Editorial Type:
Article
Article Type:
Research Article

Oppressive Heat Events in Illinois Related to Antecedent Wet Soils

Trent W. Ford Department of Geography and Environmental Resources, Southern Illinois University, Carbondale, Illinois

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Justin T. Schoof Department of Geography and Environmental Resources, Southern Illinois University, Carbondale, Illinois

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Print Publication:
01 Oct 2016
DOI:
https://doi.org/10.1175/JHM-D-16-0075.1
Page(s):
2713–2726
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Abstract

Extreme heat events have been connected with antecedent soil moisture in many global regions, such that dry soils increase sensible heat content of the near-surface atmosphere and impede precipitation through boundary layer growth. However, negative soil moisture–temperature feedbacks (dry soils = higher temperatures) are founded on investigations of maximum temperature that neglect the potentially important latent heating component provided by soil moisture. In this study, the association of spring soil moisture and subsequent summer oppressive heat events is quantified, defined by equivalent temperature. The advantage of equivalent temperature over maximum temperature is that it accounts for both the temperature and moisture components of atmospheric heat content. Quantile regression and composite analysis are used to determine the association between spring soil moisture and summer oppressive heat events using a 25-yr station observation record in Illinois. A consistent response of summer oppressive heat events to antecedent 5-cm soil moisture anomalies is found at all four stations. The frequency of oppressive summer equivalent temperature events is significantly increased following spring seasons with wetter-than-normal soils compared with spring seasons with dry soils. This provides evidence of a possible positive soil moisture–temperature feedback. Further, it is found that oppressive heat events correspond with the combination of wetter-than-normal spring soils and persistent summertime upper-level ridging to the northeast of the region, thereby leading to the conclusion that abundant-to-surplus spring soil moisture is necessary but not sufficient for the occurrence of oppressive heat in Illinois.

Corresponding author address: Trent Ford, Department of Geography and Environmental Resources, Southern Illinois University, Faner Hall, Mail Code 4514, Carbondale, IL 62901. E-mail: twford@siu.edu

Abstract

Extreme heat events have been connected with antecedent soil moisture in many global regions, such that dry soils increase sensible heat content of the near-surface atmosphere and impede precipitation through boundary layer growth. However, negative soil moisture–temperature feedbacks (dry soils = higher temperatures) are founded on investigations of maximum temperature that neglect the potentially important latent heating component provided by soil moisture. In this study, the association of spring soil moisture and subsequent summer oppressive heat events is quantified, defined by equivalent temperature. The advantage of equivalent temperature over maximum temperature is that it accounts for both the temperature and moisture components of atmospheric heat content. Quantile regression and composite analysis are used to determine the association between spring soil moisture and summer oppressive heat events using a 25-yr station observation record in Illinois. A consistent response of summer oppressive heat events to antecedent 5-cm soil moisture anomalies is found at all four stations. The frequency of oppressive summer equivalent temperature events is significantly increased following spring seasons with wetter-than-normal soils compared with spring seasons with dry soils. This provides evidence of a possible positive soil moisture–temperature feedback. Further, it is found that oppressive heat events correspond with the combination of wetter-than-normal spring soils and persistent summertime upper-level ridging to the northeast of the region, thereby leading to the conclusion that abundant-to-surplus spring soil moisture is necessary but not sufficient for the occurrence of oppressive heat in Illinois.

Corresponding author address: Trent Ford, Department of Geography and Environmental Resources, Southern Illinois University, Faner Hall, Mail Code 4514, Carbondale, IL 62901. E-mail: twford@siu.edu
Keywords: Extreme events; Atmosphere-land interaction; Soil moisture

1. Introduction

Extreme heat is responsible for more weather-related fatalities than any other meteorological phenomenon (Sandstrom et al. 2004). While studies typically focus on air temperature alone, atmospheric moisture (i.e., humidity) also plays an important role in human morbidity/mortality during heat waves. In the Midwest region of the United States, and particularly in the state of Illinois, the frequency of oppressively hot synoptic conditions has consistently increased since the 1970s (Sparks et al. 2002; Vanos et al. 2015) and has been accompanied by increases in humidity, including extreme dewpoint temperatures (Gaffen and Ross 1999; Changnon et al. 2006; Brown and DeGaetano 2013). Combined with projections of additional warming (Wuebbles and Hayhoe 2004; Pryor et al. 2014; Crimmins et al. 2016), these trends present concerns for human health and heat vulnerability in the region.

The role of humidity in human heat stress (Sheridan and Kalkstein 2010) dictates that maximum air temperature by itself is an incomplete descriptor of total heat because it does not include the heat content attributable to near-surface moisture (Pielke et al. 2004; Davey et al. 2006). Despite this, the majority of heat wave literature has historically focused on the contribution of sensible heat through analysis of (Fischer et al. 2007; Della-Marta et al. 2007; Oswald and Rood 2014). Instead, Pielke et al. (2004) recommend using moist static energy or moist enthalpy to represent near-surface atmospheric heating from both temperature and moisture contributions. Moist static energy is defined as
e1
where is the specific heat of air at constant pressure (J kg °C−1), T is temperature (°C), is the latent heat of vaporization (J kg−1), and q is specific humidity (kg kg−1). Division of H by produces equivalent temperature :
e2
which better captures the near-surface heat content. Equivalent temperature is therefore a thermodynamic measure that quantifies near-surface heat content from both sensible and latent heat contributions.

