scholarly journals Great Plains Hydroclimate Variability: The View from North American Regional Reanalysis

2006 ◽  
Vol 19 (12) ◽  
pp. 3004-3010 ◽  
Author(s):  
Alfredo Ruiz-Barradas ◽  
Sumant Nigam
Keyword(s):  
Interannual Variability ◽  
Great Plains ◽  
North American ◽  
Land Surface ◽  
Warm Season ◽  
Surface Model ◽  
Near Surface ◽  
Hydroclimate Variability ◽  
North American Regional Reanalysis ◽  
Regional Reanalysis

Abstract 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.

scholarly journals Evaluation of the Complementary Relationship Using Noah Land Surface Model and North American Regional Reanalysis (NARR) Data to Estimate Evapotranspiration in Semiarid Ecosystems

2013 ◽  
Vol 14 (1) ◽  
pp. 345-359 ◽  
Author(s):  
W. Thilini Jaksa ◽  
Venkataramana Sridhar ◽  
Justin L. Huntington ◽  
Mandar Khanal
Keyword(s):  
North American ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
B Values ◽  
Complementary Relationship ◽  
North American Regional Reanalysis ◽  
Noah Land Surface Model ◽  
Regional Reanalysis ◽  
Mean Square Errors

Abstract Estimating evapotranspiration using the complementary relationship can serve as a proxy to more sophisticated physically based approaches and can be used to better understand water and energy budget feedbacks. The authors investigated the existence of complementarity between actual evapotranspiration (ET) and potential ET (ETp) over natural vegetation in semiarid desert ecosystems of southern Idaho using only the forcing data and simulated fluxes obtained from Noah land surface model (LSM) and North American Regional Reanalysis (NARR) data. To mitigate the paucity of long-term meteorological data, the Noah LSM-simulated fluxes and the NARR forcing data were used in the advection–aridity (AA) model to derive the complementary relationship (CR) for the sagebrush and cheatgrass ecosystems. When soil moisture was a limiting factor for ET, the CR was stable and asymmetric, with b values of 2.43 and 1.43 for sagebrush and cheatgrass, respectively. Higher b values contributed to decreased ET and increased ETp, and as a result ET from the sagebrush community was less compared to that of cheatgrass. Validation of the derived CR showed that correlations between daily ET from the Noah LSM and CR-based ET were 0.76 and 0.80 for sagebrush and cheatgrass, respectively, while the root-mean-square errors were 0.53 and 0.61 mm day−1.

The Decline In Summer Fallow In The Northern Plains Cooled Near-Surface Climate But Had Minimal Impacts On Precipitation

2021 ◽  
Author(s):  
Gabriel Bromley ◽  
Andreas F. Prein ◽  
Shannon E. Albeke ◽  
Paul C. Stoy
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Great Plains ◽  
Land Management ◽  
North American ◽  
Land Surface ◽  
Convective Cloud ◽  
Cloud Formation ◽  
Near Surface ◽  
Summer Fallow

Abstract Land management strategies can moderate or intensify the impacts of a warming atmosphere. Since the early 1980s, nearly 116,000 km2 of crop land that was once held in fallow during the summer is now planted in the northern North American Great Plains. To simulate the impacts of this substantial land cover change on regional climate processes, convection-permitting model experiments using the Weather Research and Forecasting (WRF) model were performed to simulate modern and historical amounts of summer fallow, and were extensively validated using multiple observational data products as well as eddy covariance tower observations. Results of these simulations show that the transition from summer fallow to modern land cover lead to ~1.5 °C cooler temperatures and decreased vapor pressure deficit by ~0.15 kPa during the growing season, which is consistent with observed cooling trends. The cooler and wetter land surface with vegetation leads to a shallower planetary boundary layer and lower lifted condensation level, creating conditions more conducive to convective cloud formation and precipitation. Our model simulations however show little widespread evidence of land surface changes effects on precipitation. The observed precipitation increase in this region is more likely related to increased moisture transport by way of the Great Plains Low Level Jet as suggested by the ERA5 reanalysis. Our results demonstrate that land cover change is consistent with observed regional cooling in the northern North American Great Plains but changes in precipitation cannot be explained by land management alone.

scholarly journals Representation of Terrestrial Hydrology and Large-Scale Drought of the Continental United States from the North American Regional Reanalysis

