scholarly journals Improving WRF-Chem meteorological analyses and forecasts over aerosol polluted regions by incorporating NAAPS aerosol analyses

2021 ◽  
Author(s):  
Brittany N. Carson-Marquis ◽  
Jianglong Zhang ◽  
Peng Xian ◽  
Jeffrey S. Reid ◽  
Jared Marquis
Keyword(s):  
Boundary Conditions ◽  
Surface Temperature ◽  
Great Plains ◽  
Transport Model ◽  
Weather Prediction ◽  
The United States ◽  
Northern Great Plains ◽  
Chemical Transport Model ◽  
Near Surface ◽  
Initial And Boundary Conditions

AbstractWhen unaccounted for in numerical weather prediction (NWP) models, heavy aerosol events can cause significant unrealized biases in forecasted meteorological parameters such as surface temperature. To improve near-surface forecasting accuracies during heavy aerosol loadings, we demonstrate the feasibility of incorporating aerosol fields from a global chemical transport model as initial and boundary conditions into a higher resolution NWP model with aerosol-meteorological coupling. This concept is tested for a major biomass burning smoke event over the Northern Great Plains region of the United States that occurred during summer of 2015. Aerosol analyses from the global Navy Aerosol Analysis and Prediction System (NAAPS) are used as initial and boundary conditions for Weather Research and Forecasting with Chemistry (WRF-Chem) simulations. Through incorporating more realistic aerosol direct effects into the WRF-Chem simulations, errors in WRF-Chem simulated surface downward shortwave radiative fluxes and near-surface temperature are reduced compared with surface-based observations. This study confirms the ability to decrease biases induced by the aerosol direct effect for regional NWP forecasts during high-impact aerosol episodes through the incorporation of analyses and forecasts from a global aerosol transport model.

scholarly journals A mechanistic model of global soil nitric oxide emissions: implementation and space based-constraints

2012 ◽  
Vol 12 (2) ◽  
pp. 3555-3594 ◽  
Author(s):  
R. C. Hudman ◽  
N. E. Moore ◽  
R. V. Martin ◽  
A. R. Russell ◽  
A. K. Mebust ◽  
...  
Keyword(s):  
Great Plains ◽  
Transport Model ◽  
Mechanistic Model ◽  
Chemical Transport ◽  
The United States ◽  
Decay Length ◽  
Nox Emissions ◽  
Chemical Transport Model ◽  
Atmospheric N Deposition ◽  
Available Nitrogen

Abstract. Soil emissions have been identified as a major source (~15%) of global nitrogen oxide (NOx) emissions. Parameterizations of soil NOx emissions (SNOx) for use in the current generation of chemical transport models were designed to capture mean seasonal behaviour. These parameterizations do not, however, respond quantitatively to the meteorological triggers that result in pulsed SNOx as are widely observed. Here we present a new mechanistic parameterization of SNOx implemented into a global chemical transport model (GEOS-Chem). The parameterization represents available nitrogen (N) in soils using biome specific emission factors, online wet- and dry-deposition of N as well as fertilizer and manure N derived from a spatially explicit dataset distributed using seasonality derived from data obtained by the Moderate Resolution Imaging Spectrometer. Moreover, it represents the functional form of emissions derived from point measurements and ecosystem scale experiments including pulsing following soil wetting by rain or irrigation, and emissions that are a smooth function of soil moisture. This parameterization yields global above-soil SNOx of 10.7 Tg N yr−1, including 1.8 Tg N yr−1 from fertilizer N input (0.68% of applied N) and 0.5 Tg N yr−1 from atmospheric N deposition. Over the United States Great Plains, SNOx are predicted to comprise 15–40% of the tropospheric NO2 column and increase column variability by a factor of 2–4 during the summer months due to chemical fertilizer application and warm temperatures. SNOx enhancements of 50–80% of the simulated NO2 column are predicted over the African Sahel during the monsoon onset (April–June). In this region the day-to-day variability of column NO2 is increased by a factor of 5 due to pulsed-N emissions. We evaluate the model by comparison to observations of the NO2 column from the OMI instrument. We find the model is able to reproduce observations of pulsed-N induced interannual variability over the US Great Plains. We also show that the OMI mean (median) NO2 on the overpass following first rainfall over the Sahel is 49% (23%) higher than in the five days preceding. The measured NO2 on the day after rainfall is still 23% (5%) higher, providing a direct measure of the pulse's decay time of 1–2 days. This is consistent with the pulsing representation used in our parameterization and much shorter than 5–14 day pulse decay length used in current models.

