The Inclusion of chemistry modules into the NOAA UFS Weather Model with the Common Community Physics Package (CCPP)

2021 ◽  
Author(s):  
Haiqin Li ◽  
Georg Grell ◽  
Li Zhang ◽  
Ravan Ahmadov ◽  
Stuart Mckeen ◽  
...  
Keyword(s):  
Real Time ◽  
Environmental Modeling ◽  
Atmospheric Composition ◽  
Forecast System ◽  
Coupled Models ◽  
Fire Emissions ◽  
Aerosol Emission ◽  
Weather Model ◽  
The Common ◽  
Physics Parameterizations

<p>Online atmosphere-chemistry coupled models have been rapidly developed in recent years. In online models, the atmospheric model can impact air quality and atmospheric composition, while the aerosol feedbacks also impact the atmosphere through direct, semi-direct and indirect effects. At NOAA GSL, in collaboration with scientists from the Chemical Science Laboratory (CSL) and Air Resource Laboratory (ARL), we developed an atmospheric composition suite (based on WRF-Chem) and coupled it online with FV3GFS through the National Unified Operational Prediction Capability (NUOPC)-based NOAA Environmental Modeling System (NEMS) software. This modeling system has been operational since September 24<sup>th</sup>, 2020 as an ensemble member of the Global Ensemble Forecast System (named as GEFS-aerosols) for global aerosol predictions. When using the NUOPC coupler, there are two independent components for atmosphere and chemistry that communicate via the NUOPC coupler every time-step. Because of the interactive and strongly couple nature of chemistry and physics, it is natural to allow for some of the atmospheric composition modules to be called directly from inside the physics suite. This can be accomplished through the use of the Common Community Physics Package (CCPP). CCPP, designed to facilitate a host-model agnostic implementation of physics parameterizations, is a community development and will be used by many different organizations. All the physics parameterizations in the NOAA Unified Forecast System (UFS) Weather Model are CCPP-compliant. Here we broke up the chemistry suite used in GEFS-aerosols, and all the chemical modules were embedded into UFS Weather Model using CCPP as subroutines of physics. This newly developed model with CCPP has been running in real-time starting in the middle of November, 2020. Because of this development we were able to include the CCPP-compliant modules of sea salt, dust, and wild-fire emissions into the NWP model to provide input for the double moment Thompson microphysics parameterization. The inclusion of smoke and aerosol emission modules into the Rapid Refresh Forecast System (RRFS) with CCPP is also ongoing. We will show results from real-time experiments for medium range weather forecasting and compare results with runs that do not include aerosol impacts.</p>

Improving global chemical weather forecast with modern online-coupled models for the U.S. Next Generation Global Prediction System (NGGPS)

2020 ◽  
Author(s):  
Raffaele Montuoro ◽  
Georg Grell ◽  
Li Zhang ◽  
Stuart McKeen ◽  
Gregory Frost ◽  
...  
Keyword(s):  
Air Quality ◽  
Environmental Modeling ◽  
Coupled Systems ◽  
Prediction System ◽  
Next Generation ◽  
Forecast System ◽  
Coupled Models ◽  
Air Quality Forecast ◽  
Recent Advances ◽  
The U.S

<p>Significant progress has been made within the last couple of years towards developing online coupled systems aimed at providing more accurate descriptions of atmospheric chemistry processes to improve performance of global aerosol and air quality forecasts. Operating within the U.S. National Weather Service (NWS) research-to-operation initiative to implement the fully-coupled Next Generation Global Prediction System (NGGPS), cooperative development efforts have delivered two integrated online global prediction systems for aerosols (GEFS-Aerosols) and air quality (FV3GFS-AQM). These systems include recent advances in aerosol convective transport and wet deposition processes introduced into the SAS scheme of the National Center for Environmental Prediction’s (NCEP) latest Global Forecast System (GFS) based on the Finite-Volume cubed-sphere dynamical core (FV3). GEFS-Aerosols is slated to become the new control member of the NWS Global Ensemble Forecast System (GEFS). The model features an online-coupled version of the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model with a biomass-burning, plume-rise model and recent advances from NOAA Earth System Research Laboratory (ESRL), along with a state-of-the-art FENGSHA dust scheme from NOAA Air Resource Laboratory (ARL). FV3GFS-AQM incorporates a coupled, single-column adaptation of the U.S. Environmental Protection Agency’s (EPA) Community Multiscale Air Quality (CMAQ) model to improve NOAA’s current National Air Quality Forecast Capability (NAQFC). Both coupled systems’ design and development benefited from the use of the National Unified Operational Prediction Capability (NUOPC) Layer, which provided a common model architecture for interoperable, coupled model components within the framework of NOAA’s Environmental Modeling System (NEMS). Results from each of the described coupled systems will be discussed.</p>

scholarly journals Development and Evaluation of the Aerosol Forecast Member in NCEP’s Global Ensemble Forecast System (GEFS-Aerosols v1)

