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The rapid expansion of irrigation in the Great Plains since World War II has resulted in significant water table declines, threatening the long-term sustainability of the Ogallala Aquifer. As discussed in Part I of this paper, the Weather Research and Forecasting Model (WRF) was modified to simulate the effects of irrigation at subgrid scales. Simulations of nine April-October periods (three drought, three normal, and three pluvial) over the Great Plains were completed to assess the full impact of irrigation on the water budget. Averaged over all simulated years, irrigation over the Great Plains contributes to May-September evapotranspiration increases of approximately 4% and precipitation increases of 1%, with localized increases of up to 20%. Results from these WRF simulations are used along with a backward trajectory analysis to identify where evapotranspiration from irrigated fields falls as precipitation (i.e., irrigation-induced precipitation) and how irrigation impacts precipitation recycling. On average, only 15.8% of evapotranspiration from irrigated fields falls as precipitation over the Great Plains, resulting in 5.11 mm of May-September irrigation-induced precipitation and contributing to 6.71 mm of recycled precipitation. Reductions in nonrecycled precipitation suggest that irrigation reduces precipitation of moisture advected into the region. The heaviest irrigation-induced precipitation is coincident with simulated and observed precipitation increases, suggesting that observed precipitation increases in north-central Nebraska are strongly related to evapotranspiration of irrigated water. Water losses due to evapotranspiration are much larger than irrigation-induced precipitation and recycled precipitation increases, confirming that irrigation results in net water loss over the Great Plains. [ABSTRACT FROM AUTHOR]

October–September runoff increased 6% and 17% in the upper (UMRB) and lower (LMRB) Missouri River basins, respectively, in a recent (1990–2019) climate in comparison with a past (1960–89) climate. The runoff increases were unanticipated, given various projections for semipermanent drought and/or aridification in the North American Great Plains. Here, five transient coupled climate model ensembles are used to diagnose the effects of natural internal variability and anthropogenic climate change on the observed runoff increases and to project UMRB and LMRB runoff to the mid-twenty-first century. The runoff increases observed in the recent climate in comparison with the past climate were not due to anthropogenic climate change but rather resulted mostly from an extreme occurrence of internal multidecadal variability. High runoff resulted from large, mostly internally generated, precipitation increases (6% in the UMRB and 5%in the LMRB) that exceeded simulated increases attributable to climate change forcing alone (0%–2% intermodel range). The precipitation elasticity of runoff, which relates runoff sensitivity to precipitation differences in the recent climate in comparison with the past climate, led to one–threefold and two–fourfold amplifications of runoff versus precipitation in the UMRB and LMRB, respectively. Without the observed precipitation increases in the recent climate in comparison with the past climate, effects of human-induced warming of about 18C would alone have most likely induced runoff declines of 7% and 13% in the UMRB and LMRB, respectively. Ensemble model simulations overwhelmingly project lower UMRB and LRMB runoff by 2050 when compared with 1990–2019, a change found to be insensitive to whether individual realizations experienced high flows in the recent climate. [ABSTRACT FROM AUTHOR]

