• Adegoke, J. O., and A. M. Carleton, 2002: Relations between soil moisture and satellite vegetation indices in the U.S. Corn Belt. J. Hydrometeor., 3, 395405, https://doi.org/10.1175/1525-7541(2002)003<0395:RBSMAS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alfieri, L., P. Claps, P. D’Odorico, F. Laio, and T. Over, 2008: An analysis of the soil moisture feedback on convective and stratiform precipitation. J. Hydrometeor., 9, 280291, https://doi.org/10.1175/2007JHM863.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anav, A., P. M. Ruti, V. Artale, and R. Valentini, 2010: Modelling the effects of land-cover changes on surface climate in the Mediterranean region. Climate Res., 41, 91104, https://doi.org/10.3354/cr00841.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anthes, R. A., 1984: Enhancement of convective precipitation by mesoscale variations in vegetative covering in semiarid regions. J. Climate Appl. Meteor., 23, 541554, https://doi.org/10.1175/1520-0450(1984)023<0541:EOCPBM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bernhardt, J., and A. M. Carleton, 2019: Comparing daily temperature averaging methods: The role of surface and atmosphere variables in determining spatial and seasonal variability. Theor. Appl. Climatol., 136, 499512, https://doi.org/10.1007/s00704-018-2504-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonan, G. B., 1997: Effects of land use on the climate of the United States. Climatic Change, 37, 449486, https://doi.org/10.1023/A:1005305708775.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonan, G. B., 2008: Ecological Climatology. Cambridge University Press, 550 pp.

  • Bonner, W. D., 1968: Climatology of the low-level jet. Mon. Wea. Rev., 96, 833850, https://doi.org/10.1175/1520-0493(1968)096<0833:COTLLJ>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carleton, A. M., and M. O’Neal, 1995: Satellite-derived land surface climate ‘signal’ for the Midwest U.S.A. Int. J. Remote Sens., 16, 31953202, https://doi.org/10.1080/01431169508954623.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carleton, A. M., D. Travis, D. Arnold, R. Brinegar, D. E. Jelinksi, and D. R. Easterling, 1994: Climatic-scale vegetation–cloud interactions during drought using satellite data. Int. J. Climatol., 14, 593623, https://doi.org/10.1002/joc.3370140602.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carleton, A. M., J. Adegoke, J. Allard, D. L. Arnold, and D. J. Travis, 2001: Summer season land cover—Convective cloud associations for the Midwest U.S. “Corn Belt.” Geophys. Res. Lett., 28, 16791682, https://doi.org/10.1029/2000GL012635.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carleton, A. M., D. L. Arnold, D. J. Travis, S. Curran, and J. O. Adegoke, 2008a: Synoptic circulation and land surface influences on convection in the Midwest U.S. “Corn Belt” during the summers of 1999 and 2000. Part I: Composite synoptic environments. J. Climate, 21, 33893415, https://doi.org/10.1175/2007JCLI1578.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carleton, A. M., D. J. Travis, J. O. Adegoke, D. L. Arnold, and S. Curran, 2008b: Synoptic circulation and land surface influences on convection in the Midwest U.S. “Corn Belt” during the summers of 1999 and 2000. Part II: Role of vegetation boundaries. J. Climate, 21, 36173641, https://doi.org/10.1175/2007JCLI1584.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, L., and P. A. Dirmeyer, 2017: Impacts of land-use/land-cover change on afternoon precipitation over North America. J. Climate, 30, 21212140, https://doi.org/10.1175/JCLI-D-16-0589.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cioni, G., and C. Hohenegger, 2018: A simplified model of precipitation enhancement over a heterogeneous surface. Hydrol. Earth Syst. Sci., 22, 31973212, https://doi.org/10.5194/hess-22-3197-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Copeland, J. H., R. A. Pielke, and T. G. F. Kittel, 1996: Potential climatic impacts of vegetation change: A regional modeling study. J. Geophys. Res., 101, 74097418, https://doi.org/10.1029/95JD02676.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doubler, D. L., J. A. Winkler, X. Bian, C. K. Walters, and S. Zhong, 2015: An NARR-derived climatology of southerly and northerly low-level jets over North America and coastal environs. J. Appl. Meteor. Climatol., 54, 15961619, https://doi.org/10.1175/JAMC-D-14-0311.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duerinck, H., R. van der Ent, N. van de Giesen, G. Schoups, V. Babovic, and P. J.-F. Yeh, 2016: Observed soil moisture–precipitation feedback in Illinois: A systematic analysis over different scales. J. Hydrometeor., 17, 16451660, https://doi.org/10.1175/JHM-D-15-0032.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Earth Science Research Laboratory, 2020: NCEP North American Regional Reanalysis: NARR. NOAA, accessed 26 February 2020, https://www.esrl.noaa.gov/psd/data/gridded/data.narr.html.