Oppressive heat events in the Midwest such as the 1980 St. Louis event (Smoyer 1998) and the 1995 Chicago event (Kunkel et al. 1996) exhibit both anomalously high and high dewpoint temperatures. The local contribution to the former is through sensible heating via surface moisture limitations, while the latter is partially attributable to elevated atmospheric humidity. The association of soil moisture with extreme is well documented (Alexander 2011; Miralles et al. 2012; Mueller and Seneviratne 2012), as soil moisture can influence near-surface temperature through the partitioning of latent and sensible heat flux (Kunkel 1989; Basara and Crawford 2002). Dry soils increase sensible heating and enhance atmospheric heat content, thereby increasing . It is not surprising that soil moisture deficits correspond strongly with extreme temperatures in many regions of the globe (Stéfanon et al. 2014; Meng and Shen 2014), including the central U.S. Midwest (Kunkel 1989). Analyzing soil moisture–temperature coupling in Europe, Hirschi et al. (2011) demonstrated that the response to soil moisture was not consistent across the distribution of , but instead was strongest and most significant in the right tail of the distribution. The same statistical response was also shown in the U.S. southern Great Plains (Ford and Quiring 2014), suggesting that dry soils elicit the largest increase in the most extreme . Evidence from both models (Fischer et al. 2007) and observations (Mueller and Seneviratne 2012; Meng and Shen 2014) suggests lagged soil moisture feedbacks to air temperature, such that spring soil moisture anomalies are strongly related to summer temperature departures. This so-called “transfer of predictability” (Guo et al. 2011) from the land surface to the atmosphere from spring to summer is attributed to soil moisture persistence and its memory imprint on surface flux partitioning (Orth and Seneviratne 2014).

The connection between land surface moisture deficit and extreme is well established. However, the contribution of soil moisture to atmospheric heat through moisture content or latent heating is less well understood. Previous studies have suggested that local drivers enhance atmospheric heat content through increased latent heat transfer (Huang et al. 1996; Sandstrom et al. 2004; Lauritsen and Rogers 2012), while others argue that humidity and minimum temperatures are more strongly tied to large-scale drivers, such as Pacific sea surface temperature variability (Mo 2003; Alfaro et al. 2006). Given the documented response of summer to spring soil moisture anomalies in many regions of the world (Guo et al. 2011; Quesada et al. 2012; Ford and Quiring 2014), it is reasonable to postulate whether these relationships exist in the Midwest region of the United States and if summer responds similarly to anomalously wet or dry spring soils. This study seeks to investigate the connection between spring soil moisture and the occurrence of summer oppressive heat events in Illinois. In particular, we determine if anomalously dry soils or anomalously wet soils in spring are necessary for oppressive events to occur during the following summer in Illinois. We then compare and contrast the statistical response of to soil moisture with that of .

2. Data

Daily observations of temperature, , dewpoint, station pressure, total precipitation, and total potential evapotranspiration (PET) between June and August were extracted from four stations (Fig. 1a) in the Illinois Climate Network (ICN; Hollinger et al. 1994). The ICN, managed by the Illinois State Water Survey, monitors weather and soil conditions at 19 sites across the state of Illinois and has been in operation since the 1980s. ICN stations monitor both weather and soil conditions, making for an easier and more direct comparison between the land surface and atmosphere. The four stations—Belleville, Champaign, DeKalb, and Peoria—were selected because of their long, relatively complete data records. The weather and soil monitoring sensors at all four stations are located on sod; however, the surrounding land covers vary between the sites. The Belleville station is sited in generally flat terrain with a mixed hardwood forest approximately 250 m to the east and open grassland in all other directions. The Champaign site is located in a grassy opening in a more developed environment within the city limits of Champaign. Beyond the opening, the city of Champaign extends for 10 km to the north and west, and the city of Urbana extends 7–8 km to the northeast and east. The DeKalb site is located in a grassy opening on the edge of a cropped field with a corn–soybean rotation. The terrain surrounding the station is open farmland with very shallow slopes. The Peoria station is located in a grassy opening with mature deciduous trees approximately 220 m to the northwest and smaller deciduous trees approximately 100 m to the northeast. All four ICN sites have a silt loam soil texture at all depths, though the DeKalb and Champaign stations are characterized as a silty clay loam (Hollinger and Isard 1994). At each ICN station, air temperature, relative humidity, and pressure are observed every 10 s and averaged over an hour, while precipitation accumulation is measured every minute and totaled for each hour. Hourly dewpoint temperature is calculated using the methods described in Allen et al. (1998), while hourly PET is estimated using the Penman–Monteith equation. The ICN aggregates hourly observations to daily averages or totals and provides historical daily data (http://www.isws.illinois.edu/warm/datatype.asp).

Fig. 1.
Fig. 1.

(a) ICN stations, (b) average monthly , , and the difference between and at DeKalb ICN station, and (c) average monthly soil moisture at DeKalb station. Averages in (b) and (c) are computed from data spanning 1992–2014.

Citation: Journal of Hydrometeorology 17, 10; 10.1175/JHM-D-16-0075.1

Soil moisture observations from two datasets are obtained at each ICN station. The first is a series of twice-monthly observations between 1983 and 2004, taken within grass plots using a neutron depth probe and neutron surface probe. Within these plots, a soil moisture measurement was taken within the first 10-cm profile, followed by one observation every 20 cm down to a depth of 200 cm. Details of sensor calibration, installation, and data quality control are available in Hollinger and Isard (1994). Starting in 1998, this sensor system began to be replaced by an automated soil moisture monitoring system using Stevens Hydra Probes. Each of the four sites used in this study was equipped with Hydra Probes at 5-, 10-, 20-, 50-, 100-, and 150-cm depths. Since 2004, soil moisture measurements have been taken every hour using the Hydra Probes and are averaged to the daily resolution in the form of volumetric water content (cm3 cm−3). ICN weather and soil observations go through extensive quality control, including limits checks, comparison checks, duplicate record checks, missing hour checks, and time consistency checks. More details on the ICN data quality assurance can be found in Scott et al. (2010).

The seasonal cycle of temperature in Illinois is representative of a humid continental climate, with the warmest conditions between June and August (Fig. 1b). The seasonal soil moisture cycle in the region is described by Hollinger and Isard (1994) with available soil moisture peaking in March and April, followed by a drydown over the summer and recharge the following autumn and winter seasons (Fig. 1c). We focus our analysis on spring soil moisture and subsequent summer temperature at the four stations across the state.

3. Methods

The computation of requires specific humidity, which we estimate based on daily ICN observations and the empirical relation of Bolton (1980). This starts with deriving vapor pressure e from dewpoint temperature (°C):
e3
From vapor pressure and observed station pressure we can then estimate specific humidity (kg kg−1):
e4
where ρ is the station pressure.

