Winter survival response of canola to meteorological variables and adaptative areas for current canola germplasm in the United States

2021 ◽  
Vol 297 ◽  
pp. 108267
Author(s):  
Mario A. Secchi ◽  
Leonardo M. Bastos ◽  
Michael J. Stamm ◽  
Yancy Wright ◽  
Chris Foster ◽  
...  
Keyword(s):  
United States ◽  
The United States ◽  
Winter Survival ◽  
Meteorological Variables

scholarly journals Strong influence of 2000–2050 climate change on particulate matter in the United States: Results from a new statistical model

2016 ◽  
Author(s):  
Lu Shen ◽  
Loretta J. Mickley ◽  
Lee T. Murray
Keyword(s):  
Climate Change ◽  
United States ◽  
Particulate Matter ◽  
Air Quality ◽  
Statistical Model ◽  
The United States ◽  
Anthropogenic Sources ◽  
Meteorological Variables ◽  
Eastern United States ◽  
Low Cloud

Abstract. We use a statistical model to investigate the effect of 2000–2050 climate change on fine particulate matter (PM2.5) air quality across the contiguous United States. By applying observed relationships of PM2.5 and meteorology to the IPCC Coupled Model Intercomparision Project Phase 5 (CMIP5) archives, we bypass many of the uncertainties inherent in chemistry-climate models. Our approach uses both the relationships between PM2.5 and local meteorology as well as the synoptic circulation patterns, defined as the Singular Value Decomposition (SVD) pattern of the spatial correlations between PM2.5 and meteorological variables in the surrounding region. Using an ensemble of 17 GCMs under the RCP4.5 scenario, we project an increase of ~ 1 μg m−3 in annual mean PM2.5 in the eastern US and a decrease of 0.3–1.2 μg m−3 in the Intermountain West by the 2050s, assuming present-day anthropogenic sources of PM2.5. Mean summertime PM2.5 increases as much as 2–3 μg m−3 in the eastern United States due to faster oxidation rates and greater mass of organic carbon from biogenic emissions. Mean wintertime PM2.5 decreases by 0.3–3 μg m−3 over most regions in United States, likely due to the volatilization of ammonium nitrate. Our approach provides an efficient method to calculate the climate penalty or benefit on air quality across a range of models and scenarios. We find that current atmospheric chemistry models may underestimate or even fail to capture the strongly positive sensitivity of monthly mean PM2.5 to temperature in the eastern United States in summer, and may underestimate future changes in PM2.5 in a warmer climate. In GEOS-Chem, the underestimate in monthly mean PM2.5-temperature relationship in the East in summer is likely caused by overly strong negative sensitivity of monthly mean low cloud fraction to temperature in the assimilated meteorology (~ −0.04 K−1), compared to the weak sensitivity implied by satellite observations (±0.01 K−1). The strong negative dependence of low cloud cover on temperature, in turn, causes the modeled rates of sulfate aqueous oxidation to diminish too rapidly as temperatures rise, leading to the underestimate of sulfate-temperature slopes, especially in the South. Our work underscores the importance of evaluating the sensitivity of PM2.5 to its key controlling meteorological variables in climate-chemistry models on multiple timescales before they are applied to project future air quality.

scholarly journals Simulating Hydrological Drought Properties at Different Spatial Units in the United States Based on Wavelet–Bayesian Regression Approach

2012 ◽  
Vol 16 (17) ◽  
pp. 1-23 ◽  
Author(s):  
Ashok K. Mishra ◽  
Vijay P. Singh
Keyword(s):  
United States ◽  
Regression Model ◽  
Climate Models ◽  
Global Climate ◽  
The United States ◽  
Hydrological Drought ◽  
Bayesian Regression ◽  
Global Climate Models ◽  
Meteorological Variables ◽  
The Relationship

Abstract Because of their stochastic nature, droughts vary in space and time, and therefore quantifying droughts at different time units is important for water resources planning. The authors investigated the relationship between meteorological variables and hydrological drought properties using the Palmer hydrological drought index (PHDI). Twenty different spatial units were chosen from the unit of a climatic division to a regional unit across the United States. The relationship between meteorological variables and PHDI was investigated using a wavelet–Bayesian regression model, which enhances the modeling strength of a simple Bayesian regression model. Further, the wavelet–Bayesian regression model was tested for the predictability of global climate models (GCMs) to simulate PHDI, which will also help understand their role for downscaling purposes.

