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A.C. Costa
NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312 Lisboa, Portugal

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Journal article
Published: 02 January 2020 in Energies
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The fastest-growing renewable source of energy is solar photovoltaic (PV) energy, which is likely to become the largest electricity source in the world by 2050. In order to be a viable alternative energy source, PV systems should maximise their efficiency and operate flawlessly. However, in practice, many PV systems do not operate at their full capacity due to several types of anomalies. We propose tailored algorithms for the detection of different PV system anomalies, including suboptimal orientation, daytime and sunrise/sunset shading, brief and sustained daytime zero-production, and low maximum production. Furthermore, we establish simple metrics to assess the severity of suboptimal orientation and daytime shading. The proposed detection algorithms were applied to a set of time-series of electricity production in Portugal, which are based on two periods with distinct weather conditions. Under favourable weather conditions, the algorithms successfully detected most of the time-series labelled with either daytime or sunrise/sunset shading, and with either sustained or brief daytime zero-production. There was a relatively low percentage of false positives, such that most of the anomaly detections were correct. As expected, the algorithms tend to be more robust under favourable rather than under adverse weather conditions. The proposed algorithms may prove to be useful not only to research specialists, but also to energy utilities and owners of small- and medium-sized PV systems, who may thereby effortlessly monitor their operation and performance.

ACS Style

Pedro Branco; Francisco Gonçalves; Ana Cristina Costa. Tailored Algorithms for Anomaly Detection in Photovoltaic Systems. Energies 2020, 13, 225 .

AMA Style

Pedro Branco, Francisco Gonçalves, Ana Cristina Costa. Tailored Algorithms for Anomaly Detection in Photovoltaic Systems. Energies. 2020; 13 (1):225.

Chicago/Turabian Style

Pedro Branco; Francisco Gonçalves; Ana Cristina Costa. 2020. "Tailored Algorithms for Anomaly Detection in Photovoltaic Systems." Energies 13, no. 1: 225.

Short communication
Published: 11 January 2019 in Urban Climate
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In warming Europe, we are witnessing a growth in urban population with aging trend, which will make the society more exposed and vulnerable to extreme weather events. In the period 1950–2015 the occurrence of extreme heat waves increased across European capitals. As an example, in 2010 Moscow was hit by the strongest heat wave of the present era, killing more than ten thousand people. The cold extremes will have decreasing tendency as global warming progresses, however due to higher variability of future climates, the cold wave hazard may remain locally important threat. Moreover, the heat and cold-related mortality will be enhanced with foreseen demographic evolution in European cities. Here we focus on larger metropolitan areas of European capitals (EU28 plus Moscow, Oslo and Zurich). By using an ensemble of eight EURO-CORDEX models under the RCP8.5 scenario, we detected heat waves and cold waves events by deployment of Heat Wave Magnitude Index daily and its cold wave counterpart. We introduce a ranking procedure based on ensemble predictions using the median of metropolitan grid cells for each capital, and population density as a proxy to quantify the future exposure. All the investigated European metropolitan areas will be more vulnerable to extreme heat in the coming decades. Based on the impact ranking, results reveal that cold waves will represent some threat in mid of the century but they will not be the major threat in any of European capitals, and that they are projected to completely vanish by the end of this century. On the contrary, in near, but even more so in distant future, extreme heat events in European capitals will be not exclusive to traditionally exposed areas such as the Mediterranean and the Iberian Peninsula. The ranking of European capitals based on their exposure to extreme heat is of paramount importance to decision makers in order to mitigate the heat related mortality, especially with the foreseen increase of global mean temperature. Furthermore, this simple comparative indicator helps communicating the global, complex and impersonal issue of climate change locally thus contributing to raise awareness and call for action.

ACS Style

M. Smid; S. Russo; Ana Cristina Costa; C. Granell; E. Pebesma. Ranking European capitals by exposure to heat waves and cold waves. Urban Climate 2019, 27, 388 -402.

AMA Style

M. Smid, S. Russo, Ana Cristina Costa, C. Granell, E. Pebesma. Ranking European capitals by exposure to heat waves and cold waves. Urban Climate. 2019; 27 ():388-402.

Chicago/Turabian Style

M. Smid; S. Russo; Ana Cristina Costa; C. Granell; E. Pebesma. 2019. "Ranking European capitals by exposure to heat waves and cold waves." Urban Climate 27, no. : 388-402.

