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Featured researches published by Mark Iredell.


Journal of Geophysical Research | 2014

First forecast of a sudden stratospheric warming with a coupled whole‐atmosphere/ionosphere model IDEA

Houjun Wang; Rashid Akmaev; Tzu‐Wei Fang; T. J. Fuller-Rowell; Fei Wu; Naomi Maruyama; Mark Iredell

We present the first “weather forecast” with a coupled whole-atmosphere/ionosphere model of Integrated Dynamics in Earths Atmosphere (IDEA) for the January 2009 Sudden Stratospheric Warming (SSW). IDEA consists of the Whole Atmosphere Model and Global Ionosphere-Plasmasphere model. A 30 day forecast is performed using the IDEA model initialized at 0000 UT on 13 January 2009, 10 days prior to the peak of the SSW. IDEA successfully predicts both the time and amplitude of the peak warming in the polar cap. This is about 2 days earlier than the National Centers for Environmental Prediction operational Global Forecast System terrestrial weather model forecast. The forecast of the semidiurnal, westward propagating, zonal wave number 2 (SW2) tide in zonal wind also shows an increase in the amplitude and a phase shift to earlier hours in the equatorial dynamo region during and after the peak warming, before recovering to their prior values about 15 days later. The SW2 amplitude and phase changes are shown to be likely due to the stratospheric ozone and/or circulation changes. The daytime upward plasma drift and total electron content in the equatorial American sector show a clear shift to earlier hours and enhancement during and after the peak warming, before returning to their prior conditions. These ionospheric responses compare well with other observational studies. Therefore, the predicted ionospheric response to the January 2009 SSW can be largely explained in simple terms of the amplitude and phase changes of the SW2 zonal wind in the equatorial E region.


Bulletin of the American Meteorological Society | 2016

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

Gerhard Theurich; Cecelia DeLuca; Timothy Campbell; Fushan Liu; K. Saint; Mariana Vertenstein; Junye Chen; R. Oehmke; James D. Doyle; Timothy R Whitcomb; Alan J. Wallcraft; Mark Iredell; Thomas L. Black; A. da Silva; T. Clune; Robert D. Ferraro; P. Li; M. Kelley; I. Aleinov; V. Balaji; N. Zadeh; Robert L. Jacob; Benjamin Kirtman; Francis X. Giraldo; D. McCarren; Scott Sandgathe; Steven E. Peckham; R. Dunlap

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users. The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS®); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model.


Geoscientific Model Development | 2016

The implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP

Cheng-Hsuan Lu; Arlindo da Silva; Jun Wang; Shrinivas Moorthi; Mian Chin; Peter R. Colarco; Youhua Tang; Partha S. Bhattacharjee; Shen-Po Chen; Hui-Ya Chuang; Hann-Ming Henry Juang; Jeffery T. McQueen; Mark Iredell

The NOAA National Centers for Environmental Prediction (NCEP) implemented NEMS GFS Aerosol Component (NGAC) for global dust forecasting in collaboration with NASA Goddard Space Flight Center (GSFC). NGAC Version 1.0 has been providing 5 day dust forecasts at 1°×1° resolution on a global scale, once per day at 00:00 Coordinated Universal Time (UTC), since September 2012. This is the first global system capable of interactive atmosphere aerosol forecasting at NCEP. The implementation of NGAC V1.0 reflects an effective and efficient transitioning of NASA research advances to NCEP operations, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders as well as to allow the effects of aerosols on weather forecasts and climate prediction to be considered.


International Technical Meeting on Air Pollution Modelling and its Application | 2016

Dynamic Coupling of the NMMB and CMAQ Models Through the U.S. National Unified Operational Prediction Capability (NUOPC)

Pius Lee; Barry Baker; Daniel Tong; Li Pan; Dusan Jovic; Mark Iredell; Youhua Tang

