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  • View in gallery

    Timelines of (top) harvested acreage and (bottom) production of major crops in Nebraska since 1866 [data obtained from NASS (2013)]. Note that the data for irrigated crops only begin in 1947.

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    An idealized schematic depicting the local and nonlocal effects of irrigation on atmospheric thermodynamics and precipitation processes: Rnet = net surface radiation, LH = latent heat flux, SH = sensible heat flux, Td = dewpoint temperature, and T = temperature. See the main text for other term definitions. The linear depictions of Td and T show the changes in mixing ratio and dry adiabatic lapse rate, respectively, given near-surface Td and T from preirrigation (dotted lines) to full irrigation (solid lines). The intersection of these lines gives the approximate height of the LCL. Note that the downwind area on the right can be considered to be in a preirrigation condition, with either nonirrigated crops or grass.

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    (a) Map of station density by climate division. (b) Example of a time period–intensity plot from south-central Georgia (climate division 8). The precipitation bins are specified by their lower bounds; for example, the lightest bin is 0.25–2.5 mm (0.01–0.1 in.), followed by 2.5–6.4 mm (0.1–0.25 in.), etc. Information from this plot is used in Fig. 5 (and similarly in Fig. 6, for intensity): for example, south-central Georgia has a total of seven significant increases across the entire intensity distribution in July (see Fig. 5b).

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    Regional maps of changes in (top) total precipitation, (middle) precipitation frequency, and (bottom) precipitation event intensity during (left) June, (center) July, and (right) August. The time period–intensity plots within each region have the same axis labels as in Fig. 3b.

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    The sum of significant increases (p ≤ 0.05) in precipitation frequency (top) over all precipitation intensity bins, (middle) over the lightest four bins (0.25–25 mm), and (bottom) over the heaviest six bins (>25 mm) for each climate division during (left) June, (center) July, and (right) August.

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    The sum of significant increases (p ≤ 0.05) in precipitation event intensity over all precipitation bins for each climate division during (a) June, (b) July, and (c) August.

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    Regional changes in mean monthly (top) total precipitation, (middle) precipitation frequency, and (bottom) precipitation intensity during June (light gray), July (dark gray), and August (medium gray) between 1895–1933 and 1973–2011, corresponding to row 6 of the time period–intensity plots (see Fig. 3b).

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    Absolute changes in (top) total precipitation, (middle) precipitation frequency, and (bottom) precipitation intensity during (left) June, (center) July, and (right) August between 1895–1933 and 1973–2011, corresponding to row 6 of the time period–intensity plots (see Fig. 3b). Brown shadings are negative changes.

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    Monthly ranks (out of 12 months) of absolute changes in (top) total precipitation, (middle) precipitation frequency, and (bottom) precipitation intensity for (left) June, (center) July, and (right) August between 1895–1933 and 1973–2011, corresponding to row 6 of the time period–intensity plots (see Fig. 3b). Dark green represents the highest rank and dark brown the lowest.

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    Correlations of monthly mean precipitation during (left) July and (right) August with (top to bottom) monthly indices of various large-scale atmospheric circulations (averaged over 1948–2012): Niño-3.4, which measures sea surface temperature anomalies in the tropical Pacific Ocean and corresponds to the state of the ENSO; NAO; AMO; Pacific–North American teleconnection (PNA); and PDO. Absolute increases in July and August total precipitation from Fig. 8 are included on the bottom for reference. Correlations are calculated from the U.S. Climate Division Dataset seasonal correlation page (www.esrl.noaa.gov/psd/data/usclimdivs/correlation/).

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Observational Evidence that Great Plains Irrigation Has Enhanced Summer Precipitation Intensity and Totals in the Midwestern United States

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  • 1 Department of Environmental Sciences, Rutgers, The State University of New Jersey, New Brunswick, New Jersey
  • | 2 Department of Environmental Sciences, Rutgers, The State University of New Jersey, New Brunswick, and Department of Earth and Planetary Sciences, Rutgers, The State University of New Jersey, Piscataway, New Jersey
  • | 3 Department of Environmental Sciences, Rutgers, The State University of New Jersey, New Brunswick, New Jersey
  • | 4 U.S. Global Change Research Program, Washington, D.C.
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Abstract

Significant increases in summer precipitation have occurred in the midwestern United States over the last century for reasons that remain unclear. It is postulated that the expansion of irrigation and cropland in the central United States over the past 60 yr has been a major contributor to these observed increases in precipitation. As a first step toward attribution of these precipitation changes, a detailed analysis of observed daily summer precipitation frequency and intensity is conducted for the contiguous United States over multiple spatial scales and time periods from 1895 to 2011. Robust increases in precipitation frequency, total precipitation, and moderate to heavy precipitation intensity are identified during July and August in the midwestern United States. Analysis of changes in mean monthly precipitation from the early to late twentieth century initially points to increasing frequency as the source of increasing monthly precipitation in the midwestern United States during the summer, especially during August; however, these large frequency increases are not unique to the summer. On the other hand, changes in precipitation intensity and total precipitation are both greatest during July and August and coincide spatially in the midwestern United States. Additionally, the greatest intensity change occurs downwind of the most heavily irrigated regions, especially for the period between 1950 and 1980 when irrigation rapidly intensified. Thus, the seasonality and location of these regional signatures of increasing precipitation intensity (and total precipitation) are found to be broadly consistent with spatiotemporal trends in irrigation and cropland in the central United States and may be indicative of a causal link.

Current affiliation: Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts.

Corresponding author address: Ross E. Alter, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Ralph M. Parsons Laboratory, 15 Vassar Street, Cambridge, MA 02139. E-mail: ralter1@mit.edu

Abstract

Significant increases in summer precipitation have occurred in the midwestern United States over the last century for reasons that remain unclear. It is postulated that the expansion of irrigation and cropland in the central United States over the past 60 yr has been a major contributor to these observed increases in precipitation. As a first step toward attribution of these precipitation changes, a detailed analysis of observed daily summer precipitation frequency and intensity is conducted for the contiguous United States over multiple spatial scales and time periods from 1895 to 2011. Robust increases in precipitation frequency, total precipitation, and moderate to heavy precipitation intensity are identified during July and August in the midwestern United States. Analysis of changes in mean monthly precipitation from the early to late twentieth century initially points to increasing frequency as the source of increasing monthly precipitation in the midwestern United States during the summer, especially during August; however, these large frequency increases are not unique to the summer. On the other hand, changes in precipitation intensity and total precipitation are both greatest during July and August and coincide spatially in the midwestern United States. Additionally, the greatest intensity change occurs downwind of the most heavily irrigated regions, especially for the period between 1950 and 1980 when irrigation rapidly intensified. Thus, the seasonality and location of these regional signatures of increasing precipitation intensity (and total precipitation) are found to be broadly consistent with spatiotemporal trends in irrigation and cropland in the central United States and may be indicative of a causal link.