Journal article
Published: 30 November 2018 in ISPRS International Journal of Geo-Information
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Air quality has had a significant impact on public health, the environment and eventually on the economy of countries for decades. Effectively mitigating air pollution in urban areas necessitates accurate air quality exposure information. Recent advancements in sensor technology and the increasing popularity of volunteered geographic information (VGI) open up new possibilities for air quality exposure assessment in cities. However, citizens and their sensors are put in areas deemed to be subjectively of interest (e.g., where citizens live, school of their kids or working spaces), and this leads to missed opportunities when it comes to optimal air quality exposure assessment. In addition, while the current literature on VGI has extensively discussed data quality and citizen engagement issues, few works, if any, offer techniques to fine-tune VGI contributions for an optimal air quality exposure assessment. This article presents and tests an approach to minimise land use regression prediction errors on citizen-contributed data. The approach was evaluated using a dataset (N = 116 sensors) from the city of Stuttgart, Germany. The comparison between the existing network design and the combination of locations selected by the optimisation method has shown a drop in spatial mean prediction error by 52%. The ideas presented in this article are useful for the systematic deployment of VGI air quality sensors, and can aid in the creation of higher resolution, more realistic maps for air quality monitoring in cities.

ACS Style

Shivam Gupta; Edzer Pebesma; Auriol Degbelo; Ana Cristina Costa. Optimising Citizen-Driven Air Quality Monitoring Networks for Cities. ISPRS International Journal of Geo-Information 2018, 7, 468 .

AMA Style

Shivam Gupta, Edzer Pebesma, Auriol Degbelo, Ana Cristina Costa. Optimising Citizen-Driven Air Quality Monitoring Networks for Cities. ISPRS International Journal of Geo-Information. 2018; 7 (12):468.

Chicago/Turabian Style

Shivam Gupta; Edzer Pebesma; Auriol Degbelo; Ana Cristina Costa. 2018. "Optimising Citizen-Driven Air Quality Monitoring Networks for Cities." ISPRS International Journal of Geo-Information 7, no. 12: 468.

Journal article
Published: 16 November 2017 in International Journal of Urban Sciences
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ACS Style

Marek Smid; Ana Cristina Costa. Climate projections and downscaling techniques: a discussion for impact studies in urban systems. International Journal of Urban Sciences 2017, 22, 277 -307.

AMA Style

Marek Smid, Ana Cristina Costa. Climate projections and downscaling techniques: a discussion for impact studies in urban systems. International Journal of Urban Sciences. 2017; 22 (3):277-307.

Chicago/Turabian Style

Marek Smid; Ana Cristina Costa. 2017. "Climate projections and downscaling techniques: a discussion for impact studies in urban systems." International Journal of Urban Sciences 22, no. 3: 277-307.

Research article
Published: 09 August 2017 in Advances in Meteorology
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The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

ACS Style

Adeoluwa Akande; Ana Cristina Costa; Jorge Mateu; Roberto Henriques. Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps. Advances in Meteorology 2017, 2017, 1 -11.

AMA Style

Adeoluwa Akande, Ana Cristina Costa, Jorge Mateu, Roberto Henriques. Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps. Advances in Meteorology. 2017; 2017 ():1-11.

Chicago/Turabian Style

Adeoluwa Akande; Ana Cristina Costa; Jorge Mateu; Roberto Henriques. 2017. "Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps." Advances in Meteorology 2017, no. : 1-11.

Chapter
Published: 08 March 2017 in Geostatistics Valencia 2016
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Nowadays, climate data series are used in so many different studies that their importance implies the essential need of good data quality. For this reason, the process of homogenisation became a hot topic in the last decades, and many researchers have focused on developing efficient methods for the detection and correction of inhomogeneities in climate data series. This study evaluates the efficiency of the gsimcli homogenisation method, which is based on a geostatistical simulation approach. For each instant in time, gsimcli uses the direct sequential simulation algorithm to generate several equally probable realisations of the climate variable at the candidate station’s location, disregarding its values. The probability density function estimated at the candidate station’s location (local probability density functions (PDF)), for each instant in time, is then used to verify the existence of inhomogeneities in the candidate time series. When an inhomogeneity is detected, that value is replaced by a statistical value (correction parameter) derived from the estimated local PDF. In order to assess the gsimcli efficiency with different implementation strategies, we homogenised monthly precipitation data from an Austrian network of the COST-HOME benchmark data set (COST Action ES0601, Advances in homogenization methods of climate series: an integrated approach – HOME). The following parameters were tested: grid cell size, candidate order in the homogenisation process, local radius parameter, detection parameter and correction parameter. Performance metrics were computed to assess the efficiency of gsimcli. The results show the high influence of the grid cell size and of the correction parameter in the method’s performance.