  • Ek, M. B., and L. Mahrt, 1994: Daytime evolution of relative humidity at the boundary layer top. Mon. Wea. Rev., 122, 27102721, https://doi.org/10.1175/1520-0493(1994)122<2709:DEORHA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ek, M. B., and A. A. M. Holtslag, 2004: Influence of soil moisture on boundary layer cloud development. J. Hydrometeor., 5, 8699, https://doi.org/10.1175/1525-7541(2004)005<0086:IOSMOB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Famiglietti, J. S., J. W. Rudnicki, and M. Rodell, 1998: Variability in surface moisture content along a hillslope transect: Rattlesnake Hill, Texas. J. Hydrol., 210, 259281, https://doi.org/10.1016/S0022-1694(98)00187-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feng, Z., L.-Y. Leung, S. Hagos, R. A. Houze Jr., C. Burleyson, and K. Balaguru, 2016: More frequent intense and long-lived storms dominate the springtime trend in central U.S. rainfall. Nat. Commun., 7, 13429, https://doi.org/10.1038/ncomms13429.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Findell, K. L., and E. A. B. Eltahir, 1997: An analysis of the relationship between spring soil moisture and summer rainfall, based on direct observations from Illinois. Water Resour. Res., 33, 725735, https://doi.org/10.1029/96WR03756.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Findell, K. L., and E. A. B. Eltahir, 2003a: Atmospheric controls on soil moisture–boundary layer interactions. Part I: Framework development. J. Hydrometeor., 4, 552569, https://doi.org/10.1175/1525-7541(2003)004<0552:ACOSML>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Findell, K. L., and E. A. B. Eltahir, 2003b: Atmospheric controls on soil moisture–boundary layer interactions. Part II: Feedbacks within the continental United States. J. Hydrometeor., 4, 570583, https://doi.org/10.1175/1525-7541(2003)004<0570:ACOSML>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ford, T. W., A. D. Rapp, and S. M. Quiring, 2015: Does afternoon precipitation occur preferentially over dry or wet soils in Oklahoma? J. Hydrometeor., 16, 874888, https://doi.org/10.1175/JHM-D-14-0005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ford, T. W., Q. Wang, and S. M. Quiring, 2016: The observation record length necessary to generate robust soil moisture percentiles. J. Appl. Meteor. Climatol., 55, 21312149, https://doi.org/10.1175/JAMC-D-16-0143.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frye, J. D., and T. L. Mote, 2010: Convection initiation along soil moisture boundaries in the southern Great Plains. Mon. Wea. Rev., 138, 11401151, https://doi.org/10.1175/2009MWR2865.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garrett, A. J., 1982: A parameter study of interactions between convective clouds, the convective boundary layer, and forested surface. Mon. Wea. Rev., 110, 10411059, https://doi.org/10.1175/1520-0493(1982)110<1041:APSOIB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gentine, P., A. A. Holtslag, F. D’Andrea, and M. Ek, 2013: Surface and atmospheric controls on the onset of moist convection over land. J. Hydrometeor., 14, 14431462, https://doi.org/10.1175/JHM-D-12-0137.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gerken, T., G. T. Bromley, and P. C. Stoy, 2018: Surface moistening trends in the northern North American Great Plains increase the likelihood of convective initiation. J. Hydrometeor., 19, 227244, https://doi.org/10.1175/JHM-D-17-0117.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giorgi, F., L. O. Mearns, C. Shields, and L. Mayer, 1996: A regional model study of the importance of local versus remote controls of the 1988 drought and the 1993 flood over the central United States. J. Climate, 9, 11501162, https://doi.org/10.1175/1520-0442(1996)009<1150:ARMSOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guillod, B. P., B. Orlowsky, D. G. Miralles, A. J. Teuling, and S. I. Seneviratne, 2015: Reconciling spatial and temporal soil moisture effects on afternoon rainfall. Nat. Commun., 6, 6443, https://doi.org/10.1038/ncomms7443.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haines, E. H., 1922: Influence of varying soil conditions on night-air temperatures. Mon. Wea. Rev., 50, 363366, https://doi.org/10.1175/1520-0493(1922)50<363:IOVSCO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hiestand, M. P., and A. M. Carleton, 2020: Growing-season synoptic and phenological controls on heat fluxes over forest and cropland sites in the Midwest U.S. Corn Belt. J. Appl. Meteor. Climatol., 59, 381400, https://doi.org/10.1175/JAMC-D-19-0019.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hill, A. C., M. Mitchell, F. Yuan, and C. T. Ruhland, 2019: Intensification of midwestern agriculture as a regional climate modifier and atmospheric boundary layer moisture source. Ann. Amer. Assoc. Geogr., 109, 17751794, https://doi.org/10.1080/24694452.2019.1598842.

