, and K. J. Willis. "Impacts of climate change on species, populations and communities: palaeobiogeographical insights and frontiers." Progress in Physical Geography: Earth and Environment 32, no. 2 (April 2008): 139–72. http://dx.doi.org/10.1177/0309133308094081.
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Understanding climate change and its potential impact on species, populations and communities is one of the most pressing questions of twenty-first-century conservation planning. Palaeobiogeographers working on Cenozoic fossil records and other lines of evidence are producing important insights into the dynamic nature of climate and the equally dynamic response of species, populations and communities. Climatic variations ranging in length from multimillennia to decades run throughout the palaeo-records of the Quaternary and earlier Cenozoic and have been shown to have had impacts ranging from changes in the genetic structure and morphology of individual species, population sizes and distributions, community composition to large-scale bio-diversity gradients. The biogeographical impacts of climate change may be due directly to the effects of alterations in temperature and moisture on species, or they may arise due to changes in factors such as disturbance regimes. Much of the recent progress in the application of palaeobiogegraphy to issues of climate change and its impacts can be attributed to developments along a number of still advancing methodological frontiers. These include increasingly finely resolved chronological resolution, more refined atmosphere-biosphere modelling, new biological and chemical techniques in reconstructing past species distributions and past climates, the development of large and readily accessible geo-referenced databases of biogeographical and climatic information, and new approaches in fossil morphological analysis and new molecular DNA techniques.
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Pecor, Keith W., and Kristen A. Batko. "Phenology: From Natural History to Climate Change." American Biology Teacher 79, no. 5 (May 1, 2017): 412–16. http://dx.doi.org/10.1525/abt.2017.79.5.412.
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Phenology refers to the seasonal changes in activity and abundance observed in both plants and animals. This article highlights two animal groups, aquatic insects and frogs, in which phenology can be observed, using data collected directly and via databases. Effects of climate change on phenological patterns are also discussed.
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Pepler, Acacia S., Agata Imielska, Aaron Coutts-Smith, Felicity Gamble, and Martin Schweitzer. "Identifying East Coast Lows with climate hazards on the eastern seaboard." Journal of Southern Hemisphere Earth Systems Science 66, no. 2 (2016): 97. http://dx.doi.org/10.1071/es16010.
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East Coast Lows are an important weather system that can produce severe wind, wave and rainfall events along the eastern seaboard of Australia. While a number of databases of these systems have been produced, this information has historically not been readily accessible to potential users outside the research sec-tor. This paper details the development of a new product, Maps and Tables of Climate Hazards on the Eastern Seaboard (MATCHES), that bridges this gap. It combines a new database of East Coast Lows with weather impacts across the eastern seaboard. Through use of user-defined impacts thresholds and an intuitive front-end interface, this new tool provides an easy way to link East Coast Lows with their weather impacts.
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Bodeker, Greg E., Jan Nitzbon, Jordis S. Tradowsky, Stefanie Kremser, Alexander Schwertheim, and Jared Lewis. "A global total column ozone climate data record." Earth System Science Data 13, no. 8 (August 11, 2021): 3885–906. http://dx.doi.org/10.5194/essd-13-3885-2021.
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Abstract. Total column ozone (TCO) data from multiple satellite-based instruments have been combined to create a single near-global daily time series of ozone fields at 1.25∘ longitude by 1∘ latitude spanning the period 31 October 1978 to 31 December 2016. Comparisons against TCO measurements from the ground-based Dobson and Brewer spectrophotometer networks are used to remove offsets and drifts between the ground-based measurements and a subset of the satellite-based measurements. The corrected subset is then used as a basis for homogenizing the remaining data sets. The construction of this database improves on earlier versions of the database maintained first by the National Institute of Water and Atmospheric Research (NIWA) and now by Bodeker Scientific (BS), referred to as the NIWA-BS TCO database. The intention is for the NIWA-BS TCO database to serve as a climate data record for TCO, and to this end, the requirements for constructing climate data records, as detailed by GCOS (the Global Climate Observing System), have been followed as closely as possible. This new version includes a wider range of satellite-based instruments, uses updated sources of satellite data, extends the period covered, uses improved statistical methods to model the difference fields when homogenizing the data sets, and, perhaps most importantly, robustly tracks uncertainties from the source data sets through to the final climate data record which is now accompanied by associated uncertainty fields. Furthermore, a gap-free TCO database (referred to as the BS-filled TCO database) has been created and is documented in this paper. The utility of the NIWA-BS TCO database is demonstrated through an analysis of ozone trends from November 1978 to December 2016. Both databases are freely available for non-commercial purposes: the DOI for the NIWA-BS TCO database is https://doi.org/10.5281/zenodo.1346424 (Bodeker et al., 2018) and is available from https://zenodo.org/record/1346424. The DOI for the BS-filled TCO database is https://doi.org/10.5281/zenodo.3908787 (Bodeker et al., 2020) and is available from https://zenodo.org/record/3908787. In addition, both data sets are available from http://www.bodekerscientific.com/data/total-column-ozone (last access: June 2021).