2021 ◽  
Author(s):  
Li Zhang ◽  
Raffaele Montuoro ◽  
Stuart A. McKeen ◽  
Barry Baker ◽  
Partha S. Bhattacharjee ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Transport Model ◽  
Environmental Modeling ◽  
Ensemble Forecast ◽  
Atmospheric Composition ◽  
Global Forecast System ◽  
Tracer Transport ◽  
Forecast System ◽  
Aerosol Model ◽  
Aerosol Component

Abstract. NOAA’s National Weather Service (NWS) is on its way to deploy various operational prediction applications using the Unified Forecast System (https://ufscommunity.org/), a community-based coupled, comprehensive Earth modeling system. An aerosol model component developed in a collaboration between the Global Systems Laboratory, Chemical Science Laboratory, the Air Resources Laboratory, and Environmental Modeling Center (GSL, CSL, ARL, EMC) was coupled online with the FV3 Global Forecast System (FV3GFS) using the National Unified Operational Prediction Capability (NUOPC)-based NOAA Environmental Modeling System (NEMS) software framework. This aerosol prediction system replaced the NEMS GFS Aerosol Component (NGAC) system in the National Center for Environment Prediction (NCEP) production suite in September 2020 as one of the ensemble members of the Global Ensemble Forecast System (GEFS), dubbed GEFS-Aerosols v1. The aerosol component of atmospheric composition in GEFS is based on the Weather Research and Forecasting model (WRF-Chem) that was previously included into FIM-Chem (Zhang et al, 2021). GEFS-Aerosols includes bulk modules from the Goddard Chemistry Aerosol Radiation and Transport model (GOCART). Additionally, the biomass burning plume rise module from High-Resolution Rapid Refresh (HRRR)-Smoke was implemented; the GOCART dust scheme was replaced by the FENGSHA dust scheme (developed by ARL); the Blended Global Biomass Burning Emissions Product (GBBEPx V3) provides biomass burning emission and Fire Radiative Power (FRP) data; and the global anthropogenic emission inventories are derived from the Community Emissions Data System (CEDS). All sub-grid scale transport and deposition is handled inside the atmospheric physics routines, which required consistent implementation of positive definite tracer transport and wet scavenging in the physics parameterizations used by NCEP’s operational Global Forecast System based on FV3 (FV3GFS). This paper describes the details of GEFS-Aerosols model development and evaluation of real-time and retrospective runs using different observations from in situ measurement, satellite and aircraft data. GEFS-Aerosols predictions demonstrate substantial improvements for both composition and variability of aerosol distributions over those from the former operational NGAC system.

scholarly journals The FireWork v2.0 air quality forecast system with biomass burning emissions from the Canadian Forest Fire Emissions Prediction System v2.03

2019 ◽  
Author(s):  
Jack Chen ◽  
Kerry Anderson ◽  
Radenko Pavlovic ◽  
Michael D. Moran ◽  
Peter Englefield ◽  
...  
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Forest Fire ◽  
Biomass Burning ◽  
Prediction System ◽  
Forecast System ◽  
Fire Emissions ◽  
Air Quality Forecast ◽  
New System ◽  
Quality Forecast