The secondary ice process (SIP) is a major microphysical process, which can result in rapid enhancement of ice particle concentration in the presence of preexisting ice. SPICULE was conducted to further investigate the effect of collision–coalescence on the rate of the fragmentation of freezing drop (FFD) SIP mechanism in cumulus congestus clouds. Measurements were conducted over the Great Plains and central United States from two coordinated aircraft, the NSF Gulfstream V (GV) and SPEC Learjet 35A, both equipped with state-of-the-art microphysical instrumentation and vertically pointing W- and Ka-band radars, respectively. The GV primarily targeted measurements of subcloud aerosols with subsequent sampling in warm cloud. Simultaneously, the Learjet performed multiple penetrations of the ascending cumulus congestus (CuCg) cloud top. First primary ice was typically detected at temperatures colder than −10°C, consistent with measured ice nucleating particles. Subsequent production of ice via FFD SIP was strongly related to the concentration of supercooled large drops (SLDs), with diameters from about 0.2 to a few millimeters. The concentration of SLDs is directly linked to the rate of collision–coalescence, which depends primarily on the subcloud aerosol size distribution and cloud-base temperature. SPICULE supports previous observational results showing that FFD SIP efficiency could be deduced from the product of cloud-base temperature and maximum diameter of drops measured ∼300 m above cloud base. However, new measurements with higher concentrations of aerosol and total cloud-base drop concentrations show an attenuating effect on the rate of coalescence. The SPICULE dataset provides rich material for validation of numerical schemes of collision–coalescence and SIP to improve weather prediction simulations [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) are long, narrow filamentary regions of enhanced vertically integrated water vapor transport (IVT) that play an important role in regional water supply and hydrometeorological extremes. Here, an AR detection algorithm is applied to global reanalysis from Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), to objectively and consistently characterize ARs regionally across the continental United States (CONUS). The characteristics of AR and associated precipitation are computed at the gridpoint scale and summarized over the sevenU.S. National ClimateAssessment regions.ARs aremost frequent in the autumn and winter in theWest, spring in the Great Plains, and autumn in the Midwest and Northeast. ARs show regional and seasonal variability in basic geometry and IVT. AR IVT composites reveal annually consistent northeastwarddirected moisture transport from the Pacific Ocean in the West, whereas moisture transport patterns vary seasonally across the Southern Great Plains and Midwest. Linked AR precipitation characteristics suggest that a substantial proportion of extreme events, defined as the top 5% of 3-day precipitation totals, are associated with ARs over many parts of CONUS, including the East. Regional patterns of AR-associated precipitation highlight that seasonally varying moisture transport and lifting mechanisms differ between the East and the West where orographic lifting is key. Our study aims to contribute a comprehensive and consistent CONUS-wide, regional-scale analysis of ARs in support of ongoing NCA efforts. Given the CONUS-wide role ARs play in extreme precipitation, findings motivate continued study of associated climate change impacts. [ABSTRACT FROM AUTHOR]

Despite the key importance of soil moisture-evapotranspiration (ET) coupling in the climate system, limited availability of soil moisture and ET observations poses a major impediment for investigation of this coupling regarding spatiotemporal characteristics and potential modifications under climate change. To better understand and quantify soil moisture-ET coupling and relevant processes, this study takes advantage of in situ soil moisture observations from the U.S. Climate Reference Network (USCRN) for the time period of 2010-17 and a satellite-derived version of the evapotranspiration stress index (ESI), which represents anomalies in a normalized ratio of actual to reference ET. The analyses reveal strong seasonality and regional characteristics of the ESI-land surface interactions across the United States, with the strongest control of soil moisture on the ESI found in the southern Great Plains during spring, and in the north-central United States, the northern Great Plains, and the Pacific Northwest during summer. In drier climate regions such as the northern Great Plains and north-central United States, soil moisture control on the ESI is confined to surface soil layers, with subsurface soil moisture passively responding to changes in the ESI. The soil moisture-ESI interaction is more uniform between surface and subsurface soils in wetter regions with higher vegetation cover. These results provide a benchmark for simulation of soil moisture-ET coupling and are useful for projection of associated climate processes in the future. [ABSTRACT FROM AUTHOR]