Finally, we can compute the latent heat of vaporization as a function of temperature using the Priestley–Taylor method (e.g., Fall et al. 2010; Schoof et al. 2015). From these equations we calculate daily average from June to August in each calendar year between 1990 and 2014. For each of the 92 calendar days in the summer season we calculate the 95th percentile of . We then compute the percent of “hot days” or days in which the average meets or exceeds its respective 95th percentile value occurring during each summer season (e.g., Frich et al. 2002; Ford and Quiring 2014). The seasonal percent hot day record is used to represent the occurrence of oppressive heat events at each of the four stations in Illinois. The same methods are also applied to compute a summer season hot day record, which is likewise regressed against spring soil moisture.

To merge the neutron probe observations from 1983 to 2004 with the Steven’s Hydra Probe observations from 2004 to 2014, both of the datasets needed to be converted to anomalies of volumetric water content. The biweekly neutron probe observations are converted to anomalies by subtracting the mean monthly neutron probe volumetric water content at each measurement depth and site individually. The daily Hydra Probe observations are also converted to anomalies by subtracting the mean monthly Hydra Probe volumetric water content at each measurement depth and site. These biweekly and daily soil moisture anomalies were then aggregated to a spring (MAM) seasonal average for each calendar year, 1983–2014. We then combine the 5-cm Hydra Probe anomaly records with the 0–10-cm neutron probe records to create one continuous spring soil moisture time series at each station. Similarly the 20-, 50-, 100-, and 150-cm Hydra Probe records were matched with the 10–30-, 30–50-, 90–110-, and 130–150-cm neutron probe records, respectively. A two-sample Kolmogorov–Smirnov test was used to determine if the neutron probe and Hydra Probe records were drawn from a continuous population with the same distribution. At all but one of the 20 station/measurement depth records, no significant differences were found between the neutron probe anomalies and Hydra Probe anomalies. This gave us confidence that combining the two soil moisture records was a robust way of extending our soil moisture time series without introducing significant measurement bias. The one incidence where significant differences were determined between the two soil moisture records was the 150-cm depth at the Champaign site. Because of this, we do not include this depth in our analysis at Champaign.

When aggregating daily temperature and soil moisture data to seasonal averages, any season that contains a month in which five or more observations are missing or flagged as questionable is removed from the analysis. This process resulted in one season’s temperature being removed at Belleville and two seasons’ temperature being removed at Peoria (Table 1). No more than one season’s worth of soil moisture was removed at any of the stations. We also tested for significant trends (Mann–Kendall) in monthly , , and soil moisture. The and trends were predominantly negative (cooling) at all four stations, but only February trends at Champaign and Belleville were statistically significant. At both sites February decreased by 0.3°C yr−1 between 1989 and 2014. The significant, negative February trend, in the absence of a concurrent significant trend, could potentially be a result of decreased February near-surface humidity. Unfortunately, the ICN dataset does not include measurements of specific humidity or mixing ratio. Monthly soil moisture anomalies exhibited less consistent trends, none of which were statistically significant. Because of this lack of significant trends, we did not detrend either of the datasets.

Table 1.

Missing seasons in the temperature and soil moisture records at each of the four ICN stations.

Table 1.

When comparing soil moisture to the subsequent occurrence of extreme heat, previous studies have found a stronger response in the high end of the distribution (Hirschi et al. 2011; Meng and Shen 2014). In this case, ordinary least squares regression, which estimates the change in the mean of the response variable, does not capture the characteristics of the relationship. Similar to Ford and Quiring (2014), we adopt quantile regression to account for this shortcoming in ordinary least squares regression. Quantile regression estimates multiple rates of change in the dependent variable as a function of the independent variable and can provide a more complete picture of the relationship between soil moisture and . We assess the statistical relationship between spring soil moisture anomalies and subsequent summer percent hot days and hot days using a model with regressions fit to the 5th, 25th, 50th, 75th, and 95th quantiles. For example, the regression fit to the 95th quantile measures the response of the 95th percentile of or to soil moisture, and therefore the regression is based on all data points of and . The significance of the model fit is assessed with confidence intervals estimated using a bootstrapping resampling technique. We then compare the soil moisture– regression slopes to those obtained by regressing summer hot days against spring soil moisture.

Finally, we evaluate synoptic-scale atmospheric patterns associated with summer seasons exhibiting above- and below-normal hot days. The North American Regional Reanalysis (NARR) climate dataset is used to characterize low- and upper-level atmospheric conditions (Mesinger et al. 2006). NARR assimilates atmosphere and surface observations to derive a 32-km resolution dataset that covers North America. We composite both monthly and daily average NARR products to investigate potential differences in synoptic patterns contributing to the presence or absence of oppressive heat events.

4. Results

a. Response of equivalent temperatures to soil moisture

We use quantile regression to assess the response of summer hot days and hot days (>95th percentile) to spring soil moisture anomalies at four stations in Illinois. The regression is fit at the 5th, 25th, 50th, 75th, and 95th quantiles to capture the entire range of hot day response. Using similar methods, Hirschi et al. (2011) and Meng and Shen (2014) found the largest change in the highest quantile of hot days associated with decreased soil moisture. Our analysis reveals similar patterns in the response of in that at all four stations the change in the percent of hot days with soil moisture was largest at the 75th and 95th quantiles. However, the positive slopes in Fig. 2 indicate that increased occurrence of summer hot days is associated with wetter-than-normal soils, not dry soils. In fact, all significant slopes of the quantile regression of hot days on soil moisture are positive. Each scatter point in Fig. 2 represents one year; each of the lines in Fig. 2 (and later in Fig. 5) represent regressions fit using all 25 years of data and not just a few points. The regression slopes are grouped together in Figs. 2 and 5 for easier direct comparison. Despite the consistency in the soil moisture– relationship, the frequency of hot days is only significantly related to spring soil moisture at the 5-cm depth at all stations. In Champaign and DeKalb, the 5-cm measurement depth is the only one to exhibit a statistically significant fit, while significant associations occur at both the 5- and 50-cm depths in Belleville and Peoria. This is perhaps due to the higher porosity of DeKalb and Champaign soils (515 and 543 mm in the top 1 m) over those at Belleville and Peoria (474 and 470 mm in the top 1 m). The cross correlation r of daily 5- and 50-cm soil moisture at Belleville remains above 0.40 out to a 45-day lag, while the same cross correlation falls off dramatically at Champaign and is insignificant after 50 days (Fig. 3). It is therefore reasonable to expect dry or wet soil anomalies at 5 cm will persist and influence the deeper soil column over a longer period of time at Belleville and Peoria, attributable to less porous soils and slower drainage. The lack of a significant signal from the deeper-layer soil moisture could also partly be attributed to the relatively shallow root system of the sod land cover at each of the four stations, leaving the deeper soil moisture out of reach for uptake and transpiration.