ACS Style

S. Ribeiro; J. Caineta; A. C. Costa. Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark. Geostatistics Valencia 2016 2017, 19, 909 -918.

AMA Style

S. Ribeiro, J. Caineta, A. C. Costa. Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark. Geostatistics Valencia 2016. 2017; 19 ():909-918.

Chicago/Turabian Style

S. Ribeiro; J. Caineta; A. C. Costa. 2017. "Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark." Geostatistics Valencia 2016 19, no. : 909-918.

Journal article
Published: 17 November 2016 in International Journal of Climatology
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Climate data homogenisation is of major importance in monitoring climate change and in validating weather forecasts, general circulation and regional atmospheric models, modelling of erosion and drought monitoring, among other impact studies. Discontinuities in the time series, also named inhomogeneities, may lead to biased conclusions in such studies, so they should be detected and corrected. Previous studies have suggested a geostatistical stochastic approach, which uses Direct Sequential Simulation (DSS), as a promising methodology for the homogenisation of precipitation data series. Based on the spatial and temporal correlation between the neighbouring stations, DSS calculates local probability density functions at a candidate station to detect inhomogeneities. Here, we present a new method named gsimcli (Geostatistical SIMulation for the homogenisation of CLImate data), which is an improved and extended version of that approach. This technique is novel in its incorporation of spatial correlation metrics for the homogenisation of climate time series. The method's performance is assessed with annual and monthly precipitation, and monthly temperature data from two regions of the COST-HOME benchmark data set, and the results are compared using performance metrics. We also evaluate a semi-automatic version of the gsimcli method, which performs additional adjustments for sudden shifts. Both gsimcli versions provided similar results in the homogenisation of annual series. The gsimcli method was more efficient in the homogenisation of the benchmark's precipitation series than the original geostatistical approach. The gsimcli approach performed more closely to state-of-the-art procedures in the homogenisation of monthly data than in the homogenisation of annual data. We expect that the proposed procedure will open new perspectives for the development of techniques that detect and correct inhomogeneities in climate data with monthly and sub-monthly resolution.

ACS Style

Sara Ribeiro; Júlio Caineta; Ana Cristina Costa; Roberto Henriques. gsimcli: a geostatistical procedure for the homogenisation of climatic time series. International Journal of Climatology 2016, 37, 3452 -3467.

AMA Style

Sara Ribeiro, Júlio Caineta, Ana Cristina Costa, Roberto Henriques. gsimcli: a geostatistical procedure for the homogenisation of climatic time series. International Journal of Climatology. 2016; 37 (8):3452-3467.

Chicago/Turabian Style

Sara Ribeiro; Júlio Caineta; Ana Cristina Costa; Roberto Henriques. 2016. "gsimcli: a geostatistical procedure for the homogenisation of climatic time series." International Journal of Climatology 37, no. 8: 3452-3467.

Journal article
Published: 01 August 2016 in Physics and Chemistry of the Earth, Parts A/B/C
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ACS Style

S. Ribeiro; J. Caineta; Ana Cristina Costa. Review and discussion of homogenisation methods for climate data. Physics and Chemistry of the Earth, Parts A/B/C 2016, 94, 167 -179.

AMA Style

S. Ribeiro, J. Caineta, Ana Cristina Costa. Review and discussion of homogenisation methods for climate data. Physics and Chemistry of the Earth, Parts A/B/C. 2016; 94 ():167-179.

Chicago/Turabian Style

S. Ribeiro; J. Caineta; Ana Cristina Costa. 2016. "Review and discussion of homogenisation methods for climate data." Physics and Chemistry of the Earth, Parts A/B/C 94, no. : 167-179.

