Recent temperature variability and change in the Altiplano of Bolivia and Peru

López‐Moreno, Juan I.; Morán-Tejéda, Enrique; Vicente‐Serrano, Sergio M.; Bazo, Juan; Azorín-Molina, César; Revuelto, Jesús; Sánchez-Lorenzo, Arturo; Navarro-Serrano, Francisco; Aguilar, Enric; Chura, O.

doi:10.1002/joc.4459

Cited by 31 publications

(27 citation statements)

References 53 publications

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“…For example, the temperature increased by 0.15 to 0.25 • C·decades −1 over the 1965 to 2012 period [1]. ETp and ETr involved the same climatological factor for their estimation.…”

Section: Etp Etr and Rainfall Analysismentioning

confidence: 99%

Role of Climate Variability and Human Activity on Poopó Lake Droughts between 1990 and 2015 Assessed Using Remote Sensing Data

et al. 2017

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Abstract:In 2015, an emergency state was declared in Bolivia when Poopó Lake dried up. Climate variability and the increasing need for water are potential factors responsible for this situation. Because field data are missing over the region, no statements are possible about the influence of mentioned factors. This study is a preliminary step toward the understanding of Poopó Lake drought using remote sensing data. First, atmospheric corrections for Landsat (FLAASH and L8SR), seven satellite derived indexes for extracting water bodies, MOD16 evapotranspiration, PERSIANN-CDR and MSWEP rainfall products potentiality were assessed. Then, the fluctuations of Poopó Lake extent over the last 26 years are presented for the first time jointly, with the mean regional annual rainfall. Three main droughts are highlighted between 1990 and 2015: two are associated with negative annual rainfall anomalies in 1994 and 1995 and one associated with positive annual rainfall anomaly in 2015. This suggests that other factors than rainfall influenced the recent disappearance of the lake. The regional evapotranspiration increased by 12.8% between 2000 and 2014. Evapotranspiration increase is not homogeneous over the watershed but limited over the main agriculture regions. Agriculture activity is one of the major factors contributing to the regional desertification and recent disappearance of Poopó Lake.

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“…For example, the temperature increased by 0.15 to 0.25 • C·decades −1 over the 1965 to 2012 period [1]. ETp and ETr involved the same climatological factor for their estimation.…”

Section: Etp Etr and Rainfall Analysismentioning

confidence: 99%

Role of Climate Variability and Human Activity on Poopó Lake Droughts between 1990 and 2015 Assessed Using Remote Sensing Data

et al. 2017

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“…This was observed in many parts of the world and for various climate variables and indices, such as minimum temperature (López-Moreno et al, 2016), precipitation (Rosas et al, 2016;Vuille et al, 2003), diurnal temperature range (Jaswal et al, 2016;New et al, 2006), and extremes indices (Skansi et al, 2013;You et al, 2013). Certain trend differences may be expected even on short spatial scales due to factors such as topography and feedback processes (You et al, 2010).…”

Section: Introductionmentioning

confidence: 94%

“…For instance, studies have found stronger positive trends in maximum than minimum temperatures since the middle of the 20th century in the Bolivian and Peruvian Altiplano (e.g. López-Moreno et al, 2016), and Alexander et al (2006) detected a decrease in the number of warm nights in the same region. These findings are not in accordance with the globally observed and expected increase in night-time temperatures and the decrease in the diurnal temperature range (Alexander et al, 2006;Donat et al, 2013b;IPCC, 2013;Morak et al, 2011;New et al, 2006;QuintanaGomez, 1999;Vincent et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Effects of undetected data quality issues on climatological analyses

et al. 2018

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Abstract. Systematic data quality issues may occur at various stages of the data generation process. They may affect large fractions of observational datasets and remain largely undetected with standard data quality control. This study investigates the effects of such undetected data quality issues on the results of climatological analyses. For this purpose, we quality controlled daily observations of manned weather stations from the Central Andean area with a standard and an enhanced approach. The climate variables analysed are minimum and maximum temperature and precipitation. About 40 % of the observations are inappropriate for the calculation of monthly temperature means and precipitation sums due to data quality issues. These quality problems undetected with the standard quality control approach strongly affect climatological analyses, since they reduce the correlation coefficients of station pairs, deteriorate the performance of data homogenization methods, increase the spread of individual station trends, and significantly bias regional temperature trends. Our findings indicate that undetected data quality issues are included in important and frequently used observational datasets and hence may affect a high number of climatological studies. It is of utmost importance to apply comprehensive and adequate data quality control approaches on manned weather station records in order to avoid biased results and large uncertainties.

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“…Nevertheless, the approach is currently being implemented in several weather services [e.g. Météo‐France, the Norwegian Meteorological Institute, MeteoSwiss, the Irish Meteorological Service Met Éireann, and the Slovenian Environment Agency (Vertačnik et al ., )], and it is already applied in countries where station networks are sparse such as Bolivia (Vicente‐Serrano et al ., ; López‐Moreno et al ., ) or Tanzania (Luhunga et al ., ).…”

Section: Introductionmentioning

confidence: 99%

The influence of station density on climate data homogenization

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Hunziker

Begert

et al. 2017

Intl Journal of Climatology

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ABSTRACT:Relative homogenization methods assume that measurements of nearby stations experience similar climate signals and rely therefore on dense station networks with high-temporal correlations. In developing countries such as Peru, however, networks often suffer from low-station density. The aim of this study is to quantify the influence of network density on homogenization. To this end, the homogenization method HOMER was applied to an artificially thinned Swiss network.Four homogenization experiments, reflecting different homogenization approaches, were examined. Such approaches include diverse levels of interaction of the homogenization operators with HOMER, and different application of metadata. To evaluate the performance of HOMER in the sparse networks, a reference series was built by applying HOMER under the best possible conditions. Applied in completely automatic mode, HOMER decreases the reliability of temperature records. Therefore, automatic use of HOMER is not recommended. If HOMER is applied in interactive mode, the reliability of temperature and precipitation data may be increased in sparse networks. However, breakpoints must be inserted conservatively. Information from metadata should be used only to determine the exact timing of statistically detected breaks. Insertion of additional breakpoints based solely on metadata may lead to harmful corrections due to the high noise in sparse networks.

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Recent temperature variability and change in the Altiplano of Bolivia and Peru

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Cited by 31 publications

References 53 publications

Role of Climate Variability and Human Activity on Poopó Lake Droughts between 1990 and 2015 Assessed Using Remote Sensing Data

Role of Climate Variability and Human Activity on Poopó Lake Droughts between 1990 and 2015 Assessed Using Remote Sensing Data

Effects of undetected data quality issues on climatological analyses

The influence of station density on climate data homogenization

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