Abstract

Hot droughts, or compound drought and heatwaves, have a significant impact on arid regions in southwestern North America (SWNA). In the summer of 2023, SWNA experienced unusually intense hot droughts during both the daytime and nighttime, with their severity amplified three to five times above values during the prior four decades. Over this period, a significant increase was found in the coupling between nighttime and daytime conditions at local scales and across different regions of the SWNA. The hot drought was due to a suppressed North American monsoon (NAM) in response to synoptic-scale subsidence and moisture divergence. Nevertheless, we identified a remote connection between soil moisture in upwind areas and hot drought conditions in downwind regions across the US-Mexico border. Our findings indicate that hot droughts need to be analyzed over complete diurnal cycles and over regions that are connected through atmospheric pathways to improve their prediction, response, and mitigation.

Plain Language Summary

In the summer of 2023, the southwestern United States and northern Mexico faced an unusually harsh combination of extreme heat and drought or a “hot drought.” These conditions were not only more intense than usual but also occurred both during the day and at night, reaching levels up to five times more severe than what the region has experienced over the past 40 years. We found that daytime and nighttime hot droughts have become more closely linked. One major reason for the 2023 hot drought was a weakened North American monsoon caused by large-scale weather patterns that suppressed rainfall. We also found that dry soils in upwind areas can influence hot droughts in downwind regions across the U.S.-Mexico border. As a result, to better predict and respond to hot droughts, a closer inspection is needed for both day and night conditions and for how different regions are connected through the atmosphere.

Key Points

Hot drought severity was amplified by up to five times over southwestern North America due to an anomalously dry monsoon season in 2023
Nighttime and daytime hot droughts showed significant coupling across different regions with growing importance between 1980 and 2023
Upwind dry soil conditions in northern Mexico correlated highly with downwind day and nighttime hot drought in the United States

1 Introduction

Over the past century, the frequency and intensity of heatwaves (HW) and droughts (Dr) has grown worldwide (AghaKouchak et al., 2014; Alizadeh et al., 2020). When these events coincide, they create a compound drought and heatwave (CDHW) event or “hot drought” (King et al., 2024), which can have significant socioeconomic and ecosystem impacts, such as tree mortality (Goulden & Bales, 2019), crop failures (Feng et al., 2019), increases in wildfire risks (Afroz et al., 2023), and cascading effects on hydropower generation (Meng et al., 2023).

The onset and progression of CDHW events arise from multiple factors. Synoptic drivers include persistent anticyclonic circulations (e.g., Mondal & Mishra, 2021; Seager et al., 2023) and moisture divergence. Local influences through land-atmosphere feedbacks (Seneviratne et al., 2010) also play a critical role in amplifying these events (Miralles et al., 2014, 2019; Zscheischler & Seneviratne, 2017). However, prior CDHW studies have only considered daytime (CDHW_day) phenomena (Mukherjee & Mishra, 2021; Tripathy et al., 2023). The omission of nighttime hot drought (CDHW_night) is an important oversight since the energy balances during the night and day can influence each other (e.g., Han et al., 2021; Miralles et al., 2014).

Among global areas experiencing hot drought, southwestern North America (SWNA) stands out for its unprecedented CDHW events in recent decades relative to historical records (e.g., King et al., 2024; McKinnon et al., 2021). Our emphasis on hot droughts in the SWNA is motivated by three factors. First, warm season CDHW events are modulated by precipitation during the North American monsoon (NAM) which has a high interannual variability (Forzieri et al., 2011; Mitchell et al., 2002). Second, regional atmospheric flows during the NAM have both daytime and nocturnal components (Fawcett et al., 2002), such that anomalous conditions in upwind areas may remotely influence hot droughts in downwind regions. Third, nighttime HWs are becoming more frequent than daytime counterparts (Wu et al., 2023).