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Fiorino, Steven T., Robb M. Randall, Richard J. Bartell, Adam D. Downs, Peter C. Chu, and C. W. Fan. "Climate Change: Anticipated Effects on High-Energy Laser Weapon Systems in Maritime Environments." Journal of Applied Meteorology and Climatology 50, no. 1 (January 1, 2011): 153–66. http://dx.doi.org/10.1175/2010jamc2482.1.
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Abstract This study quantifies the potential impacts on ship-defense high-energy-laser (HEL) performance due to atmospheric effects in the marine boundary layer driven by recent observations and analysis of worldwide sea surface temperatures (SSTs). The atmospheric effects are defined using the worldwide probabilistic climatic database available in the High Energy Laser End-to-End Operational Simulation (HELEEOS) model, which includes an SST database for the period 1854–1997. A more recent worldwide sea surface temperature database was provided by the Naval Postgraduate School for the period 1990–2008. Mean differences and trends between the two SST databases are used to deduce possible climate change impacts on simulated maritime HEL engagements. The anticipated effects on HEL propagation performance are assessed at an operating wavelength of 1.0642 μm across the world’s oceans and mapped onto a 1° × 1° grid. The scenario evaluated is near surface and nearly horizontal over a range of 5000 m in which anticipated clear-air maritime aerosols occur. Summer and winter scenarios are considered. In addition to realistic vertical profiles of molecular and aerosol absorption and scattering, correlated optical turbulence profiles in probabilistic (percentile) format are used.
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Hashimoto, Shoji, Kazuki Nanko, Boris Ťupek, and Aleksi Lehtonen. "Data-mining analysis of the global distribution of soil carbon in observational databases and Earth system models." Geoscientific Model Development 10, no. 3 (March 28, 2017): 1321–37. http://dx.doi.org/10.5194/gmd-10-1321-2017.
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Abstract. Future climate change will dramatically change the carbon balance in the soil, and this change will affect the terrestrial carbon stock and the climate itself. Earth system models (ESMs) are used to understand the current climate and to project future climate conditions, but the soil organic carbon (SOC) stock simulated by ESMs and those of observational databases are not well correlated when the two are compared at fine grid scales. However, the specific key processes and factors, as well as the relationships among these factors that govern the SOC stock, remain unclear; the inclusion of such missing information would improve the agreement between modeled and observational data. In this study, we sought to identify the influential factors that govern global SOC distribution in observational databases, as well as those simulated by ESMs. We used a data-mining (machine-learning) (boosted regression trees – BRT) scheme to identify the factors affecting the SOC stock. We applied BRT scheme to three observational databases and 15 ESM outputs from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and examined the effects of 13 variables/factors categorized into five groups (climate, soil property, topography, vegetation, and land-use history). Globally, the contributions of mean annual temperature, clay content, carbon-to-nitrogen (CN) ratio, wetland ratio, and land cover were high in observational databases, whereas the contributions of the mean annual temperature, land cover, and net primary productivity (NPP) were predominant in the SOC distribution in ESMs. A comparison of the influential factors at a global scale revealed that the most distinct differences between the SOCs from the observational databases and ESMs were the low clay content and CN ratio contributions, and the high NPP contribution in the ESMs. The results of this study will aid in identifying the causes of the current mismatches between observational SOC databases and ESM outputs and improve the modeling of terrestrial carbon dynamics in ESMs. This study also reveals how a data-mining algorithm can be used to assess model outputs.
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Soutullo, S., E. Giancola, M. J. Jiménez, J. A. Ferrer, and M. N. Sánchez. "How Climate Trends Impact on the Thermal Performance of a Typical Residential Building in Madrid." Energies 13, no. 1 (January 3, 2020): 237. http://dx.doi.org/10.3390/en13010237.
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Based on the European energy directives, the building sector has to provide comfortable levels for occupants with minimum energy consumption as well as to reduce greenhouse gas emissions. This paper aims to compare the impact of climate change on the energy performance of residential buildings in order to derive potential design strategies. Different climate file inputs of Madrid have been used to quantify comparatively the thermal needs of two reference residential buildings located in this city. One of them represents buildings older than 40 years built according to the applicable Spanish regulations prior to 1979. The other refers to buildings erected in the last decade under more energy-restrictive constructive regulations. Three different climate databases of Madrid have been used to assess the impact of the evolution of the climate in recent years on the thermal demands of these two reference buildings. Two of them are typical meteorological years (TMY) derived from weather data measured before 2000. On the contrary, the third one is an experimental file representing the average values of the meteorological variables registered in Madrid during the last decade. Annual and monthly comparisons are done between the three climate databases assessing the climate changes. Compared to the TMYs databases, the experimental one records an average air temperature of 1.8 °C higher and an average value of relative humidity that is 9% lower.