Abstract. Biomass burning activities can produce large quantities of smoke and result in adverse air quality conditions in regional environments. In Canada, Environment and Climate Change Canada's (ECCC) operational FireWork air quality forecast system incorporates near-real-time biomass burning emissions to forecast smoke plumes from fire events. The system is based on the ECCC operational Regional Air Quality Deterministic Prediction System (RAQDPS) augmented with near-real-time wildfire emissions using inputs from the Canadian Forest Service's (CFS) Canadian Wildland Fire Information System (CWFIS). Recent improvements to the representation of fire behaviour and fire emissions have been incorporated into the CFS Canadian Forest Fire Emissions Prediction System (CFFEPS). This is a bottom-up system linked to CWFIS in which hourly changes in biomass fuel consumption are parameterized with hourly forecasted meteorology at fire locations. CFFEPS has now also been connected to FireWork. In addition, a plume-rise parameterization based on fire energy thermodynamics is used to define the smoke injection height and the distribution of emissions within a model vertical column. The new system, FireWork-CFFEPS, has been evaluated over North America for July–September 2017 and June–August 2018, both periods when western Canada experienced historical levels of fire activity with poor air quality conditions in several cities as well as other fires affecting northern Canada and Ontario. Forecast results were evaluated against hourly surface measurements for the three pollutant species used to calculate the Canadian Air Quality Health Index (AQHI), namely PM2.5, O3, and NO2, and benchmarked against the operational FireWork system (FireWork-Ops). This comparison shows improved forecast performance and predictive skills for the FireWork-CFFEPS system. Modelled fire plume injection heights from CFFEPS based on fire energy thermodynamics show higher plume injection heights and larger variability. The changes in predicted fire emissions and injection height reduced the consistent over-predictions of PM2.5 and O3 seen in FireWork-Ops. On the other hand, there were minimal fire emission contributions to surface NO2, and results from FireWork-CFFEPS do not degrade NO2 forecast skill compared to the RAQDPS. Model performances statistics are slightly better for Canada than for the U.S., with lower errors and biases. The new system is still unable to capture the hourly variability of the observed values for PM2.5, but it captured the observed hourly variability for O3 concentration adequately. FireWork-CFFEPS also improves upon FireWork-Ops categorical scores for forecasting the occurrence of elevated air pollutant concentrations in terms of false alarm ratio (FAR), and critical success index (CSI).

Advances in operational air quality and aerosol prediction at NOAA/National Weather Service

2020 ◽  
Author(s):  
Ivanka Stajner ◽  
Keyword(s):  
Air Quality ◽  
Satellite Data ◽  
Weather Prediction ◽  
Satellite Observations ◽  
Atmospheric Composition ◽  
Forecast System ◽  
National Weather Service ◽  
Aerosol Composition ◽  
Fire Emissions ◽  
Weather Service

<p>NOAA is developing the Unified Forecast System (UFS) (https://ufscommunity.org/) as the source system for operational numerical weather prediction applications.  The UFS will be a coupled, comprehensive Earth modeling system with community contributions. The UFS is designed to streamline and simplify NOAA/National Weather Service operational modeling suite.  Integration of air quality predictions into the UFS began with testing of the Community Multiscale Air Quality modeling system (CMAQ) predictions driven by the operational version of the Global Forecast System (GFS), which includes the Finite-Volume Cubed-Sphere (FV3) dynamical core since June 2019.  In addition to system integration, this testing allows us to extend ozone and PM2.5 predictions to 72 hours (from 48 hours that operational predictions currently cover).  Integration of global aerosol prediction based on the Goddard Chemistry Aerosol Radiation and Transport (GOCART) scheme into the UFS begun by including it into one member of the Global Ensemble Forecast System (GEFS-Aerosol). GEFS-Aerosol predictions demonstrate a substantial improvement for both composition and variability of aerosol distributions over those from the currently operational standalone global aerosol prediction system.</p><p>The use of satellite observations in atmospheric composition and air quality predictions is increasing at NOAA.  Real-time estimates of biomass burning emissions for predictions are based on satellite data.  Challenges for these emissions involve detection of fires, the strength and composition of the emissions, altitude of the plume rise, temporal distribution of the emissions and the uncertainty in persistence or change of emissions during the forecast period. Representation of changing fire emissions in the model becomes more important with increasing prediction length.  Assimilation of Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) observations is under development to constrain aerosol distribution in the global system. Initial testing shows promise for improvement of predictions as well as limitations indicating a need for refinements in quality control, data assimilation impacts on aerosol composition and vertical distribution, as well as a need for bias correction of satellite observations.   Plans for the next-generation regional system include assimilation of satellite retrievals of VIIRS AOD and Sentinel-5 Precursor Tropospheric Ozone Monitoring Instrument (S5P TROPOMI) NO2. Satellite data also play an important role in verification of aerosol predictions. Additional uses of satellite data include verification and evaluation of model predictions such as aerosol vertical profile with TROPOMI aerosol layer height product as well as efforts to constrain and update anthropogenic emissions.</p><p>This presentation will overview advances and challenges in model development and the use of satellite data for operational atmospheric composition and air quality predictions at NOAA.</p>

scholarly journals The FireWork v2.0 air quality forecast system with biomass burning emissions from the Canadian Forest Fire Emissions Prediction System v2.03