Agricultural development is among the most significant forms of land-use change globally. In central North America it has consisted of cropland expansion in the early 1900s, yield intensification starting in the 1930s, and the development of large irrigated areas beginning in the 1950s. The area of this study encompasses the Midwest and Great Plains of the United States not only because significant agricultural change has occurred here but also because of the significant cooling (warming hole) there in the midcentury. This study investigates the relative contribution of agricultural development and greenhouse gas (GHG) emissions on the observed patterns of regional changes in summer temperature, precipitation, and evapotranspiration using a long-term twentieth-century reanalysis dataset (CERA-20C) as boundary conditions for simulations with the MIT Regional Climate Model (MRCM). Temperatures in the Great Plains (33°–43°N, 95°–109°W) and the Midwest (38°–48°N, 82°–109°W) would have been significantly higher in the second half of the twentieth century without the influence of agricultural development, largely due to an increase in evaporative cooling. The simulations of precipitation changes reflect a significant influence of global SST teleconnections at decadal time scales. Numerical simulations also demonstrate the competing effects of cropland expansion and yield intensification on shaping the observed pattern of increases in precipitation. Ultimately, a combination of agricultural development and decadal variability of global sea surface temperatures (SST) explains most of the observed variability of summer temperature and precipitation during the twentieth century over central North America. [ABSTRACT FROM AUTHOR]

Although the link between droughts and heat waves is widely recognized, how climate change affects this link remains uncertain. Here we assess how, and by how much, human-induced climate change affects summertime hot drought compound events over the contiguous United States. Results are derived by comparing hot drought statistics in long simulations of a coupled climate model (CESM1) subjected to year-1850 and year-2000 radiative forcings. Within each climate state, a strong and nonlinear dependency of heat-wave intensity on drought severity is found in water-limited regions of the southern Great Plains and southwestern United States whereas heat-wave intensity is found to be insensitive to drought severity in energy-limited regions of the northern and/or northeastern United States. Applying a statistical model that is based on pair-copula constructions, we find that anthropogenic warming leads to enhanced soil moisture–temperature coupling in water-limited areas of the southern Great Plains and/or southwestern United States and consequently amplifies the intensity of extreme heat waves during severe droughts. This strengthened coupling accounts for a substantial fraction of rising temperature extremes related to the long-term climate change in CESM1, highlighting the importance of changes in land–atmosphere feedback in a warmer climate. In contrast, coupling effects remain weak and largely unchanged in energy-limited regions, thereby yielding no appreciable contribution to heat-wave intensification over the northern and/or northeastern United States apart from the long-term warming effects. [ABSTRACT FROM AUTHOR]

Meteorological droughts in the continental United States (CONUS) are known to oscillate at the multidecadal time scale in response to the sea surface temperatures (SST) variability over the Pacific Ocean and the North Atlantic Ocean. While previous studies have focused on understanding the influence of SST oscillations on drought frequency over the CONUS, this information has not been integrated with global warming for future drought risk assessment at the decadal scale. In this study, we use the support vector machines (SVMs) to handle correlation between input variables for quantifying the influence of internal variability [Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO)] and global warming on the decadal changes in the severity of seasonal droughts over the CONUS during 1901–2015. The regional drivers of drought severity identified using SVMs are used for the assessment of decadal drought risk in the near future. We find internal variability as the dominant driver of decadal changes in drought severity in the southern and central Great Plains and global warming as the dominant driver for the southeastern and southwestern United States. In the southern Plains, the existing pattern of increasing drought severity is likely to persist in the near future if AMO and PDO remain in their positive and negative phases, respectively, while global warming is likely to contribute to increasing drought severity in the Southeast and Southwest. This study suggests an emerging role of global warming in drought risk over the southern states, where near-term climate change adaptation is necessary. [ABSTRACT FROM AUTHOR]

Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land-atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land-atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land-atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer. [ABSTRACT FROM AUTHOR]

This study investigates the seasonality of the relationship between the Great Plains low-level jet (GPLLJ) and the Pacific Ocean from spring to summer, using observational analysis and coupled model experiments. The observed GPLLJ and El Niño-Southern Oscillation (ENSO) relation undergoes seasonal changes with a stronger GPLLJ associated with La Niña in boreal spring and El Niño in boreal summer. The ability of the GFDL Forecast-Oriented Low Ocean Resolution (FLOR) global coupled climate model, which has the high-resolution atmospheric and land components, to simulate the observed seasonality in the GPLLJ-ENSO relationship is assessed. The importance of simulating the magnitude and phase locking of ENSO accurately in order to better simulate its seasonal teleconnections with the Intra-Americas Sea (IAS) is demonstrated. This study explores the mechanisms for seasonal changes in the GPLLJ-ENSO relation in model and observations. It is hypothesized that ENSO affects the GPLLJ variability through the Caribbean low-level jet (CLLJ) during the summer and spring seasons. These results suggest that climate models with improved ENSO variability would advance our ability to simulate and predict seasonal variations of the GPLLJ and their associated impacts on the United States. [ABSTRACT FROM AUTHOR]