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Goudarzi, Fatemeh Moazami, Amirpouya Sarraf, and Hassan Ahmadi. "Assessment of SM2RAIN-ASCAT and CMORPH satellite precipitation products over Maharlu Lake basin in Iran." Water Supply 20, no. 5 (May 13, 2020): 1799–806. http://dx.doi.org/10.2166/ws.2020.088.
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Abstract In recent years, the use of climatic databases and satellite products by researchers has become increasingly common in the field of climate modeling and research. These datasets play an important role in developing countries. This study evaluated two reanalyses, CMORPH and SM2RAIN-ASCAT over Maharlu Lake, a semi-arid region in Iran. The results showed that these two near-time datasets do not have accurate data over this basin. However, the probability of detection (POD), critical success index (CSI), and false alarm ratio (FAR) statistics showed acceptable accuracy in the detection of precipitation. The coefficient of determination and root mean square error statistics have unacceptable accuracy over this area. The monthly changes in each of the indices showed that the CMORPH database had more errors in the spring months, but in other months the error rate was improved. SM2RAIN-ASCAT had better accuracy over this area relative to CMORPH. The estimation of the total accuracy of the data showed that these two satellite databases were not capable of estimating precipitation in the area.
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Honti, Gergely, and János Abonyi. "Frequent Itemset Mining and Multi-Layer Network-Based Analysis of RDF Databases." Mathematics 9, no. 4 (February 23, 2021): 450. http://dx.doi.org/10.3390/math9040450.
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Triplestores or resource description framework (RDF) stores are purpose-built databases used to organise, store and share data with context. Knowledge extraction from a large amount of interconnected data requires effective tools and methods to address the complexity and the underlying structure of semantic information. We propose a method that generates an interpretable multilayered network from an RDF database. The method utilises frequent itemset mining (FIM) of the subjects, predicates and the objects of the RDF data, and automatically extracts informative subsets of the database for the analysis. The results are used to form layers in an analysable multidimensional network. The methodology enables a consistent, transparent, multi-aspect-oriented knowledge extraction from the linked dataset. To demonstrate the usability and effectiveness of the methodology, we analyse how the science of sustainability and climate change are structured using the Microsoft Academic Knowledge Graph. In the case study, the FIM forms networks of disciplines to reveal the significant interdisciplinary science communities in sustainability and climate change. The constructed multilayer network then enables an analysis of the significant disciplines and interdisciplinary scientific areas. To demonstrate the proposed knowledge extraction process, we search for interdisciplinary science communities and then measure and rank their multidisciplinary effects. The analysis identifies discipline similarities, pinpointing the similarity between atmospheric science and meteorology as well as between geomorphology and oceanography. The results confirm that frequent itemset mining provides an informative sampled subsets of RDF databases which can be simultaneously analysed as layers of a multilayer network.
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Mehta, Suril, Jennifer Parker, Lara Akinbami, Raghu Murtugudde, and Amir Sapkota. "Climate Events and Health Outcomes: Data Linkage From 2 Large National Databases." Epidemiology 22 (January 2011): S25. http://dx.doi.org/10.1097/01.ede.0000391735.47441.e0.
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Degourmond, Nyemb Pagbe Rémi. "Institutions and Economic Growth in Sub-Saharan African Countries: The Effect of Investment Climate Quality." International Journal of Scientific Research and Management 8, no. 04 (April 24, 2020): 1706–30. http://dx.doi.org/10.18535/ijsrm/v8i04.em04.
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This paper assesses the impact of investment climate quality on economic growth for a sample of 21 countries in Sub-Saharan Africa (SSA), over the period 1996-2014. The investment climate is measured simultaneously by individual components and composite indices, in order to capture both its global and specific effects, with a view to possibly identifying the most determining factors in the economic growth of SSA countries. In addition, in order to verify the robustness of our results, two composite indices of investment climate were constructed using the Principal Component Analysis method, with variables from two main databases (the World Governance Indicators database of World Bank and the International Country Risk Guide database).By using fixed and random effects models based on Hausman test results, we generally find that investment climate is a major determinant of economic growth in the countries of the SSA of the study sample. This result is valid regardless of the composite index or the individual component considered. Fight against corruption, protection of private property rights, efficiency of government, the quality of bureaucracy and regulation appear to be the most decisive components in accelerating economic growth for the sample of country considered.
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Mínguez, R., B. G. Reguero, A. Luceño, and F. J. Méndez. "Regression Models for Outlier Identification (Hurricanes and Typhoons) in Wave Hindcast Databases." Journal of Atmospheric and Oceanic Technology 29, no. 2 (February 1, 2012): 267–85. http://dx.doi.org/10.1175/jtech-d-11-00059.1.