Current affiliation: Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts.

Corresponding author address: Ross E. Alter, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Ralph M. Parsons Laboratory, 15 Vassar Street, Cambridge, MA 02139. E-mail: ralter1@mit.edu

1. Introduction

Over the course of the twentieth century, statistically significant increases in precipitation have occurred in the midwestern United States (Karl et al. 1996; Angel and Huff 1997; Pryor et al. 2009; Groisman et al. 2012; Villarini et al. 2013; Melillo et al. 2014), especially during the summer (June–August; Changnon and Kunkel 1995; Karl and Knight 1998; Groisman et al. 2004; DeAngelis et al. 2010; Higgins and Kousky 2013). Several potential drivers of such increases have been proposed, including large-scale atmospheric circulations and teleconnections, for example, El Niño–Southern Oscillation (ENSO; Groisman et al. 2012); shifts in the nocturnal Great Plains low-level jet (Weaver and Nigam 2008); and increases in temperature as a result of greenhouse gas emissions (Groisman et al. 2004; Villarini et al. 2013). Land use and land cover changes (LULCCs) over the last century, such as dam and reservoir construction (Hossain et al. 2009), conversion of forest and grassland to cropland (Baidya Roy et al. 2003), increasing crop acreage and yield (Groisman et al. 2012), and the development of large-scale cropland irrigation (Barnston and Schickedanz 1984; DeAngelis et al. 2010) have also been hypothesized as potential drivers of precipitation change. However, uncertainty remains in the relative importance of each driver in explaining the observed changes in total precipitation.

In the present study, we analyze observed changes in regional precipitation characteristics in the midwestern United States and consider how these may relate to the historical intensification of irrigation and expansion of cropland in the central United States, especially Nebraska. Irrigation in the U.S. Great Plains began rapidly developing in Texas in the 1930s and across the rest of the Great Plains in the 1940s and 1950s. In Nebraska—the most densely irrigated of the Great Plains states—the abundance of water from the Ogallala Aquifer combined with lower energy costs and improved technology (Guru and Horne 2000) facilitated expansion of irrigated acreage from approximately 876 000 acres in 1949 to 5 700 000 acres in 1978, and further to 8 559 000 acres in 2007—almost twice the area of the state of New Jersey (NASS 2013). Groundwater withdrawal for irrigation experienced similar rapid development from about 600 000 acre ft in 1950 to about 6 500 000 acre ft in 1980 (USGS 2013). In 2013, total irrigation-related groundwater withdrawal for Nebraska counties over the Ogallala Aquifer was estimated at 7 960 000 acre ft, or 13 times larger than the estimated amount in 1950 (NRCS 2013).

As a result of the expansion of irrigation, irrigated cropland became the dominant type of warm-season agriculture in Nebraska (see Fig. 1). In 1950, approximately 7% of corn and soybean acreage in Nebraska was irrigated; by 2011, approximately 54% of the same crop acreage was irrigated (NASS 2013). A similar change occurred for production of these crops: in 1950, approximately 12% of corn and soybean production was irrigated, while in 2011, approximately 64% of that production was irrigated (NASS 2013). Generally, the expansion of crops in Nebraska over the last 60 yr, in acreage by a factor of 2 and in production by a factor of 7, may be largely attributed to enhanced cropland irrigation during this time period.

Fig. 1.
Fig. 1.

Timelines of (top) harvested acreage and (bottom) production of major crops in Nebraska since 1866 [data obtained from NASS (2013)]. Note that the data for irrigated crops only begin in 1947.

Citation: Journal of Hydrometeorology 16, 4; 10.1175/JHM-D-14-0115.1

In the 1970s and 1980s, several studies analyzed station observations of precipitation to demonstrate a supposed “irrigation effect” on local precipitation, that is, precipitation enhancement in the vicinity of heavily irrigated regions (Stidd 1975; Barnston and Schickedanz 1984). These early studies indicated enhanced precipitation about 50–100 km downwind of heavily irrigated areas in Washington State during July and August and in the Texas Panhandle during June. Later studies focused on larger regions of the United States (Segal et al. 1998) and analyzed precipitation patterns using weather radar (Moore and Rojstaczer 2002) and water vapor tracking (DeAngelis et al. 2010; Harding and Snyder 2012b) to demonstrate the plausibility of irrigation effects on precipitation. Recent numerical modeling experiments for the United States (Ozdogan et al. 2010; Lo and Famiglietti 2013; Qian et al. 2013) and other areas globally (e.g., De Ridder and Gallée 1998; Douglas et al. 2009; Sacks et al. 2009; Jódar et al. 2010; Puma and Cook 2010; Lee et al. 2011; Wei et al. 2013) provide additional support for irrigation-related influences on precipitation patterns, both locally and remotely.

In the current study, we perform a comprehensive analysis of station observations of summer precipitation and attempt to identify signals in precipitation frequency, intensity, and totals that are indicative of an irrigation-induced enhancement of precipitation. While the analyses cover the entire contiguous United States (CONUS), we emphasize two target regions—the Upper Midwest (Minnesota, Wisconsin, Michigan, and Iowa) and the Midwest (Missouri, Illinois, Indiana, Ohio, and Kentucky)—which together form the midwestern United States. Since the midwestern United States is downwind of Nebraska, which contains more irrigated acres than any state in the United States, this is the area where the largest irrigation-induced enhancement in precipitation is expected to occur. In section 2, we describe potential mechanisms for how irrigation affects precipitation as well as related hypotheses, while in sections 3 and 4, we describe our methodology and results. As a first step toward attribution, we discuss in section 5 how the results compare with expectations based on the mechanisms outlined in section 2.

2. Potential mechanisms for LULCC enhancement of precipitation

a. Irrigation

Figure 2 illustrates several potential influences of irrigation on atmospheric thermodynamics and associated precipitation processes. The basic premise of an irrigation effect on precipitation is that irrigation increases soil moisture, thereby lowering surface albedo (Eltahir 1998; Pielke 2001) and repartitioning the surface energy budget toward larger latent heat flux, smaller sensible heat flux, and consequently a lower Bowen ratio (Eltahir 1998; Adegoke et al. 2003; Betts 2004; Mahmood et al. 2004). Both the lower albedo and repartitioned energy budget may increase net radiation at the surface: reduced albedo increases the absorption of incident solar radiation, while the repartitioning of sensible and latent heat fluxes results in decreased outgoing surface longwave emission, both through lower surface temperatures and an amplified water vapor greenhouse effect (Eltahir 1998). Since increasing net radiation at the surface necessitates an increase in total outgoing surface heat fluxes (Betts et al. 1996; Eltahir 1998), the flux of moist static energy (MSE) into the planetary boundary layer (PBL) should increase (Eltahir 1998; Pal and Eltahir 2001). However, the dense crop cover during the summer may prevent a noticeable change in soil albedo even under irrigated conditions. In fact, other studies suggest that net radiation is rather insensitive to soil moisture (Betts 2004; Jones and Brunsell 2009), so the hypothesized enhanced flux of MSE into the PBL may be overemphasized. The historical increase of (irrigated) crop acreage, density, and greenness as a result of irrigation further strengthens the magnitude of these fluxes into the PBL (Wang et al. 2003).

