scholarly journals High‐Resolution Climate Projections for the Northeastern United States Using Dynamical Downscaling at Convection‐Permitting Scales

2018 ◽  
Vol 5 (11) ◽  
pp. 801-826 ◽  
Author(s):  
M. Komurcu ◽  
K. A. Emanuel ◽  
M. Huber ◽  
R. P. Acosta
Keyword(s):  
United States ◽  
High Resolution ◽  
Dynamical Downscaling ◽  
Climate Projections ◽  
Northeastern United States

A high-resolution hydrogen isotope record of behenic acid for the past 16 kyr in the northeastern United States

2017 ◽  
Vol 449 ◽  
pp. 1-11 ◽  
Author(s):  
Li Gao ◽  
Yongsong Huang ◽  
Bryan Shuman ◽  
W. Wyatt Oswald ◽  
David Foster
Keyword(s):  
United States ◽  
High Resolution ◽  
Hydrogen Isotope ◽  
Behenic Acid ◽  
Northeastern United States ◽  
The Past ◽  
Isotope Record

scholarly journals Seasonal Simulation of Tropospheric Ozone over the Midwestern and Northeastern United States: An Application of a Coupled Regional Climate and Air Quality Modeling System

2007 ◽  
Vol 46 (7) ◽  
pp. 945-960 ◽  
Author(s):  
Ho-Chun Huang ◽  
Xin-Zhong Liang ◽  
Kenneth E. Kunkel ◽  
Michael Caughey ◽  
Allen Williams
Keyword(s):  
United States ◽  
Air Quality ◽  
Tropospheric Ozone ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Future Climate ◽  
Climate Projections ◽  
Northeastern United States ◽  
Ozone Episodes

Abstract The impacts of air pollution on the environment and human health could increase as a result of potential climate change. To assess such possible changes, model simulations of pollutant concentrations need to be performed at climatic (seasonal) rather than episodic (days) time scales, using future climate projections from a general circulation model. Such a modeling system was employed here, consisting of a regional climate model (RCM), an emissions model, and an air quality model. To assess overall model performance with one-way coupling, this system was used to simulate tropospheric ozone concentrations in the midwestern and northeastern United States for summer seasons between 1995 and 2000. The RCM meteorological conditions were driven by the National Centers for Environmental Prediction/Department of Energy global reanalysis (R-2) using the same procedure that integrates future climate model projections. Based on analyses for several urban and rural areas and regional domains, fairly good agreement with observations was found for the diurnal cycle and for several multiday periods of high ozone episodes. Even better agreement occurred between monthly and seasonal mean quantities of observed and model-simulated values. This is consistent with an RCM designed primarily to produce good simulations of monthly and seasonal mean statistics of weather systems.

scholarly journals Added value of high-resolution climate projections over South Korea on the scaling of precipitation with temperature

2021 ◽  
Author(s):  
Liying Qiu ◽  
Eun-Soon Im
Keyword(s):  
Global Warming ◽  
High Resolution ◽  
South Korea ◽  
Spatial Pattern ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Models ◽  
Added Value ◽  
Climate Projections

Abstract This study evaluates the resolution dependency of scaling precipitation with temperature from the perspective of the added value of high-resolution (5-km) dynamical downscaling using various kinds of long-term climate change projections over South Korea. Three CMIP5 Global Climate Models (GCMs) with different climate sensitivities, and one pseudo global warming (PGW) experiment, are downscaled by Weather Research and Forecasting (WRF) one-way double nested modeling system with convective parameterization for the reference (1976-2005) and future (2071-2100) periods under RCP8.5 scenario. A detailed comparison of the driving GCM/PGW, 20-km mother simulation, and 5-km nested simulation demonstrates improved representation of precipitation with increasing resolution not only in the spatial pattern and magnitude for both the mean and the extremes, but also in a more realistic representation of extreme precipitation’s sensitivities to temperature. According to the projected precipitation changes downscaled from both GCM ensemble and PGW, there will be intensified precipitation, particularly for the extremes, over South Korea under the warming, which is primarily contributed by CP increase that shows higher temperature sensitivity. This study also compares the extreme precipitation-temperature scaling relations within-epoch (apparent scaling) and between-epoch (climate scaling). It confirms that the magnitude and spatial pattern of the two scaling rates can be quite different, and the precipitation change over Korea under global warming is mainly controlled by thermodynamic factors.

scholarly journals Projecting wildfire emissions over the south-eastern United States to mid-century

2018 ◽  
Vol 27 (5) ◽  
pp. 313 ◽  
Author(s):  
Uma Shankar ◽  
Jeffrey P. Prestemon ◽  
Donald McKenzie ◽  
Kevin Talgo ◽  
Aijun Xiu ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Socioeconomic Factors ◽  
Dynamical Downscaling ◽  
Climate Projections ◽  
Particulate Emissions ◽  
Eastern United States ◽  
The South ◽  
South Eastern ◽  
The Us

Wildfires can impair human health because of the toxicity of emitted pollutants, and threaten communities, structures and the integrity of ecosystems sensitive to disturbance. Climate and socioeconomic factors (e.g. population and income growth) are known regional drivers of wildfires. Reflecting changes in these factors in wildfire emissions estimates is thus a critical need in air quality and health risk assessments in the south-eastern United States. We developed such a methodology leveraging published statistical models of annual area burned (AAB) over the US Southeast for 2011–2060, based on county-level socioeconomic and climate projections, to estimate daily wildfire emissions in selected historical and future years. Projected AABs were 7 to 150% lower on average than the historical mean AABs for 1992–2010; projected wildfire fine-particulate emissions were 13 to 62% lower than those based on historical AABs, with a temporal variability driven by the climate system. The greatest differences were in areas of large wildfire impacts from socioeconomic factors, suggesting that historically based (static) wildfire inventories cannot properly represent future air quality responses to changes in these factors. The results also underscore the need to correct biases in the dynamical downscaling of wildfire climate drivers to project the health risks of wildfire emissions more reliably.