Fig. 2.
Fig. 2.

Quantile regression of summer percent hot days against spring 5-cm soil moisture at (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria. The regression lines represent the fit at the 95th, 75th, 50th, 25th, and 5th quantiles.

Citation: Journal of Hydrometeorology 17, 10; 10.1175/JHM-D-16-0075.1

Fig. 3.
Fig. 3.

Lagged cross correlations between daily 5- and 50-cm soil moisture at (a) Belleville and (b) Champaign stations.

Citation: Journal of Hydrometeorology 17, 10; 10.1175/JHM-D-16-0075.1

The statistical relationships revealed by the quantile regression suggest the response of summer to spring soil moisture is not consistent across the distribution, but instead the right tail, or most oppressive values increase at a higher rate than the middle or left tail in response to wetter soils. To better demonstrate this, we compare distributions of from summers that follow wetter-than-normal springs (high soil moisture) and those that follow drier-than-normal springs (low soil moisture) at each station. Figure 4 displays distributions of daily summer (JJA) average (°C) for all years. The median of the distribution (solid black line) is compared with the median of the daily summer distribution associated with the eight wettest (solid red line) and eight driest (solid blue line) springs. Similarly, we compare the 5th and 95th percentiles of these distributions, denoted by dashed lines in the same color scheme (Fig. 4). At all four stations, the 5th percentile, median, and 95th percentile of summer are lowest for dry spring years, slightly higher for all years, and higher still for wet spring years. However, at all stations except for Peoria, the increase between dry spring years/all years and the wet spring years is largest (and statistically significant) at the 95th percentile. At the Peoria station, a similar increase associated with wet spring years occurs at the 5th percentile, median, and 95th percentile. This is also reflected in the relatively smaller slope of the 95th quantile regression fit in Peoria, with respect to the other three stations (Fig. 2d).

Fig. 4.
Fig. 4.

Distributions of summer (°C). The distribution medians are shown by the solid black line, while the 5th and 95th percentiles are shown by the dashed black line. The red (blue) thick and dashed lines represent the median and 5th, 95th percentile values of distributions from the summers associated with the eight wettest (driest) springs, respectively. Results are from (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria.

Citation: Journal of Hydrometeorology 17, 10; 10.1175/JHM-D-16-0075.1

b. Response of maximum temperatures to soil moisture

Quantile regression was used to evaluate the response of summer to spring soil moisture in the same method as the assessment. The ensuing regression slopes were predominantly negative, implying increased hot days in response to drier-than-normal soils (e.g., Hirschi et al. 2011; Mueller and Seneviratne 2012). However, the response of , based on the regressions, was less consistent than that of . At Belleville and Champaign stations, the 95th and 75th quantile regression slopes were stronger (more negative) than the lower quantiles (Fig. 5), similar to the regression slopes in Fig. 2. The 95th quantile regression was the only significant fit at both Belleville and Champaign stations. All regression slopes at the Peoria station were negative, but none were statistically significant. The response of hot days to soil moisture at DeKalb resulted in both positive and negative regression slopes. However, similar to Peoria, none of the DeKalb regressions were statistically significant. No significant relationships existed between and soil moisture at depths below 5 cm.

Fig. 5.
Fig. 5.

Quantile regression of summer percent hot days against spring 5-cm soil moisture at (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria. The regression lines represent the fit at the 95th, 75th, 50th, 25th, and 5th quantiles.

Citation: Journal of Hydrometeorology 17, 10; 10.1175/JHM-D-16-0075.1

The weaker regression slopes and inconsistent relationship between summer and spring soil moisture is reflected in the change in the distribution of between dry spring years, wet spring years, and all years (Fig. 6). Dry spring years are associated with higher summer than wet spring years and all years put together. However, as Fig. 6 shows, the largest change in occurs in the 5th percentile and not the 95th percentile in response to drier-than-normal springs. Indeed, the dry spring years’ 5th percentile of summer is significantly different from those of wet spring years and all years at Belleville, Champaign, and Peoria while differences in the median and 95th percentile are apparent but not statistically significant at DeKalb (Fig. 6). The lack of a consistent shift in the 95th percentile of in response to drier-than-normal spring soils explains the weak, insignificant regression slopes in Fig. 5.

Fig. 6.
Fig. 6.

Distributions of summer (°C). The distribution medians are shown by the solid black line, while the 5th and 95th percentiles are shown by the dashed black line. The red (blue) thick and dashed lines represent the median and 5th, 95th percentile values of distributions from the summers associated with the eight wettest (driest) springs, respectively. Results are from (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria.

Citation: Journal of Hydrometeorology 17, 10; 10.1175/JHM-D-16-0075.1

c. Synoptic conditions associated with oppressive equivalent temperature events

Extreme heat and heat waves have been connected to antecedent dry soils, limitation of evapotranspiration, and a dry stable boundary layer (Fischer et al. 2007; Lorenz et al. 2010). Continued increased temperatures and stronger evaporative demand/less soil moisture availability could therefore manifest in longer, more intense heat waves in arid and semiarid regions (Schär et al. 2004; Diffenbaugh et al. 2007; Della-Marta et al. 2007). Previous studies have documented a consistently stronger response of extreme temperatures to soil moisture in the highest part of the temperature distribution, meaning the frequency of the most extreme heat events increase most markedly to soil moisture limitations (Hirschi et al. 2011; Mueller and Seneviratne 2012; Meng and Shen 2014). This feedback is consistently strongest at the subseasonal to seasonal time scale when soil moisture precedes temperature (Guo et al. 2011; Quesada et al. 2012). Using similar methods, our results from four stations in Illinois show weak, inconsistent responses of summer hot days to spring soil moisture anomalies. The discrepancy of our results with previous literature could perhaps be attributable to our analysis taking place in a humid region like the U. S. Midwest, whereas semiarid regions have historically exhibited the strongest soil moisture–maximum temperature coupling.

