scholarly journals Impact of Spaceborne Carbon Monoxide Observations from the S-5P platform on Tropospheric Composition Analyses and Forecasts

2016 ◽  
Author(s):  
R. Abida ◽  
J.-L. Attié ◽  
L. El Amraoui ◽  
P. Ricaud ◽  
W. Lahoz ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Forest Fires ◽  
System Simulation ◽  
Weather Conditions ◽  
Simulation Experiments ◽  
Northern Summer ◽  
Free Model ◽  
Comparison Of The Results ◽  
The Impact ◽  
Total Column

Abstract. We use the technique of Observing System Simulation Experiments (OSSEs) to quantify the impact of spaceborne carbon monoxide (CO) total column observations from the Sentinel-5 Precursor (S-5P) platform on tropospheric analyses and forecasts. We focus on Europe for the period of northern summer 2003, when there was a severe heat wave episode associated with extremely hot and dry weather conditions. We describe different elements of the OSSE: (i) the Nature Run (NR), i.e., the "Truth"; ii) the CO synthetic observations; (iii) the assimilation run (AR), where we assimilate the observations of interest; (iv) the control run (CR), in this study a free model run without assimilation; and (v) efforts to establish the fidelity of the OSSE results. Comparison of the results from AR and the CR, against the NR, shows that CO total column observations from S-5P provide a significant benefit (at the 99 % confidence level) at the surface, with the largest benefit occurring over land in remote regions. Furthermore, the S-5P CO total column observations are able to capture phenomena such as the forest fires that occurred in Portugal during summer 2003. These results provide evidence of the benefit of S-5P observations for monitoring processes contributing to atmospheric pollution.

scholarly journals Impact of spaceborne carbon monoxide observations from the S-5P platform on tropospheric composition analyses and forecasts

2017 ◽  
Vol 17 (2) ◽  
pp. 1081-1103 ◽  
Author(s):  
Rachid Abida ◽  
Jean-Luc Attié ◽  
Laaziz El Amraoui ◽  
Philippe Ricaud ◽  
William Lahoz ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Forest Fires ◽  
Weather Conditions ◽  
Emission Sources ◽  
Simulation Experiments ◽  
Northern Summer ◽  
Free Model ◽  
Comparison Of The Results ◽  
The Impact ◽  
Total Column

Abstract. We use the technique of Observing System Simulation Experiments (OSSEs) to quantify the impact of spaceborne carbon monoxide (CO) total column observations from the Sentinel-5 Precursor (S-5P) platform on tropospheric analyses and forecasts. We focus on Europe for the period of northern summer 2003, when there was a severe heat wave episode associated with extremely hot and dry weather conditions. We describe different elements of the OSSE: (i) the nature run (NR), i.e., the truth; (ii) the CO synthetic observations; (iii) the assimilation run (AR), where we assimilate the observations of interest; (iv) the control run (CR), in this study a free model run without assimilation; and (v) efforts to establish the fidelity of the OSSE results. Comparison of the results from AR and the CR, against the NR, shows that CO total column observations from S-5P provide a significant benefit (at the 99 % confidence level) at the surface, with the largest benefit occurring over land in regions far away from emission sources. Furthermore, the S-5P CO total column observations are able to capture phenomena such as the forest fires that occurred in Portugal during northern summer 2003. These results provide evidence of the benefit of S-5P observations for monitoring processes contributing to atmospheric pollution.

scholarly journals Forest Fire in East Nusa Tenggara during 2015-2019: Comparison to Forest Fire in Kalimantan and Sumatera

2021 ◽  
Vol 893 (1) ◽  
pp. 012010
Author(s):  
Sumaryati ◽  
D F Andarini ◽  
N Cholianawati ◽  
A Indrawati
Keyword(s):  
Carbon Monoxide ◽  
Forest Fire ◽  
Forest Fires ◽  
Forest Biomass ◽  
Comparison Method ◽  
Atmospheric Environment ◽  
Annual Average ◽  
Statistical Comparison ◽  
Fire Area ◽  
Total Column

Abstract East Nusa Tenggara is one of the provinces in Indonesia that has big forest fires following some provinces in Kalimantan and Sumatra. However, forest fires in East Nusa Tenggara have less attention in forest fires discussion in Indonesia. This study aims to analyze forest fires in East Nusa Tenggara and their impact on reducing visibility and increasing carbon monoxide (CO) from 2015 to 2019. In this study, hotspot, forest fire area, Oceanic Niño Index, visibility, and CO total column data were used to analyze the forest fires using a statistical comparison method in East Nusa Tenggara, Kalimantan, and Sumatra. The result shows that the number of hotspots in East Nusa Tenggara less than in Kalimantan and Sumatra for the same forest fire area. The forest fires in East Nusa Tenggara do not harm the atmospheric environment significantly. East Nusa Tenggara dominantly consists of savanna areas with no peatland, hence, the forest biomass burning produces less smoke and CO. Furthermore, the forest fire in East Nusa Tenggara has not an impact on decreasing visibility and increasing CO total column, in contrast, visibility in Sumatra and Kalimantan has fallen to 6 km from the annual average, and CO total column rise three times of normal condition during peak fire.