Journal article
Published: 01 May 2016 in Atmospheric Research
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ACS Style

Sara Ribeiro; Júlio Caineta; Ana Cristina Costa; Roberto Henriques; Amílcar Soares. Detection of inhomogeneities in precipitation time series in Portugal using direct sequential simulation. Atmospheric Research 2016, 171, 147 -158.

AMA Style

Sara Ribeiro, Júlio Caineta, Ana Cristina Costa, Roberto Henriques, Amílcar Soares. Detection of inhomogeneities in precipitation time series in Portugal using direct sequential simulation. Atmospheric Research. 2016; 171 ():147-158.

Chicago/Turabian Style

Sara Ribeiro; Júlio Caineta; Ana Cristina Costa; Roberto Henriques; Amílcar Soares. 2016. "Detection of inhomogeneities in precipitation time series in Portugal using direct sequential simulation." Atmospheric Research 171, no. : 147-158.

Journal article
Published: 14 August 2015 in Procedia Environmental Sciences
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Non-natural irregularities are an inevitable part of long-time climate records. They are originated during the process of measuring and collecting data from weather stations. In order to use those records as an input for environmental projects or climate studies, it is essential to detect and correct the irregularities through the process of homogenisation. The use of geostatistical approaches as homogenisation techniques has already been proven to be successful. The gsimcli homogenisation process is based on a geostatistical simulation method, the direct sequential simulation. This method generates a set of equally probable and independent realisations, and calculates a probability distribution function at the candidate station's location. This probability distribution function is then used in the identification and correction of irregularities. Currently, gsimcli is being developed into an open source software package. During the homogenisation process, gsimcli requires the selection of several parameters in the detection and correction of irregularities. The candidate stations’ order to be homogenised, the value of the probability used in the detection of irregularities, and the statistic value to be used in the correction of the irregularity or in the replacement of missing data, are examples of parameters to be chosen for the homogenisation with gsimcli. This work presents a sensitivity analysis of those parameters, in order to find the most suitable set of values for the homogenisation of monthly precipitation data. A benchmark data set, comprising climate records from an Austrian precipitation network, will be used in this analysis. Performance metrics are calculated to evaluate the efficiency of the homogenisation process. The set of parameters providing the best values of performance metrics will be defined as the default set of homogenisation parameters for precipitation data.

ACS Style

S. Ribeiro; J. Caineta; Ana Cristina Costa; A. Soares. Establishment of Detection and Correction Parameters for a Geostatistical Homogenisation Approach. Procedia Environmental Sciences 2015, 27, 83 -88.

AMA Style

S. Ribeiro, J. Caineta, Ana Cristina Costa, A. Soares. Establishment of Detection and Correction Parameters for a Geostatistical Homogenisation Approach. Procedia Environmental Sciences. 2015; 27 ():83-88.

Chicago/Turabian Style

S. Ribeiro; J. Caineta; Ana Cristina Costa; A. Soares. 2015. "Establishment of Detection and Correction Parameters for a Geostatistical Homogenisation Approach." Procedia Environmental Sciences 27, no. : 83-88.

Journal article
Published: 17 April 2015 in Theoretical and Applied Climatology
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Drought is among the least understood natural hazards and requires particular notice in the context of climate change. While the Mediterranean climate is by itself prone to droughts, a rise of temperatures and alteration of rainfall patterns already render the southern parts of continental Portugal and Spain highly susceptible to desertification. Precipitation in the Iberian Peninsula is mainly controlled by the large-scale mode of North Atlantic Oscillation (NAO) and is distributed with elevated variability over the cold months. Most drought studies of this region rely on meteorological data or apply information on vegetation dynamics, such as the Normalised Differenced Vegetation Index (NDVI), to indirectly investigate droughts. This paper evaluates the influence of the NAO winter index on the spatiotemporal occurrence of droughts in the Iberian Peninsula during the spring and summer seasons (March to August) for the years 2001–2005, 2007 and 2010. We applied the Vegetation Temperature Condition Index (VTCI) to identify local droughts. VTCI is a remote sensing drought index developed for reflecting soil moisture conditions in agricultural areas and combines information on land surface temperature (LST) and NDVI. As such, VTCI overcomes the shortcomings of NDVI in terms of drought monitoring. We derived biweekly information on LST and NDVI from MODIS/Terra and produced VTCI–NAO correlation maps at a confidence level of at least 90 % based on the VTCI time series. The results reflect a typical Mediterranean pattern in most parts of Iberia that is highly influenced by relief. Spring seasons are marked by great variability of precipitation, while summers persistently become dry, particularly in the south. NAO exerts its greatest influence in April and June, clearly delineating high correlation areas in the northwest and southeast with reverse patterns between the spring and early summer months. Due to the impact on water availability, the spring months are important for plant growth. At the same time, agricultural lands were found with types of land cover less resilient to droughts. The knowledge acquired in studies like the one reported here is therefore likely to be used in drought warning models for agriculture in spring.