With that being said, we do find patterns of statistical coupling similar to those demonstrated in previous studies, only in this case between spring soil moisture and summer . The 95th quantile slopes of the –soil moisture regressions were consistently stronger than the 75th, 50th, 25th, and 5th percentiles. However, in contrast to the predominantly negative soil moisture– relationships exhibited in semiarid regions (e.g., Ford and Quiring 2014), the relationship between spring soil moisture and summer hot days is positive. This represents an increase in the frequency and likelihood of oppressive events in response to wet, not dry soils. Therefore, we argue that the most extreme summertime oppressive heat events that have occurred over the last 25 years in the Midwest, those exhibiting both anomalously high and dewpoint temperatures (Semenza et al. 1999; Palecki et al. 2001; Andresen et al. 2012), are statistically associated with abundant rainfall and adequate to above-normal soil moisture during the previous spring.

It is important to distinguish the statistical relationship between spring soil moisture and summer demonstrated here from diurnal-to-daily temperature variability within a summer season. The former will not determine the latter, as such temperature variability is primarily driven by a number of meteorological and nonmeteorological factors that fluctuate on diverse temporal and spatial scales. Instead, the purpose of this study is to investigate the connection between spring soil moisture and summer oppressive heat events and to determine the necessity and/or sufficiency of positive (wet) or negative (dry) spring soil moisture anomalies for the occurrence of oppressive heat events. Given that hot days comprised no more than 11% of all summer seasons following springs with below-normal soil moisture, we argue abundant-to-surplus spring soil moisture is necessary for the occurrence of summertime oppressive heat events in Illinois. However, the range of summer percent hot days following wet springs indicates that above-normal soil moisture in the spring does not always lead to oppressive heat events in the summer. For example, the average 5-cm soil moisture anomaly for the spring of 1999 in Belleville was 0.01, meaning 1% volumetric water content above the long-term spring mean. The subsequent summer experienced over 20% hot days, the highest in the Belleville record. On the other hand, the spring of 2008 in Belleville saw an average 5-cm soil moisture anomaly of 0.04, but the following summer did not experience a single hot day. Therefore, we cannot conclude that wet spring soils are sufficient for the occurrence of summertime oppressive heat events in Illinois.

In an attempt to reconcile the different summer responses to the same spring soil moisture, we composite summer synoptic patterns associated with wet springs (5-cm soil moisture anomaly >0.01) and a high frequency of hot days (>10%), and contrast to synoptic patterns associated with wet springs and a low frequency (<2%) of hot days. The former include the years 1990, 1995, and 1999, while the latter include the years 1996, 2008, and 2009. The summers of 1990, 1995, and 1999 exhibited double-digit percent hot days and coincide with an upper-level ridge situated to the northeast of the study region (Fig. 7a). The ridge acts to force the area of strongest westerly flow to the north, into the upper Midwest and southern Canada (Fig. 7c). A composite of 850-hPa geopotential heights from all hot days in 1990, 1995, and 1999 shows suppression of the ridge southward as a disturbance migrates over the upper Midwest and southern Canada (Fig. 8). This synoptic pattern has been previously linked to persistence of extreme dewpoint events in the Midwest (Bentley and Stallins 2008), as the flow of cooler air from the west is diverted northward away from the study region. These features are contrasted by a trough situated over the Midwest and stronger westerly to northwesterly upper-level flow into the study region during the summers exhibiting less than 2% hot days (Figs. 8b,d).

Fig. 7.
Fig. 7.

(a),(b) The 500-hPa geopotential height anomalies and (c),(d) 300-mb mean vector winds composited for the summers 1990, 1995, and 1999 (left) and 1996, 2008, and 2009 (right).

Citation: Journal of Hydrometeorology 17, 10; 10.1175/JHM-D-16-0075.1

Fig. 8.
Fig. 8.

The 850-hPa geopotential height anomalies composited from all hot days for the summers 1990, 1995, and 1999.

Citation: Journal of Hydrometeorology 17, 10; 10.1175/JHM-D-16-0075.1

Ridging over the Great Lakes and extension of the ridge into the Midwest could result in increased both through suppression of mechanisms leading to precipitation and enhancement of evaporative demand and evapotranspiration from local moisture sources. Figure 9 shows the evolution of daily precipitation P (cm) minus daily PET (cm) between 1 June and 1 September at Belleville (Fig. 9a) and Champaign (Fig. 9b) stations. The red line represents the 1990, 1995, and 1999 average, while the blue line represents the 1996, 2008, and 2009 average. Both sets of years show moisture surplus entering the summer season and the typical drawdown of moisture reserves, reaching a soil moisture minimum on 31 August. However, the lines begin to diverge dramatically after 1 July, with PET exceeding P at a much higher rate during the years with higher percent hot days. This forces a significantly larger decline in soil moisture (Fig. 9, squares) during these years as increased evapotranspiration adds to atmospheric energy through latent heating. When examining years separately at the Belleville station, we see very close correspondence in the daily evolution of moisture balance (P − PET) and associated 5-cm soil moisture between years with a high frequency of hot days (Fig. 9c). High atmospheric demand draws down soil moisture reserves, leading to severe moisture deficit throughout July and August in each of these years. The correspondence between years with low hot day frequency is weaker, although the absolute P − PET values during each of these years are much larger than those of the previous 3 years (Fig. 9d). In particular, the daily evolution of P − PET in 1996 diverges from 2008 and 2009; however, 5-cm soil moisture in 1996 still remains above or near normal throughout the majority of the season.

Fig. 9.
Fig. 9.