High-Resolution Observations and Model Simulations of the Life Cycle of an Intense Mesoscale Snowband over the Northeastern United States

2008 ◽  
Vol 136 (4) ◽  
pp. 1433-1456 ◽  
Author(s):  
David R. Novak ◽  
Brian A. Colle ◽  
Sandra E. Yuter
Keyword(s):  
United States ◽  
High Resolution ◽  
Mesoscale Model ◽  
Dramatic Improvement ◽  
Conditional Stability ◽  
Grid Spacing ◽  
Northeastern United States ◽  
Band Formation ◽  
Model Simulations ◽  
Inertial Instability

Abstract This paper investigates the structural and dynamical evolution of an intense mesoscale snowband occurring 25–26 December 2002 over the northeastern United States. Dual-Doppler, wind profiler, aircraft, and water vapor observations in concert with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model run at 4-km grid spacing are used to highlight evolutionary aspects of a snowband unresolved by previous studies. The high-resolution observations and model simulations show that band formation was coincident with a sharpening of a midlevel trough and associated increase in frontogenesis in an environment of conditional and inertial instability. Band maturity was marked by increasing conditional stability and a threefold increase in frontogenetical forcing. Band dissipation occurred as the midlevel trough and associated frontogenetical forcing weakened, while the conditional stability continued to increase. The effect of changing ascent is shown to dominate over changing moisture in explaining band dissipation in this case. Unconventional aspects of band structure and dynamics revealed by the high-resolution data are discussed, including the location of the band relative to the frontogenesis maximum, increasing stability during the band-formation process, and the presence of inertial instability. The model realistically predicted the band evolution; however, maximum precipitation was underforecast within the banded region by ∼30% at 4-km grid spacing, and the axis of heaviest precipitation was displaced ∼50 km to the southeast of the observed location. Higher horizontal model resolution is shown to contribute toward improved QPF in this case; however, it appears more dramatic improvement may be gained by better simulating the frontogenesis, stability, and moisture evolution.

Estimations of Hazardous Convective Weather in the United States Using Dynamical Downscaling

2014 ◽  
Vol 27 (17) ◽  
pp. 6581-6589 ◽  
Author(s):  
Vittorio A. Gensini ◽  
Thomas L. Mote
Keyword(s):  
United States ◽  
High Resolution ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate Model ◽  
Regional Climate ◽  
The United States ◽  
Regional Model ◽  
Severe Weather ◽  
Convective Weather

Abstract High-resolution (4 km; hourly) regional climate modeling is utilized to resolve March–May hazardous convective weather east of the U.S. Continental Divide for a historical climate period (1980–90). A hazardous convective weather model proxy is used to depict occurrences of tornadoes, damaging thunderstorm wind gusts, and large hail at hourly intervals during the period of record. Through dynamical downscaling, the regional climate model does an admirable job of replicating the seasonal spatial shifts of hazardous convective weather occurrence during the months examined. Additionally, the interannual variability and diurnal progression of observed severe weather reports closely mimic cycles produced by the regional model. While this methodology has been tested in previous research, this is the first study to use coarse-resolution global climate model data to force a high-resolution regional model with continuous seasonal integration in the United States for purposes of resolving severe convection. Overall, it is recommended that dynamical downscaling play an integral role in measuring climatological distributions of severe weather, both in historical and future climates.

scholarly journals Development and Evaluation of High-Resolution Climate Simulations over the Mountainous Northeastern United States

2016 ◽  
Vol 17 (3) ◽  
pp. 881-896 ◽  
Author(s):  
Jonathan M. Winter ◽  
Brian Beckage ◽  
Gabriela Bucini ◽  
Radley M. Horton ◽  
Patrick J. Clemins
Keyword(s):  
United States ◽  
High Resolution ◽  
Air Temperature ◽  
Climate Models ◽  
Global Climate ◽  
Probability Distributions ◽  
New York State ◽  
High Elevation ◽  
Global Climate Models ◽  
Northeastern United States

Abstract The mountain regions of the northeastern United States are a critical socioeconomic resource for Vermont, New York State, New Hampshire, Maine, and southern Quebec. While global climate models (GCMs) are important tools for climate change risk assessment at regional scales, even the increased spatial resolution of statistically downscaled GCMs (commonly ~⅛°) is not sufficient for hydrologic, ecologic, and land-use modeling of small watersheds within the mountainous Northeast. To address this limitation, an ensemble of topographically downscaled, high-resolution (30″), daily 2-m maximum air temperature; 2-m minimum air temperature; and precipitation simulations are developed for the mountainous Northeast by applying an additional level of downscaling to intermediately downscaled (⅛°) data using high-resolution topography and station observations. First, observed relationships between 2-m air temperature and elevation and between precipitation and elevation are derived. Then, these relationships are combined with spatial interpolation to enhance the resolution of intermediately downscaled GCM simulations. The resulting topographically downscaled dataset is analyzed for its ability to reproduce station observations. Topographic downscaling adds value to intermediately downscaled maximum and minimum 2-m air temperature at high-elevation stations, as well as moderately improves domain-averaged maximum and minimum 2-m air temperature. Topographic downscaling also improves mean precipitation but not daily probability distributions of precipitation. Overall, the utility of topographic downscaling is dependent on the initial bias of the intermediately downscaled product and the magnitude of the elevation adjustment. As the initial bias or elevation adjustment increases, more value is added to the topographically downscaled product.

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