Dry season circulation‐type classification applied to precipitation and temperature in the Peruvian Andes

Bonshoms, Martí; Alvarez-Garcia, F.; Úbeda, José; Cabos, William; Quispe, Kelita; Liguori, Giovanni

doi:10.1002/joc.6593

Cited by 2 publications

(4 citation statements)

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“…Therefore, the four central months of the dry (MJJA) and wet (DJFM) seasons were considered as proposed in previous works (eg. Bonshoms et al 2020;Francou et al 2003;Kane 2000;Rosales et al 2022;Segura et al 2019). These four-month periods allowed us to reduce distortions that could arise due to regional differences in the length of both seasons.…”

Section: Hourly Assessment and Mean Daily Cyclesmentioning

confidence: 98%

“…In general terms, fluctuations in upperlevel zonal winds are related to the moisture transport variability at the diurnal (Garreaud et al 2009;Reuder and Egger 2006), intraseasonal (Falvey and Garreaud 2005;Garreaud 2000) and interannual time scales (Garreaud and Aceituno 2001;Garreaud et al 2003;Vuille and Keimig 2004;Segura et al 2016). However, in the southern Peruvian Andes negative (positive) anomalies in daily maximum and minimum temperatures (precipitation) during the DS were related to the presence of extratropical upper tropospheric troughs located off the southern coast of Peru (Bonshoms et al 2020). In addition, the influence of dynamic and orographic convergence of moist air from the Amazon may have an impact on precipitation over the eastern Andes glaciers (Cordillera Vilcanota and, to a lesser intensity, in Cordillera Blanca).…”

Section: Study Areamentioning

confidence: 99%

“…Cordillera Vilcanota (CV): A mountain range located in the eastern Peruvian Andes with a glacier surface of 255.44 km 2 (INAIGEM 2018). Wetter conditions prevail due to their proximity to the rainfall hot spot east of the Andes (Chavez and Takahashi 2017) and the occasional influence of upper tropospheric troughs during the austral winter (Bonshoms et al 2020). The Quelccaya ice-cap with a surface of 42.8 km 2 in 2009 (Salzmann et al 2013) has been considered the largest tropical glacier for many years (Salzmann et al 2013;Thompson et al 2006).…”

Section: Study Areamentioning

confidence: 99%

“…Based on the classification proposed in Bonshoms et al (2020), we included the four analysed Peruvian glaciers in 3 different climatic regimes (Fig. 1):…”

Section: Study Areamentioning

confidence: 99%

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Validation of ERA5-Land temperature and relative humidity on four Peruvian glaciers using on-glacier observations

et al. 2022

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Weather and climate conditions drive the evolution of tropical glaciers which play an important role as water reservoirs for Peruvian inhabitants in the arid coast and semi-arid Andean region. The scarcity of long-term high-quality observations over Peruvian glaciers has motivated the extensive use of reanalysis data to describe the climatic evolution of these glaciers. However, the representativeness and uncertainties of these reanalysis products over these glaciers are still poorly constrained. This study evaluates the ability of the ERA5-Land reanalysis (ERA5L) to reproduce hourly and monthly 2 m air temperature and relative humidity (T2m and Rh2m, respectively) over several Peruvian glaciers. We compared the ERA5L with data from four on-glacier automatic weather stations (AWS), whose hourly time series were completed with nearby stations, for the period January 2017 to December 2019. Results indicates a better performance of the reanalysis for T2m (r >0.80) than for Rh2m (∼0.4< r <∼0.6) in all four glaciers. Concerning the observations, both parameters show a daily cycle influenced by the presence of the glacier. This influence is more prominent during the dry months when the so-called glacier damping and cooling effects are stronger. On a monthly time scale, the ERA5L validation for both parameters are better in wet outer tropical sites (RMSE between ±0.2°C for T2m and between 3%–7% for Rh2m) rather than in dry outer tropical sites (RMSE between ±0.2°C for T2m and between 3%–7% for Rh2m). Among all sites considered in the study, the Rh2m bias is the highest in the Cavalca glacier (correlation of 0.81; RMSE 13%, MAE 11% and bias 8.3%) and the lowest in Artesonraju glacier (correlation of 0.96; RMSE 3%; MAE 2.3% and bias — 0.8%). Based on certain considerations outlined in this paper, it is appropriate to use ERA5L to characterize T2m and Rh2m conditions on Peruvian glaciers, particularly in the wet outer tropics.

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Section: Hourly Assessment and Mean Daily Cyclesmentioning

confidence: 98%

Section: Study Areamentioning

confidence: 99%

Section: Study Areamentioning

confidence: 99%

“…Based on the classification proposed in Bonshoms et al (2020), we included the four analysed Peruvian glaciers in 3 different climatic regimes (Fig. 1):…”

Section: Study Areamentioning

confidence: 99%

See 2 more Smart Citations