Daily cumulative sum of P − PET (cm), averaged over the summers (red line) 1990, 1995, and 1999 and (blue line) 1996, 2008, and 2009 at the (a) Belleville and (b) Champaign sites. The squares represent monthly soil moisture anomalies from each set of summers. The daily cumulative sum of P − PET and soil moisture anomalies for each of the individual years [(c) 1990, 1995, and 1999; (d) 1996, 2008, and 2009] at the Belleville station.

Citation: Journal of Hydrometeorology 17, 10; 10.1175/JHM-D-16-0075.1

It is clear from the synoptic cases assessed (Figs. 8, 9) and the dramatically different response to similar spring soil moisture anomalies that wet spring soils alone are not a sufficient condition for the occurrence of oppressive heat events in Illinois. Instead, these heat events are a complex amalgamation of meteorological (precipitation, soil moisture, atmospheric demand, etc.) and nonmeteorological (vegetation development, soil texture, etc.) factors. Further, the synoptic-scale atmospheric patterns associated with increased or decreased frequency of oppressive heat events are independent from the preceding spring soil moisture anomalies. The composites in Fig. 9 provide an explanation of how similarly positive (wet) spring soil moisture anomalies result in high and low frequencies of hot days (e.g., Fig. 3), suggesting that the connection between spring soil moisture conditions and summer oppressive heat occurrence is dependent on atmospheric circulation patterns and associated evaporative demand over the course of the summer season. Therefore, we suggest, based on our results, that adequate-to-surplus soil moisture in spring is a necessary but not a sufficient condition for the occurrence of oppressive events during the following summer in Illinois. Indeed, it is the combination of adequate local moisture supply and increased atmospheric demand driven by synoptic-scale features that make for conditions conducive to oppressive heat events in the region. Further research is worthwhile and necessary to quantify the separate contributions of the local land surface and synoptic-scale atmospheric circulation features to the occurrence of oppressive heat in the Midwest.

5. Summary and conclusions

We use quantile regression and composite analysis to determine the association between spring soil moisture and summer oppressive heat events in Illinois. Summer percent hot days and hot days are regressed against spring soil moisture anomalies at four ICN stations across the state. The results show weak, inconsistent relationships between spring soil moisture and summer extreme maximum temperatures. However, we find a consistent response of summer hot days to antecedent 5-cm soil moisture anomalies at all four sites. The regression slopes of the 95th quantile are positive and larger than slopes at the 75th, 50th, 25th, and 5th quantiles, suggesting that the highest (warmest) end of the distribution responds most strongly to spring soil moisture. More specifically, the frequency and likelihood of oppressive summer events is increased following spring seasons with wetter-than-normal soils compared to spring seasons with drier-than-normal soils. Years in which wet soils in spring result in high frequency of hot days coincide with strong ridging over the Great Lakes and a diversion of disturbances to the north of the study region. These features act to increase evaporative demand and decrease precipitation over the summer season, allowing for larger consumption of local soil moisture reserves and increased energy to the atmosphere through latent heating.

The results of this paper should be placed within the context of the limitations of its datasets and methods. The relationships developed here are based on less than 30 years of meteorological and soil observations from four stations. Although high quality, ICN observations do not necessarily capture the conditions of the broader Midwest region and are subject to biases because of microscale perturbations from land cover or soil heterogeneity. Indeed, the sod landscape and associated shallow rooting depth at each of the four stations analyzed could potentially explain the contrast in the statistical relationships between and surficial soil moisture versus soil moisture in deeper layers. Similarly, the results of this study cannot be extrapolated to other global humid continental regions without proper assessment of the relationships demonstrated here. With those limitations in mind, the results of this evaluation suggest that characterizing soil moisture’s role in the onset or persistence of extreme heat events as a positive feedback (i.e., dry soils = extreme heat) may not capture the entire contribution of the land surface. In the humid Midwest region of the United States, the most severe heat events, in terms of human mortality, are associated with anomalously high atmospheric heat content through both sensible and latent contributions. Our results show these events, as defined by equivalent temperature, are strongly related to antecedent wet soils. It is therefore worth exploring a possible negative feedback (wet soils = oppressive heat) in other global humid regions and reexamining these relationships in the Midwest in order to more fully capture the role of land–atmosphere interactions in the onset and persistence of heat waves.

Acknowledgments

Data were provided by the Water and Atmospheric Resources Monitoring Program, a part of the Illinois State Water Survey (ISWS) located in Champaign and Peoria, Illinois, and on the web at www.isws.illinois.edu/warm. We thank Jennie Atkins for her insight and assistance with the Illinois Climate Network data. We would also like to thank the three anonymous reviewers for their valuable comments and suggestions. This work was partially supported by NSF Grant BCS-1339655 to Southern Illinois University.

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Journal of Hydrometeorology

  • Alexander, L., 2011: Climate science: Extreme heat rooted in dry soils. Nat. Geosci., 4, 12–13, doi:10.1038/ngeo1045.

  • Alfaro, E. J., Gershunov A. , and Cayan D. , 2006: Prediction of summer maximum and minimum temperature over the central and western United States: The roles of soil moisture and sea surface temperature. J. Climate, 19, 1407–1421, doi:10.1175/JCLI3665.1.

    • Search Google Scholar
    • Export Citation

  • Allen, R. G., Pereira L. S. , Raes D. , and Smith M. , 1998: Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56, 300 pp. [Available online at www.fao.org/docrep/X0490E/X0490E00.htm.]

  • Andresen, J. S., Hilberg S. , and Kunkel K. , 2012: Historical climate and climate trends in the midwestern USA. U.S. National Climate Assessment Midwest technical input report, GLISA, 18 pp. [Available online at http://glisa.msu.edu/docs/NCA/MTIT_Historical.pdf.]

  • Basara, J. B., and Crawford K. C. , 2002: Linear relationships between root-zone soil moisture and atmospheric processes in the planetary boundary layer. J. Geophys. Res., 107, 4274, doi:10.1029/2001JD000633.

    • Search Google Scholar
    • Export Citation

  • Bentley, M. L., and Stallins J. A. , 2008: Synoptic evolution of midwestern US extreme dew point events. Int. J. Climatol., 28, 1213–1225, doi:10.1002/joc.1626.