VARIATION IN PATHOGENICITY BETWEEN ISOLATES OF CLAVICEPS PURPUREA

1977 ◽  
Vol 57 (3) ◽  
pp. 729-733 ◽  
Author(s):  
L. C. DARLINGTON ◽  
D. E. MATHRE ◽  
R. H. JOHNSTON
Keyword(s):  
Great Plains ◽  
Triticum Aestivum L ◽  
The United States ◽  
Northern Great Plains ◽  
Claviceps Purpurea ◽  
Male Sterile ◽  
Hordeum Vulgare L ◽  
Clear Cut ◽  
Weakly Virulent ◽  
Grass Hosts

Isolates of Claviceps purpurea (Fr.) Tul. originally isolated from many different grass hosts in the northern Great Plains and several other areas in the United States and England were tested for their pathogenicity to selected cultivars or lines of male-sterile wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.). While there was a great range in the level of virulence, no clear-cut evidence of specific races was obtained. A few isolates were weakly virulent on two cultivars of male-sterile spring wheat but were highly virulent on the other two cultivars tested. Wheat and barley breeders are advised to use a mixture of isolates in screening germ plasm for resistance to ergot.

Rearing the wheat stem sawfly on an artificial diet

2005 ◽  
Vol 137 (4) ◽  
pp. 497-500 ◽  
Author(s):  
Tuilo B. Macedo ◽  
Paula A. Macedo ◽  
Robert K.D. Peterson ◽  
David K. Weaver ◽  
Wendell L. Morrill
Keyword(s):  
Great Plains ◽  
Cropping Systems ◽  
Insect Pest ◽  
The United States ◽  
Northern Great Plains ◽  
Yield Losses ◽  
Canadian Prairies ◽  
Wheat Stem Sawfly ◽  
Head Weight ◽  
Harvest Efficiency

The wheat stem sawfly, Cephus cinctus Norton (Hymenoptera: Cephidae), is an insect pest in dryland wheat cropping systems in the southern Canadian Prairies and the northern Great Plains of the United States (Morrill 1997). Yield losses caused by C. cinctus are due to reduced head weight (Holmes 1977; Morrill et al. 1992) and lodging, which decreases harvest efficiency. Estimates of yield losses in Montana alone are about US$25 million per year.

scholarly journals Physiologic Specialization of Puccinia triticina on Wheat in the United States in 2013

Plant Disease ◽  
2015 ◽  
Vol 99 (9) ◽  
pp. 1261-1267 ◽  
Author(s):  
J. A. Kolmer ◽  
M. E. Hughes
Keyword(s):  
United States ◽  
Winter Wheat ◽  
Leaf Rust ◽  
Great Plains ◽  
Puccinia Triticina ◽  
The United States ◽  
Northern Great Plains ◽  
Ohio River ◽  
Ohio Valley ◽  
Red Winter Wheat

Collections of Puccinia triticina were obtained from rust-infected leaves provided by cooperators throughout the United States and from wheat fields and breeding plots by USDA-ARS personnel and cooperators in the Great Plains, Ohio River Valley, and southeastern states in order to determine the virulence of the wheat leaf rust population in 2013. Single uredinial isolates (490 total) were derived from the collections and tested for virulence phenotype on 20 lines of Thatcher wheat that are near-isogenic for leaf rust resistance genes. In 2013, 79 virulence phenotypes were described in the United States. Virulence phenotypes MBTNB, TNBGJ, and MCTNB were the three most common phenotypes. Phenotypes MBTNB and MCTNB are both virulent to Lr11, and MCTNB is virulent to Lr26. MBTNB and MCTNB were most common in the soft red winter wheat region of the southeastern states and Ohio Valley. Phenotype TNBGJ is virulent to Lr39/41 and was widely distributed throughout the hard red winter wheat region of the Great Plains. Isolates with virulence to Lr11, Lr18, and Lr26 were common in the southeastern states and Ohio Valley region. Isolates with virulence to Lr21, Lr24, and Lr39/41 were frequent in the hard red wheat region of the southern and northern Great Plains.