2012 ◽  
Vol 13 (3) ◽  
pp. 856-876 ◽  
Author(s):  
Justin Sheffield ◽  
Ben Livneh ◽  
Eric F. Wood
Keyword(s):  
United States ◽  
Soil Moisture ◽  
North American ◽  
Land Surface ◽  
Large Scale ◽  
State Of The Art ◽  
Vic Model ◽  
The North ◽  
North American Regional Reanalysis ◽  
Regional Reanalysis

Abstract The North American Regional Reanalysis (NARR) is a state-of-the-art land–atmosphere reanalysis product that provides improved representation of the terrestrial hydrologic cycle compared to previous global reanalyses, having the potential to provide an enhanced picture of hydrologic extremes such as floods and droughts and their driving mechanisms. This is partly because of the novel assimilation of observed precipitation, state-of-the-art land surface scheme, and higher spatial resolution. NARR is evaluated in terms of the terrestrial water budget and its depiction of drought at monthly to annual time scales against two offline land surface model [Noah v2.7.1 and Variable Infiltration Capacity (VIC)] simulations and observation-based runoff estimates over the continental United States for 1979–2003. An earlier version of the Noah model forms the land component of NARR and so the offline simulation provides an opportunity to diagnose NARR land surface variables independently of atmospheric feedbacks. The VIC model has been calibrated against measured streamflow and so provides a reasonable estimate of large-scale evapotranspiration. Despite similar precipitation, there are large differences in the partitioning of precipitation into evapotranspiration and runoff. Relative to VIC, NARR and Noah annual evapotranspiration is biased high by 28% and 24%, respectively, and the runoff ratios are 50% and 40% lower. This is confirmed by comparison with observation-based runoff estimates from 1130 small, relatively unmanaged basins across the continental United States. The overestimation of evapotranspiration by NARR is largely attributed to the evapotranspiration component of the Noah model, whereas other factors such as atmospheric forcings or biases induced by precipitation assimilation into NARR play only a minor role. A combination of differences in the parameterization of evapotranspiration and in particular low stomatal resistance values in NARR, the seasonality of vegetation characteristics, the near-surface radiation and meteorology, and the representation of soil moisture dynamics, including high infiltration rates and the relative coupling of soil moisture with baseflow in NARR, are responsible for the differences in the water budgets. Large-scale drought as quantified by soil moisture percentiles covaries closely over the continental United States between the three datasets, despite large differences in the seasonal water budgets. However, there are large regional differences, especially in the eastern United States where the VIC model shows higher variability in drought dynamics. This is mostly due to increased frequency of completely dry conditions in NARR that result from differences in soil depth, higher evapotranspiration, early snowmelt, and early peak runoff. In the western United States, differences in the precipitation forcing contribute to large discrepancies between NARR and Noah/VIC simulations in the representation of the early 2000s drought.

Relationships between Land Surface and Near-Surface Atmospheric Variables in the NCEP North American Regional Reanalysis

2007 ◽  
Vol 8 (6) ◽  
pp. 1184-1203 ◽  
Author(s):  
Yan Luo ◽  
Ernesto H. Berbery ◽  
Kenneth E. Mitchell ◽  
Alan K. Betts
Keyword(s):  
Soil Moisture ◽  
Surface Water ◽  
Land Surface ◽  
Cloud Cover ◽  
Near Surface ◽  
Positive Correlation ◽  
Precipitation Anomalies ◽  
North American Regional Reanalysis ◽  
Regional Reanalysis ◽  
Atmospheric Variables