ACS Style

Stefan Mühlbauer; Ana Cristina Costa; Mario Caetano. A spatiotemporal analysis of droughts and the influence of North Atlantic Oscillation in the Iberian Peninsula based on MODIS imagery. Theoretical and Applied Climatology 2015, 124, 703 -721.

AMA Style

Stefan Mühlbauer, Ana Cristina Costa, Mario Caetano. A spatiotemporal analysis of droughts and the influence of North Atlantic Oscillation in the Iberian Peninsula based on MODIS imagery. Theoretical and Applied Climatology. 2015; 124 (3-4):703-721.

Chicago/Turabian Style

Stefan Mühlbauer; Ana Cristina Costa; Mario Caetano. 2015. "A spatiotemporal analysis of droughts and the influence of North Atlantic Oscillation in the Iberian Peninsula based on MODIS imagery." Theoretical and Applied Climatology 124, no. 3-4: 703-721.

Journal article
Published: 14 July 2014 in Meteorological Applications
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Data scarcity is a major scientific challenge for accuracy and precision of the spatial interpolation of climatic fields, especially in climate‐stressed developing countries. Methodologies have been suggested for coping with data scarcity but data have rarely been checked for their representativeness of corresponding climatic fields. This study proved that satisfactory accuracy and precision can be ensured in spatial interpolation if data are satisfactorily representative of corresponding climatic fields despite their scarcity. The influence of number and representativeness of climate data on accuracy and precision of their spatial interpolation has been investigated and compared. Two precipitation and temperature indices were computed for a long time series in Bangladesh, which is a data‐scarce region. The representativeness was quantified by dispersion in the data and the accuracy and precision of spatial interpolation were computed by four commonly used error statistics derived through cross‐validation. The precipitation data showed very little and sometimes null representativeness whereas the temperature data showed very high representativeness of the corresponding fields. Consequently, precipitation data denoted scarcity but the temperature data denoted sufficiency regarding the required number of data for ensuring satisfactory accuracy and precision for spatial interpolation. It was also found that with the available data, accurate and precise precipitation surfaces can be produced only for representative synoptic spatial scales whereas such temperature surfaces can be generated for the regional scale of Bangladesh. It is highly recommended that the rain‐gauge network of Bangladesh be increased or redistributed for computing representative regional precipitation surfaces.

ACS Style

Avit Kumar Bhowmik; Ana Cristina Costa. Representativeness impacts on accuracy and precision of climate spatial interpolation in data-scarce regions. Meteorological Applications 2014, 22, 368 -377.

AMA Style

Avit Kumar Bhowmik, Ana Cristina Costa. Representativeness impacts on accuracy and precision of climate spatial interpolation in data-scarce regions. Meteorological Applications. 2014; 22 (3):368-377.

Chicago/Turabian Style

Avit Kumar Bhowmik; Ana Cristina Costa. 2014. "Representativeness impacts on accuracy and precision of climate spatial interpolation in data-scarce regions." Meteorological Applications 22, no. 3: 368-377.

Scholarly incursion
Published: 15 July 2013 in Historical Methods: A Journal of Quantitative and Interdisciplinary History
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Surpassing the national perspective usually adopted, the authors confirmed the existence of a pattern of population distribution common to the whole Iberian Peninsula in the long run. This pattern is clearly associated with geographical factors. These variables seem to have more weight in explaining changes between 1877/78 and 1940 than in the period from 1940 to 2001. The observation of the cross-border region has shown that proximity to the frontier has not generated any distinct pattern of population density on either side of the boundary line. The spatial coherence of the observed phenomena throughout the Peninsula and of its evolution, independent of the border between states, reinforces the importance of geographic factors in their explanation. At the same time, this verification opens up new issues related to the effect of national political and economic policies.

