Virgílio A. Bento

Dr. Virgílio A. Bento

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 2018 in Agricultural and Forest Meteorology
Verified
Journal Article
Closed access
VBVirgílio A. Bento
Virgílio A. Bento
Célia GouveiaCélia Gouveia
Célia Gouveia
CDCarlos C. DaCamara
Carlos C. DaCamara
Isabel TrigoIsabel Trigo
Isabel Trigo

20 January 2022 in Weather and Climate Extremes
Verified
Journal Article
Open access
JZJingyu Zeng
Jingyu Zeng
RZRongrong Zhang
Rongrong Zhang
YQYanping Qu
Yanping Qu
VBVirgílio A. Bento
Virgílio A. Bento
TZTao Zhou
Tao Zhou
QWQianfeng Wang
Qianfeng Wang

1 July 2020 in Global and Planetary Change
Verified
Journal Article
Closed access
VBVirgílio A. Bento
Virgílio A. Bento
Célia GouveiaCélia Gouveia
Célia Gouveia
CDCarlos C. DaCamara
Carlos C. DaCamara
Renata LibonatiRenata Libonati
Renata Libonati
Isabel TrigoIsabel Trigo
Isabel Trigo

2 October 2015 in Remote Sensing
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Journal Article
Open access
PDF file
ADAnke Duguay-Tetzlaff
Anke Duguay-Tetzlaff
VBVirgílio A. Bento
Virgílio A. Bento
Frank-Michael GöttscheFrank-Michael Göttsche
Frank-Michael Göttsche
RSReto Stöckli
Reto Stöckli
Joao Paulo Afonso MartinsJoao Paulo Afonso Martins
Joao Paulo Afonso Martins
HKHeike Kunz
Heike Kunz
The European Organization for the Exploitation of Meteorological Satellites’ (EUMETSAT) Meteosat satellites provide the unique opportunity to compile a 30+ year land surface temperature (LST) climate data record. Since the Meteosat instrument on-board Meteosat 2–7 is equipped with a single thermal channel, single-channel LST retrieval algorithms are used to ensure consistency across Meteosat satellites. The present study compares the performance of two single-channel LST retrieval algorithms: (1) A physical radiative transfer-based mono-window (PMW); and (2) a statistical mono-window model (SMW). The performance of the single-channel algorithms is assessed using a database of synthetic radiances for a wide range of atmospheric profiles and surface variables. The two single-channel algorithms are evaluated against the commonly-used generalized split-window (GSW) model. The three algorithms are verified against more than 60,000 LST ground observations with dry to very moist atmospheres (total column water vapor (TCWV) 1–56 mm). Except for very moist atmospheres (TCWV > 45 mm), results show that Meteosat single-channel retrievals match those of the GSW algorithm by 0.1–0.5 K. This study also outlines that it is possible to put realistic uncertainties on Meteosat single-channel LSTs, except for very moist atmospheres: simulated theoretical uncertainties are within 0.3–1.0 K of the in situ root mean square differences for TCWV < 45 mm.

18 September 2022 in Remote Sensing
Verified
Journal Article
Open access
PDF file
XWXiaoping Wu
Xiaoping Wu
RZRongrong Zhang
Rongrong Zhang
VBVirgílio A. Bento
Virgílio A. Bento
SLSONG LENG
SONG LENG
Junyu QiJunyu Qi
Junyu Qi
QWQianfeng Wang
Qianfeng Wang
Climate change has exacerbated the frequency and severity of droughts worldwide. Evaluating the response of gross primary productivity (GPP) to drought is thus beneficial to improving our understanding of the impact of drought on the carbon cycle balance. Although many studies have investigated the relationship between vegetation productivity and dry/wet conditions, the capability of different drought indices of assessing the influence of water deficit is not well understood. Moreover, few studies consider the effects of drought on vegetation with a focus on periods of drought. Here, we investigated the spatial-temporal patterns of GPP, the standardized precipitation evapotranspiration index (SPEI), and the vapor pressure deficit (VPD) in China from 2001 to 2020 and examined the relationship between GPP and water deficit/drought for different vegetation types. The results revealed that SPEI and GPP were positively correlated over approximately 70.7% of the total area, and VPD was negatively correlated with GPP over about 66.2% of the domain. Furthermore, vegetation productivity was more negatively affected by water deficit in summer and autumn. During periods of drought, the greatest negative impact was on deciduous forests and croplands, and woody savannas were the least impacted. This research provides a scientific reference for developing mitigation and adaptation measures to lessen the impact of drought disasters under a changing climate.

29 July 2021 in Scientific Reports
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Journal Article
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VBVirgílio A. Bento
Virgílio A. Bento
ARAndreia F. S. Ribeiro
Andreia F. S. Ribeiro
Ana RussoAna Russo
Ana Russo
CGCélia M. Gouveia
Célia M. Gouveia
RCRita M. Cardoso
Rita M. Cardoso
PSPedro M. M. Soares
Pedro M. M. Soares
The impact of climate change on wheat and barley yields in two regions of the Iberian Peninsula is here examined. Regression models are developed by using EURO-CORDEX regional climate model (RCM) simulations, forced by ERA-Interim, with monthly maximum and minimum air temperatures and monthly accumulated precipitation as predictors. Additionally, RCM simulations forced by different global climate models for the historical period (1972–2000) and mid-of-century (2042–2070; under the two emission scenarios RCP4.5 and RCP8.5) are analysed. Results point to different regional responses of wheat and barley. In the southernmost regions, results indicate that the main yield driver is spring maximum temperature, while further north a larger dependence on spring precipitation and early winter maximum temperature is observed. Climate change seems to induce severe yield losses in the southern region, mainly due to an increase in spring maximum temperature. On the contrary, a yield increase is projected in the northern regions, with the main driver being early winter warming that stimulates earlier growth. These results warn on the need to implement sustainable agriculture policies, and on the necessity of regional adaptation strategies.