Fig. 2.
Fig. 2.

An idealized schematic depicting the local and nonlocal effects of irrigation on atmospheric thermodynamics and precipitation processes: Rnet = net surface radiation, LH = latent heat flux, SH = sensible heat flux, Td = dewpoint temperature, and T = temperature. See the main text for other term definitions. The linear depictions of Td and T show the changes in mixing ratio and dry adiabatic lapse rate, respectively, given near-surface Td and T from preirrigation (dotted lines) to full irrigation (solid lines). The intersection of these lines gives the approximate height of the LCL. Note that the downwind area on the right can be considered to be in a preirrigation condition, with either nonirrigated crops or grass.

Citation: Journal of Hydrometeorology 16, 4; 10.1175/JHM-D-14-0115.1

In contrast, the effects of the repartitioned radiative budget have rather direct implications for PBL structure and thermodynamics. The smaller sensible heat flux and the associated decrease in temperature (Adegoke et al. 2003, 2007; Mahmood et al. 2004, 2006; Lobell et al. 2008) lower PBL height, which simultaneously reduces entrainment of low-MSE air at the top of the PBL (Betts et al. 1996) and increases the MSE per unit mass of PBL air (Eltahir 1998), both of which are expected to encourage atmospheric convection. Additionally, the greater latent heat flux is indicative of increased evapotranspiration (ET) from the surface (Pielke 2001; Ozdogan et al. 2010), which moistens the PBL. This moistening of the PBL over irrigated areas, which has been documented in studies of changes in dewpoint temperature (Mahmood et al. 2006, 2008) and specific and relative humidity (Brown and DeGaetano 2013; Qian et al. 2013), lowers the lifting condensation level (LCL; cloud base) (Betts 2004; Sun et al. 2007), allowing rising air parcels to more readily form clouds and potentially reach their level of free convection (LFC). Increased moisture in the PBL also enhances convective available potential energy (CAPE; Pielke and Zeng 1989; Pielke 2001; Qian et al. 2013; Huber et al. 2014), which represents the conduciveness of the upper-air environment for convective development.

However, it is also possible that irrigation-induced radiative changes may reduce the potential for convection over the irrigated areas. In particular, the expected decreases in the LCL over the irrigated areas may be greater than those of the LFC because the LCL is closer to the surface and therefore would likely respond more readily to increased irrigation. The greater decrease of the LCL is evident in the irrigation-induced changes to the atmospheric vertical profile depicted in Huber et al. (2014). If the LCL of a parcel is lowered more than its LFC, then the vertical distance over which a saturated air parcel must rise to reach its LFC, attain positive buoyancy, and utilize CAPE would increase. The increasing distance between the LCL and LFC would likely increase convective inhibition (CIN), that is, the energy needed for a saturated parcel to overcome negative buoyancy and reach its LFC, thus reducing the likelihood of deep, moist convective development and precipitation (Huber et al. 2014; Im et al. 2014). Additionally, if the height of the LCL is lowered more than the height of the PBL, it is possible that shallow convective clouds would preferentially develop (Qian et al. 2013). Since enhanced CIN hinders the development of convective precipitation, these shallow, nonprecipitating clouds may block incoming solar radiation, thereby reducing net surface radiation and creating a negative feedback on the initial flux perturbations caused by irrigation (Qian et al. 2013). Such mechanisms may account for the results of some studies showing reduced frequency of summer precipitation events over irrigated areas (Harding and Snyder 2012a; Huber et al. 2014; Im et al. 2014).

The aforementioned mechanisms are effectively local responses to irrigation. However, the advection of air with additional moisture and moist static energy from irrigated areas to more convectively favorable areas downwind, for example, where CIN is not enhanced, could increase the frequency and/or intensity of storms in downwind regions (DeAngelis et al. 2010). This is especially true during the summer, when the characteristics of the PBL can be important in determining the probability of rainfall occurrence (Findell and Eltahir 2003a,b). The downwind enhancement of irrigation on precipitation has already been demonstrated on local scales (see above) and remotely (e.g., DeAngelis et al. 2010; Harding and Snyder 2012b; Lo and Famiglietti 2013; Wei et al. 2013; Huber et al. 2014), but uncertainty remains in the degree and location of irrigation impacts on more regional scales. Average winds during July and August at the 850-hPa pressure level, which is often used to diagnose moisture transport (Harding and Snyder 2012a; Huber et al. 2014), are generally southwesterly over eastern Nebraska, where extensive cropland irrigation occurs. Thus, if irrigation in Nebraska were to cause downwind enhancement of precipitation via an increase in moisture (convergence), it would likely be in the Upper Midwest states of Iowa, Minnesota, Wisconsin, and Michigan, assuming enough vertical transport of the air parcels to reach the 850-hPa pressure level; otherwise, winds at the surface are generally more southerly and would likely lead to precipitation enhancement in the Dakotas and Minnesota. Note that the scale of irrigation in the states downwind of Nebraska is much less than that of Nebraska itself because of the more humid climate; thus, irrigation in these downwind regions are not expected to significantly add to the rainfall effects expected from irrigation in Nebraska.