ACS Style

Luís Espinha Da Silveira; Daniel Alves; Marco Painho; Ana Cristina Costa; Ana Alcântara. The Evolution of Population Distribution on the Iberian Peninsula: A Transnational Approach (1877–2001). Historical Methods: A Journal of Quantitative and Interdisciplinary History 2013, 46, 157 -174.

AMA Style

Luís Espinha Da Silveira, Daniel Alves, Marco Painho, Ana Cristina Costa, Ana Alcântara. The Evolution of Population Distribution on the Iberian Peninsula: A Transnational Approach (1877–2001). Historical Methods: A Journal of Quantitative and Interdisciplinary History. 2013; 46 (3):157-174.

Chicago/Turabian Style

Luís Espinha Da Silveira; Daniel Alves; Marco Painho; Ana Cristina Costa; Ana Alcântara. 2013. "The Evolution of Population Distribution on the Iberian Peninsula: A Transnational Approach (1877–2001)." Historical Methods: A Journal of Quantitative and Interdisciplinary History 46, no. 3: 157-174.

Journal article
Published: 27 August 2012 in Journal of Arid Environments
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Increased aridity is a robust proximate cause of desertification, both indirectly through greater rainfall variability and directly through prolonged droughts. The south of continental Portugal has large areas with high susceptibility to desertification. This study evaluates local dynamics in dryness in the south of Portugal based on the Aridity Intensity Index (AII), which is a numerical indicator of the degree of dryness of the climate and an indirect indicator of soil moisture availability. The AII was computed using daily precipitation data from stations with records within the 1940–1999 period in the south of Portugal. Annual scenarios of the AII were generated from 1940 to 1999 using direct sequential simulation (DSS). Those scenarios were then used to produce an additional set of maps that summarize their underlying space–time patterns. Two desertification indicators accounting for local dryness dynamics are proposed, namely the Dryness Susceptibility Indicator and the Dryness Trend Indicator. The results show that the southeast region is the most threatened by droughts and extreme dryness. Moreover, there is a tendency towards drier climatic conditions in coastal areas and in the centre of the study region. These findings are likely to have profound implications in agricultural planning and water supply management.

ACS Style

A.C. Costa; A. Soares. Local spatiotemporal dynamics of a simple aridity index in a region susceptible to desertification. Journal of Arid Environments 2012, 87, 8 -18.

AMA Style

A.C. Costa, A. Soares. Local spatiotemporal dynamics of a simple aridity index in a region susceptible to desertification. Journal of Arid Environments. 2012; 87 ():8-18.

Chicago/Turabian Style

A.C. Costa; A. Soares. 2012. "Local spatiotemporal dynamics of a simple aridity index in a region susceptible to desertification." Journal of Arid Environments 87, no. : 8-18.

Journal article
Published: 01 January 2012 in International Journal of Geosciences
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Geographical assessments on the relationship between climate variability and crop production are important for planning adaptation programs to climate change impacts on Asian rice production. This paper analyses the seasonal precipitation consequences to irrigated crop yields, in opposition to the idea that irrigated crop yields are not affected by precipitation changes. Geostatistical methods are applied to assess changes in the patterns of seasonal precipitation and corresponding changes in the Boro crop production in Bangladesh. Surfaces depicting changes in the monsoon, non-monsoon and total precipitation from 2006 to 2007, and changes in three varieties of Boro crop yield and Total Boro yield from 2006-2007 to 2007-2008 crop year are generated through Splines, Inverse Distance Weighting and Ordinary Kriging methods. Performance evaluation of these models is also performed. The relationships between the surfaces of different precipitation seasons and the surfaces of different Boro yield seasons are then assessed. The results show that there is a significant correlation between seasonal precipitation changes and Boro yield changes with notable correlation coefficients and similarity in the patterns. A significant conformity of the high precipitation zones to the high Boro yielding zones is also depicted.

ACS Style

Avit Bhowmik; Ana Cristina Costa. A Geostatistical Approach to the Seasonal Precipitation Effect on Boro Rice Production in Bangladesh. International Journal of Geosciences 2012, 03, 443 -462.

AMA Style

Avit Bhowmik, Ana Cristina Costa. A Geostatistical Approach to the Seasonal Precipitation Effect on Boro Rice Production in Bangladesh. International Journal of Geosciences. 2012; 03 (03):443-462.