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Abstract The development of numerical wave prediction models for hindcast applications allows a detailed description of wave climate in locations where long-term instrumental records are not available. Wave hindcast databases (WHDBs) have become a powerful tool for the design of offshore and coastal structures, offering important advantages for the statistical characterization of wave climate all over the globe (continuous time series, wide spatial coverage, constant time span, homogeneous forcing, and more than 60-yr-long time series). However, WHDBs present several deficiencies reported in the literature. One of these deficiencies is related to typhoons and hurricanes, which are inappropriately reproduced by numerical models. The main reasons are (i) the difficulty of specifying accurate wind fields during these events and (ii) the insufficient spatiotemporal resolution used. These difficulties make the data related to these events appear as “outliers” when compared with instrumental records. These bad data distort results from calibration and/or correction techniques. In this paper, several methods for detecting the presence of typhoons and/or hurricane data are presented, and their automatic outlier identification capabilities are analyzed and compared. All the methods are applied to a global wave hindcast database and results are compared with existing hurricane and buoy databases in the Gulf of Mexico, Caribbean Sea, and North Atlantic Ocean.
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Robinson, Joanne, Leam A. Craig, and Matthew Tonkin. "Perceptions of Social Climate and Aggressive Behavior in Forensic Services: A Systematic Review." Trauma, Violence, & Abuse 19, no. 4 (August 12, 2016): 391–405. http://dx.doi.org/10.1177/1524838016663936.
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Social climate is a term used to describe the environment of a particular setting which may influence the moods and behaviors of the people inhabiting that setting. This review explores perceptions of social climate in secure forensic services and the associations with aggression. Article searches were conducted using electronic databases, hand-searching reference lists, and contacting experts. Inclusion/exclusion criteria were applied to each study, and quality screens conducted on the remaining articles to establish those for inclusion. A total of seven studies were identified. Factors which were found to have an association with aggression included patients’ perceptions of safety, the level of cohesion between patients, the atmosphere of the environment, and an open group climate. It is argued that services which create positive social climates for both staff and patients are more likely to observe lower levels of aggression.
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Ehler, Niels, and Jesper M. Aaslyng. "Real-time Monitoring of Greenhouse Climate Control Using the Internet." HortTechnology 11, no. 4 (January 2001): 639–43. http://dx.doi.org/10.21273/horttech.11.4.639.
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The possibility of constructing an Internet application that would enable greenhouse users to track climate and control parameters from any Internet-connected computer was investigated. By constructing a set of HTML-templates, dynamic information from the control-system databases was integrated in real-time, and was uploaded to a common net-server by automatic generation of web pages using software developed during the project. Good performance, reliability and security were obtained and the technology proved to be an efficient way of supplying a broad range of users not only with climatic data but also with results from ongoing research.
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Pauer, Erik, Bernhard Wohner, and Manfred Tacker. "The Influence of Database Selection on Environmental Impact Results. Life Cycle Assessment of Packaging Using GaBi, Ecoinvent 3.6, and the Environmental Footprint Database." Sustainability 12, no. 23 (November 27, 2020): 9948. http://dx.doi.org/10.3390/su12239948.
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This research analyses the differences in impact assessment results depending on the choice of a certain software-database combination. Six packaging systems were modelled in three software-database combinations (GaBi database in GaBi software, ecoinvent 3.6 database in openLCA, Environmental Footprint database in openLCA). The chosen Life Cycle Impact Assessment (LCIA) method is EF 2.0. Differences and errors in the implementation of the LCIA method are a possible source of deviations. We compared the published characterisation factors with the factors implemented in the software-database combinations. While results for the climate change category are similar between the different databases, this is not the case for the other impact categories. In most cases, the use of the ecoinvent 3.6 database leads to higher results compared to GaBi. This is partly due to the fact, that ecoinvent datasets often include more background processes than the corresponding GaBi datasets. We found striking discrepancies in LCIA implementation, including the lack of regionalisation for water use in ecoinvent. A meaningful communication of LCIA results requires an excellent knowledge of the analysed product system, as well as of database quality issues and LCIA methodology. We fully acknowledge the constant efforts of database providers to improve their databases.
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Booth, Trevor H. "Species distribution modelling tools and databases to assist managing forests under climate change." Forest Ecology and Management 430 (December 2018): 196–203. http://dx.doi.org/10.1016/j.foreco.2018.08.019.
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Joksimovic, Marko, Mirjana Gajic, Snezana Vujadinovic, Rajko Golic, and Darko Vukovic. "The effect of the thermal component change on regional climate indices in Serbia." Thermal Science 19, suppl. 2 (2015): 391–403. http://dx.doi.org/10.2298/tsci150430105j.