The contrasts in phenology between irrigated crops, rain-fed crops, and potential vegetation are important for determining the most appropriate timing for an irrigation effect. Most irrigation occurs during July and August in Nebraska, when ET is highest and crop water demand is maximized [Suyker and Verma (2008); Ozdogan et al. (2010); see Fig. 1c in DeAngelis et al. (2010) for a depiction of monthly crop water use in the Great Plains]. For both semiarid and subhumid climates within Nebraska, irrigated corn has been demonstrated to have a longer growing season than rain-fed corn and grass, which results in higher values of ET lasting into August (Mahmood and Hubbard 2002). While peak ET from irrigated corn is in July, the largest difference between ET from irrigated corn fields and that of rain-fed corn and grass is in August; this is also reflected in a modeling study done by Ozdogan et al. (2010). Hence, if more irrigation-induced moisture is available in August, then the largest, most expansive irrigation effect on precipitation would be expected in August, a more moderate irrigation effect in July, and not much effect at all in June.

b. Other potential mechanisms

A similar mechanism may apply to the expansion of nonirrigated cropland in the Corn Belt of the United States, which extends eastward from Nebraska to Ohio and northward to Minnesota and the eastern Dakotas. Instead of a soil moisture–precipitation feedback, plant transpiration would increase as a result of increasing crop acreage, density, and greenness. From 1940 to 2011, the acreage of corn and soybeans roughly doubled in Iowa and Illinois, and production of corn and soybeans increased in the two states by a factor of 5 (NASS 2013). However, the degree to which this increase in nonirrigated crop acreage and production affects precipitation is unclear. Latent heat flux, and thus ET, has been shown to increase when converting from grassland to rain-fed cropland (Wang et al. 2003), and specific humidity (Bonan 1997) and precipitation (Bonan 1997; Raddatz 2007) have also exhibited increases as a result of land cover conversion to cropland. However, Adegoke et al. (2003) demonstrate that increases in latent heat flux in Nebraska are stronger for conversion from rain-fed to irrigated agriculture than for conversion from natural vegetation to rain-fed agriculture. Additionally, Baidya Roy et al. (2003) show no significant change in July precipitation in the midwestern United States between 1910 and 1990 when accounting solely for changes in historical land cover fractions (without irrigation). Therefore, while the potential contribution of nonirrigated cropland expansion and greater crop production to changes in precipitation patterns cannot be ruled out, it may be secondary to the forcing caused by irrigation development.

Other studies have demonstrated potential impacts of irrigation on the dynamical forcings of summer precipitation, for example, the Great Plains low-level jet (Huber et al. 2014) and monsoonal circulations (Douglas et al. 2009; Lee et al. 2011; Im et al. 2014). Moisture convergence may be enhanced in certain areas if irrigation modifies the direction, magnitude, and/or moisture transport of these background wind patterns. However, further attribution of long-term precipitation changes to these phenomena would require the long-term (>60 yr) determination of observational or modeled changes to the Great Plains low-level jet and/or to wind speed and direction over time, both of which are not readily available. Though the limited observational nature of the present study precludes diagnosis of potential circulation changes, they are likely important links between irrigation and its effects on precipitation patterns.

Finally, climate change (CC) from greenhouse gas emissions may be a potential mechanism. For CC, enhancements in ET and saturation vapor pressure from rising temperatures (Clausius–Clapeyron relation) may cause distinct changes in precipitation patterns that, along with those caused by irrigation, may be ascertained from analysis of the observational record. Therefore, our hypotheses, outlined in the next subsection, describe the expected precipitation effects from both CC and irrigation (or more generally, LULCC) to determine which one has been more important in influencing observed changes in summer precipitation patterns.

c. Hypotheses

While the aforementioned mechanisms are each plausible, it is difficult to establish direct causal linkages, especially with observations. Some of this difficulty may be the result of not separating changes in precipitation frequency from those of precipitation intensity; the relative contributions of frequency and intensity change may provide insight into mechanisms. Moreover, it is possible that distinct mechanisms account for changes in different portions of the precipitation distribution, for example, the controls on light precipitation events may differ from those on heavy events. Therefore, our hypotheses incorporate both of these dichotomies—frequency and intensity, and lighter and heavier precipitation—to better attribute the observed changes in precipitation.

We hypothesize that CC and LULCC (specifically, irrigation and nonirrigated crop expansion) have distinct signatures in changes of the precipitation distribution. Note that we investigate CC and LULCC as separate hypotheses, rather than CC and CC + LULCC. While summer temperatures may have indeed increased across much of the midwestern United States over the last century (NCDC 2014), warming has not occurred over the entire area during the summer (e.g., Brown and DeGaetano 2013). This precludes the assumption that CC has been a given in this region. Additionally, separation of these hypotheses may allow for better attribution of the observed changes to one mechanism over the other.

If CC is the main driver, warmer temperatures would increase ET, saturation vapor pressure, and atmospheric water vapor, thus stimulating more intense and more frequent heavy precipitation events (Trenberth et al. 2003). However, the overall frequency of precipitation events—especially those of light and moderate intensity—would likely stay roughly the same or decrease (Hennessy et al. 1997; Sun et al. 2007). This expected decrease in overall precipitation frequency would largely cancel out the effects on total precipitation of general increases in precipitation intensity (due to the extra water vapor). Indeed, an ensemble of global climate model simulations using the RCP8.5 scenario (where greenhouse gas emissions result in a +8.5 W m−2 radiative forcing by the year 2100) indicates that total summer precipitation is projected to either remain roughly constant or increase slightly (less than 10%) in the midwestern United States by the years 2081–2100, even though annual average surface temperature in the same region is projected to be 5–7 K greater than present (Collins et al. 2013). Thus, it is expected that increases in surface temperature due to CC would likely result in only a small (if any) net change in total precipitation.

On the other hand, if LULCC is the main driver, the combination of enhanced MSE from greater net radiation and enhanced atmospheric water vapor from greater ET could destabilize the PBL and create more frequent convective precipitation events over the entire precipitation distribution (Findell and Eltahir 2003a). However, LULCC likely does not have as much of an effect on precipitation frequency compared with precipitation intensity since 1) the increase in net radiation, and therefore in MSE, is less prominent than the repartitioning of heat fluxes and consequent increase in water vapor and 2) nonlocal (synoptic and mesoscale) forcings likely determine the periods during which convective precipitation is most favorable (Allard and Carleton 2010; Huber et al. 2014). On the other hand, the added moisture in the PBL, potentially altered wind patterns, and thus increased moisture convergence downwind would very likely enhance precipitation intensity. Therefore, we expect that LULCC would have a stronger effect on precipitation intensity than on precipitation frequency in the midwestern United States. The increase in precipitation intensity (combined with potentially greater precipitation frequency) would likely enhance total precipitation if LULCC is the main driver. It is expected that the largest increases in total precipitation would occur downwind of the irrigated regions because of the offsetting effects of greater CIN and greater shallow cloud cover directly over the irrigated areas.

In summary, if CC is the main driver, the precipitation distribution would shift toward more frequent and intense heavy events, less frequent lighter events, and small changes in total amounts. If LULCC is the main driver, the precipitation signal would be weak over the irrigated areas but more pronounced downwind, especially in the Upper Midwest spatially and in August temporally. In this region, we would expect to see enhancements in intensity and perhaps frequency, giving higher total precipitation amounts. These are the signals that we attempt to detect in the following data analyses.