The atmospheric moisture budget and surface interactions for the southern Great Plains are evaluated for contrasting May-June periods (1998, 2002, 2006, and 2007) as background for the Cloud and Land Surface Interaction Campaign (CLASIC) of (wet) 7-30 June 2007. Budget components [flux divergence (MFD), storage change (dPW), and inflow (IF/ A)] are estimated from North American Regional Reanalysis data. Precipitation ( P) is calculated from NCEP daily gridded data, evapotranspiration ( E) is obtained as moisture budget equation residual, and the recycling ratio ( PE/ P) is estimated using a new equation. Regional averages are presented for months and five daily P categories. Monthly budget results show that E and E − P are strongly positively related to P; E − P generally is positive and balanced by positive MFD that results from its horizontal velocity divergence component (HD, positive) exceeding its horizontal advection component (HA, negative). An exception is 2007 (CLASIC), when E − P and MFD are negative and supported primarily by negative HA. These overall monthly results characterize low P days (≤0.6 mm), including for nonanomalous 2007, but weaken as daily P approaches 4 mm. In contrast, for 4 < P ≤ 8 mm day−1 E − P and MFD are moderately negative and balanced largely by negative HD except in 2007 (negative HA). This overall pattern was accentuated (including for nonanomalous 2007) when daily P > 8 mm. Daily P E/ P ratios are small and of limited range, with P category averages 0.15-0.19. Ratios for 2007 are above average only for daily P ≤ 4 mm. CLASIC wetness principally resulted from distinctive MFD characteristics. Solar radiation, soil moisture, and crop status/yield information document surface interactions. [ABSTRACT FROM AUTHOR]

Multicentury preindustrial control simulations from six of the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) models are used to examine the relationship between low-frequency precipitation variations in the Great Plains (GP) region of the United States and global sea surface temperatures (SSTs). This study builds on previous work performed with atmospheric models forced by observed SSTs during the twentieth century and extends it to a coupled model context and longer time series. The climate models used in this study reproduce the precipitation climatology over the United States reasonably well, with maximum precipitation occurring in early summer, as observed. The modeled precipitation time series exhibit negative “decadal” anomalies, identified using a 5-yr running mean, of amplitude comparable to that of the twentieth-century droughts. It is found that low-frequency anomalies over the GP are part of a large-scale pattern of precipitation variations, characterized by anomalies of the same sign as in the GP region over Europe and southern South America and anomalies of opposite sign over northern South America, India, and Australia. The large-scale pattern of the precipitation anomalies is associated with global-scale atmospheric circulation changes; during wet periods in the GP, geopotential heights are raised in the tropics and high latitudes and lowered in the midlatitudes in most models, with the midlatitude jets displaced toward the equator in both hemispheres. Statistically significant correlations are found between the decadal precipitation anomalies in the GP region and tropical Pacific SSTs in all the models. The influence of other oceans (Indian and tropical and North Atlantic), which previous studies have identified as potentially important, appears to be model dependent. [ABSTRACT FROM AUTHOR]