Here, we considered both daytime and nighttime hot drought events in the SWNA where CDHW_day and CDHW_night denote the simultaneous occurrence of drought (Dr) and HWs during the day (HW_day) and at night (HW_night), respectively. Our research objectives were to: (a) assess the characteristics of HWs, droughts, and hot droughts during the warm season of 2023 within a historical context (1980–2023), (b) evaluate the links between nighttime and subsequent daytime hot droughts at a location and across the region, and (c) understand the driving factors, including synoptic conditions and land-atmosphere feedbacks, that might have led to the exceptional hot drought of the summer 2023 over the SWNA.

2 Data

We used the Climatic Prediction Center (CPC) Global Unified Gauge-Based Analysis (Chen et al., 2008) for daily maximum temperature (T_max), daily minimum temperature (T_min) and daily total precipitation (P) from 1980 to 2023, at a spatial resolution of 0.5° × 0.5° (https://psl.noaa.gov/data). The CPC data set combines data from a global network of rain gauges, with over 30,000 gauges contributing to the retrospective version (1980–2005) and around 17,000 to the real-time version (2006-present). The data set features dense gauge networks over the US and Mexico. For visualization, we interpolated the data using a natural neighbor algorithm. We utilized soil moisture (SM) data from the GLEAM4.1 (Miralles et al., 2025) daily data set (https://www.gleam.eu) over the period of 1980–2023 at a spatial resolution of 0.1° × 0.1°. To maintain consistency with CPC data, SM data were re-gridded to 0.5° × 0.5°. Geopotential height, and zonal and meridional winds at 500 and 850 mb were obtained from NCEP/NCAR reanalysis data (Kalnay et al., 1996) available at https://psl.noaa.gov/data.

3 Methodology

3.1 Defining Heatwaves

Here, we defined HWs during the daytime using daily maximum temperature (T_max) and for nighttime using daily minimum temperature (T_min). A heatwave for each grid location was defined as a period (≥3 consecutive days) when T_max or T_min exceeds the calendar day 80th percentile during the warm season (April-September) of the considered years from 1980 to 2023. While the 90th or 95th percentiles are commonly used to define HWs (Mondal & Mishra, 2021; Perkins & Alexander, 2013), we used a lower threshold to capture moderate HWs co-occurring with drought (Hao et al., 2022; Tripathy et al., 2023), as applied previously (Meng et al., 2023). For comparison, we also conducted analyses for the 90th and 95th percentiles. The severity (S) of a heatwave event was obtained as the cumulative difference between temperature (T_d) and the corresponding calendar day 80th percentile (T₈₀, Tripathy & Mishra, 2023) as:

S={T}_{d}-{T}_{80,}

(1)

and was obtained for daytime (HW_day) or nighttime (HW_night) HWs using T_max or T_min for T_d.

3.2 Defining Droughts

We used CPC precipitation data to calculate the weekly Standardized Precipitation Index (SPI) for both short-term (3 months, SPI03) and long-term (12 months, SPI12) periods. We employed run theory to identify drought events (Dr) using a threshold (Mishra & Singh, 2011). Droughts began when SPI falls below a specified threshold and continued until it rises above that level. We considered the onset of drought to be when SPI12 decreased below −0.5 and tested this selection by also applying a threshold of −1.0. We also tested the sensitivity of the method by using SPI03 and a −0.5 threshold. To capture drought activity during a single season, we categorized Dr events as: (a) terminating droughts, which began before the summer season but ended (Dr_term), and (b) initiating droughts, which started during the summer but may or may not have ended in that season (Dr_init). We set a minimum drought duration (D) of 2 weeks. The drought severity (S) was defined as cumulative sum of SPI during D as:

S=\sum\limits _{j=1}^{D}{\mathrm{S}\mathrm{P}\mathrm{I}}_{j}.

(2)

3.3 Defining Compound Drought and Heatwaves

A week was said to have experienced a CDHW event when both drought and heatwave episodes simultaneously occurred. Mathematically:

\mathrm{D}\mathrm{r}=1\quad if\,\mathrm{S}\mathrm{P}\mathrm{I}\mathit{\le }-0.5

(3)

{\text{HW}}_{j}=1\ if\,{T}_{d}\mathit{\ge }{T}_{80}

(4)

{\text{CDHW}}_{\mathrm{j}}=\left\{\begin{array}{@{}l@{}}1,\left({\mathrm{H}\mathrm{W}}_{j}=1\ \text{and}{\,\mathrm{D}\mathrm{r}}_{j}=1\right)\\ 0\qquad \text{else}\end{array}\right..

