PISCOeo_pm, a reference evapotranspiration gridded database based on FAO Penman-Monteith in Peru

Huerta, Adrian; Bonnesoeur, Vivien; Cuadros-Adriazola, José; Gutierrez, Leonardo; Ochoa‐Tocachi, B. F.; Román-Dañobeytia, Francisco; Lavado‐Casimiro, Waldo

doi:10.1038/s41597-022-01373-8

Cited by 12 publications

(7 citation statements)

References 93 publications

(101 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The records of the target station with differences greater than a percentile of 0.85 concerning the average of the neighbouring stations were identified. The percentile difference approach allows for identifying only the most extreme spatial variations 71 – 73 . Visual inspection: a visual inspection of the daily time series was carried out to identify periods with inhomogeneities that cannot be corrected (rounding errors, asymmetric rounding patterns, measurement precision, time irregularities, and obvious inhomogeneities) 51 , 74 .…”

Section: Methodsmentioning

confidence: 99%

High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset

Huerta,

Aybar,

Imfeld

et al. 2023

Sci Data

Self Cite

View full text Add to dashboard Cite

Gridded high-resolution climate datasets are increasingly important for a wide range of modelling applications. Here we present PISCOt (v1.2), a novel high spatial resolution (0.01°) dataset of daily air temperature for entire Peru (1981–2020). The dataset development involves four main steps: (i) quality control; (ii) gap-filling; (iii) homogenisation of weather stations, and (iv) spatial interpolation using additional data, a revised calculation sequence and an enhanced version control. This improved methodological framework enables capturing complex spatial variability of maximum and minimum air temperature at a more accurate scale compared to other existing datasets (e.g. PISCOt v1.1, ERA5-Land, TerraClimate, CHIRTS). PISCOt performs well with mean absolute errors of 1.4 °C and 1.2 °C for maximum and minimum air temperature, respectively. For the first time, PISCOt v1.2 adequately captures complex climatology at high spatiotemporal resolution and therefore provides a substantial improvement for numerous applications at local-regional level. This is particularly useful in view of data scarcity and urgently needed model-based decision making for climate change, water balance and ecosystem assessment studies in Peru.

show abstract

Section: Methodsmentioning

confidence: 99%

High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset

Huerta,

Aybar,

Imfeld

et al. 2023

Sci Data

Self Cite

View full text Add to dashboard Cite

show abstract

“…With CAI, deviations from the average (anomalies) on a given day were interpolated and combined with an average field (climatology) to produce the final daily product. The CAI approach has been employed in several studies 13,18,57,66 . It has proven to be effective in improving the accuracy of air temperature estimation in regions of complex terrain with limited observations [96][97][98][99] .…”

Section: Air Temperature Interpolationmentioning

confidence: 99%

High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset

Huerta¹,

Camacho²,

Imfeld³

et al. 2023

Preprint

View full text Add to dashboard Cite

This study describes the development of PISCOt (v1.2), an innovative high-spatial resolution (0.01°) daily air temperature dataset for Peru (1981-2020). The development of PISCOt involves four main steps: i) quality control; ii) gap-filling; iii) homogenisation of weather stations; and iv) spatial interpolation. The methodological framework allows the representation of the complex spatial variability of air temperature at a more accurate scale than other national and global products (e.g. PISCOt v1.1, ERA5-Land, TerraClimate, CHIRTS). The technical validation indicates mean absolute errors of less than 1.5 °C at climatological and daily mean scales. The new PISCOt dataset appropriately captures the temporal trends which highlights its usefulness to understand the historical variability of air temperature. For the first time, PISCOt v1.2 provides a suitable and widely applicable baseline at the local and regional level in the face of data scarcity in several regions of Peru for applications related to climate change, water balance studies, or the assessment of ecosystems, among others.

show abstract

“…In addition to the use of these three precipitation products, the PISCO precipitation product [30], developed by SENAMHI, was also employed to generate daily streamflows in the 30 basins, and we used these streamflows as observed values when quantifying the Skill Score (SS). Moreover, SENAMHI's evapotranspiration product [32] was used to complement the input variables for the GR4J model.…”

Section: Gridded Precipitation Productsmentioning

confidence: 99%

Assessment of Bottom-Up Satellite Precipitation Products on River Streamflow Estimations in the Peruvian Pacific Drainage

Qquenta,

Rau,

Bourrel

et al. 2023

Remote Sensing

Self Cite

View full text Add to dashboard Cite

In regions with limited precipitation information, like Peru, many studies rely on precipitation data derived from satellite products (SPP) and model reanalysis. These products provide near-real-time information and offer global spatial coverage, making them attractive for various applications. However, it is essential to consider their uncertainties when conducting hydrological simulations, especially in a key region like the Pacific drainage (Pd), where 56% of the Peruvian population resides (including the capital, Lima). This study, for the first time, assessed the performance of two bottom-up Satellite-based Precipitation Products (SPP), GPM + SM2RAIN and SM2RAIN-ASCAT, and one top-down approach SPP, ERA5-Land, for runoff simulation in the Pacific drainage of Peru. Hydrological modeling was conducted on 30 basins distributed across the Pd, which were grouped into 5 regions (I–V, ordered from south to north). The results showed that SM2RAIN-ASCAT performed well in regions I-III-IV, ERA5-Land in region II, and GPM + SM2RAIN in region V. The hydrological model GR4J was tested, and better efficiency criteria were obtained with SM2RAIN-ASCAT and GPM + SM2RAIN when comparing the simulated versus observed streamflows. The hydrological modeling using SM2RAIN-ASCAT and GPM + SM2RAIN demonstrated satisfactory efficiency metrics (KGE > 0.75; NSE > 0.65). Additionally, ten hydrological signatures were quantified to assess the variability of the simulated streamflows in each basin, with metrics such as Mean Flow (Q mean), 5th Quantile Flow (Q5), and 95th Quantile Flow (Q95) showing an overall better performance. Finally, the results of this study demonstrate the reliability of using bottom-up satellite products in Pd basins.

show abstract

PISCOeo_pm, a reference evapotranspiration gridded database based on FAO Penman-Monteith in Peru

Cited by 12 publications

References 93 publications

High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset

High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset

High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset

Assessment of Bottom-Up Satellite Precipitation Products on River Streamflow Estimations in the Peruvian Pacific Drainage

Contact Info

Product

Resources

About