    • Search Google Scholar
    • Export Citation
  • Jiang, X., N.-C. Lau, I. M. Held, and J. J. Ploshay, 2007: Mechanisms of the Great Plains low-level let as simulated in an AGCM. J. Atmos. Sci., 64, 532547, https://doi.org/10.1175/JAS3847.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR Reanalysis 40-Year Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Leeper, R. D., J. E. Bell, and M. A. Palecki, 2019: A description and evaluation of U.S. Climate Reference Network standardized soil moisture dataset. J. Appl. Meteor. Climatol., 58, 14171428, https://doi.org/10.1175/JAMC-D-18-0269.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahfouf, J. F., E. Richard, and P. Mascart, 1987: The influence of soil and vegetation on the development of mesoscale circulations. J. Climate Appl. Meteor., 26, 14831495, https://doi.org/10.1175/1520-0450(1987)026<1483:TIOSAV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marsh, G. P., 1874: The Earth as Modified by Human Action. Scribner, Armstrong & Co., 656 pp.

  • Matyas, C. J., and A. M. Carleton, 2010: Surface radar-derived convective rainfall associations with Midwest US land surface conditions in summer seasons 1999 and 2000. Theor. Appl. Climatol., 99, 315330, https://doi.org/10.1007/s00704-009-0144-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343360, https://doi.org/10.1175/BAMS-87-3-343.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rabin, R., S. Stadler, P. J. Wetzel, D. J. Stensrud, and M. Gregory, 1990: Observed effects of landscape variability on convective clouds. Bull. Amer. Meteor. Soc., 71, 272280, https://doi.org/10.1175/1520-0477(1990)071<0272:OEOLVO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sacks, W. J., and C. J. Kucharik, 2011: Crop management and phenology trends in the U.S. Corn Belt: Impacts on yields, evapotranspiration and energy balance. Agric. For. Meteor., 151, 882894, https://doi.org/10.1016/j.agrformet.2011.02.010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salvucci, G., 1998: Limiting relations between soil moisture and soil texture with implications for measured, modeled and remotely sensed estimates. Geophys. Res. Lett., 25, 17571760, https://doi.org/10.1029/98GL01138.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schaefer, G. L., M. H. Cosh, and T. J. Jackson, 2007: The USDA natural resources conservation service Soil Climate Analysis Network (SCAN). J. Atmos. Oceanic Technol., 24, 20732077, https://doi.org/10.1175/2007JTECHA930.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Soil Survey Staff, 1999: Soils of the United States. Soil Taxonomy: A Basic System of Soil Classification for Making and Interpreting Soil Surveys. 2nd ed. Natural Resources Conservation Service, 837850.

