AUTHOR=Alvial Vásquez Francisco-J. , Abarca-del-Río Rodrigo , Ávila Andrés I. 

TITLE=High-Resolution Precipitation Gridded Dataset on the South-Central Zone (34° S–41° S) of Chile

JOURNAL=Frontiers in Earth Science

VOLUME=8

YEAR=2020

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2020.519975

DOI=10.3389/feart.2020.519975

ISSN=2296-6463

ABSTRACT=<p>Chile is well known as a narrow and long country (over 4,000 km) that encompasses many climate zones and that presents significant west–east gradients as altitudes change from sea level to several thousand meters. Although Chile is recognized as one of the most affected countries by climate change, it is also one of the least covered by hydrometeorological measuring instruments. This data scarcity prevents thorough characterization of hydrological basins. To solve this problem, we constructed a decade-long (2000–2011) high-resolution <inline-formula id="inf2"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mo>∼</mml:mo><mml:mn>800</mml:mn><mml:mtext> m</mml:mtext></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math></inline-formula> monthly gridded precipitation product for the central-southern zone <inline-formula id="inf3"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msup><mml:mn>34</mml:mn><mml:mo>∘</mml:mo></mml:msup><mml:mtext>S–</mml:mtext><mml:msup><mml:mn>41</mml:mn><mml:mo>∘</mml:mo></mml:msup><mml:mtext>S</mml:mtext></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math></inline-formula> covering regions from O’Higgins to Los Ríos. These regions contain most of Chile’s agricultural land, livestock, forestry, and hydroelectric production. The study zone covers a variety of topographies and climates, including eight hydrological basins: Rapel, Mataquito, Maule, Itata, BioBío, Imperial, Toltén, and Valdivia. We develop a dynamic topo-climatic methodology that includes local and global data. We combined a dynamic downscaling and a spatial-temporal multivariate model over different geographical areas that considered high-resolution precipitation fields from model data, <italic>in situ</italic> stations, and different global precipitation datasets that also understand satellite observations. Results show that most of the precipitation spatial-temporal variability is well-captured by the model in the north and central regions, from O’Higgins to Biobío, with the goodness of fit <inline-formula id="inf4"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:msup><mml:mi>R</mml:mi><mml:mn>2</mml:mn></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math></inline-formula> fluctuating around 0.86 and 0.82, respectively. Toward the south, Araucanía and Los Ríos, the goodness of fit <inline-formula id="inf5"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:msup><mml:mi>R</mml:mi><mml:mn>2</mml:mn></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math></inline-formula> decreased to values around 0.74 and 0.72, respectively. Both the modified Willmott coefficient <inline-formula id="inf6"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mi>d</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math></inline-formula> and the <italic>nse</italic> indicated a good model skill, with values over 0.8 and 0.7, respectively. Meanwhile, the <inline-formula id="inf7"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>σ</mml:mi><mml:mi>e</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, <italic>nrmse</italic>, and <italic>pbias</italic> changed between <inline-formula id="inf8"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>0.04</mml:mn><mml:mtext>–</mml:mtext><mml:mn>0.2</mml:mn></mml:mrow></mml:math></inline-formula>, <inline-formula id="inf9"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>0.35</mml:mn><mml:mtext>–</mml:mtext><mml:mn>0.52</mml:mn></mml:mrow></mml:math></inline-formula>, and <inline-formula id="inf10"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>12</mml:mn><mml:mtext>–</mml:mtext><mml:mn>22</mml:mn><mml:mtext>%</mml:mtext></mml:mrow></mml:math></inline-formula>, respectively. This database is freely available to different regional or national institutions and will help the development of a better understanding and management of local and regional hydrology.</p>