Hot Extremes and Climatological Drought Indicators in the Transitional Semiarid-Subtropical Region of Sinaloa, Northwest Mexico

Abstract

The main goal of this study was to explore the historical and recent spatial concurrence between the frequency (F), duration (D) and intensity (I) of hot extremes (HEs) and the frequency and evolution of meteorological drought in the region of Sinaloa. Based on the values of daily maximum temperature (Tmax) and precipitation obtained from CLImate COMputing for the interval April-October of a historical period and a recent period , the HE and the standardized precipitation index (SPI) were calculated on one-month (SPI-1) and four-month (SPI-4) timescales. Spearman rank correlation coefficients (Sr) were used to obtain the significant concurrences (SCs) between HEs and SPI-1, and HEs and SPI-4. El Quelite weather station showed the highest historical SCs between HEs and SPI-1 (−0.66≤Sr≤−0.57). Jaina is the only station that showed SCs with all four indicators of HEs and SPI-4 (−0.47≤Sr≤−0.34). In this study, the concurrence between HEs and SPI-1, and HEs and SPI-4 was determined for the first time. These are phenomena that can decrease the crop yield, particularly for rainfed crops such as maize, sesame and sorghum in the region commonly known as "the breadbasket of Mexico".

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

“…To obtain some of the most important variables used worldwide to characterize extreme weather, the following HE indicators were calculated following Li's method (Li et al, 2018): FR, AAD, ADD and IN. These authors define a HE event as occurring when the value of daily maximum temperature exceeds the 85 th and 90 th percentiles (P85 and P90, respectively) for three consecutive days (Stefanon et al, 2012, Zschenderlein et al, 2019and Llanes et al, 2022a. The values of MmT were obtained according to Ruiz et al (2005), who defined these variables as the maximum monthly value in a series of maximum daily temperatures.…”

“…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). Globally, the HE maximum maximorum (highest maximum) temperatures (MmT) are some of the most important indicators of change climate and can provide valuable information about the climate conditions to which the crops in a region are subjected (Li et al, 2018;Ruiz et al, 2005).…”

“…To learn about previous research related to this study, a review was done of the literature (documents available locally and worldwide). Jaiswal et al (2023) calculated extreme climate indices in India (hot days and daily maximum temperature) and Llanes et al (2022a) calculated indicators of MeT (HE and MmT) in Sinaloa, but did not calculate their trends or return periods through fitted probability distribution functions.…”

Modeling Yield of Irrigated and Rainfed Bean in Central and Southern Sinaloa State, Mexico, Based on Essential Climate Variables

“…Although this autumn-winter bean is the most widely cultivated in Sinaloa, there are still no predictive models of its IBY-RBY. This condition exacerbates the vulnerability of this crop to extreme essential climate variables events, such as frost [21], hot extremes [22], and CEP irregularity, which are common meteorological phenomena in this state [11,22].…”

Modeling of Yield of Irrigated and Rainfed Bean, Based on Essential Climatic Variables, in the Center and South from Sinaloa State, Mexico

“…Although autumn-winter bean is the most widely cultivated in Sinaloa, there are still no prediction models of IBY-RBY. This condition exacerbates the vulnerability of this crop to extreme ECV events, such as frost [25], hot extremes [26] and CEP irregularity, which are common meteorological phenomena in this state [17,26].…”