(5)

The severity S of CDHW events was obtained as:

S=\left(-1\ast {\mathrm{S}\mathrm{P}\mathrm{I}}_{\text{week}}\right)\times \left(\frac{{T}_{d}-{T}_{25}}{{T}_{75}-{T}_{25}}\right),

(6)

where T_d is T_max or T_min, and T₂₅ and T₇₅ represent the 25th and 75th percentiles. For CDHW_day (CDHW_night), daily maximum (minimum) temperature was standardized by its deviation from the 25th percentile and normalized by the interquartile range. This allowed for comparison across sites with different levels of variability. We classified multiple HWs during a drought as distinct episodes if HWs were separated by four or more days, following Mukherjee and Mishra (2021). We calculated the percentage change (%) in severity (S) for HWs, droughts, and hot droughts in 2023 with respect to the average conditions during 1980–2023.

3.4 Spatiotemporal Dependence Analysis

We employed a cross-correlation analysis to quantify the relationship between spatially averaged CDHW_night severity and CDHW_day severity between regions in SWNA (e.g., northern Mexico, Arizona, and New Mexico) as:

{p}_{i-j}=\frac{\sum\limits _{t=1}^{n}[\left({X}_{i}^{t}-\overline{{X}_{i}}\right)\left({X}_{j}^{t}-\overline{{X}_{j}}\right)}{\sqrt{\sum\limits _{t=1}^{n}{\left({X}_{j}^{t}-\overline{{X}_{j}}\right)}^{2}\sum\limits _{t=1}^{n}{\left({X}_{j}^{t}-\overline{{X}_{j}}\right)}^{2}}},

(7)

where

{p}_{i-j}

is the magnitude of cross-correlation.

{X}_{i}^{t}

represents the CDHW severity over ith region at tth time step, whereas

\overline{{X}_{i}}

represents the average CDHW severity. We calculate the

{p}_{i-j}

by considering 26 weeks (April to September) for each year from 1980 to 2023 along with its statistical significance using bootstrapping (Text S1 in Supporting Information S1). Trends in coupling values were quantified using the Mann-Kendall test along with the trend significance and the annual rate of change in coupling (Δ). Local coupling was assessed within Arizona (p_AZ–_AZ), northern Mexico (p_MX–MX), and New Mexico (p_NM–NM), while remote coupling was examined across regional pairs.

4 Results

4.1 Anomalous Warm Season of 2023

Droughts in SWNA typically stem from insufficient cool-season precipitation (e.g., Jana et al., 2018; Seager et al., 2023), but can also start or worsen during the summer. Since the NAM provides about 40%–80% of the annual rainfall from July to September (Mitchell et al., 2002; Vivoni et al., 2008), a suppressed NAM, along with summer HWs, can trigger or intensify hot droughts. Figure 1 shows the spatial distribution of mean anomalies in T_max, T_min, and P during the NAM of 2023 relative to the climate normal (1991–2020). In addition, the evolutions of the spatially averaged cumulative anomalies are shown in Figure 1d. In 2023, precipitation was suppressed during the NAM, particularly over northern Mexico. P anomalies ranged from −1 to −2 mm/day in Sonora, Chihuahua, Durango, and Sinaloa, and from −0.5 to −1 mm/day in the Four Corners region (Arizona, New Mexico, Colorado, Utah). Negative P anomalies were present from April to June but were less severe than during the NAM (Figure S1 in Supporting Information S1). We compared this analysis to anomalies derived from MSWEP (Beck et al., 2019) and found consistent patterns (Figure S2 in Supporting Information S1), with more heterogeneity in the anomalies for MSWEP due to its higher resolution.

Details are in the caption following the image — **Figure 1**
Open in figure viewer PowerPoint

Hydroclimatic anomalies during the warm season of 2023 with respect to the most recent climate normal (1991–2020). (a) Daily precipitation (P). (b) Daily maximum temperature (T_max). (c) Daily minimum temperature (T_min). (d) Cumulative daily anomalies for the spatially averaged T_max, T_min, and P. Spatial maps are average anomalies for the North American monsoon season (July–September).