2019 ◽  
Vol 12 (7) ◽  
pp. 3283-3310 ◽  
Author(s):  
Jack Chen ◽  
Kerry Anderson ◽  
Radenko Pavlovic ◽  
Michael D. Moran ◽  
Peter Englefield ◽  
...  
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Forest Fire ◽  
Biomass Burning ◽  
Prediction System ◽  
Forecast System ◽  
Fire Emissions ◽  
Air Quality Forecast ◽  
New System ◽  
Quality Forecast

Abstract. Biomass burning activities can produce large quantities of smoke and result in adverse air quality conditions in regional environments. In Canada, the Environment and Climate Change Canada (ECCC) operational FireWork (v1.0) air quality forecast system incorporates near-real-time biomass burning emissions to forecast smoke plumes from fire events. The system is based on the ECCC operational Regional Air Quality Deterministic Prediction System (RAQDPS) augmented with near-real-time wildfire emissions using inputs from the Canadian Forest Service (CFS) Canadian Wildland Fire Information System (CWFIS). Recent improvements to the representation of fire behaviour and fire emissions have been incorporated into the CFS Canadian Forest Fire Emissions Prediction System (CFFEPS) v2.03. This is a bottom-up system linked to CWFIS in which hourly changes in biomass fuel consumption are parameterized with hourly forecasted meteorology at fire locations. CFFEPS has now also been connected to FireWork. In addition, a plume-rise parameterization based on fire-energy thermodynamics is used to define the smoke injection height and the distribution of emissions within a model vertical column. The new system, FireWork v2.0 (FireWork–CFFEPS), has been evaluated over North America for July–September 2017 and June–August 2018, which are both periods when western Canada experienced historical levels of fire activity with poor air quality conditions in several cities as well as other fires affecting northern Canada and Ontario. Forecast results were evaluated against hourly surface measurements for the three pollutant species used to calculate the Canadian Air Quality Health Index (AQHI), namely PM2.5, O3, and NO2, and benchmarked against the operational FireWork v1.0 system (FireWork-Ops). This comparison shows improved forecast performance and predictive skills for the FireWork–CFFEPS system. Modelled fire-plume injection heights from CFFEPS based on fire-energy thermodynamics show higher plume injection heights and larger variability. The changes in predicted fire emissions and injection height reduced the consistent over-predictions of PM2.5 and O3 seen in FireWork-Ops. On the other hand, there were minimal fire emission contributions to surface NO2, and results from FireWork–CFFEPS do not degrade NO2 forecast skill compared to the RAQDPS. Model performance statistics are slightly better for Canada than for the US, with lower errors and biases. The new system is still unable to capture the hourly variability of the observed values for PM2.5, but it captured the observed hourly variability for O3 concentration adequately. FireWork–CFFEPS also improves upon FireWork-Ops categorical scores for forecasting the occurrence of elevated air pollutant concentrations in terms of false alarm ratio (FAR) and critical success index (CSI).

The Debris Flow Disaster Faster-Than-Early Forecast System (DFS) with Multi-Sensors Integrated Wireless Sensor Networks

2013 ◽  
Vol 347-350 ◽  
pp. 975-979
Author(s):  
Rong Zhao ◽  
Cai Hong Li ◽  
Yun Jian Tan ◽  
Jun Shi ◽  
Fu Qiang Mu ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Debris Flow ◽  
Real Time ◽  
Debris Flows ◽  
Base Station ◽  
Base Stations ◽  
Wireless Sensor ◽  
Forecast System ◽  
Debris Flow Disaster

This paper presents a Debris Flow Disaster Faster-than-early Forecast System (DFS) with wireless sensor networks. Debris flows carrying saturated solid materials in water flowing downslope often cause severe damage to the lives and properties in their path. Faster-than-early or faster-than-real-time forecasts are imperative to save lives and reduce damage. This paper presents a novel multi-sensor networks for monitoring debris flows. The main idea is to let these sensors drift with the debris flow, to collect flow information as they move along, and to transmit the collected data to base stations in real time. The Raw data are sent to the cloud processing center from the base station. And the processed data and the video of the debris flow are display on the remote PC. The design of the system address many challenging issues, including cost, deployment efforts, and fast reaction.

scholarly journals Forecasting Tropical Cyclones in the Western North Pacific Basin Using the NCEP Operational HWRF: Real-Time Implementation in 2012