Chicago/Turabian Style

Avit Bhowmik; Ana Cristina Costa. 2012. "A Geostatistical Approach to the Seasonal Precipitation Effect on Boro Rice Production in Bangladesh." International Journal of Geosciences 03, no. 03: 443-462.

Original paper
Published: 29 September 2011 in Theoretical and Applied Climatology
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Precipitation indices are commonly used as climate change indicators. Considering four Climate Variability and Predictability-recommended indices, this study assesses possible changes in their spatial patterns over Portugal under future climatic conditions. Precipitation data from the regional climate model Consortium for Small-Scale Modelling–Climate version of the Local Model (CCLM) ensemble simulations with ECHAM5/MPI-OM1 boundary conditions are used for this purpose. For recent–past, medians and probability density functions of the CCLM-based indices are validated against station-based and gridded observational dataset from ENSEMBLES-based (gridded daily precipitation data provided by the European Climate Assessment & Dataset project) indices. It is demonstrated that the model is able to realistically reproduce not only precipitation but also the corresponding extreme indices. Climate change projections for 2071–2100 (A1B and B1 SRES scenarios) reveal significant decreases in total precipitation, particularly in autumn over northwestern and southern Portugal, though changes exhibit distinct local and seasonal patterns and are typically stronger for A1B than for B1. The increase in winter precipitation over northeastern Portugal in A1B is the most important exception to the overall drying trend. Contributions of extreme precipitation events to total precipitation are also expected to increase, mainly in winter and spring over northeastern Portugal. Strong projected increases in the dry spell lengths in autumn and spring are also noteworthy, giving evidence for an extension of the dry season from summer to spring and autumn. Although no coupling analysis is undertaken, these changes are qualitatively related to modifications in the large-scale circulation over the Euro-Atlantic area, more specifically to shifts in the position of the Azores High and associated changes in the large-scale pressure gradient over the area.

ACS Style

Ana C. Costa; João Carlos Andrade dos Santos; Joaquim G. Pinto. Climate change scenarios for precipitation extremes in Portugal. Theoretical and Applied Climatology 2011, 108, 217 -234.

AMA Style

Ana C. Costa, João Carlos Andrade dos Santos, Joaquim G. Pinto. Climate change scenarios for precipitation extremes in Portugal. Theoretical and Applied Climatology. 2011; 108 ():217-234.

Chicago/Turabian Style

Ana C. Costa; João Carlos Andrade dos Santos; Joaquim G. Pinto. 2011. "Climate change scenarios for precipitation extremes in Portugal." Theoretical and Applied Climatology 108, no. : 217-234.

Journal article
Published: 09 May 2011 in Advances in Geosciences
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This paper analyzes the yearly changes in precipitation from 1940 to 1999 on local and regional scales over the southern region of continental Portugal, which has large areas threatened by desertification. The Standard Precipitation Index (SPI) time series with the 12-month time scale is calculated for 43 meteorological stations. A geostatistical approach is used to evaluate the temporal dynamics of the spatial patterns of precipitation. The spatial homogeneity of the SPI is evaluated for each decade. Afterwards, a geostatistical simulation algorithm (direct sequential simulation) is used to produce 100 equiprobable maps of the SPI for each year. This gridded data set (6000 maps with 800 m × 800 m grid cells) is then used to produce yearly scenarios of the SPI from 1940 to 1999, and uncertainty evaluations of the produced scenarios. The linear trend of SPI values over the sixty years period is calculated at each grid cell of the scenarios' maps using a nonparametric estimator. Wilcoxon-Mann-Whitney one-sided tests are used to compare the local median of the SPI in 1940/1969 with its median in 1970/1999. Results show that moderate drought conditions occur frequently over the study region, except in the northwest coast. Severe drought frequency patterns are found in areas of the centre and southeast regions. A significant trend towards drying occurs in the centre region and in the northeast. Considering the amount of water consumption and irrigation already required in some municipalities, water shortage due to drought is a viable threat in most of the Alentejo region if those local trends persist.

ACS Style

A. C. Costa. Local patterns and trends of the Standard Precipitation Index in southern Portugal (1940–1999). Advances in Geosciences 2011, 30, 11 -16.