    • Search Google Scholar
    • Export Citation

  • Bolton, D., 1980: The computation of equivalent potential temperature. Mon. Wea. Rev., 108, 1046–1053, doi:10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Brown, P. J., and DeGaetano A. T. , 2013: Trends in U.S. surface humidity, 1930–2010. J. Appl. Meteor. Climatol., 52, 147–163, doi:10.1175/JAMC-D-12-035.1.

    • Search Google Scholar
    • Export Citation

  • Changnon, D., Sandstrom M. , and Bentley M. , 2006: Midwestern high dew point events 1960–2000. Phys. Geogr., 27, 494–504, doi:10.2747/0272-3646.27.6.494.

    • Search Google Scholar
    • Export Citation

  • Crimmins, A. J., and Coauthors, 2016: Appendix 1: Technical support document: Modeling future climate impacts on human health. The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment, U. S. Global Change Research Program, 287–300, doi:10.7930/J0KH0K83.

  • Davey, C. A., Pielke R. A. Sr., and Gallo K. P. , 2006: Differences between near-surface equivalent temperature and temperature trends for the eastern United States: Equivalent temperature as an alternative measure of heat content. Global Planet. Change, 54, 19–32, doi:10.1016/j.gloplacha.2005.11.002.

    • Search Google Scholar
    • Export Citation

  • Della-Marta, P. M., Haylock M. R. , Luterbacher J. , and Wanner H. , 2007: Doubled length of western European summer heat waves since 1880. J. Geophys. Res., 112, D15103, doi:10.1029/2007JD008510.

    • Search Google Scholar
    • Export Citation

  • Diffenbaugh, N. S., Pal J. S. , Giorgi F. , and Gao X. , 2007: Heat stress identification in the Mediterranean climate change hotspot. Geophys. Res. Lett., 34, L11706, doi:10.1029/2007GL030000.

    • Search Google Scholar
    • Export Citation

  • Fall, S., Diffenbaugh N. S. , Niyogi D. , Pielke R. A. Sr., and Rochon G. , 2010: Temperature and equivalent temperature over the United States (1979–2005). Int. J. Climatol., 30, 2045–2054, doi:10.1002/joc.2094.

    • Search Google Scholar
    • Export Citation

  • Fischer, E. M., Seneviratne S. I. , Vidale P. L. , Lüthi D. , and Schär C. , 2007: Soil moisture–atmosphere interactions during the 2003 European summer heat wave. J. Climate, 20, 5081–5099, doi:10.1175/JCLI4288.1.

    • Search Google Scholar
    • Export Citation

  • Ford, T. W., and Quiring S. M. , 2014: In situ soil moisture coupled with extreme temperatures: A study based on the Oklahoma Mesonet. Geophys. Res. Lett., 41, 4727–4734, doi:10.1002/2014GL060949.

    • Search Google Scholar
    • Export Citation

  • Frich, P., Alexander L. V. , Della-Marta P. , Gleason B. , Haylock M. , Klein Tank A. M. G. , and Peterson T. , 2002: Observed coherent changes in climatic extremes during the second half of the twentieth century. Climate Res., 19, 193–212, doi:10.3354/cr019193.

    • Search Google Scholar
    • Export Citation

  • Gaffen, D. J., and Ross R. J. , 1999: Climatology and trends of U.S. surface humidity and temperature. J. Climate, 12, 811–828, doi:10.1175/1520-0442(1999)012<0811:CATOUS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Guo, Z., Dirmeyer P. A. , and DelSole T. , 2011: Land surface impacts on subseasonal and seasonal predictability. Geophys. Res. Lett., 38, L24812, doi:10.1029/2011GL049945.

    • Search Google Scholar
    • Export Citation

  • Hirschi, M., and Coauthors, 2011: Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nat. Geosci., 4, 17–21, doi:10.1038/ngeo1032.

    • Search Google Scholar
    • Export Citation

  • Hollinger, S. E., and Isard S. A. , 1994: A soil moisture climatology of Illinois. J. Climate, 7, 822–833, doi:10.1175/1520-0442(1994)007<0822:ASMCOI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Hollinger, S. E., Reineke B. C. , and Peppler R. A. , 1994: Illinois Climate Network: Site descriptions, instrumentation, and data management. Circular 178, Illinois State Water Survey, 70 pp. [Available online at http://webh2o.sws.uiuc.edu/pubdoc/C/ISWSC-178.pdf.]

  • Huang, J., van den Dool H. M. , and Georgarakos K. P. , 1996: Analysis of model-calculated soil moisture over the United States (1931–1993) and applications to long-range temperature forecasts. J. Climate, 9, 1350–1362, doi:10.1175/1520-0442(1996)009<1350:AOMCSM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kunkel, K. E., 1989: A surface energy budget view of the 1988 midwestern United States drought. Bound.-Layer Meteor., 48, 217–225, doi:10.1007/BF00158325.

    • Search Google Scholar
    • Export Citation

  • Kunkel, K. E., Changnon S. A. , and Reinke B. C. , 1996: The July 1995 heat wave in the Midwest: A climatic perspective and critical weather factors. Bull. Amer. Meteor. Soc., 77, 1507–1518, doi:10.1175/1520-0477(1996)077<1507:TJHWIT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Lauritsen, R. G., and Rogers J. C. , 2012: U.S. diurnal temperature range variability and regional causal mechanisms, 1901–2002. J. Climate, 25, 7216–7231, doi:10.1175/JCLI-D-11-00429.1.

    • Search Google Scholar
    • Export Citation

  • Lorenz, R., Jaeger E. B. , and Seneviratne S. I. , 2010: Persistence of heat waves and its link to soil moisture memory. Geophys. Res. Lett., 37, L09703, doi:10.1029/2010GL042764.

    • Search Google Scholar
    • Export Citation

  • Meng, L., and Shen Y. , 2014: On the relationship of soil moisture and extreme temperatures in east China. Earth Interact., 18, doi:10.1175/2013EI000551.1.

    • Search Google Scholar
    • Export Citation

  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343–360, doi:10.1175/BAMS-87-3-343.