In 2023, daytime (T_max) and nighttime (T_min) temperatures showed positive anomalies (Figures 1b and 1c) during the NAM that exceeded those from April to June (Figure S1 in Supporting Information S1). The Mexican Plateau and southern Texas experienced T_max anomalies exceeding 4°C, while the Four Corners region had anomalies ranging from 1 to 3°C. Interestingly, high T_min anomalies occurred across SWNA, with values in Phoenix, Arizona, exceeding T_max anomalies, potentially linked to the nocturnal urban heat island (Chow et al., 2012). Cumulative T_max anomalies increased from mid-June to September, showing that heating preceded the NAM precipitation deficit (Figure 1d), while cumulative T_min anomalies only increased after mid-July, indicating compounded diurnal and nocturnal heating during the suppressed NAM. Analyses for individual areas (Figure S3 in Supporting Information S1) revealed differences in the timing of P, T_max, and T_min anomalies. Compared to other decades (Figure S1 in Supporting Information S1), the warm season of 2023 had higher T_max and T_min anomalies, as well as more negative P anomalies.

4.2 Heatwave and Drought Severity in 2023

We calculated HWs corresponding to daytime (HW_day) and nighttime (HW_night) conditions and droughts corresponding to their initiation (Dr_init) or termination (Dr_term) during the warm season. The percent change in severity (S) at each grid location was calculated with respect to averages from 1980 to 2023 (Figure 2). Positive (negative) ΔS values indicate amplification (attenuation) of severity. During 2023, a large portion of SWNA experienced a 2.5 to 4 times (ΔS ∼ 250–400%) increase in HW_day severity, especially along the US-Mexico border and the Gulf of Mexico. In contrast, the most amplified HW_night severity occurred in Arizona, New Mexico, Texas, and Coahuila, Mexico, with distinct spatial patterns from HW_day. Regions with high positive ΔS in HW_night were located over urban areas (e.g., Phoenix, Arizona) or across higher topography. To assess the robustness of the analysis, we also calculated ΔS for HW_day and HW_night using the 90th and 95th percentiles (Figure S4 in Supporting Information S1). While slight differences in magnitude are observed, the spatial patterns of ΔS remain consistent with those based on the 80th percentile.

The spatial distribution of ΔS of Dr_term and Dr_init are provided in Figures 2c and 2d. ΔS of Dr_term was up to and above 400% in the Great Plains (e.g., Nebraska, Kansas, Oklahoma, Texas) and portions of northeast Mexico, indicating a pre-existing precipitation deficit. However, Dr_init was attenuated (ΔS ∼ 150%) over the Great Plains, possibly due to above-average warm season precipitation (Figure 1a, Figure S1c in Supporting Information S1). In Arizona, New Mexico, Sonora, and Chihuahua, however, ΔS of Dr_init had a spatial signature related to the below-average NAM precipitation. For instance, Sonora had a large ΔS of 250%–300% in an area with high interannual variability in precipitation (Forzieri et al., 2011) and a large precipitation deficit in 2023 (Figure 1a). For completeness, we tested the SPI12 threshold of −1 (Figures S5a and S5b in Supporting Information S1) and found consistent spatial patterns, but a slight reduction in ΔS, as expected. When using SPI03 with a threshold of −0.5 (Figures S5c and S5d in Supporting Information S1), ΔS increased substantially in magnitude and extent for Dr_term and Dr_init, suggesting that amplification occurred primarily among mild to moderate short-term droughts across SWNA.

To quantify longer-term trends, we calculated decadal averages in the frequency, duration, and severity of HWs (HW_day, HW_night) and droughts (Dr_init, Dr_term) in Figures S6 and S7 in Supporting Information S1. Changes in the probability distributions for these decades showed that HWs over SWNA have shifted to higher frequency, duration, and severity. For instance, the average number of HW_day per decade nearly doubled from 42 to 70 events from 1980 to 2023, while HW_night shows a similar trend but a lower magnitude. Dr_term also increased in frequency, duration, and severity. However, minimal changes are noted for Dr_init over the four decades. The metrics suggest that pre-summer droughts have intensified, while warm season drought onsets show limited trends, consistent with high NAM interannual variability (Grantz et al., 2007).