Abstract This study examines the recently released National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) products over diverse climate regimes to determine the regional relationships between soil moisture and near-surface atmospheric variables. NARR assimilates observed precipitation, as well as near-surface observations of humidity and wind, while seeking a balance of the surface water and energy budgets with a modern land surface model. The results of this study indicate that for most basins (of approximate size of 0.5–1.0 × 106 km2) the NARR surface water budgets have relatively small residuals (about 0.2 mm day−1), and slightly larger residuals (about 0.4 mm day−1) for basins with complex terrain like those in the western United States. Given that the NARR is an assimilation system (especially one that assimilates observed precipitation), the NARR does not include feedbacks between soil moisture and precipitation. Nonetheless, as a diagnostic tool anchored to observations, the NARR does show that the extent of positive correlation between anomalies of soil moisture and anomalies of precipitation in a given region depends on that region’s dryness. The existence of correlations among all variables is a necessary—but not sufficient—condition for land–atmosphere feedbacks to exist, as a region with no correlations would not be expected to have feedbacks. Likewise, a high degree of persistence of soil moisture anomalies in a given basin does not by itself guarantee a positive correlation between anomalies of soil moisture and precipitation. Land surface–atmosphere relationships at monthly time scales are identified by examining the associations between soil moisture and surface and boundary layer variables. Low soil moisture is consistently associated with increased net shortwave radiation and increased outgoing longwave radiation through the effects of less cloud cover and lower atmospheric humidity. No systematic association is revealed between soil moisture and total net surface radiation, as this relation varies substantially between different basins. Low soil moisture is positively correlated with increased sensible heat and lower latent heat (reflected in a smaller evaporative fraction), decreased low-cloud cover, and higher lifting condensation level. The relation between soil moisture anomalies and precipitation anomalies is found to be quite variable between the basins, depending on whether availability of surface water exceeds the available energy for evaporation, or vice versa. Wetter basins, like the Columbia and Ohio, display weak or no correlations between soil moisture anomalies and precipitation anomalies. On the other hand, transitional regions between wet and dry regions, like the central Great Plains, manifest a positive correlation between soil moisture anomalies and precipitation anomalies. These results further the understanding of previous predictability studies (in coupled land–atmosphere prediction models), which indicates that in order for precipitation anomalies to emerge in response to soil moisture anomalies in a given region, it is necessary that the region’s seasonal climate be neither too dry nor too wet.

scholarly journals A SMAP-Based Drought Monitoring Index for the United States

2018 ◽  
Author(s):  
Sara Sadri ◽  
Eric F. Wood ◽  
Ming Pan
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Land Surface ◽  
Surface Soil ◽  
Root Zone ◽  
Warm Season ◽  
The United States ◽  
Surface Model ◽  
Surface Soil Moisture ◽  
Near Surface

Abstract. Since April 2015, NASA's Soil Moisture Active Passive (SMAP) mission has monitored near-surface soil moisture, mapping the globe between the latitude bands of 85.044° N/S in 2–3 days depending on location. SMAP Level 3 passive radiometer product (SPL3SMP) measures the amount of water in the top 5 cm of soil except for regions of heavy vegetation (vegetation water content >4.5 kg/m2) and frozen or snow covered locations. SPL3SMP retrievals are spatially and temporally discontinuous, so the 33 months offers a short SMAP record length and poses a statistical challenge for meaningful assessment of its indices. The SMAP SPL4SMAU data product provides global surface and root zone soil moisture at 9-km resolution based on assimilating the SPL3SMP product into the NASA Catchment land surface model. Of particular interest to SMAP-based agricultural applications is a monitoring product that assesses the SMAP near-surface soil moisture in terms of probability percentiles for dry and wet conditions. We describe here SMAP-based indices over the continental United States (CONUS) based on both near-surface and root zone soil moisture percentiles. The percentiles are based on fitting a Beta distribution to the retrieved moisture values. To assess the data adequacy, a statistical comparison is made between fitting the distribution to VIC soil moisture values for the days when SPL3SMP are available, versus fitting to a 1979–2017 VIC data record. For the cold season (November–April), 57 % of grids were deemed to be consistent between the periods, and 68 % in the warm season (May–October), based on a Kolmogorov–Smirnov statistical test. It is assumed that if grids passed the consistency test using VIC data, then the grid had sufficient SMAP data. Our near-surface and root zone drought index on maps are shown to be similar to those produced by the U.S. Drought Monitor (from D0-D4) and GRACE. In a similar manner, we extend the index to include pluvial conditions using indices W0-W4. This study is a step forward towards building a national and international soil moisture monitoring system, without which, quantitative measures of drought and pluvial conditions will remain difficult to judge.

Teleconnections Governing the Interannual Variability of Great Plains Low-Level Jets in May

2021 ◽  
pp. 1-60
Author(s):  
Shubhi Agrawal ◽  
Craig R. Ferguson ◽  
Lance Bosart ◽  
D. Alex Burrows
Keyword(s):  
Interannual Variability ◽  
Great Plains ◽  
Large Scale ◽  
Warm Season ◽  
Near Surface ◽  
Low Level ◽  
South Central ◽  
Decadal Scale ◽  
Low Level Jets ◽  
Upper Level