AMA Style

A. C. Costa. Local patterns and trends of the Standard Precipitation Index in southern Portugal (1940–1999). Advances in Geosciences. 2011; 30 ():11-16.

Chicago/Turabian Style

A. C. Costa. 2011. "Local patterns and trends of the Standard Precipitation Index in southern Portugal (1940–1999)." Advances in Geosciences 30, no. : 11-16.

Journal article
Published: 01 March 2011 in Trends in Applied Sciences Research
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ACS Style

J. Negreiros; Ana Cristina Costa; M. Painho. Evaluation of Stochastic Geographical Matters: Morphologic Geostatistics, Conditional Sequential Simulation and Geographical Weighted Regression. Trends in Applied Sciences Research 2011, 6, 237 -255.

AMA Style

J. Negreiros, Ana Cristina Costa, M. Painho. Evaluation of Stochastic Geographical Matters: Morphologic Geostatistics, Conditional Sequential Simulation and Geographical Weighted Regression. Trends in Applied Sciences Research. 2011; 6 (3):237-255.

Chicago/Turabian Style

J. Negreiros; Ana Cristina Costa; M. Painho. 2011. "Evaluation of Stochastic Geographical Matters: Morphologic Geostatistics, Conditional Sequential Simulation and Geographical Weighted Regression." Trends in Applied Sciences Research 6, no. 3: 237-255.

Chapter
Published: 26 May 2010 in Encyclopedia of Networked and Virtual Organizations
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Geographic information systems are largely used in different levels of administration and planning where geo-referenced information is a crucial factor behind analysis and determination of different decision-making scenarios. The potential of these systems is increasingly being perceived as a support to facilitate public participation in planning processes.

ACS Style

Dulce Magalhaes De Sá; Ana Cristina M. Costa. Participatory Geographic Information Systems. Encyclopedia of Networked and Virtual Organizations 2010, 1179 -1184.

AMA Style

Dulce Magalhaes De Sá, Ana Cristina M. Costa. Participatory Geographic Information Systems. Encyclopedia of Networked and Virtual Organizations. 2010; ():1179-1184.

Chicago/Turabian Style

Dulce Magalhaes De Sá; Ana Cristina M. Costa. 2010. "Participatory Geographic Information Systems." Encyclopedia of Networked and Virtual Organizations , no. : 1179-1184.

Journal article
Published: 26 February 2009 in Natural Hazards and Earth System Sciences
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Most of the actual studies and previews of future rainfall patterns, based on past observed records for Mediterranean climate areas, focus on the decline of the rainfall amounts over the years, and also on the increase of the frequency of heavy/intense rainfall events particularly in the winter season. These changes in heavy rainfall events may have severe implications and impacts on soil erosion resulting in increased soil degradation risks. The objective of the present work is to evaluate the spatial distribution of extreme precipitation events in Southern Portugal, using a geostatistical approach to assess the relationships between spatial and temporal extreme rainfall patterns. The used dataset comprises a set of 105 stations' records of daily precipitation within the period 1960–1999. Two indices of extreme precipitation were selected to be computed based on the daily precipitation observation series: one representing the frequency of extremely heavy precipitation events (R30) and another one characterizing flood events (R5D). The space-time patterns of the precipitation indices were evaluated and simulated using a geostatistical approach. Despite no significant temporal trends were detected on the calculated indices series, the space-time decadal patterns are becoming more continuous in the last two decades than the previous ones.

ACS Style

Rita Durão; M. J. Pereira; Ana Cristina Costa; J. M. Côrte-Real; Amilcar Soares. Indices of precipitation extremes in Southern Portugal – a geostatistical approach. Natural Hazards and Earth System Sciences 2009, 9, 241 -250.

AMA Style

Rita Durão, M. J. Pereira, Ana Cristina Costa, J. M. Côrte-Real, Amilcar Soares. Indices of precipitation extremes in Southern Portugal – a geostatistical approach. Natural Hazards and Earth System Sciences. 2009; 9 (1):241-250.

Chicago/Turabian Style

Rita Durão; M. J. Pereira; Ana Cristina Costa; J. M. Côrte-Real; Amilcar Soares. 2009. "Indices of precipitation extremes in Southern Portugal – a geostatistical approach." Natural Hazards and Earth System Sciences 9, no. 1: 241-250.