    • Search Google Scholar
    • Export Citation
  • Taylor, C. M., R. A. M. de Jeu, F. Guichard, P. P. Harris, and W. A. Dorigo, 2012: Afternoon rain more likely over drier soils. Nature, 489, 423426, https://doi.org/10.1038/nature11377.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tuttle, S., and G. Salvucci, 2016: Empirical evidence of contrasting soil moisture–precipitation feedbacks across the United States. Science, 352, 825828, https://doi.org/10.1126/science.aaa7185.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • University of Wyoming, 2021: Sounding data. Accessed 29 April 2021, http://www.weather.uwyo.edu/upperair/sounding.html.

  • USDA, 1997: Usual planting and harvesting dates for U.S. field crops, accessed December 1997. National Agricultural Statistics Service Agricultural Handbook 628, 51 pp., https://swat.tamu.edu/media/90113/crops-typicalplanting-harvestingdates-by-states.pdf.

  • Walters, C. K., J. A. Winkler, R. P. Shadbolt, J. van Ravensway, and G. D. Bierly, 2008: A long-term climatology of southerly and northerly low-level jets for the central United States. Ann. Assoc. Amer. Geogr., 98, 521552, https://doi.org/10.1080/00045600802046387.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, S. Y., and T. C. Chen, 2009: The late-spring maximum rainfall over the U.S. central plains and the role of the low-level jet. J. Climate, 22, 46964709, https://doi.org/10.1175/2009JCLI2719.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Welty, J., and X. Zeng, 2018: Does soil moisture affect warm season precipitation over the southern Great Plains? Geophys. Res. Lett., 45, 78667873, https://doi.org/10.1029/2018GL078598.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wesely, M. L., 1976: The combined effect of temperature and humidity on the refractive index. J. Appl. Meteor., 15, 4349, https://doi.org/10.1175/1520-0450(1976)015<0043:TCEOTA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, L., G. Sun, L. Zhi, and J. Zhao, 2018a: Negative soil moisture-precipitation feedback in dry and wet regions. Sci. Rep., 8, 4026, https://doi.org/10.1038/s41598-018-22394-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, L., and Coauthors, 2018b: A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies. ISPRS J. Photogramm. Remote Sens., 146, 108123, https://doi.org/10.1016/j.isprsjprs.2018.09.006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yin, J., J. D. Albertson, J. R. Rigby, and A. Porporato, 2015: Land and atmospheric controls on initiation and intensity of moist convection: CAPE dynamics and LCL crossings. Water Resour. Res., 51, 84768493, https://doi.org/10.1002/2015WR017286.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zaitchik, B. F., J. A. Santanello, S. V. Kumar, and C. D. Peters-Lidard, 2013: Representation of soil moisture feedbacks during drought in NASA Unified WRF (NU-WRF). J. Hydrometeor., 14, 360367, https://doi.org/10.1175/JHM-D-12-069.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 330 315 11
Full Text Views 113 109 3
PDF Downloads 140 132 4

Soil Moisture Influence on Warm-Season Convective Precipitation for the U.S. Corn Belt

View More View Less
  • 1 aDepartment of Geography, The Pennsylvania State University, University Park, Pennsylvania
Restricted access