scholarly journals Meteorological modes of variability for fine particulate matter (PM2.5) air quality in the United States: implications for PM2.5 sensitivity to climate change

2012 ◽  
Vol 12 (6) ◽  
pp. 3131-3145 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Transport Model ◽  
Circulation Model ◽  
Multiple Linear Regression Model ◽  
The United States ◽  
Chemical Transport Model ◽  
Modes Of Variability ◽  
The Us ◽  
Cyclone Frequency

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.

scholarly journals Phytoplankton productivity across prairie saline lakes of the Great Plains (USA): a step toward deciphering patterns through lake classification models

2009 ◽  
Vol 66 (9) ◽  
pp. 1435-1448 ◽  
Author(s):  
Courtney R. Salm ◽  
Jasmine E. Saros ◽  
Sherilyn C. Fritz ◽  
Christopher L. Osburn ◽  
David M. Reineke
Keyword(s):  
Primary Production ◽  
Nutrient Limitation ◽  
Great Plains ◽  
Saline Lakes ◽  
Information Criterion ◽  
The United States ◽  
Northern Great Plains ◽  
Classification Models ◽  
Phytoplankton Productivity ◽  
P Limitation

We investigated patterns of primary production across prairie saline lakes in the central and northern Great Plains of the United States. Based on comparative lake sampling in 2004, seasonal predictors of algal primary productivity were identified within subsets of similar lakes using a combination of Akaike’s information criterion (AIC) and classification and regression trees (CART). These models indicated complex patterns of nutrient limitation by nitrogen (N), phosphorus (P), and iron (Fe) within different lake groups. Nutrient enrichment assays (control, + Fe, + N, + P, + N + P) were performed in spring and summer of 2006 to determine if phytoplankton in selected lakes followed predicted patterns of nutrient limitation. Both the comparative lake sampling and experimental results indicated that N limitation was widespread in these prairie lakes, with evidence for secondary P limitation in certain lakes. In the experiments, iron did not stimulate primary production. Our results suggest that given the diverse geochemical nature of these lakes, classification models that separate saline lakes into subsets may be an effective method for improving predictions of algal production.

scholarly journals Estimating ground-level PM<sub>2.5</sub> in Eastern China using aerosol optical depth determined from the GOCI Satellite Instrument

2015 ◽  
Vol 15 (12) ◽  
pp. 17251-17281 ◽  
Author(s):  
J. Xu ◽  
R. V. Martin ◽  
A. van Donkelaar ◽  
J. Kim ◽  
M. Choi ◽  
...  
Keyword(s):  
Organic Matter ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Eastern China ◽  
Ground Level ◽  
East China ◽  
Chemical Transport Model ◽  
Near Surface ◽  
Significant Agreement

Abstract. We determine and interpret fine particulate matter (PM2.5) concentrations in East China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean Geostationary Ocean Color Imager (GOCI) satellite instrument. We implement a set of filters to minimize cloud contamination in GOCI AOD. Evaluation of filtered GOCI AOD with AOD from the Aerosol Robotic Network (AERONET) indicates significant agreement with mean fractional bias (MFB) in Beijing of 6.7 % and northern Taiwan of −1.2 %. We use a global chemical transport model (GEOS-Chem) to relate the total column AOD to the near-surface PM2.5. The simulated PM2.5/AOD ratio exhibits high consistency with ground-based measurements (MFB = −0.52–8.0 %). We evaluate the satellite-derived PM2.5 vs. the ground-level PM2.5 in 2013 measured by the China Environmental Monitoring Center. Significant agreement is found between GOCI-derived PM2.5 and in-situ observations in both annual averages (r = 0.81, N = 494) and monthly averages (MFB = 13.1 %), indicating GOCI provides valuable data for air quality studies in Northeast Asia. The GEOS-Chem simulated chemical speciation of GOCI-derived PM2.5 reveals that secondary inorganics (SO42−, NO3−, NH4+) and organic matter are the most significant components. Biofuel emissions in northern China for heating are responsible for an increase in the concentration of organic matter in winter. The population-weighted GOCI-derived PM2.5 over East China for 2013 is 53.8 μg m−3, threatening the health and life expectancy of its 600 million residents.