4.3 Severity of Hot Drought in 2023

Figure 3 presents the spatial distribution of the ∆S of CDHW_day and CDHW_night events in 2023. The severity patterns of CDHW_day and CDHW_night exhibit spatial heterogeneity, which parallels that of HWs and droughts, although the contributions of each factor can vary in the region (Tripathy et al., 2023). For instance, the coast of the Gulf of Mexico exhibits a high severity in CDHW_day (ΔS > 400%) due to HW_day, with a limited role noted for Dr_init, which suggest that direct daytime heating was a main factor. In contrast, the amplified CDHW_night in Sonora shows the superposition of Dr_init and HW_night, indicating a strong coupling between drought and nighttime HW. The ΔS of CDHW_night is also amplified over urban centers in the region which possibly reflects enhanced radiative trapping during a suppressed NAM.

To explore the regional variations, we computed the spatially averaged weekly severity (S) of CDHW_day and CDHW_night for northern Mexico, Arizona, and New Mexico (Figures 3c–3e). In northern Mexico, S of CDHW_night preceded and dominated that of CDHW_day early in the warm season, followed by a daytime strengthening toward the end of the warm season. An opposite pattern was noted in Arizona, and to some extent in New Mexico. Since the dominance of CDHW_night decreases northward in 2023, a suppressed NAM appears to have led to favorable conditions for nighttime hot droughts to commence in northern Mexico. Causal analysis (Text S1 in Supporting Information S1) further confirms that a suppressed NAM enhanced CDHW_night, which preceded CDHW_day over northern Mexico and New Mexico (Figure S8 in Supporting Information S1), while downwind in Arizona, the sequence reversed, with CDHW_day leading CDHW_night. Additionally, the conditions observed during the 2023 warm season are a result of an increased frequency, duration, and severity of hot droughts over the last four decades (Figure S9 in Supporting Information S1).

4.4 Spatiotemporal Coupling of Daytime and Nighttime Hot Droughts

We quantified the spatiotemporal coupling between CDHW_night and CDHW_day at local scales resulting from boundary layer heat entrapment (Miralles et al., 2014) and over different regions due to heat and moisture transport (Schumacher et al., 2022). Quantifying the association between CDHW_night in upwind areas and CDHW_day in downwind regions could help elucidate if atmospheric transport during the NAM propagates hot drought conditions from northern Mexico into New Mexico and Arizona. Specifically, we assessed local coupling within Arizona (p_AZ–AZ), northern Mexico (p_MX–MX), and New Mexico (p_NM–NM) (Figures 4a–4c), and evaluated the coupling between regions by examining the correlation between severity (S) of CDHW_night over northern Mexico to CDHW_day over Arizona (p_AZ–MX), CDHW_night over northern Mexico to CDHW_day over New Mexico (p_NM–MX), and CDHW_night over New Mexico (p_AZ–NM) to CDHW_day over Arizona (Figures 4d–4f).

In the warm season of 2023, local and remote coupling values between CDHW_night and CDHW_day were high (local >0.9, remote >0.8), whereas large interannual variability was present during 1980–2023. Arizona exhibited the strongest local coupling (p_AZ–AZ) in 2023, but a weak and statistically insignificant trend in time. In contrast, New Mexico (p_NM–NM) had a statistically significant increasing trend in the link between nighttime and daytime hot droughts. More importantly, significant increasing trends for p_AZ–MX and p_NM–MX were noted (p < 0.01), such that atmospheric transport of hot drought conditions has increased across the US-Mexico border. Note that the rate of increase of the remote couplings is nearly double that of local couplings. Furthermore, consistent results are obtained when coupling between CDHW_day over northern Mexico and CDHW_day over New Mexico or Arizona were assessed. These results suggest that the increasing spatial coherence of hot drought severity across northern Mexico, Arizona, and New Mexico is more dominated by remote atmospheric connectivity than by local interactions alone.

