scholarly journals Scientific considerations for acidification monitoring in the U.S. Mid-Atlantic Region

2019 ◽  
Vol 225 ◽  
pp. 106189 ◽  
Author(s):  
Kaitlin A. Goldsmith ◽  
Sherilyn Lau ◽  
Matthew E. Poach ◽  
Gregg P. Sakowicz ◽  
T. Mark Trice ◽  
...  
Keyword(s):  
Atlantic Region ◽  
The U.S

Evaluating the productivity and costs of five energywood harvesting operations in the lower Mid-Atlantic region of the U.S

2021 ◽  
pp. 1-11
Author(s):  
Austin M. Garren ◽  
M. Chad Bolding ◽  
Scott M. Barrett ◽  
W. Michael Aust ◽  
T. Adam Coates
Keyword(s):  
Atlantic Region ◽  
The U.S

scholarly journals Potential for shoreline changes due to sea-level rise along the U.S. mid-Atlantic region

2007 ◽  
Author(s):  
Benjamin T. Gutierrez ◽  
S. Jeffress Williams ◽  
E. Robert Thieler
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Atlantic Region ◽  
Shoreline Changes ◽  
The U.S

An Optimization Model for Selecting Sample Days

2021 ◽  
pp. 2050052
Author(s):  
Tao Li
Keyword(s):  
North Atlantic ◽  
Optimization Model ◽  
Federal Aviation Administration ◽  
Selection Method ◽  
North Atlantic Region ◽  
Atlantic Region ◽  
Managerial Decisions ◽  
The North ◽  
The North Atlantic ◽  
The U.S

Sample day selection method plays an important role in managerial decisions which require analyses that are prohibitively expensive to apply to a large number of days. We develop a general sample day selection model that selects sample days based on the cumulative distributions of airspace conditions and characteristics (C&C) by considering factors such as sampling targets, degree of diversity and coverage of the selected days. We introduce indicators that capture the airspace C&C of the North Atlantic region (NAT) and apply the model to select sample days for the NAT. The results show that the model outperforms the methods used by the U.S. Federal Aviation Administration.

Using Local Ecological Knowledge to Assess Morel Decline in the U.S. Mid–Atlantic Region

2010 ◽  
Vol 64 (3) ◽  
pp. 205-216 ◽  
Author(s):  
Marla R. Emery ◽  
Elizabeth S. Barron
Keyword(s):  
Local Ecological Knowledge ◽  
Ecological Knowledge ◽  
Atlantic Region ◽  
The U.S

The Geomorphic Effects of Existing Dams and Historic Dam Removals in the U.S. Mid-Atlantic Region

2011 ◽  
pp. 83-96 ◽  
Author(s):  
Katherine Skalak ◽  
James Pizzuto ◽  
Jennifer Egan ◽  
Nicholas Allmendinger
Keyword(s):  
Atlantic Region ◽  
Dam Removals ◽  
The U.S

scholarly journals Ensemble Streamflow Forecasting across the U.S. Mid-Atlantic Region with a Distributed Hydrological Model Forced by GEFS Reforecasts

2017 ◽  
Vol 18 (7) ◽  
pp. 1905-1928 ◽  
Author(s):  
Ridwan Siddique ◽  
Alfonso Mejia
Keyword(s):  
Hydrological Model ◽  
Hydrologic Model ◽  
Ensemble Prediction ◽  
Lead Times ◽  
Distributed Hydrological Model ◽  
Streamflow Forecasting ◽  
Atlantic Region ◽  
Meteorological Forcing ◽  
Streamflow Forecasts ◽  
The U.S

Abstract The quality of ensemble streamflow forecasts in the U.S. mid-Atlantic region (MAR) is investigated for short- to medium-range forecast lead times (6–168 h). To this end, a regional hydrological ensemble prediction system (RHEPS) is assembled and implemented. The RHEPS in this case comprises the ensemble meteorological forcing, a distributed hydrological model, and a statistical postprocessor. As the meteorological forcing, precipitation, and near-surface temperature outputs from the National Oceanic and Atmospheric Administration (NOAA)/National Centers for Environmental Prediction (NCEP) 11-member Global Ensemble Forecast System Reforecast, version 2 (GEFSRv2), are used. The Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) is used as the distributed hydrological model, and a statistical autoregressive model with an exogenous variable is used as the postprocessor. To verify streamflow forecasts from the RHEPS, eight river basins in the MAR are selected, ranging in drainage area from ~262 to 29 965 km2 and covering some of the major rivers in the MAR. The verification results for the RHEPS show that, at the initial lead times (1–3 days), the hydrological uncertainties have more impact on forecast skill than the meteorological ones. The former become less pronounced, and the meteorological uncertainties dominate, across longer lead times (>3 days). Nonetheless, the ensemble streamflow forecasts remain skillful for lead times of up to 7 days. Additionally, postprocessing increases forecast skills across lead times and spatial scales, particularly for the high-flow conditions. Overall, the proposed RHEPS is able to improve streamflow forecasting in the MAR relative to the deterministic (unperturbed GEFSRv2 member) forecasting case.

Expanding the mercury deposition network in Virginia and the U.S. mid-Atlantic region

Fact Sheet ◽  
2005 ◽  
Author(s):  
Allan Kolker ◽  
Douglas G. Mose ◽  
Shane Spitzer ◽  
Joseph A. East
Keyword(s):  
Mercury Deposition ◽  
Atlantic Region ◽  
The U.S
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