scholarly journals Trends in Stratospheric Ozone: Lessons Learned from a 3D Chemical Transport Model

2006 ◽  
Vol 63 (3) ◽  
pp. 1028-1041 ◽  
Author(s):  
Richard S. Stolarski ◽  
Anne R. Douglass ◽  
Stephen Steenrod ◽  
Steven Pawson
Keyword(s):  
Time Series ◽  
Solar Cycle ◽  
Ultraviolet Radiation ◽  
Boundary Conditions ◽  
Interannual Variability ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
The Past

Abstract Stratospheric ozone is affected by external factors such as chlorofluorcarbons (CFCs), volcanoes, and the 11-yr solar cycle variation of ultraviolet radiation. Dynamical variability due to the quasi-biennial oscillation and other factors also contribute to stratospheric ozone variability. A research focus during the past two decades has been to quantify the downward trend in ozone due to the increase in industrially produced CFCs. During the coming decades research will focus on detection and attribution of the expected recovery of ozone as the CFCs are slowly removed from the atmosphere. A chemical transport model (CTM) has been used to simulate stratospheric composition for the past 30 yr and the next 20 yr using 50 yr of winds and temperatures from a general circulation model (GCM). The simulation includes the solar cycle in ultraviolet radiation, a representation of aerosol surface areas based on observations including volcanic perturbations from El Chichon in 1982 and Pinatubo in 1991, and time-dependent mixing ratio boundary conditions for CFCs, halons, and other source gases such as N2O and CH4. A second CTM simulation was carried out for identical solar flux and boundary conditions but with constant “background” aerosol conditions. The GCM integration included an online ozonelike tracer with specified production and loss that was used to evaluate the effects of interannual variability in dynamics. Statistical time series analysis was applied to both observed and simulated ozone to examine the capability of the analyses for the determination of trends in ozone due to CFCs and to separate these trends from the solar cycle and volcanic effects in the atmosphere. The results point out several difficulties associated with the interpretation of time series analyses of atmospheric ozone data. In particular, it is shown that lengthening the dataset reduces the uncertainty in derived trend due to interannual dynamic variability. It is further shown that interannual variability can make it difficult to accurately assess the impact of a volcanic eruption, such as Pinatubo, on ozone. Such uncertainties make it difficult to obtain an early proof of ozone recovery in response to decreasing chlorine.

scholarly journals Regional uptake and release of crop carbon in the United States

2011 ◽  
Vol 8 (8) ◽  
pp. 2037-2046 ◽  
Author(s):  
T. O. West ◽  
V. Bandaru ◽  
C. C. Brandt ◽  
A. E. Schuh ◽  
S. M. Ogle
Keyword(s):  
Great Plains ◽  
Carbon Budget ◽  
Supply And Demand ◽  
The United States ◽  
Northern Great Plains ◽  
Agricultural Crops ◽  
Biomass Storage ◽  
The Us ◽  
Import And Export ◽  
Crop Biomass

Abstract. Carbon fixed by agricultural crops in the US creates regional CO2 sinks where it is harvested and regional CO2 sources where it is released back to the atmosphere. The quantity and location of these fluxes differ depending on the annual supply and demand of crop commodities. Data on the harvest of crop biomass, storage, import and export, and on the use of biomass for food, feed, fiber, and fuel were compiled to estimate an annual crop carbon budget for 2000 to 2008. With respect to US Farm Resource Regions, net sources of CO2 associated with the consumption of crop commodities occurred in the Eastern Uplands, Southern Seaboard, and Fruitful Rim regions. Net sinks associated with the production of crop commodities occurred in the Heartland, Northern Great Plains, and Mississippi Portal regions. The national crop carbon budget was balanced to within 0.3 to 6.1 % yr−1 during the period of this analysis.

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