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The study of climate changes is most often based on the analysis of time series of temperature and precipitation in urban areas and the increase in the emission of gases having a greenhouse effect. On the other hand, the selection of representative and relevant stations and comprehensive analysis of climate indicators lead to better and more exact assessments on climate changes at the regional level. In order to connect climate changes with agricultural, biological, socio-economic and tourism databases, the paper deals with the dynamic analysis of changes in thermal component expressed through the values of regional climate indices in four climatological stations with different geographical positions in Serbia. There are significant differences between the two time series data (1961-1990 and 1991-2013) on temperature and humidity, precipitation, insolation and wind speed. However, after using the climatic indices as a tool for assessing climate changes, the results of the study suggest the relative influence of the thermal component on the change of climate indices, with a slight increase in the index of significance for human activities. Relying on the results of this alternative approach to the study of climate changes, the fact remains that the climate is not fixed but highly variable factor that should be taken into consideration in terms of monitoring, evaluation and management of the area.
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Malhotra, Avni, Katherine Todd-Brown, Lucas E. Nave, Niels H. Batjes, James R. Holmquist, Alison M. Hoyt, Colleen M. Iversen, et al. "The landscape of soil carbon data: Emerging questions, synergies and databases." Progress in Physical Geography: Earth and Environment 43, no. 5 (September 8, 2019): 707–19. http://dx.doi.org/10.1177/0309133319873309.
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Soil carbon has been measured for over a century in applications ranging from understanding biogeochemical processes in natural ecosystems to quantifying the productivity and health of managed systems. Consolidating diverse soil carbon datasets is increasingly important to maximize their value, particularly with growing anthropogenic and climate change pressures. In this progress report, we describe recent advances in soil carbon data led by the International Soil Carbon Network and other networks. We highlight priority areas of research requiring soil carbon data, including (a) quantifying boreal, arctic and wetland carbon stocks, (b) understanding the timescales of soil carbon persistence using radiocarbon and chronosequence studies, (c) synthesizing long-term and experimental data to inform carbon stock vulnerability to global change, (d) quantifying root influences on soil carbon and (e) identifying gaps in model–data integration. We also describe the landscape of soil datasets currently available, highlighting their strengths, weaknesses and synergies. Now more than ever, integrated soil data are needed to inform climate mitigation, land management and agricultural practices. This report will aid new data users in navigating various soil databases and encourage scientists to make their measurements publicly available and to join forces to find soil-related solutions.
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Papagiannopoulou, Christina, Diego G. Miralles, Stijn Decubber, Matthias Demuzere, Niko E. C. Verhoest, Wouter A. Dorigo, and Willem Waegeman. "A non-linear Granger-causality framework to investigate climate–vegetation dynamics." Geoscientific Model Development 10, no. 5 (May 17, 2017): 1945–60. http://dx.doi.org/10.5194/gmd-10-1945-2017.
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Abstract. Satellite Earth observation has led to the creation of global climate data records of many important environmental and climatic variables. These come in the form of multivariate time series with different spatial and temporal resolutions. Data of this kind provide new means to further unravel the influence of climate on vegetation dynamics. However, as advocated in this article, commonly used statistical methods are often too simplistic to represent complex climate–vegetation relationships due to linearity assumptions. Therefore, as an extension of linear Granger-causality analysis, we present a novel non-linear framework consisting of several components, such as data collection from various databases, time series decomposition techniques, feature construction methods, and predictive modelling by means of random forests. Experimental results on global data sets indicate that, with this framework, it is possible to detect non-linear patterns that are much less visible with traditional Granger-causality methods. In addition, we discuss extensive experimental results that highlight the importance of considering non-linear aspects of climate–vegetation dynamics.
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Kitka, Gergely, Anna Kovács-Győri, János Tátrai, and Viktor György Oroszi. "Application of GIS for a Climate Change Prepared Disaster Management in Csongrád County, Hungary." Journal of Environmental Geography 11, no. 3-4 (November 1, 2018): 49–56. http://dx.doi.org/10.2478/jengeo-2018-0012.
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Abstract The work of disaster management can only properly be supported by data stored in certified databases, since correct decisions can be made on the base of such data. Nowadays these data can be found in databases managed by several organisations, or only a part of the necessary data is available through GIS services. The tasks of disaster management include prevention, i.e. the preparation for potential incidents and the elaboration of related scenarios and plans taking into consideration the altering risk landscape caused by climate change. The development of modelling processes and applications based on GIS databases and the integration of the results in work processes gain ground more and more in this work phase. Geoinformatics is able to provide support for decision-making in two ways: in strategic planning and in the operative task solution. The present study demonstrates a multi-hazard multi-scale GIS tool development in Csongrád County (Hungary) in accordance with the aims of the Sendai Framework. This geoinformatic tool is applicable to support the decision-making not only of the management board but the deployed rescue units in case of an evacuation through the optimized locations of the gathering places.