3. Data and methods

Daily precipitation data were obtained from the Global Historical Climatology Network–Daily (GHCND) archive of the National Climatic Data Center (NCDC). The GHCND dataset and its predecessor, the Global Daily Climatology Network, have been utilized by several previous works to analyze extreme precipitation patterns, determine historical precipitation frequencies, and calculate long-term trends in precipitation (e.g., Groisman et al. 2005; Alexander et al. 2006; Sun et al. 2006; Degu et al. 2011; Utsumi et al. 2011; Peterson et al. 2013). Another advantage of GHCND is that in 2011, it became the official archive of all U.S. daily climate data, including the U.S. National Weather Service Cooperative Observer Network, which has been previously used in long-term precipitation studies (e.g., Karl and Knight 1998; Kunkel et al. 2003; Groisman et al. 2004, 2012). With these updates, GHCND now features unparalleled spatial coverage and hundreds of long-term precipitation stations throughout the contiguous United States. Additionally, the GHCND dataset is regularly subjected to a suite of 19 quality-control tests, as well as format testing and record integrity checks (Menne et al. 2012). The main caveat with GHCND is that it is not adjusted for systematic biases resulting from instrument and/or reporting changes that may have occurred over the period of record for a particular station. A more systematic and extensive quality-control effort, for example, removal of statistical biases resulting from the above issues, is beyond the scope of this paper; thus, it is worth noting that the results may be affected by inconsistencies in data homogeneity. However, given the pros and cons of the dataset, we believe that inclusion of multiple overlapping temporal and spatial scales (described below), precedent in other peer-reviewed literature, and unparalleled spatiotemporal coverage of daily data permit the use of GHCND in determining long-term, observed changes in precipitation.

To further enhance the robustness of the following analyses of long-term precipitation changes, only those stations containing at least 90 years of data over 1895–2011 were considered for this study. Data flagged for potential quality concerns were not included in the analysis, and missing values were removed. A total of 1736 stations were retained for analysis, with the highest station densities in the central United States, Texas, and California (Fig. 3a).

Fig. 3.
Fig. 3.

(a) Map of station density by climate division. (b) Example of a time period–intensity plot from south-central Georgia (climate division 8). The precipitation bins are specified by their lower bounds; for example, the lightest bin is 0.25–2.5 mm (0.01–0.1 in.), followed by 2.5–6.4 mm (0.1–0.25 in.), etc. Information from this plot is used in Fig. 5 (and similarly in Fig. 6, for intensity): for example, south-central Georgia has a total of seven significant increases across the entire intensity distribution in July (see Fig. 5b).

Citation: Journal of Hydrometeorology 16, 4; 10.1175/JHM-D-14-0115.1

Our choice of spatial aggregates (climate divisions and regions) is motivated by NCDC practice. While the former match the standards used by the NCDC, the latter are defined by the authors and differ slightly from the NCDC definitions (not shown; Karl and Koss 1984). Among the principal differences are 1) redistribution of climate regions in the southeastern United States to isolate potential impacts of shifts in tropical storm activity; 2) partitioning of the “northern Rockies and Plains” region into “northern Rockies” and “northern plains” to isolate the plains from the more topographically diverse northern Rockies; and 3) redistribution of states within the Midwest and Northeast regions to even out the areal coverage of the climate regions.

To reduce the sensitivity to temporal period, precipitation was compared across different temporal segments (Fig. 3b, vertical axis). The precipitation data were first sorted into 10 bins of different intensity, ranging from 0.25–2.5 mm (0.01–0.1 in.) to 152+ mm (6+ in.) (Fig. 3b, horizontal axis). A time series of 117 data points—one for each year from 1895 to 2011—was compiled for each intensity bin for frequency, intensity, and total precipitation, with each datum representing a per-station average for each climate region or division. Segments of different temporal length (e.g., 36 values each for 1895–1930 and 1976–2011) were then compared using a two-sample, two-tailed Student’s t test to determine the significance of any changes between the means of the distributions. The results were concatenated into “time period–intensity” plots (Fig. 3b).

Similar to the methodology of Groisman et al. (2012), use of irregularly spaced widths of precipitation intensity bins reflects the nature of the original precipitation measurements (reported in inches, rather than millimeters). The first two bins are termed “light precipitation” [0.25–6.4 mm day−1 (0.01–0.25 in. day−1)], the third and fourth bins are “moderate precipitation” [6.4–25 mm day−1 (0.25–1 in. day−1)]; the fifth and sixth bins are “heavy precipitation” [25–76 mm day−1 (1–3 in. day−1)]; and the remaining four bins are “very heavy precipitation” [>76 mm day−1 (3 in. day−1)].

4. Results

a. Statistically significant changes in precipitation

1) Precipitation frequency

Figures 4d–f summarize changes in the frequency of precipitation events in June–August. The Midwest and the Upper Midwest clearly stand out, with significant increases (p ≤ 0.05) over the second half of the twentieth century during July and August (Figs. 4e,f). In the Upper Midwest, almost all precipitation bins exhibit significant increases in precipitation frequency during these two months, especially during August, when nearly every temporal period experiences significant increases. In the Midwest during July, significant increases in precipitation frequency are evident for the heavier precipitation bins when evaluated over longer temporal periods, but almost no significant increases occurred in August. Overall, the magnitude and robustness of these increases far exceed those elsewhere in the CONUS domain; aside from a few significant increases in moderate precipitation frequency in the Northwest and West, no other region exhibits consistent, significant frequency increases outside of the lightest two bins (Figs. 4d–f).

Fig. 4.
Fig. 4.

Regional maps of changes in (top) total precipitation, (middle) precipitation frequency, and (bottom) precipitation event intensity during (left) June, (center) July, and (right) August. The time period–intensity plots within each region have the same axis labels as in Fig. 3b.

Citation: Journal of Hydrometeorology 16, 4; 10.1175/JHM-D-14-0115.1

Figure 5 summarizes changes in June–August precipitation frequency across the 344 climate divisions, giving a finer spatial view of the changes in precipitation frequency. In Fig. 5 (top), total counts of significant increases (p ≤ 0.05) over all precipitation intensity bins and pairs of time periods are indicated for each climate division; for example, a total of seven significant increases, shown in the two darker shades of green, is counted in Fig. 3b. Again, the Midwest and Upper Midwest regions stand out. Most of Iowa, southern Minnesota, Wisconsin, and Michigan experienced widespread significant increases in precipitation frequency over the observational record in both July and August and to a lesser degree in June, while eastern Illinois and Indiana experienced many significant increases in precipitation frequency in July only. These results correlate reasonably well with the expected areas of an LULCC impact on precipitation frequency, as discussed in section 2.