2015 ◽  
Vol 30 (5) ◽  
pp. 1355-1373 ◽  
Author(s):  
Vijay Tallapragada ◽  
Chanh Kieu ◽  
Samuel Trahan ◽  
Zhan Zhang ◽  
Qingfu Liu ◽  
...  
Keyword(s):  
Real Time ◽  
North Pacific ◽  
Western North Pacific ◽  
Large Scale ◽  
Environmental Modeling ◽  
Pacific Basin ◽  
Forecast Errors ◽  
Storm Intensity ◽  
Intensity Forecast ◽  
North Pacific Basin

Abstract This study documents the recent efforts of the hurricane modeling team at the National Centers for Environmental Prediction’s (NCEP) Environmental Modeling Center (EMC) in implementing the operational Hurricane Weather Research and Forecasting Model (HWRF) for real-time tropical cyclone (TC) forecast guidance in the western North Pacific basin (WPAC) from May to December 2012 in support of the operational forecasters at the Joint Typhoon Warning Center (JTWC). Evaluation of model performance for the WPAC in 2012 reveals that the model has promising skill with the 3-, 4-, and 5-day track errors being 125, 220, and 290 nautical miles (n mi; 1 n mi = 1.852 km), respectively. Intensity forecasts also show good performance, with the most significant intensity error reduction achieved during the first 24 h. Stratification of the track and intensity forecast errors based on storm initial intensity reveals that HWRF tends to underestimate storm intensity for weak storms and overestimate storm intensity for strong storms. Further analysis of the horizontal distribution of track and intensity forecast errors over the WPAC suggests that HWRF possesses a systematic negative intensity bias, slower movement, and a rightward bias in the lower latitudes. At higher latitudes near the East China Sea, HWRF shows a positive intensity bias and faster storm movement. This appears to be related to underestimation of the dominant large-scale system associated with the western Pacific subtropical high, which renders weaker steering flows in this basin.

Investigation of volcanic emissions in Antikythera PANGEA station using near-real-time alerts

2021 ◽  
Author(s):  
Anna Kampouri ◽  
Vassilis Amiridis ◽  
Stavros Solomos ◽  
Anna Gialitaki ◽  
Eleni Marinou ◽  
...  
Keyword(s):  
Real Time ◽  
Dispersion Model ◽  
Atmospheric Composition ◽  
Dust Particles ◽  
Volcanic Plume ◽  
Observation Data ◽  
National Observatory ◽  
Development Fund ◽  
Model Simulations ◽  
Geophysical Observatory

<p>In the last years, several Etna eruption events are documented, forming lava flows and explosive activity. The Pilot EO4D_ash – Earth observation data for detection, discrimination & distribution (4D) of volcanic ash of the e-shape project provides the PANhellenic GEophysical observatory of Antikythera (PANGEA) of the National Observatory of Athens (NOA), in Greece with near-real-time alerts from Etna volcano eruptions. These alerts are used in the PANGEA station to monitor and reveal the presence of volcanic particles above the area the days following an eruption, also the station is supported by a volcanic particle monitoring and forecasting warning system. In this work, we investigate the volcano eruption between 30 May and 6 June 2019 which affected the southern parts of Greece and reaching the Antikythera station. Due to the prevailing meteorological conditions, volcanic particles and gases followed an easterly direction and were dispersed towards Greece. FLEXPART dispersion model simulations confirm the volcanic plume transport from Etna towards PANGEA, mixing also with co-existing desert dust particles. Model simulations are evaluated with Polly<sup>XT</sup> lidar measurements performed at PANGEA and satellite-based SO<sub>2</sub> observations from the TROPOspheric Monitoring Instrument onboard the Sentinel-5 Precursor (TROPOMI/S5P). This is the first time that Etna volcanic products are monitored at the Antikythera station, in Greece with implications for the investigation of their role in the Mediterranean weather and climate.</p><p><strong>Acknowledgments</strong>: We acknowledge the support by EU H2020 E-shape project (Grant Agreement n. 820852). Also, this research was supported by data and services obtained from the PANhellenic Geophysical Observatory of Antikythera (PANGEA) of the National Observatory of Athens (NOA), Greece, and by the project “PANhellenic infrastructure for Atmospheric Composition and climatE change” (MIS 5021516) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme "Competitiveness, Entrepreneurship and Innovation" (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund). NOA team acknowledges the support of the Stavros Niarchos Foundation (SNF).</p>

Sign in / Sign up

Export Citation Format

Share Document