Several advanced analysis tools are applied to depict the time–frequency characteristics of the variations of Great Plains (GP) precipitation and its relationship with tropical central-eastern Pacific Ocean sea surface temperature (SST). These tools are advantageous because they reveal the detailed features of the dominant time scales of precipitation variations, the combined effects of multiscale oscillating signals on the intensity of precipitation, and the variations of SST–precipitation relationships in time and frequency domains. The variability of GP precipitation is characterized by strong annual and semiannual signals, which have the most stable oscillating frequencies and the largest amplitudes. However, nonseasonal signals, which are less oscillatory and have smaller amplitudes and more variable frequencies with time, also contribute significantly to precipitation variability and may modify the seasonal cycle of GP precipitation. The phase of these nonseasonal signals is in phase (out of phase) with that of seasonal signals during the periods of heavy (deficient) precipitation. Significant correlations exist between GP precipitation and Niño-3.4 SST, and the strongest relationship appears when the SST leads the precipitation by 1 month. The GP precipitation increases (decreases) during El Niño (La Niña) episodes. Significant relationships appear on semiannual and annual time scales in the 1950s and on interannual time scales in the 1910s, 1940s, and 1980s. A particularly significant relationship appears on biennial time scales in the 1980s. The revealed SST–precipitation relationship is strongly seasonally dependent, with the greatest significance in summer. Warming of tropical central-eastern Pacific SST weakens the overlying easterly trade winds and strengthens the northward moisture supply from Central America through the Gulf of Mexico to the Great Plains. This dominant SST influence prevails in all seasons. However, the moisture transport from the southwest coast and the Gulf of California also contributes to the variability of GP precipitation in September–November, December–February, and March–May. In June–August, the increase in GP precipitation is caused by convergence between anomalous northerly flow over the northern plains, associated with the warming in the northeastern Pacific, and southerly flow over the southern plains, associated with the warming in the tropical central-eastern Pacific. [ABSTRACT FROM AUTHOR]

Interannual variability of warm-season rainfall over the Great Plains is analyzed using the recently released North American Regional Reanalysis (NARR). The new dataset differs from its global counterparts in the additional assimilation of precipitation and radiances. This along with the use of a more comprehensive land surface model in generation of NARR offers the prospect of obtaining improved estimates of surface hydrologic and near-surface meteorological fields. NARR’s representation of hydroclimate is used to weigh in on the authors’ recent finding of the dominance of large-scale moisture flux convergence over evaporation in accounting for Great Plains precipitation variations. Evaporation estimates are notoriously uncertain and, while the NARR ones are not assured to be realistic, they are more constrained than those diagnosed before from inline and offline assessments. NARR’s portrayal of warm-season hydroclimate variability corroborates the importance of remote water sources in generation of Great Plains precipitation variability and supports the authors’ claim that some state-of-the-art atmosphere/land surface models vigorously recycle precipitation, erroneously, at least in context of Great Plains interannual variability. These very models have been key to recent claims of strong coupling between soil moisture and precipitation. [ABSTRACT FROM AUTHOR]

In a recently developed approach to climate modeling, called the multiscale modeling framework (MMF), a two-dimensional cloud-resolving model (CRM) is embedded into each grid column of the Community Atmospheric Model (CAM), replacing traditional cloud and radiation parameterizations. This study presents an evaluation of the MMF through a comparison of its output with the output from the CAM and with data from two observational sites operated by the Atmospheric Radiation Measurement Program, one at the Southern Great Plains (SGP) in Oklahoma and one at the island of Nauru in the tropical western Pacific (TWP) region. Two sets of one-year-long simulations are considered: one using climatological sea surface temperatures (SSTs) and another using 1999 SST. Each set includes a run with the MMF as well as a CAM run with traditional or standard cloud and radiation treatments. Time series of cloud fraction, precipitation intensity, and downwelling solar radiation flux at the surface are analyzed. For the TWP site, the distributions of these variables from the MMF run are shown to be more consistent with observation than those from the CAM run. This change is attributed to the improved representation of convective clouds in the MMF compared to the conventional climate model. For the SGP, the MMF shows little to no improvement in predicting the same quantities. Possible causes of this lack of improvement are discussed. [ABSTRACT FROM AUTHOR]