Fig. 5.
Fig. 5.

The sum of significant increases (p ≤ 0.05) in precipitation frequency (top) over all precipitation intensity bins, (middle) over the lightest four bins (0.25–25 mm), and (bottom) over the heaviest six bins (>25 mm) for each climate division during (left) June, (center) July, and (right) August.

Citation: Journal of Hydrometeorology 16, 4; 10.1175/JHM-D-14-0115.1

Figure 5 (middle, bottom) depicts the results of similar climate division analyses but for the lightest four bins (≤25 mm or 1 in.; Fig. 5, middle) and for the heaviest six bins (>25 mm; Fig. 5, bottom). Partitioning the analysis into these bins is useful for distinguishing between the CC (i.e., heavy precipitation) and LULCC (i.e., light and heavy precipitation) hypotheses. In general, the results from the lighter bins are nearly identical to that of all precipitation bins (Fig. 5, top). However, the heavier bins only show isolated significant increases in Iowa, Illinois, and Indiana in July and in Iowa and some climate divisions in the Upper Midwest in August. We note that differences in station density are likely not an issue: for example, central Indiana and eastern Indiana have 11 and 2 stations, respectively, yet both show widespread significant increases in July.

2) Precipitation event intensity

Figure 4 (bottom) summarizes the changes in precipitation event intensity by climate region. The Midwest and Upper Midwest show significant increases in event intensity for the moderate and heavy precipitation bins during each summer month. However, several other regions also show significant increases. Changes in event intensity by climate division (Fig. 6) are more scattered and generally less robust, though climate divisions in the north-central United States—especially near Nebraska and Iowa—reflect more significant changes than elsewhere. Overall, since the pattern of significant increases in precipitation intensity is not unique to the midwestern United States, an LULCC signal on precipitation intensity is not readily apparent in these figures.

Fig. 6.
Fig. 6.

The sum of significant increases (p ≤ 0.05) in precipitation event intensity over all precipitation bins for each climate division during (a) June, (b) July, and (c) August.

Citation: Journal of Hydrometeorology 16, 4; 10.1175/JHM-D-14-0115.1

3) Total monthly precipitation

Spatially, changes in total monthly precipitation (Fig. 4, top) correlate well with changes in precipitation frequency (Fig. 4, middle). For a more quantitative comparison, Fig. 7 depicts the mean monthly changes in frequency, intensity, and total precipitation for each climate region. From 1895–1933 to 1973–2011 (row 6 on the time period–intensity plots in Fig. 3b), the average June, July, and August precipitation in the Upper Midwest increased by 12.5, 13.4, and 20.7 mm, respectively, while July precipitation in the Midwest increased by 11.3 mm (Fig. 7, top). These increases exceed those of the other regions in all three months (except the southern plains in June), usually by a factor of 2 or greater, mirroring the large increases in precipitation frequency (Fig. 7, middle).

Fig. 7.
Fig. 7.

Regional changes in mean monthly (top) total precipitation, (middle) precipitation frequency, and (bottom) precipitation intensity during June (light gray), July (dark gray), and August (medium gray) between 1895–1933 and 1973–2011, corresponding to row 6 of the time period–intensity plots (see Fig. 3b).

Citation: Journal of Hydrometeorology 16, 4; 10.1175/JHM-D-14-0115.1

At first glance, the results in Fig. 7 point to daily frequency change as the principal determinant of total precipitation change. However, while changes in frequency dominate the magnitude of total monthly precipitation changes in the midwestern United States, changes in intensity exert a notable secondary influence. For frequency change, the differences among June, July, and August are relatively small in both the Midwest and Upper Midwest (Fig. 7, middle). However, intensity changes are much less negative in the Midwest during July and in the Upper Midwest during August (Fig. 7, bottom), and total precipitation changes are likewise amplified in the Midwest and Upper Midwest during July and August, respectively, when compared to the other summer months (Fig. 7, top). Thus, anomalous intensity changes do exert some influence on month-to-month patterns of total precipitation change.

b. Absolute and percent changes

Figure 8 depicts the absolute changes in mean monthly total precipitation, frequency, and intensity from pre- to full irrigation. We analyze absolute changes because more distinct patterns may emerge using mean changes rather than only analyzing statistically significant changes, especially for precipitation intensity, which displays weak spatial patterns in Fig. 6. Additionally, whereas the previous figures sum the significant changes over all 10 temporal pairings, Fig. 8 specifically illustrates changes that occurred from pre- to postirrigation. In particular, we focus on precipitation changes between 1895–1933 and 1973–2011, that is, row 6 on the temporal axis of the time period–intensity plots (Fig. 3b), for a few reasons: 1) it is one of the rows that compares a preirrigation to a full-irrigation period; 2) it avoids the Dust Bowl drought of the mid-1930s, unlike rows 1–4; and 3) it utilizes more years than rows 8 and 9, thereby improving the robustness of any potential conclusions.

Fig. 8.
Fig. 8.

Absolute changes in (top) total precipitation, (middle) precipitation frequency, and (bottom) precipitation intensity during (left) June, (center) July, and (right) August between 1895–1933 and 1973–2011, corresponding to row 6 of the time period–intensity plots (see Fig. 3b). Brown shadings are negative changes.

Citation: Journal of Hydrometeorology 16, 4; 10.1175/JHM-D-14-0115.1

In summary, Fig. 8 displays mixed correlations between absolute changes in precipitation frequency and total precipitation in the midwestern United States. In August, absolute frequency changes (Fig. 8f) match up well with the pattern of changes in total precipitation (Fig. 8c), though they are displaced a bit farther north than the total precipitation swath. Intensity increases (Fig. 8i) only slightly overlap with the southern edge of the total precipitation swath (Fig. 8c). In this way, it seems that frequency changes dominate the changes in August total precipitation, while intensity changes exert a small secondary influence. However, in July, the larger frequency changes lie much farther north than those of total precipitation; intensity changes, on the other hand, spatially coincide with the total precipitation changes. Maps of percent changes (not shown) are almost exactly the same east of the Rocky Mountains; the main difference is larger increases in frequency and total precipitation in the West Coast states, where summer season rainfall is sparse. Hence, frequency changes do not always dictate the patterns of total precipitation change during the summer months in the midwestern United States, and intensity changes may actually exert a notable influence.

c. Monthly ranks of absolute and percent changes

Since the patterns of absolute frequency change are inconsistent with those of total precipitation change, the rank of each variable is computed relative to the other months of the year in Fig. 9 to provide an additional means of determining the seasonal intercorrelation and uniqueness of these frequency, intensity, and total precipitation changes. Climate divisions with a monthly value that ranks as one of the three highest of the year (out of 12) are illustrated in darker green shades; the three lowest values of the year are in darker brown shades.