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Mahmood, Rezaul, Roger A. Pielke, and Clive A. McAlpine. "Climate-Relevant Land Use and Land Cover Change Policies." Bulletin of the American Meteorological Society 97, no. 2 (February 1, 2016): 195–202. http://dx.doi.org/10.1175/bams-d-14-00221.1.
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Abstract Both observational and modeling studies clearly demonstrate that land-use and land-cover change (LULCC) play an important biogeophysical and biogeochemical role in the climate system from the landscape to regional and even continental scales. Without comprehensively considering these impacts, an adequate response to the threats posed by human intervention into the climate system will not be adequate. Public policy plays an important role in shaping local- to national-scale land-use practices. An array of national policies has been developed to influence the nature and spatial extent of LULCC. Observational evidence suggests that these policies, in addition to international trade treaties and protocols, have direct effects on LULCC and thus the climate system. However, these policies, agreements, and protocols fail to adequately recognize these impacts. To make these more effective and thus to minimize climatic impacts, we propose several recommendations: 1) translating international treaties and protocols into national policies and actions to ensure positive climate outcomes; 2) updating international protocols to reflect advancement in climate–LULCC science; 3) continuing to invest in the measurements, databases, reporting, and verification activities associated with LULCC and LULCC-relevant climate monitoring; and 4) reshaping Reducing Emissions from Deforestation and Forest Degradation+ (REDD+) to fully account for the multiscale biogeophysical and biogeochemical impacts of LULCC on the climate system.
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Dugerdil, Lucas, Sébastien Joannin, Odile Peyron, Isabelle Jouffroy-Bapicot, Boris Vannière, Bazartseren Boldgiv, Julia Unkelbach, Hermann Behling, and Guillemette Ménot. "Climate reconstructions based on GDGT and pollen surface datasets from Mongolia and Baikal area: calibrations and applicability to extremely cold–dry environments over the Late Holocene." Climate of the Past 17, no. 3 (June 16, 2021): 1199–226. http://dx.doi.org/10.5194/cp-17-1199-2021.
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Abstract. Our understanding of climate and vegetation changes throughout the Holocene is hampered by representativeness in sedimentary archives. Potential biases such as production and preservation of the markers are identified by comparing these proxies with modern environments. It is important to conduct multi-proxy studies and robust calibrations on each terrestrial biome. These calibrations use large databases dominated by forest samples. Therefore, including data from steppe and desert–steppe sites becomes necessary to better calibrate arid environments. The Mongolian Plateau, ranging from the Baikal area to the Gobi desert, is especially characterized by low annual precipitation and continental annual air temperature. The characterization of the climate system of this area is crucial for the understanding of Holocene monsoon oscillations. This study focuses on the calibration of proxy–climate relationships for pollen and glycerol dialkyl glycerol tetraethers (GDGTs) by comparing large Eurasian calibrations with a set of 49 new surface samples (moss polster, soil and mud from temporary dry ponds). These calibrations are then cross-validated by an independent dataset of top-core samples and applied to four Late Holocene paleosequences (two brGDGT and two pollen records) surrounding the Mongolian Plateau: in the Altai mountains, the Baikal area and the Qaidam basin, to test the accuracy of local and global calibrations. We show that (1) preserved pollen assemblages are clearly imprinted on the extremities of the ecosystem range but mitigated and unclear on the ecotones; (2) for both proxies, inferred relationships depend on the geographical range covered by the calibration database as well as on the nature of samples; (3) even if local calibrations suffer from reduced amplitude of climatic parameters due to local homogeneity, they better reflect actual climate than the global ones by reducing the limits for saturation impact; (4) a bias in climatic reconstructions is induced by the over-parameterization of the models by the addition of artificial correlation; and (5) paleoclimate values reconstructed here are consistent with Mongolia–China Late Holocene climate trends and validate the application of local calibrations for both pollen and GDGTs (closest fit to actual values and realistic paleoclimate amplitude). We encourage the application of this surface calibration method to reconstruct paleoclimate and especially consolidate our understanding of the Holocene climate and environment variations in arid central Asia.
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Halfpenny, J., and J. Clark. "Climate Calendars: Computer Graphics Reveal Patterns in Large Databases That Are Useful to Ecologists." BioScience 38, no. 6 (June 1988): 399–405. http://dx.doi.org/10.2307/1310926.
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Mitchell, Carrie L., Sarah L. Burch, and Patrick A. Driscoll. "(Mis)communicating climate change? Why online adaptation databases may fail to catalyze adaptation action." Wiley Interdisciplinary Reviews: Climate Change 7, no. 4 (May 19, 2016): 600–613. http://dx.doi.org/10.1002/wcc.401.