scholarly journals Influence of 2000–2050 climate change on particulate matter in the United States: results from a new statistical model

2017 ◽  
Vol 17 (6) ◽  
pp. 4355-4367 ◽  
Author(s):  
Lu Shen ◽  
Loretta J. Mickley ◽  
Lee T. Murray
Keyword(s):  
Climate Change ◽  
United States ◽  
Particulate Matter ◽  
Air Quality ◽  
Statistical Model ◽  
Climate Models ◽  
The United States ◽  
Meteorological Variables ◽  
Eastern United States ◽  
Low Cloud

Abstract. We use a statistical model to investigate the effect of 2000–2050 climate change on fine particulate matter (PM2. 5) air quality across the contiguous United States. By applying observed relationships of PM2. 5 and meteorology to the IPCC Coupled Model Intercomparision Project Phase 5 (CMIP5) archives, we bypass some of the uncertainties inherent in chemistry-climate models. Our approach uses both the relationships between PM2. 5 and local meteorology as well as the synoptic circulation patterns, defined as the singular value decomposition (SVD) pattern of the spatial correlations between PM2. 5 and meteorological variables in the surrounding region. Using an ensemble of 19 global climate models (GCMs) under the RCP4.5 scenario, we project an increase of 0.4–1.4 µg m−3 in annual mean PM2. 5 in the eastern US and a decrease of 0.3–1.2 µg m−3 in the Intermountain West by the 2050s, assuming present-day anthropogenic sources of PM2. 5. Mean summertime PM2. 5 increases as much as 2–3 µg m−3 in the eastern United States due to faster oxidation rates and greater mass of organic aerosols from biogenic emissions. Mean wintertime PM2. 5 decreases by 0.3–3 µg m−3 over most regions in the United States, likely due to the volatilization of ammonium nitrate. Our approach provides an efficient method to calculate the potential climate penalty on air quality across a range of models and scenarios. We find that current atmospheric chemistry models may underestimate or even fail to capture the strongly positive sensitivity of monthly mean PM2. 5 to temperature in the eastern United States in summer, and they may underestimate future changes in PM2. 5 in a warmer climate. In GEOS-Chem, the underestimate in monthly mean PM2. 5–temperature relationship in the east in summer is likely caused by overly strong negative sensitivity of monthly mean low cloud fraction to temperature in the assimilated meteorology ( ∼  −0.04 K−1) compared to the weak sensitivity implied by satellite observations (±0.01 K−1). The strong negative dependence of low cloud cover on temperature in turn causes the modeled rates of sulfate aqueous oxidation to diminish too rapidly as temperatures rise, leading to the underestimate of sulfate–temperature slopes, especially in the south. Our work underscores the importance of evaluating the sensitivity of PM2. 5 to its key controlling meteorological variables in climate-chemistry models on multiple timescales before they are applied to project future air quality.

Wetland Nightshade (Solanum tampicense) Growth Response to Temperature, and Winter Survival, in Relation to Potential Spread

2006 ◽  
Vol 20 (3) ◽  
pp. 778-783
Author(s):  
Charles T. Bryson ◽  
Alison M. Fox ◽  
John D. Byrd
Keyword(s):  
United States ◽  
Growth Response ◽  
Southeastern United States ◽  
The United States ◽  
Fruit Production ◽  
Water Levels ◽  
Winter Survival ◽  
Growth Time ◽  
Survival Studies ◽  
Response To Temperature

Greenhouse, growth chamber, and winter survival studies were conducted at Stoneville, MS from 1996 to 2002 to determine growth, time to first flower, and winter survival of wetland nightshade. At 12 wk after emergence, wetland nightshade plants had 58-, 45-, 48-, and 4-cm heights, respectively; 24, 21, 21, and 12 nodes/plant, respectively; 62, 31, 36, and 21 leaves/plant, respectively; and 7.1, 3.9, 5.1, and 0.3 g/plant dry weights, respectively, at temperatures of 26/36, 20/30, 14/24, and 8/18 (±0.5) C at the 14/10 day/night length. Flowering occurred at 79, 85, and 85 days after emergence at 26/36, 20/30, and 14/24 C night/day, respectively at the 14/10 day/night cycle. Wetland nightshade plants did not flower at 8/18 C. Wetland nightshade growth was adequate for flowering and fruit production in additional areas of the southeastern United States with night/day temperatures greater than or equal to 14/24 C. Winter survival was greater than or equal to 33% for established wetland nightshade plants in 5 of 6(1996 to 2002) above water levels and 82% from 20 cm below the water surface. Based on these results, wetland nightshade has the potential to continue to spread in the United States.