Fig. 9.
Fig. 9.

Monthly ranks (out of 12 months) of absolute changes in (top) total precipitation, (middle) precipitation frequency, and (bottom) precipitation intensity for (left) June, (center) July, and (right) August between 1895–1933 and 1973–2011, corresponding to row 6 of the time period–intensity plots (see Fig. 3b). Dark green represents the highest rank and dark brown the lowest.

Citation: Journal of Hydrometeorology 16, 4; 10.1175/JHM-D-14-0115.1

Ranking the absolute changes highlights a distinct relationship between the three variables: intensity patterns, rather than those of frequency, coincide better with total precipitation patterns (in terms of both magnitude and location) in all three summer months (Fig. 9, top and bottom). On the other hand, it seems as though the large absolute changes in frequency (Figs. 8d–f) are not as unique in the midwestern United States during the summer months. The spatial distribution of the top three August frequency changes in the Upper Midwest is disjointed and, unlike those of intensity and total precipitation, does not extend into northern New England. In July and August, the top three frequency rankings only overlap with those of total precipitation for 7 and 13 climate divisions in the midwestern United States and combined midwestern United States + Northeast, respectively; in contrast, the top three intensity rankings in July and August overlap with those of total precipitation in 21 and 36 climate divisions throughout the midwestern United States and combined midwestern United States + Northeast, respectively. Additionally, the total precipitation rankings for percent change show an even stronger correlation with those of intensity and even weaker correlation with those of frequency (not shown). In summary, the rankings suggest that changes in both intensity and total precipitation in the midwestern United States are greatest during the summer, especially during July and August.

5. Discussion

We now interpret the above results in the context of the CC and LULCC hypotheses. The argument that CC is the main driver of the observed precipitation changes is supported by the significant increase in the frequency of heavy and very heavy precipitation events in the midwestern United States, with no other region showing changes of similar magnitude. The increases in precipitation intensity for moderate and heavy precipitation bins are also consistent with a CC signal. Combined with observed increases in growing season (Villarini et al. 2013) and summer temperature (NCDC 2014) over the midwestern United States during the last century and large increases in specific humidity since 1947 (Brown and DeGaetano 2013), one might conclude that CC has been a major factor in influencing precipitation changes over this region.

However, CC over the midwestern United States may be overemphasized as the primary cause. While temperature over the Upper Midwest may have increased by up to 1.2°C century−1 during August since 1950 (NCDC 2014), this increase is actually less than the average change (1.4°C) of the nine NCDC-defined climate regions. Brown and DeGaetano (2013) actually report, at best, statistically insignificant increases in summer temperature across the Upper Midwest from 1947 to 2010. Furthermore, temperature has actually increased by a greater amount in the Northeast since 1950 (1.7°C century−1; NCDC 2014), yet its increases in moderate and heavy precipitation have not been as large as those of the midwestern regions. This observed temperature–precipitation relationship is counterintuitive to a CC effect on heavier precipitation. Other aspects of the analyses that contradict changes expected from the CC hypothesis include large increases in total monthly precipitation throughout the midwestern United States during July and August, sometimes by more than 25 mm (1 in.) (Figs. 8b,c) and significant increases in the frequency of light and moderate precipitation events (Figs. 4 and 5, middle).

On the other hand, support for an LULCC influence on these precipitation changes is evident in the spatial and temporal aspects of the results of this study. Temporally, the most robust increases in precipitation frequency and total precipitation are evident when comparing pre-1950 time periods with post-1975 time periods (Fig. 4, top and middle). The timing here is consistent with the rapid development of cropland and irrigation between 1950 and 1980 in the central United States. The temporal aspect was further examined by creating precipitation time series and trend slopes for each climate region and for various daily precipitation intensities (not shown). The time series for the Midwest and Upper Midwest reveals either steplike or steady increases in moderate and heavy precipitation beginning around the mid-1900s during July and August, which generally coincides with the onset of rapid irrigation development in the Great Plains. Spatially, the location of the strongest increases in precipitation, that is, downwind of a major irrigated region in the Great Plains, is consistent with the argument of an LULCC influence on precipitation patterns. Thus, while CC may still have influenced precipitation changes in the midwestern United States, observed changes in the spatiotemporal patterns of total precipitation seem to favor a stronger influence from LULCC.

Furthermore, our analyses of absolute and percent changes in mean frequency, intensity, and total precipitation from pre- to full irrigation shed light on how changes in frequency and intensity may have affected the observed changes in total precipitation. While the analysis of absolute (and percent) changes seems to indicate that frequency is the main determinant of total precipitation patterns (Fig. 8), a comparison of the monthly rankings for each variable (Fig. 9) reveals that changes in intensity and total precipitation are both greatest during July and August in the midwestern United States and are spatially coincident. Meanwhile, the large increases in frequency evident during July and August are not unique to the summer, as comparable increases in frequency also occur during other months of the year. Since the seasonal ranks of the increases in frequency and total precipitation are dissimilar, the large absolute increases in frequency during the summer are less likely to be the primary cause of the increases in total precipitation. On the other hand, the anomalously positive changes in precipitation intensity may be more closely linked to changes in total precipitation than originally implied by Fig. 8.

The strong correlation of summer intensity rankings with summer monthly precipitation rankings is consistent with the hypothesis that increased moisture and altered wind patterns from irrigation and/or cropland expansion, and thus increased moisture convergence, are responsible for a nonnegligible portion of total precipitation change during July and August in the midwestern United States. This is even more apparent when comparing the intensity changes of the Midwest and Upper Midwest to those of other regions. Since percent increases in summer frequency are generally larger than those of total precipitation across the United States (not shown), decreases in intensity would appear to be favored; indeed, most climate regions across the United States have exhibited decreases in intensity during the summer. However, the changes of intensity in the Midwest during July and in the Upper Midwest during August are much less negative than the strongly negative mean established by the other climate regions in the summer and are thus anomalously positive. Therefore, even though most of the intensity changes in the United States have been negative and seemingly antithetical to increasing total precipitation, the anomalously positive intensity changes in the midwestern United States are likely indicative of an increase in moisture and/or moisture convergence in this region. This is consistent with observational evidence of increased moisture across the Corn Belt during the second half of the twentieth century (Mahmood et al. 2004; Brown and DeGaetano 2013) and with the numerical model simulation of Huber et al. (2014) that shows large increases in precipitation intensity (though not in precipitation frequency) because of irrigation development.

