scholarly journals Potential natural vegetation and NPP responses to future climates in the U.S. Great Plains

Ecosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
Author(s):  
Toni Klemm ◽  
David D. Briske ◽  
Matthew C. Reeves
Keyword(s):  
Great Plains ◽  
Natural Vegetation ◽  
Potential Natural Vegetation ◽  
The U.S

VEMAP 1: U.S. POTENTIAL NATURAL VEGETATION

1998 ◽  
Author(s):  
C. DALY ◽  
H. H. FISHER ◽  
A. GRIMSDELL ◽  
E. R. HUNT ◽  
T. G. F. KITTEL ◽  
...  
Keyword(s):  
Natural Vegetation ◽  
Potential Natural Vegetation

Seasonal and interannual variability in13C composition of ecosystem carbon fluxes in the U.S. Southern Great Plains

Tellus B ◽  
2011 ◽  
Vol 63 (2) ◽  
Author(s):  
Margaret S. Torn ◽  
Sebastien C. Biraud ◽  
Christopher J. Still ◽  
William J. Riley ◽  
Joe A. Berry
Keyword(s):  
Interannual Variability ◽  
Great Plains ◽  
Carbon Fluxes ◽  
Southern Great Plains ◽  
Seasonal And Interannual Variability ◽  
Ecosystem Carbon ◽  
Ecosystem Carbon Fluxes ◽  
The U.S

scholarly journals Vulnerability of crops and native grasses to summer drying in the U.S. Southern Great Plains

2015 ◽  
Vol 213 ◽  
pp. 209-218 ◽  
Author(s):  
Naama Raz-Yaseef ◽  
Dave P. Billesbach ◽  
Marc L. Fischer ◽  
Sebastien C. Biraud ◽  
Stacey A. Gunter ◽  
...  
Keyword(s):  
Great Plains ◽  
Native Grasses ◽  
Southern Great Plains ◽  
The U.S

Carbon dioxide and water vapor fluxes of multi-purpose winter wheat production systems in the U.S. Southern Great Plains

2021 ◽  
Vol 310 ◽  
pp. 108631
Author(s):  
Pradeep Wagle ◽  
Prasanna H. Gowda ◽  
Brian K. Northup ◽  
James P.S. Neel ◽  
Patrick J. Starks ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Water Vapor ◽  
Winter Wheat ◽  
Great Plains ◽  
Production Systems ◽  
Wheat Production ◽  
Southern Great Plains ◽  
The U.S

scholarly journals Quantifying the Land–Atmosphere Coupling Behavior in Modern Reanalysis Products over the U.S. Southern Great Plains

2015 ◽  
Vol 28 (14) ◽  
pp. 5813-5829 ◽  
Author(s):  
Joseph A. Santanello ◽  
Joshua Roundy ◽  
Paul A. Dirmeyer
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Southern Great Plains ◽  
Diurnal Cycles ◽  
The North ◽  
Energy Cycle ◽  
Coupling Behavior ◽  
Regional Reanalysis ◽  
Modern Era ◽  
The U.S

Abstract The coupling of the land with the planetary boundary layer (PBL) on diurnal time scales is critical to regulating the strength of the connection between soil moisture and precipitation. To improve understanding of land–atmosphere (L–A) interactions, recent studies have focused on the development of diagnostics to quantify the strength and accuracy of the land–PBL coupling at the process level. In this paper, the authors apply a suite of local land–atmosphere coupling (LoCo) metrics to modern reanalysis (RA) products and observations during a 17-yr period over the U.S. southern Great Plains. Specifically, a range of diagnostics exploring the links between soil moisture, evaporation, PBL height, temperature, humidity, and precipitation is applied to the summertime monthly mean diurnal cycles of the North American Regional Reanalysis (NARR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR). Results show that CFSR is the driest and MERRA the wettest of the three RAs in terms of overall surface–PBL coupling. When compared against observations, CFSR has a significant dry bias that impacts all components of the land–PBL system. CFSR and NARR are more similar in terms of PBL dynamics and response to dry and wet extremes, while MERRA is more constrained in terms of evaporation and PBL variability. Each RA has a unique land–PBL coupling that has implications for downstream impacts on the diurnal cycle of PBL evolution, clouds, convection, and precipitation as well as representation of extremes and drought. As a result, caution should be used when treating RAs as truth in terms of their water and energy cycle processes.

Natural Vegetation as an Indicator of the Capabilities of Land for Crop Production in the Great Plains Area

Science ◽  
1911 ◽  
Vol 34 (863) ◽  
pp. 55-57
Author(s):  
F. E. CLEMENTS
Keyword(s):  
Great Plains ◽  
Crop Production ◽  
Natural Vegetation

scholarly journals Assessment of Regional Global Climate Model Water Vapor Bias and Trends Using Precipitable Water Vapor (PWV) Observations from a Network of Global Positioning Satellite (GPS) Receivers in the U.S. Great Plains and Midwest

2012 ◽  
Vol 25 (16) ◽  
pp. 5471-5493 ◽  
Author(s):  
Jacola A. Roman ◽  
Robert O. Knuteson ◽  
Steven A. Ackerman ◽  
David C. Tobin ◽  
Henry E. Revercomb
Keyword(s):  
Water Vapor ◽  
Great Plains ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Precipitable Water ◽  
Specific Humidity ◽  
Model Output ◽  
Global Positioning ◽  
The U.S

Abstract Precipitable water vapor (PWV) observations from the National Center of Atmospheric Research (NCAR) SuomiNet networks of ground-based global positioning system (GPS) receivers and the National Oceanic and Atmospheric Administration (NOAA) Profiler Network (NPN) are used in the regional assessment of global climate models. Study regions in the U.S. Great Plains and Midwest highlight the differences among global climate model output from the Fourth Assessment Report (AR4) Special Report on Emissions Scenarios (SRES) A2 scenario in their seasonal representation of column water vapor and the vertical distribution of moisture. In particular, the Community Climate System model, version 3 (CCSM3) is shown to exhibit a dry bias of over 30% in the summertime water vapor column, while the Goddard Institute for Space Studies Model E20 (GISS E20) agrees well with PWV observations. A detailed assessment of vertical profiles of temperature, relative humidity, and specific humidity confirm that only GISS E20 was able to represent the summertime specific humidity profile in the atmospheric boundary layer (<3%) and thus the correct total column water vapor. All models show good agreement in the winter season for the region. Regional trends using station-elevation-corrected GPS PWV data from two complimentary networks are found to be consistent with null trends predicted in the AR4 A2 scenario model output for the period 2000–09. The time to detect (TTD) a 0.05 mm yr−1 PWV trend, as predicted in the A2 scenario for the period 2000–2100, is shown to be 25–30 yr with 95% confidence in the Oklahoma–Kansas region.

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