4.5 Attribution of the Hot Drought of 2023

Synoptic conditions during the NAM of 2023 led to regional subsidence and moisture divergence, which reduced atmospheric transport into SWNA from its nearby oceanic sources, relative to climatology (Text S2, Figure S10 in Supporting Information S1). As shown by Dominguez et al. (2008), a weakened connection with oceanic sources enhances the role of land-atmosphere interactions during the NAM. In response, precipitation (P) anomalies during the NAM were negative (Figures 1a and 1d) and led to decreases in SM that persisted for longer time periods across northern Mexico, Arizona, and New Mexico (Figure S11 in Supporting Information S1). The severity (S) of CDHW_day and CDHW_night responded to the P and SM anomalies in each region. For instance, in northern Mexico, linear regressions between CDHW_night and P anomalies had an R² = −0.52 (p < 0.01) and between CDHW_night and SM anomalies of R² = −0.77 (p < 0.01). As a result, daytime and nighttime hot droughts were correlated strongly with local conditions, which included a long-memory SM component, as shown in other regions (e.g., Kim et al., 2025; Liang et al., 2025).

We calculated cross-correlations ( ${p}_{i-j}$ ) between SM anomalies in one region and the severity (S) of CDHW_night averaged in a downwind area. We focused on CDHW_night due to its higher correlation with long-memory SM anomalies, as compared to P anomalies in northern Mexico. Figure S12 in Supporting Information S1 presents this analysis for the upwind northern Mexico and downwind New Mexico (consistent results were obtained for the northern Mexico-Arizona pair). Note that the strength of remote coupling, as quantified by the correlation between SM anomalies in northern Mexico and CDHW_night severity in New Mexico, was substantially higher (|r| ≈ 0.8) than the corresponding local coupling between SM and CDHW_night severity within New Mexico (|r| ≈ 0.5). This suggests that anomalous dry soils in upwind regions impact the nighttime hot drought in downwind areas. This upwind-downwind interaction remains nearly invariant when considering S of CDHW_day for both northern Mexico and New Mexico (Figure S13 in Supporting Information S1), demonstrating that the linkage of anomalous dry soils to hot drought in downwind regions is diurnally robust.

5 Conclusions

Synoptic conditions during the warm season of 2023 enhanced atmospheric subsidence and disrupted southerly moisture transport during the NAM. The resulting decrease in precipitation along with high temperature anomalies led to intensified hot drought conditions over SWNA. Daytime heatwave severity increased three to five times more than average throughout the US-Mexico border and especially along the Gulf of Mexico. These conditions also initiated droughts in Sonora, Chihuahua, Arizona, and New Mexico. As a result, the severity of hot droughts amplified nearly five-fold and led to nighttime hot drought influencing the subsequent daytime hot drought. Both local and remote coupling of nighttime and daytime hot droughts were found in Arizona, New Mexico, and northern Mexico. Furthermore, the strength of the remote coupling has grown significantly in the past four decades at nearly twice the rate of local coupling. These previously unreported findings highlight a need to study the role of diurnal atmospheric transport and land surface conditions during the NAM in propagating hot droughts regionally across the US-Mexico border.

Acknowledgments

We thank support from the Arizona Water Innovation Initiative, a multi-year partnership with the State of Arizona led by Arizona State University's Julie Ann Wrigley Global Futures Laboratory in collaboration with the Ira A. Fulton Schools of Engineering.

Conflict of Interest

The authors declare no conflicts of interest relevant to this study.

Open Research

Data Availability Statement

Daily temperature data can be obtained from the NOAA/OAR/ESRL (https://psl.noaa.gov/data/gridded/data.cpc.globaltemp.html) and precipitation data can be obtained from https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html. Analysis codes are available at Mondal (2025).

Supporting Information

Filename	Description
2025GL118308-sup-0001-Supporting Information SI-S01.pdf9.3 MB	Supporting Information S1

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Hot Drought of Summer 2023 in Southwestern North America