    • Search Google Scholar
    • Export Citation

  • Miralles, D. G., van den Berg M. J. , Teuling A. J. , and de Jeu R. A. M. , 2012: Soil moisture–temperature coupling: A multiscale observational analysis. Geophys. Res. Lett., 39, L21707, doi:10.1029/2012GL053703.

    • Search Google Scholar
    • Export Citation

  • Mo, K., 2003: Ensemble canonical correlation prediction of surface prediction over the United States. J. Climate, 16, 1665–1683, doi:10.1175/1520-0442(2003)016<1665:ECCPOS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Mueller, B., and Seneviratne S. I. , 2012: Hot days induced by precipitation deficits at the global scale. Proc. Natl. Acad. Sci. USA, 109, 12 398–12 403, doi:10.1073/pnas.1204330109.

    • Search Google Scholar
    • Export Citation

  • Orth, R., and Seneviratne S. I. , 2014: Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe. Climate Dyn., 43, 3403–3418, doi:10.1007/s00382-014-2112-x.

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  • <sc>Fig</sc>. 1.
    View in gallery
    Fig. 1.

    (a) ICN stations, (b) average monthly , , and the difference between and at DeKalb ICN station, and (c) average monthly soil moisture at DeKalb station. Averages in (b) and (c) are computed from data spanning 1992–2014.

  • <sc>Fig</sc>. 2.
    View in gallery
    Fig. 2.

    Quantile regression of summer percent hot days against spring 5-cm soil moisture at (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria. The regression lines represent the fit at the 95th, 75th, 50th, 25th, and 5th quantiles.

  • <sc>Fig</sc>. 3.
    View in gallery
    Fig. 3.

    Lagged cross correlations between daily 5- and 50-cm soil moisture at (a) Belleville and (b) Champaign stations.

  • <sc>Fig</sc>. 4.
    View in gallery
    Fig. 4.

    Distributions of summer (°C). The distribution medians are shown by the solid black line, while the 5th and 95th percentiles are shown by the dashed black line. The red (blue) thick and dashed lines represent the median and 5th, 95th percentile values of distributions from the summers associated with the eight wettest (driest) springs, respectively. Results are from (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria.

  • <sc>Fig</sc>. 5.
    View in gallery
    Fig. 5.

    Quantile regression of summer percent hot days against spring 5-cm soil moisture at (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria. The regression lines represent the fit at the 95th, 75th, 50th, 25th, and 5th quantiles.

  • <sc>Fig</sc>. 6.
    View in gallery
    Fig. 6.

    Distributions of summer (°C). The distribution medians are shown by the solid black line, while the 5th and 95th percentiles are shown by the dashed black line. The red (blue) thick and dashed lines represent the median and 5th, 95th percentile values of distributions from the summers associated with the eight wettest (driest) springs, respectively. Results are from (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria.

  • <sc>Fig</sc>. 7.
    View in gallery
    Fig. 7.

    (a),(b) The 500-hPa geopotential height anomalies and (c),(d) 300-mb mean vector winds composited for the summers 1990, 1995, and 1999 (left) and 1996, 2008, and 2009 (right).

  • <sc>Fig</sc>. 8.
    View in gallery
    Fig. 8.

    The 850-hPa geopotential height anomalies composited from all hot days for the summers 1990, 1995, and 1999.

  • <sc>Fig</sc>. 9.
    View in gallery
    Fig. 9.

    Daily cumulative sum of P − PET (cm), averaged over the summers (red line) 1990, 1995, and 1999 and (blue line) 1996, 2008, and 2009 at the (a) Belleville and (b) Champaign sites. The squares represent monthly soil moisture anomalies from each set of summers. The daily cumulative sum of P − PET and soil moisture anomalies for each of the individual years [(c) 1990, 1995, and 1999; (d) 1996, 2008, and 2009] at the Belleville station.

Fig. 1.

(a) ICN stations, (b) average monthly , , and the difference between and at DeKalb ICN station, and (c) average monthly soil moisture at DeKalb station. Averages in (b) and (c) are computed from data spanning 1992–2014.
Fig. 2.

Quantile regression of summer percent hot days against spring 5-cm soil moisture at (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria. The regression lines represent the fit at the 95th, 75th, 50th, 25th, and 5th quantiles.
Fig. 3.

Lagged cross correlations between daily 5- and 50-cm soil moisture at (a) Belleville and (b) Champaign stations.
Fig. 4.

Distributions of summer (°C). The distribution medians are shown by the solid black line, while the 5th and 95th percentiles are shown by the dashed black line. The red (blue) thick and dashed lines represent the median and 5th, 95th percentile values of distributions from the summers associated with the eight wettest (driest) springs, respectively. Results are from (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria.
Fig. 5.

Quantile regression of summer percent hot days against spring 5-cm soil moisture at (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria. The regression lines represent the fit at the 95th, 75th, 50th, 25th, and 5th quantiles.
Fig. 6.

Distributions of summer (°C). The distribution medians are shown by the solid black line, while the 5th and 95th percentiles are shown by the dashed black line. The red (blue) thick and dashed lines represent the median and 5th, 95th percentile values of distributions from the summers associated with the eight wettest (driest) springs, respectively. Results are from (a) Belleville, (b) Champaign, (c) DeKalb, and (d) Peoria.
Fig. 7.

(a),(b) The 500-hPa geopotential height anomalies and (c),(d) 300-mb mean vector winds composited for the summers 1990, 1995, and 1999 (left) and 1996, 2008, and 2009 (right).
Fig. 8.

The 850-hPa geopotential height anomalies composited from all hot days for the summers 1990, 1995, and 1999.
Fig. 9.

Daily cumulative sum of P − PET (cm), averaged over the summers (red line) 1990, 1995, and 1999 and (blue line) 1996, 2008, and 2009 at the (a) Belleville and (b) Champaign sites. The squares represent monthly soil moisture anomalies from each set of summers. The daily cumulative sum of P − PET and soil moisture anomalies for each of the individual years [(c) 1990, 1995, and 1999; (d) 1996, 2008, and 2009] at the Belleville station.
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