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Gall, Melanie. "The suitability of disaster loss databases to measure loss and damage from climate change." International Journal of Global Warming 8, no. 2 (2015): 170. http://dx.doi.org/10.1504/ijgw.2015.071966.
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Brook, Barry W., and Damien A. Fordham. "Hot topics in biodiversity and climate change research." F1000Research 4 (September 30, 2015): 928. http://dx.doi.org/10.12688/f1000research.6508.1.
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With scientific and societal interest in biodiversity impacts of climate change growing enormously over the last decade, we analysed directions and biases in the recent most highly cited data papers in this field of research (from 2012 to 2014). The majority of this work relied on leveraging large databases of already collected historical information (but not paleo- or genetic data), and coupled these to new methodologies for making forward projections of shifts in species’ geographical ranges, with a focus on temperate and montane plants. A consistent finding was that the pace of climate-driven habitat change, along with increased frequency of extreme events, is outpacing the capacity of species or ecological communities to respond and adapt.
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Katunský, Dušan, Lenka Kabošová, Erika Dolníková, and Marek Zozulák. "Research of building structures in extreme climate conditions." Selected Scientific Papers - Journal of Civil Engineering 14, no. 2 (December 1, 2019): 127–36. http://dx.doi.org/10.1515/sspjce-2019-0024.
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AbstractThe paper provides information on the solution of project supported by the Scientific Grant Agency of VEGA of the Ministry of Education, Science, Research and Sports of Slovak Republic and of the Slovak Academy of Sciences of Slovak Republic. There is project: VEGA 1/0674/18. This research project is programmed for the years 2018 to 2021. In this paper are presented information on the results obtained in 2019, solution of this project objectives and project solution. The results are presented in realized publications. We focused mainly on the presentation of major publications, articles in domestic and foreign journals, articles in conference proceedings with an emphasis on publications that are indexed in the WOS and SCOPUS databases.
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Szilassi, Péter, Gábor Szatmári, László Pásztor, Mátyás Árvai, József Szatmári, Katalin Szitár, and Levente Papp. "Understanding the Environmental Background of an Invasive Plant Species (Asclepias syriaca) for the Future: An Application of LUCAS Field Photographs and Machine Learning Algorithm Methods." Plants 8, no. 12 (December 12, 2019): 593. http://dx.doi.org/10.3390/plants8120593.
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For developing global strategies against the dramatic spread of invasive species, we need to identify the geographical, environmental, and socioeconomic factors determining the spatial distribution of invasive species. In our study, we investigated these factors influencing the occurrences of common milkweed (Asclepias syriaca L.), an invasive plant species that is of great concern to the European Union (EU). In a Hungarian study area, we used country-scale soil and climate databases, as well as an EU-scale land cover databases (CORINE) for the analyses. For the abundance data of A. syriaca, we applied the field survey photos from the Land Use and Coverage Area Frame Survey (LUCAS) Land Cover database for the European Union. With machine learning algorithm methods, we quantified the relative weight of the environmental variables on the abundance of common milkweed. According to our findings, soil texture and soil type (sandy soils) were the most important variables determining the occurrence of this species. We could exactly identify the actual land cover types and the recent land cover changes that have a significant role in the occurrence the common milkweed in Europe. We could also show the role of climatic conditions of the study area in the occurrence of this species, and we could prepare the potential distribution map of common milkweed for the study area.
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Ahmed, Abubakar, Mukhtar Suleiman, Musbahu Jibrin Abubakar, and Abba Saleh. "Impacts of climate change on agriculture in Senegal: A systematic review." Journal of Sustainability, Environment and Peace 4, no. 1 (September 13, 2021): 30–38. http://dx.doi.org/10.53537/jsep.2021.09.004.
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Climate change is a global environmental threat, affecting every sector of the economy with agriculture being the most affected as a result of its dependence on climate especially rainfall and temperature. The objective of this study is to examine the impacts of climate change on agriculture (crop production) and identify the farmers’ adaptation strategies to the impacts of climate change in Senegal. This study employed systematic literature review. Searching of relevant documents were conducted between 26th December 2020 and 10th February, 2021. A comprehensive search of six databases were conducted. The databases searched were Scopus, African Journal Online (AJOL), ProQuest, Elsevier, Research gate, and Google scholar. The findings revealed that temperature is expected to increase by median value of 0.90C (0.70C-1.50C) by 2035, by 2.10 (1.60C-3.30C) by 2065, and 4.00C (2.6-5.90C) by 2100 and rainfall could increase by 1% (uncertainty range of −4% to +8%) by 2035, 2% (−8% to +8%) by 2065, and 5% (−10% to +16%) by 2100. As a result of rising temperatures, local agricultural production will be less than 50kg per capita by 2050. This is expected to have an effect on crop imports as well as regional migration. The decrease in rainfall under RCP2.6, (Representative Concentration Pathway) combined with the effect of temperature, has a significant impact on the yield of sorghum, maize, and millet, with production decreasing by up to 20-50%. Farmers employed several adaptation strategies to adapt to the impacts of climate change; sowing improved variety, mixed cropping, income diversification, ownership of multiple farms, religious practices in form of prayer. The review recommends strengthening of climate related institutions, adoption of new innovations, implementation of new climate related policies, climate monitoring and forecasting, enhancing and strengthening community-based adaptation through sensitization and incentives.