Two other mechanisms that may factor into the observed increases in precipitation intensity and frequency are nonclassical mesoscale circulations (NCMCs) and precipitation recycling. Similar in concept to the dynamics of classical mesoscale circulations like land–sea breezes, NCMCs may form at the boundary between two land types with different radiative and/or roughness characteristics, such as cropland and forest (Segal et al. 1988; Carleton et al. 2001; Weaver 2004; Allard and Carleton 2010). The horizontal gradients of temperature and moisture between irrigated and nonirrigated regions may induce ascent and moisture convergence on the nonirrigated, warmer side (see Fig. 2), which can potentially enhance convective rainfall under relatively weak synoptic conditions (Carleton et al. 2008). Because enhanced precipitation from NCMCs tends to occur within 100 km of the boundary (see Carleton et al. 2008), one might anticipate enhanced uplift and rainfall over western Iowa, the nonirrigated region immediately adjacent to the heavily irrigated areas in eastern Nebraska. Incidentally, a regional simulation of irrigation-induced radiative changes during the summer by Qian et al. (2013) depicts an area in western Iowa with higher LCL and PBL heights immediately adjacent to a wide swath of (irrigation induced) lower LCL and PBL heights, which is indicative of greater sensible heat flux on the Iowa side and potentially an irrigation-induced NCMC. Our analyses show that frequency, intensity, and total precipitation have increased in western (and often, most of) Iowa in the figures with climate division analyses, especially during July for frequency and total precipitation (e.g., Fig. 8). Though the mechanism posited here would need to be validated using a climate model, the coincident location of the observed precipitation increases adds evidence to the notion that an NCMC has influenced local precipitation patterns.

Another potential mechanism for expanding the swath of enhanced precipitation is precipitation recycling. Precipitation recycling occurs when soil moisture from precipitation in a particular area is evaporated into the PBL and cycled back into precipitation downwind of its source (Eltahir and Bras 1996; Zangvil et al. 2004; Dominguez et al. 2006). This mechanism may be a secondary transport of moisture downwind of Iowa, where total precipitation in July increased by at least 20% (~12.7 mm) from pre- to full irrigation. Wind vectors at the 850-hPa level illustrate that the areas in August with the largest increases in total precipitation (Great Lakes and northern New England) are downwind of Iowa, so this mechanism has some physical plausibility. However, numerical modeling experiments are necessary to diagnose the degree to which precipitation recycling may have contributed to the observed increases in precipitation downwind of Iowa.

Other factors, such as the Great Plains low-level jet (GPLLJ), may have also contributed to the observed changes in midwestern precipitation. For example, Wang and Chen (2009) conclude that about 65% of July and August precipitation in the Upper Midwest is influenced by the GPLLJ. Furthermore, Weaver and Nigam (2008) indicate that the GPLLJ index and Great Plains precipitation index (which includes eastern Nebraska and Iowa) have a correlation of 0.71 during July, and the first principal component of GPLLJ variability explains up to 1.6 mm day−1 (~50 mm month−1) of July precipitation in Iowa. Dirmeyer and Kinter (2010) suggest that the GPLLJ serves as a conduit of moisture from the Caribbean Sea into the central United States from May to July during months with very heavy precipitation. Though Midwestern precipitation seems to be less influenced by the GPLLJ in August (Weaver and Nigam 2008; Wang and Chen 2009), the GPLLJ may still be a significant factor in attributing the observed changes in midwestern summer precipitation.

Additionally, while the indices of various circulation patterns [e.g., ENSO, North Atlantic Oscillation (NAO), and Atlantic multidecadal oscillation (AMO)] are not strongly correlated with monthly precipitation during July and August in the midwestern United States [with the exception of August Pacific decadal oscillation (PDO); Fig. 10], there is slightly better correlation between the Niño-3.4 index and July and August precipitation when the Niño-3.4 index leads by 1–3 months (e.g., June Niño-3.4 versus July precipitation; not shown). It is also possible that the large increases in Texas precipitation during June could be linked via either precipitation recycling or the GPLLJ to the increases in precipitation in the midwestern United States during July and August. The accumulation of aerosols in the United States over the last century also has the potential to alter precipitation patterns, especially those of heavy precipitation (Tao et al. 2012). Connecting the observed increases in rainfall with all of these potential factors requires a more comprehensive investigation that is beyond the scope of this paper.

Fig. 10.
Fig. 10.

Correlations of monthly mean precipitation during (left) July and (right) August with (top to bottom) monthly indices of various large-scale atmospheric circulations (averaged over 1948–2012): Niño-3.4, which measures sea surface temperature anomalies in the tropical Pacific Ocean and corresponds to the state of the ENSO; NAO; AMO; Pacific–North American teleconnection (PNA); and PDO. Absolute increases in July and August total precipitation from Fig. 8 are included on the bottom for reference. Correlations are calculated from the U.S. Climate Division Dataset seasonal correlation page (www.esrl.noaa.gov/psd/data/usclimdivs/correlation/).

Citation: Journal of Hydrometeorology 16, 4; 10.1175/JHM-D-14-0115.1

We point out a few caveats on these interpretations. First, observations of dynamic variables such as vertical wind are not readily available, precluding further attribution of these changes. Second, the location and strength of irrigation-induced impacts may vary depending on mesoscale or synoptic conditions, so the overall signature in precipitation may be weakened with averaging over long temporal or coarse spatial scales. Third, while LULCC is hypothesized as an important contributor to the observed changes in precipitation, quantification of its contribution to precipitation (and those of other factors) requires further research. We anticipate that future sensitivity studies using regional model simulations may reduce these uncertainties.

In conclusion, this study sheds new light on the possible causes of the observed increase in summer precipitation in the midwestern United States. The balance of evidence suggests that while changes in frequency appear to largely control the magnitude of changes in total precipitation, the moderate to strong correlations of intensity changes with total precipitation changes (especially when ranked against other nonsummer months) implies an increase in atmospheric moisture and/or moisture convergence during the summer. We speculate that the rapid development of irrigation and expansion of cropland in the central United States may have contributed to this increase in atmospheric moisture and moisture convergence. In combination with previous studies, these analyses strengthen the argument that historical, large-scale LULCC was a key factor in enhancing summer precipitation in the midwestern United States over the late twentieth century. Understanding the drivers of such precipitation changes is essential for sound management and adaptation strategies in a changing climate.

Acknowledgments

This research has been funded by the U.S. Environmental Protection Agency (EPA-STAR-RD834190), the American Meteorological Society (through an AMS/Industry/Government Graduate Fellowship), and the National Science Foundation (NSF-AGS-1045110). We thank Anthony DeAngelis for his assistance with data analysis and visualization and for helpful discussions. Finally, we thank three anonymous reviewers for their constructive and insightful comments that improved the quality of this paper.

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