Correlative microscopy in distrubuted (client/server) computing environments: tools for catalyzing the rapid dissemination of information about the cell biology of the human prostate

1995 ◽  
Vol 53 ◽  
pp. 682-683
Author(s):  
A. Hakam ◽  
J.T. Gau ◽  
M.L. Grove ◽  
B.A. Evans ◽  
M. Shuman ◽  
...  
Keyword(s):  
United States ◽  
Cell Biology ◽  
Tissue Bank ◽  
The United States ◽  
Prostate Adenocarcinoma ◽  
Correlative Microscopy ◽  
Client Server ◽  
Critical Elements ◽  
Transplant Organ

Prostate adenocarcinoma is the most common malignant tumor of men in the United States and is the third leading cause of death in men. Despite attempts at early detection, there will be 244,000 new cases and 44,000 deaths from the disease in the United States in 1995. Therapeutic progress against this disease is hindered by an incomplete understanding of prostate epithelial cell biology, the availability of human tissues for in vitro experimentation, slow dissemination of information between prostate cancer research teams and the increasing pressure to “ stretch” research dollars at the same time staff reductions are occurring.To meet these challenges, we have used the correlative microscopy (CM) and client/server (C/S) computing to increase productivity while decreasing costs. Critical elements of our program are as follows:1) Establishing the Western Pennsylvania Genitourinary (GU) Tissue Bank which includes >100 prostates from patients with prostate adenocarcinoma as well as >20 normal prostates from transplant organ donors.

Digital image acquisition, processing, and analysis in a polymer microscopy laboratory

1994 ◽  
Vol 52 ◽  
pp. 454-455
Author(s):  
Vinod K. Berry ◽  
Xiao Zhang
Keyword(s):  
United States ◽  
Image Analysis ◽  
Digital Image ◽  
Image Acquisition ◽  
Image Transmission ◽  
The United States ◽  
Quantitative Image Analysis ◽  
Quantitative Image

In recent years it became apparent that we needed to improve productivity and efficiency in the Microscopy Laboratories in GE Plastics. It was realized that digital image acquisition, archiving, processing, analysis, and transmission over a network would be the best way to achieve this goal. Also, the capabilities of quantitative image analysis, image transmission etc. available with this approach would help us to increase our efficiency. Although the advantages of digital image acquisition, processing, archiving, etc. have been described and are being practiced in many SEM, laboratories, they have not been generally applied in microscopy laboratories (TEM, Optical, SEM and others) and impact on increased productivity has not been yet exploited as well.In order to attain our objective we have acquired a SEMICAPS imaging workstation for each of the GE Plastic sites in the United States. We have integrated the workstation with the microscopes and their peripherals as shown in Figure 1.

Silence of the Land: On the Historical Irrelevance of Territory to Congressional Districting and Political Representation in the United States

2001 ◽  
Vol 15 (01) ◽  
pp. 53-87 ◽  
Author(s):  
Andrew Rehfeld
Keyword(s):  
United States ◽  
House Of Representatives ◽  
Political Representation ◽  
The United States ◽  
Representative Government ◽  
Congressional District ◽  
Congressional Districts ◽  
Communities Of Interest

Every ten years, the United States “constructs” itself politically. On a decennial basis, U.S. Congressional districts are quite literally drawn, physically constructing political representation in the House of Representatives on the basis of where one lives. Why does the United States do it this way? What justifies domicile as the sole criteria of constituency construction? These are the questions raised in this article. Contrary to many contemporary understandings of representation at the founding, I argue that there were no principled reasons for using domicile as the method of organizing for political representation. Even in 1787, the Congressional district was expected to be far too large to map onto existing communities of interest. Instead, territory should be understood as forming a habit of mind for the founders, even while it was necessary to achieve other democratic aims of representative government.

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