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Rekker, Saphira A. C., Jacquelyn E. Humphrey, and Katherine R. O’Brien. "Do Sustainability Rating Schemes Capture Climate Goals?" Business & Society 60, no. 1 (March 6, 2019): 125–60. http://dx.doi.org/10.1177/0007650319825764.
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The 2015 Paris Agreement set a global warming limit of 2°C above preindustrial levels. Corporations play an important role in achieving this objective, and methods have recently been developed to map global climate targets to specific industries, and individual corporations within those industries. In this article, we assess whether Sustainability ratings capture corporate performance in meeting the 2°C target. We analyze nine rating schemes used by investors and three commonly used in academic studies. Most rating schemes do consider corporate greenhouse gas emissions in their analysis, whereas only a minority scale emissions by factors that have the potential to allow benchmarking against science-based targets. None take the final step of mapping climate indicators against the 2°C target. Furthermore, we find a lack of consistency in the climate change ratings of the databases used in academic studies. These results are concerning in the context of being able to meet global climate change goals.
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Poulsen, Mikkel, Michael Lauring, and Camilla Brunsgaard. "A REVIEW OF CLIMATE CHANGE ADAPTIVE MEASURES IN ARCHITECTURE WITHIN TEMPERATE CLIMATE ZONES." Journal of Green Building 15, no. 2 (March 1, 2020): 113–30. http://dx.doi.org/10.3992/1943-4618.15.2.113.
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ABSTRACT Since a large portion of greenhouse gases are emitted by the building sector, there has been a push towards sustainable low energy architecture, which could help mitigate the effects of climate change. Although climate change is considered inevitable, adaptive measures must be taken in the field of architecture to alleviate its impact. Creating an overview of the state of the art in the field of architecture as it adapts to climate change will help identify the problems and possibilities of architectural adaptation. The aim must be to create buildings that are as suitable to the current climate as they are to the climate of the future and maintain an ability to resist the impacts of climate change; this ability to resist potential change is defined as adaptive capacity. It is challenging to reconcile the energy requirements for contemporary buildings with rising temperatures and extreme weather in temperate climate zones. The literature on the subject is explored through iterative searches in scientific databases. In discussions about the possible adaptations to climate change, there needs to be a focus on human adaptation facilitated by architecture and the built environment’s utilization and support of ecosystem services in adaptation strategies, since the scope of climate change reaches beyond the singular building. There are plenty of strategies and technologies from which to draw but little focus on how these should support the design of a building and its inhabitants. In the future it will be necessary to look at the adaptive capacity of a building itself and how the building can benefit its surroundings.
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Vettor, Roberto, and C. Guedes Soares. "Assessment of the Storm Avoidance Effect on the Wave Climate along the Main North Atlantic Routes." Journal of Navigation 69, no. 1 (June 24, 2015): 127–44. http://dx.doi.org/10.1017/s037346331500048x.
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The wave climate along the main transoceanic routes of the North Atlantic sub basin is determined using three different databases: two derived by numerical models in the HIPOCAS and ERA40 databases and one from Voluntary Observing Ships. For each route the distribution of the mean significant wave height along the path is computed as well as the specific scatter diagram. In addition an assessment of the relative wave heading probability is provided. The results highlight a bias in the visual observations especially in the summer and, more in general, for low sea states. The correction of this bias allows better understanding of rough weather avoidance by ships and to determine a storm avoidance correction.
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Stefanakos, Christos. "Global Wind and Wave Climate Based on Two Reanalysis Databases: ECMWF ERA5 and NCEP CFSR." Journal of Marine Science and Engineering 9, no. 9 (September 11, 2021): 990. http://dx.doi.org/10.3390/jmse9090990.
Full textAbstract:
In the present work, the global wind and wave climate is studied on the basis of two well-known reanalysis products, namely ERA5 and CFSR-W (WW3 hereafter). Several statistical features of the datasets are assessed, such as seasonal variability, quantiles of the probability distribution, monthly, annual and inter-annual variability, and several error metrics. The time span covers a period of 31 years (1979–2009), a fact that assures that most of the long-scale features are equally present in both datasets. The analysis performed is depicted both on a global and regional scale. The results are also assessed by means of a global satellite altimeter dataset.