AbstractA spectral analysis of Great Plains 850-hPa meridional winds (V850) from ECMWF’s coupled climate reanalysis of 1901-2010 (CERA-20C) reveals that their warm season (April-September) interannual variability peaks in May with 2-6 year periodicity, suggestive of an underlying teleconnection influence on low-level jets (LLJs). Using an objective, dynamical jet classification framework based on 500-hPa wave activity, we pursue a large scale teleconnection hypothesis separately for LLJs that are uncoupled (LLJUC) and coupled (LLJC) to the upper-level jet stream. Differentiating between jet types enables isolation of their respective sources of variability. In the South Central Plains (SCP), May LLJCs account for nearly 1.6 times more precipitation and 1.5 times greater V850 compared to LLJUCs. Composite analyses of May 250-hPa geopotential height (Z250) conditioned on LLJC and LLJUC frequencies highlight a distinct planetary-scale Rossby wave pattern with wavenumber-five, indicative of an underlying Circumglobal Teleconnection (CGT). An index of May CGT is found to be significantly correlated with both LLJC (r = 0.62) and LLJUC (r = −0.48) frequencies. Additionally, a significant correlation is found between May LLJUC frequency and NAO (r = 0.33). Further analyses expose decadal scale variations in the CGT-LLJC(LLJUC) teleconnection that are linked to the PDO. Dynamically, these large scale teleconnections impact LLJ class frequency and intensity via upper-level geopotential anomalies over the western U.S. that modulate near-surface geopotential and temperature gradients across the SCP.

Seasonal Hydroclimate Variability over North America in Global and Regional Reanalyses and AMIP Simulations: Varied Representation

2006 ◽  
Vol 19 (5) ◽  
pp. 815-837 ◽  
Author(s):  
Sumant Nigam ◽  
Alfredo Ruiz-Barradas
Keyword(s):  
Great Plains ◽  
North American ◽  
Climate Models ◽  
Gulf Coast ◽  
Surface Air Temperature ◽  
Moisture Flux ◽  
Atmospheric Model ◽  
Eastern United States ◽  
Hydroclimate Variability ◽  
Regional Reanalysis

Abstract The monotony of seasonal variability is often compensated by the complexity of its spatial structure—the case in North American hydroclimate. The structure of hydroclimate variability is analyzed to provide insights into the functioning of the climate system and climate models. The consistency of hydroclimate representation in two global [40-yr ECMWF Re-Analysis (ERA-40) and NCEP] and one regional [North American Regional Reanalysis (NARR)] reanalysis is examined first, from analysis of precipitation, evaporation, surface air temperature (SAT), and moisture flux distributions. The intercomparisons benchmark the recently released NARR data and provide context for evaluation of the simulation potential of two state-of-the-art atmospheric models [NCAR's Community Atmospheric Model (CAM3.0) and NASA's Seasonal-to-Interannual Prediction Project (NSIPP) atmospheric model]. Intercomparisons paint a gloomy picture: great divergence in global reanalysis representations of precipitation, with the eastern United States being drier in ERA-40 and wetter in NCEP in the annual mean by up to a third in each case; model averages are like ERA-40. The annual means, in fact, mask even larger but offsetting seasonal departures. Analysis of moisture transport shows winter fluxes to be more consistently represented. Summer flux convergence over the Gulf Coast and Great Plains, however, differs considerably between global and regional reanalyses. Flux distributions help in understanding the choice of rainy season, especially the winter one in the Pacific Northwest; stationary fluxes are key. Land–ocean competition for convection is too intense in the models—so much so that the oceanic ITCZ in July is southward of its winter position in the both simulations! The overresponsiveness of land is also manifest in SAT; the winter-to-summer change over the Great Plains is 5–9 K larger than in observations, with implications for modeling of climate sensitivity. The nature of atmospheric water balance over the Great Plains is probed, despite unbalanced moisture budgets in reanalyses and model simulations. The imbalance is smaller in NARR but still unacceptably large, resulting from excessive evaporation in spring and summer. Adjusting evaporation during precipitation assimilation could lead to a more balanced budget. Global and regional reanalysis will remain of limited use for hydroclimate studies until they comply with the operative water and energy balance constraints.

