Can we replace observed forcing with weather generator in land surface modeling? Insights from long-term simulations at two contrasting boreal sites

Alves, Marco; Nadeau, Daniel F.; Music, Biljana; Anctil, François; Fatichi, Simone

doi:10.1007/s00704-021-03615-y

Cited by 2 publications

(1 citation statement)

References 85 publications

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“…According to Flores et al (2012), the area in the state of Sinaloa is predominantly classified as subtropical-intertropical, with zones of low topographic relief near the Pacific Ocean and extreme elevations in the mountain system known as the Sierra Madre Occidental. The climatic variabilityrandomness of this area can be numerically modeled using criteria based on significant trends (ST), adjusted return periods (ARP) and fitted probability distribution functions (Cohen et al, 2012;Rustom 2012;Franzke 2015;Kienzle 2018;Chapman et al, 2019;Garry et al, 2019;Latif & Mustafa 2020;Alves et al, 2021). These mathematical tools were used to characterize the climate variability (Llanes et al, 2022b;Llanes, 2023) and randomness of Sinaloa; i.e., indicators of hot extremes (HE, Llanes et al, 2022a), since determination of the STs can be helpful for identifying zones where extreme climate changes occur, and knowledge about such changes has been demonstrated to be very useful for designing adaptation/prevention strategies to face natural disasters (Blanco et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Calculation of indicators of maximum extreme temperature in Sinaloa state, northwestern Mexico

Llanes Cárdenas,

Cervantes Arce,

González González

2023

Earth sci. res. j.

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One of the climate problems that causes the most environmental impact worldwide is the trend of increasing occurrence of events of maximum extreme temperature, signaled by indicators such as hot extremes (HE) and maximum maximorum (highest maximum) temperature (MmT). These events can cause conditions ranging from severe droughts to heat stroke, which can cause death in any population. Indicators of maximum extreme temperature in one of the most important agricultural areas in northwestern Mexico were calculated based on significant trends (ST) and adjusted return periods. To calculate the trends of the maximum extreme temperature, frequency (FR), annual average duration (AAD), annual daily duration (ADD), intensity (IN) of HE, and MmT, the Mann-Kendall and Sen’s slope tests were applied to data obtained for 19 weather stations from the CLImate COMputing database for the period 1982–2014. Adjusted return periods (ARP) were calculated for each indicator of maximum extreme temperature by fitting a probability distribution function. For the study area, the ST and maximum extreme temperature shows a prevailing cooling trend. This can be deduced by observing the proportion of negative ST compared with positive ST. The highest positive magnitudes of ST were recorded at stations CUL (FR = 3.44 HE dec-1), GUT (AAD = 6.15 day HE-1 dec-1 and IN = 13.62 °C dec-1), IXP (ADD = 35.00 day dec-1) and POT (MmT = 2.50 °C day-1 dec-1). For ARP, the estimate of the average occurrence frequency of extreme events per100 years are FR = 6.11 HE dec-1 (1 time), AAD = 6.64 day HE-1 dec-1 (4 times), ADD = 38.68 day dec-1 (1 time), IN = 39.09 °C dec-1 (6 times) and MmT = 41.95 °C day-1 dec-1 (1 time). These findings are of key importance for the economic sectors related to agricultural production in the state known, at least to date, as “the breadbasket of Mexico” (Sinaloa). The results will help to develop adaptation/prevention measures before the coming socioeconomic and hydrological disasters.

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