An earth system modeling framework (ESMF) that enables unprecedented insight into the various aspects of the geophysical sciences of Planet Earth in an integrated and holistic manner is needed to study the physical phenomena of weather and climate. The ESMF concept has recently been promoted and elevated by multiple governmental agencies and institutions in the U.S.A. to unify a standard engineering practice and coding protocol in building geophysical model interfaces towards efficient dynamic coupling of earth models and deployment of earth modeling systems for operational services. This new capability is called the National Unified Operational Prediction Capability (NUOPC) (available at http://www.nws.noaa.gov/nuopc/). This project demonstrates the efficacy of using NUOPC as the software package to efficiently in-line, or 2-way couple at every synchronization time-step, the dust prediction capability of the U.S. National Air Quality Forecasting Capability (NAQFC). The NAQFC in the National Centers for Environmental Prediction (NCEP) operations comprises of an off-line coupled National Weather Service (NWS) North American Mesoscale-model (NAM) and the U.S. EPA Community Air Quality Multiscale Model (CMAQ). The limitation of the off-line coupled NAM-CMAQ is that NAM gives meteorological prediction to CMAQ hourly and uni-directionally. This project attempted a new coupling paradigm allowing NAM and CMAQ communicate with one another per synchronization time-step at roughly 5 min intervals uni-directionally or bi-directionally. In this project, the NUOPC protocol was tightly followed and the in-line NAM-CMAQ ability tested to forecast fine mode particulates concentration with earth-crustal origin. A strong dust storm occurred in the South Western U.S. on May 11 2014 was used as a test case for the NUOPC in-line NAM-CMAQ forecasting capability. The forecast performance for the test case was evaluated against measured surface concentration of fine particulate smaller than 2.5 μm in diameter (PM2.5).


Archive | 2007

Linking the ETA Model with the Community Multiscale Air Quality (CMAQ) Modeling System: Ozone Boundary Conditions

Pius Lee; Jonathan E. Pleim; Rohit Mathur; Jeffery T. McQueen; Marina Tsidulko; Geoff DiMego; Mark Iredell; Tanya L. Otte; George Pouliot; Jeffrey Young; David C. Wong; Daiwen Kang; Mary Hart; Kenneth L. Schere

Until the recent decade, air quality forecasts have been largely based on statistical modeling techniques. There have been significant improvements and innovations made to these statistically based air quality forecast models during past years (Ryan et al., 2000). Forecast fidelity has improved considerably using these methods. Nonetheless, being non-physically-based models, the performance of these models can vary dramatically, both spatially and temporally. Recent strides in computational technology and the increasing speed of supercomputers, combined with scientific improvements in meteorological and air quality models has spurred the development of operational numerical air quality prediction models (e.g., Vaughn et al., 2004, McHenry et al., 2004). In 2003, NOAA and the U.S. Environmental Protection Agency (EPA) signed a memorandum of agreement to work collaboratively on the development of a national air quality forecast capability. Shortly afterwards, a joint team of scientists from the two agencies developed and evaluated a prototype surface ozone concentration forecast capability for the Eastern U.S. (Davidson et al., 2004). The National Weather Service (NWS) / National Centers for Environmental Prediction (NCEP) ETA model (Black, 1994, Rogers et al., 1996, and Ferrier et al., 2003) with 12-km


Geophysical Research Letters | 2011

Forecasting the dynamic and electrodynamic response to the January 2009 sudden stratospheric warming

T. J. Fuller-Rowell; Houjun Wang; Rashid Akmaev; Fei Wu; Tzu-Wei Fang; Mark Iredell; A. D. Richmond


Geophysical Research Letters | 2008

Tidal variability in the lower thermosphere: Comparison of Whole Atmosphere Model (WAM) simulations with observations from TIMED

R. A. Akmaev; T. J. Fuller-Rowell; Francis T. Wu; Jeffrey M. Forbes; Xiaoli Zhang; A. F. Anghel; Mark Iredell; S. Moorthi; H.-M. Juang


Geophysical Research Letters | 2008

Impact of terrestrial weather on the upper atmosphere

T. J. Fuller-Rowell; Rashid Akmaev; F. Wu; Adela Florina Anghel; N. Maruyama; David N. Anderson; M.V. Codrescu; Mark Iredell; S. Moorthi; H.-M. Juang; Y.-T. Hou; George Millward


Journal of Geophysical Research | 2010

Midnight density and temperature maxima, and thermospheric dynamics in Whole Atmosphere Model simulations

Rashid Akmaev; F. Wu; T. J. Fuller-Rowell; H. Wang; Mark Iredell


Journal of Geophysical Research | 2011

First simulations with a whole atmosphere data assimilation and forecast system: The January 2009 major sudden stratospheric warming

Houjun Wang; T. J. Fuller-Rowell; Rashid Akmaev; Ming Hu; Daryl T. Kleist; Mark Iredell

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Rashid Akmaev

University of Colorado Boulder

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Stefanie D. Moorthi

National Oceanic and Atmospheric Administration

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T. J. Fuller-Rowell

Cooperative Institute for Research in Environmental Sciences

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Hann-Ming Henry Juang

National Oceanic and Atmospheric Administration

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Houjun Wang

National Oceanic and Atmospheric Administration

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Shan Lu

National Oceanic and Atmospheric Administration

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George Millward

University College London

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A. da Silva

Goddard Space Flight Center

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Adela Florina Anghel

University of Colorado Boulder

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