Spurious Grid-Scale Precipitation in the North American Regional Reanalysis

2007 ◽  
Vol 135 (6) ◽  
pp. 2168-2184 ◽  
Author(s):  
Gregory L. West ◽  
W. James Steenburgh ◽  
William Y. Y. Cheng
Keyword(s):  
North American ◽  
Prediction Models ◽  
Weather Prediction ◽  
Regional Climate ◽  
Potential Temperature ◽  
Climate Data ◽  
The North ◽  
North American Regional Reanalysis ◽  
Upper Level ◽  
Regional Reanalysis

Abstract Spurious grid-scale precipitation (SGSP) occurs in many mesoscale numerical weather prediction models when the simulated atmosphere becomes convectively unstable and the convective parameterization fails to relieve the instability. Case studies presented in this paper illustrate that SGSP events are also found in the North American Regional Reanalysis (NARR) and are accompanied by excessive maxima in grid-scale precipitation, vertical velocity, moisture variables (e.g., relative humidity and precipitable water), mid- and upper-level equivalent potential temperature, and mid- and upper-level absolute vorticity. SGSP events in environments favorable for high-based convection can also feature low-level cold pools and sea level pressure maxima. Prior to 2003, retrospectively generated NARR analyses feature an average of approximately 370 SGSP events annually. Beginning in 2003, however, NARR analyses are generated in near–real time by the Regional Climate Data Assimilation System (R-CDAS), which is identical to the retrospective NARR analysis system except for the input precipitation and ice cover datasets. Analyses produced by the R-CDAS feature a substantially larger number of SGSP events with more than 4000 occurring in the original 2003 analyses. An oceanic precipitation data processing error, which resulted in a reprocessing of NARR analyses from 2003 to 2005, only partially explains this increase since the reprocessed analyses still produce approximately 2000 SGSP events annually. These results suggest that many NARR SGSP events are not produced by shortcomings in the underlying Eta Model, but by the specification of anomalous latent heating when there is a strong mismatch between modeled and assimilated precipitation. NARR users should ensure that they are using the reprocessed NARR analyses from 2003 to 2005 and consider the possible influence of SGSP on their findings, particularly after the transition to the R-CDAS.

scholarly journals Climate pattern-scaling set for an ensemble of 22 GCMs – adding uncertainty to the IMOGEN version 2.0 impact system

2018 ◽  
Vol 11 (2) ◽  
pp. 541-560 ◽  
Author(s):  
Przemyslaw Zelazowski ◽  
Chris Huntingford ◽  
Lina M. Mercado ◽  
Nathalie Schaller
Keyword(s):  
Climate Change ◽  
Relative Humidity ◽  
Land Surface ◽  
Land Surface Model ◽  
Individual Performance ◽  
Balance Model ◽  
Surface Model ◽  
Near Surface ◽  
Global Circulation Models ◽  
Version 2.0

Abstract. Global circulation models (GCMs) are the best tool to understand climate change, as they attempt to represent all the important Earth system processes, including anthropogenic perturbation through fossil fuel burning. However, GCMs are computationally very expensive, which limits the number of simulations that can be made. Pattern scaling is an emulation technique that takes advantage of the fact that local and seasonal changes in surface climate are often approximately linear in the rate of warming over land and across the globe. This allows interpolation away from a limited number of available GCM simulations, to assess alternative future emissions scenarios. In this paper, we present a climate pattern-scaling set consisting of spatial climate change patterns along with parameters for an energy-balance model that calculates the amount of global warming. The set, available for download, is derived from 22 GCMs of the WCRP CMIP3 database, setting the basis for similar eventual pattern development for the CMIP5 and forthcoming CMIP6 ensemble. Critically, it extends the use of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) framework to enable scanning across full uncertainty in GCMs for impact studies. Across models, the presented climate patterns represent consistent global mean trends, with a maximum of 4 (out of 22) GCMs exhibiting the opposite sign to the global trend per variable (relative humidity). The described new climate regimes are generally warmer, wetter (but with less snowfall), cloudier and windier, and have decreased relative humidity. Overall, when averaging individual performance across all variables, and without considering co-variance, the patterns explain one-third of regional change in decadal averages (mean percentage variance explained, PVE, 34.25±5.21), but the signal in some models exhibits much more linearity (e.g. MIROC3.2(hires): 41.53) than in others (GISS_ER: 22.67). The two most often considered variables, near-surface temperature and precipitation, have a PVE of 85.44±4.37 and 14.98±4.61, respectively. We also provide an example assessment of a terrestrial impact (changes in mean runoff) and compare projections by the IMOGEN system, which has one land surface model, against direct GCM outputs, which all have alternative representations of land functioning. The latter is noted as an additional source of uncertainty. Finally, current and potential future applications of the IMOGEN version 2.0 modelling system in the areas of ecosystem modelling and climate change impact assessment are presented and discussed.

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