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Jeffrey T. Morisette, Louis Giglio, Ivan Csiszar, Alberto Setzer, Wilfrid Schroeder, Douglas Morton, and Christopher O. Justice

of fire statistics to the Large-Scale Biosphere–Atmosphere (LBA) Experiment in Amazonia. Polar-orbiting satellite systems have been extensively used to monitor the global distribution of fire ( Dwyer et al. 2000 ; Malingreau and Gregoire 1996 ; Justice and Dowty 1994 ). Regional fire monitoring in Brazil has been done with Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) ( Elvidge et al. 2001 ), Advanced Very High Resolution Radiometer (AVHRR) ( Setzer and

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Gian Villamil-Otero, Ryan Meiszberg, Jennifer S. Haase, Ki-Hong Min, Mark R. Jury, and John J. Braun

1. Introduction One of the challenges of short-term (multihour) coastal weather forecasting is factoring in the variable influence of sea-breeze circulations. These often lead to abrupt wind shifts, convergence lines, and thunderstorm downdrafts that impact aviation. Despite extensive research ( Atkins and Wakimoto 1997 ), it is difficult to accurately predict the intensity and position of sea breezes and their interaction with the synoptic flow. The classical definition of sea breeze is a

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Richard R. Heim Jr. and Michael J. Brewer

are too complex for use by decision makers, unreliable seasonal forecasts, inadequate indices for detecting the early onset and end of drought, the lack of integrated physical and socioeconomic indicators for drought, the lack of impact assessment methodology, data and information frequently unavailable on an operational real-time basis, and inadequate comprehensive global historical database and assessment products ( Wilhite et al. 2000 ; Wilhite and Buchanan-Smith 2005 ; Adger et al. 2007

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Ashok K. Mishra and Vijay P. Singh

of droughts or an increase in their severity ( Wilhite and Hayes 1998 ), and based on the National Climatic Data Center ( National Climatic Data Center 2002 ) nearly 10% of the total land area experienced either severe or extreme droughts at any given time during the last century. There has been a variety of concepts ( Mishra and Singh 2010 ) applied to modeling droughts, ranging from simplistic approaches to more complex models ( Mishra and Singh 2011 ). Drought prediction or forecasting plays a

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Ana M. B. Nunes and John O. Roads

, which means that it is not assimilated, but entirely determined by the model 6-h forecasts ( Kalnay et al. 1996 ). Janowiak et al. ( Janowiak et al. 1998 ), Roads and Betts ( Roads and Betts 2000 ), and Roads and Chen ( Roads and Chen 2000 ) showed that although large-scale patterns of precipitation fields from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) global reanalysis project [R-1 ( Kalnay et al. 1996 ); R-2 ( Kanamitsu et al. 2002

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Ayan H. Chaudhuri and Rui M. Ponte

inconsistencies in near-surface fields important for determining the state of the atmosphere–ocean–sea ice Arctic system. 2. Data and methods We consider five recent reanalysis products—namely, CFSR, MERRA, ERA-Interim, JRA-25, and ASR—for our analysis. CFSR uses a global, high-spatial-resolution (≈40 km) coupled atmosphere–ocean–land surface–sea ice model. This reanalysis is designed to provide initial conditions for historical forecasts and operational NCEP climate forecasts. CFSR utilizes the NCEP

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Mark R. Jury

Research Institute for Climate and Society (IRI) Climate Library website: http://iridl.ldeo.columbia.edu/ ]; Weather Research and Forecasting Nonhydrostatic Mesoscale Model (WRF-NMM) weather model–analyzed boundary layer height and winds [ Janjić 2003 ; National Operational Model Archive and Distribution System (NOMADS) National Climatic Data Center (NCDC) website: http://nomads.ncdc.noaa.gov/ ]; Geostationary Operational Environmental Satellite (GOES) infrared cloud temperatures from NASA [Goddard

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Amanda Markert, Robert Griffin, Kevin Knupp, Andrew Molthan, and Tim Coleman

2 (EF2) and greater] in the country. In addition, north Alabama has suffered from the most prolific tornado outbreaks in recorded history including the 3 April 1974 and 25–27 April 2011 outbreaks ( Knupp 2014 ). Within north Alabama, the NOAA National Weather Service Weather Forecast Office (WFO) operational forecasters, broadcast meteorologists, private industry weather companies, and the public have observed spatial patterns in tornado distribution and frequency. A spatial density map

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Brian E. Potter and Daniel McEvoy

scaled linear growth, results for scaled area will be discussed below. Because results for area and scaled linear growth may differ and add insight, they appear in the appendix . 2) Atmospheric data To increase the relevance of this study to fire operations, we chose an atmospheric dataset that is operationally available and widely used, with broad coverage and relatively fine grid spacing. We used the North American Mesoscale Forecast System (NAM) 218 grid (12 km grid spacing) 0000 UTC analysis, 0

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Olivia Kellner and Dev Niyogi

.2.3. Land-use classification buffers While currently not explicitly considered as part of the operational forecast process for the probability of tornado development, surface roughness has been analyzed for impacts on vortex dynamics for decades. Dessens ( Dessens 1972 ) conducted a series of simple experiments exploring the effects of surface roughness on an air tornado model using two surface types: a smooth plate to simulate smooth flow and a wood plate with 6-mm pebbles to simulate a rough surface

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