Abstract

Recent climatic studies for the dominantly rain-fed agricultural U.S. Corn Belt (CB) suggest an influence of land-use/land-cover (LULC) spatial differences on convective development, set within the larger-scale (synoptic) atmospheric conditions of pressure, winds, and vertical motion. However, the potential role of soil moisture (SM) in the LULC association with atmospheric humidity, horizontal wind, and convective precipitation (CVP) has received more limited attention, mostly as modeling studies or empirical analyses for regions nonanalogous to the CB. Accordingly, we determine the categorical associations between SM and the near-surface atmospheric humidity q, with 850-hPa horizontal wind V 850 at four representative CB locations for the nine warm seasons of 2011–19. Recurring configurations of joint SM–qV 850 conducive to CVP are then identified and stratified into three phenologically distinct subseasons (early, middle, and late). We show that the stations show some statistical similarity in their SM–CVP relationships. Corn Belt CVP occurs preferentially with high humidity and southerly winds, sometimes composing a low-level jet (LLJ), particularly on early-season days having low SM and late-season days having high SM. Additionally, midseason CVP days having weaker V 850 (i.e., non-LLJ) tend to be associated with medium SM values and high humidity. Conversely, late-season CVP days are frequently characterized by high values of both SM and humidity. These empirical results are likely explained by the inferred sensible and latent heat fluxes varying according to SM content and LULC type. They provide a basis for future mesoscale modeling studies of Corn Belt SM and CVP interactions to test the hypothesized physical processes.

Significance Statement

The effects of soil moisture on precipitation are not well understood, as previous research has found contrasting results depending on study region and period of focus. We determine these associations for the Corn Belt, a humid lowland region that has received less attention than the drier neighboring Great Plains. Our study finds strong soil moisture–precipitation relationships in the presence of high humidity, which may be explained by mechanisms associated with the subseasonal cycle of vegetation activity. Additionally, our results suggest a generally weaker influence of soil moisture on precipitation for the Corn Belt than for the Great Plains, highlighting the importance of understanding how these relationships vary spatially. Future work should test the inferred surface–atmosphere mechanisms introduced here using mesoscale modeling.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Connor J. Chapman, cjc358@psu.edu

Abstract

Recent climatic studies for the dominantly rain-fed agricultural U.S. Corn Belt (CB) suggest an influence of land-use/land-cover (LULC) spatial differences on convective development, set within the larger-scale (synoptic) atmospheric conditions of pressure, winds, and vertical motion. However, the potential role of soil moisture (SM) in the LULC association with atmospheric humidity, horizontal wind, and convective precipitation (CVP) has received more limited attention, mostly as modeling studies or empirical analyses for regions nonanalogous to the CB. Accordingly, we determine the categorical associations between SM and the near-surface atmospheric humidity q, with 850-hPa horizontal wind V 850 at four representative CB locations for the nine warm seasons of 2011–19. Recurring configurations of joint SM–qV 850 conducive to CVP are then identified and stratified into three phenologically distinct subseasons (early, middle, and late). We show that the stations show some statistical similarity in their SM–CVP relationships. Corn Belt CVP occurs preferentially with high humidity and southerly winds, sometimes composing a low-level jet (LLJ), particularly on early-season days having low SM and late-season days having high SM. Additionally, midseason CVP days having weaker V 850 (i.e., non-LLJ) tend to be associated with medium SM values and high humidity. Conversely, late-season CVP days are frequently characterized by high values of both SM and humidity. These empirical results are likely explained by the inferred sensible and latent heat fluxes varying according to SM content and LULC type. They provide a basis for future mesoscale modeling studies of Corn Belt SM and CVP interactions to test the hypothesized physical processes.

Significance Statement

The effects of soil moisture on precipitation are not well understood, as previous research has found contrasting results depending on study region and period of focus. We determine these associations for the Corn Belt, a humid lowland region that has received less attention than the drier neighboring Great Plains. Our study finds strong soil moisture–precipitation relationships in the presence of high humidity, which may be explained by mechanisms associated with the subseasonal cycle of vegetation activity. Additionally, our results suggest a generally weaker influence of soil moisture on precipitation for the Corn Belt than for the Great Plains, highlighting the importance of understanding how these relationships vary spatially. Future work should test the inferred surface–atmosphere mechanisms introduced here using mesoscale modeling.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Connor J. Chapman, cjc358@psu.edu
Save