scholarly journals The Impact of Covariance Localization for Radar Data on EnKF Analyses of a Developing MCS: Observing System Simulation Experiments

2013 ◽  
Vol 141 (11) ◽  
pp. 3691-3709 ◽  
Author(s):  
Ryan A. Sobash ◽  
David J. Stensrud
Keyword(s):  
System Simulation ◽  
Three Dimensional ◽  
Radar Data ◽  
Convective System ◽  
State Variables ◽  
Simulation Experiments ◽  
Length Scales ◽  
Convective Scale ◽  
The Impact ◽  
Prior State

Abstract Several observing system simulation experiments (OSSEs) were performed to assess the impact of covariance localization of radar data on ensemble Kalman filter (EnKF) analyses of a developing convective system. Simulated Weather Surveillance Radar-1988 Doppler (WSR-88D) observations were extracted from a truth simulation and assimilated into experiments with localization cutoff choices of 6, 12, and 18 km in the horizontal and 3, 6, and 12 km in the vertical. Overall, increasing the horizontal localization and decreasing the vertical localization produced analyses with the smallest RMSE for most of the state variables. The convective mode of the analyzed system had an impact on the localization results. During cell mergers, larger horizontal localization improved the results. Prior state correlations between the observations and state variables were used to construct reverse cumulative density functions (RCDFs) to identify the correlation length scales for various observation-state pairs. The OSSE with the smallest RMSE employed localization cutoff values that were similar to the horizontal and vertical length scales of the prior state correlations, especially for observation-state correlations above 0.6. Vertical correlations were restricted to state points closer to the observations than in the horizontal, as determined by the RCDFs. Further, the microphysical state variables were correlated with the reflectivity observations on smaller scales than the three-dimensional wind field and radial velocity observations. The ramifications of these findings on localization choices in convective-scale EnKF experiments that assimilate radar data are discussed.

Improved impacts in observing system simulation experiments of radio occultation observations as a result of model and data assimilation changes

2020 ◽  
Author(s):  
L. CUCURULL ◽  
S. P. F. CASEY
Keyword(s):  
Data Assimilation ◽  
Radio Occultation ◽  
Weather Forecasting ◽  
Positive Impact ◽  
System Simulation ◽  
Weather Prediction ◽  
Wind Fields ◽  
Simulation Experiments ◽  
The Impact ◽  
Forward Operator

AbstractAs global data assimilation systems continue to evolve, Observing System Simulation Experiments (OSSEs) need to be updated to accurately quantify the impact of proposed observing technologies in weather forecasting. Earlier OSSEs with radio occultation (RO) observations have been updated and the impact of the originally proposed Constellation Observing Satellites for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) mission, with a high-inclination and low-inclination component, has been investigated by using the operational data assimilation system at NOAA and a 1-dimensional bending angle RO forward operator. It is found that the impact of the low-inclination component of the originally planned COSMIC-2 mission (now officially named COSMIC-2) has significantly increased as compared to earlier studies, and significant positive impact is now found globally in terms of mass and wind fields. These are encouraging results as COSMIC-2 was successfully launched in June 2019 and data have been recently released to operational weather centers. Earlier findings remain valid indicating that globally distributed RO observations are more important to improve weather prediction globally than a denser sampling of the tropical latitudes. Overall, the benefits reported here from assimilating RO soundings are much more significant than the impacts found in previous OSSEs. This is largely attributed to changes in the data assimilation and forecast system and less to the more advanced 1-dimensional forward operator chosen for the assimilation of RO observations.

An Analysis of Alternatives for the COSMIC-2 Constellation in the Context of Global Observing System Simulation Experiments

2020 ◽  
Vol 35 (1) ◽  
pp. 51-66 ◽  
Author(s):  
L. Cucurull ◽  
M. J. Mueller
Keyword(s):  
System Simulation ◽  
Three Dimensional ◽  
Lower Troposphere ◽  
Weather Forecast ◽  
Satellite System ◽  
Forecast Skill ◽  
Added Value ◽  
Simulation Experiments ◽  
Global Navigation Satellite ◽  
The Impact

Abstract Observing system simulation experiments (OSSEs) were conducted to evaluate the potential impact of the six Global Navigation Satellite System (GNSS) radio occultation (RO) receiver satellites in equatorial orbit from the initially proposed Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) mission, known as COSMIC-2A. Furthermore, the added value of the high-inclination component of the proposed mission was investigated by considering a few alternative architecture designs, including the originally proposed polar constellation of six satellites (COSMIC-2B), a constellation with a reduced number of RO receiving satellites, and a constellation of six satellites but with fewer observations in the lower troposphere. The 2015 year version of the operational three-dimensional ensemble–variational data assimilation system of the National Centers for Environment Prediction (NCEP) was used to run the OSSEs. Observations were simulated and assimilated using the same methodology and their errors assumed uncorrelated. The largest benefit from the assimilation of COSMIC-2A, with denser equatorial coverage, was to improve tropical winds, and its impact was found to be overall neutral in the extratropics. When soundings from the high-inclination orbit were assimilated in addition to COSMIC-2A, positive benefits were found globally, confirming that a high-inclination orbit constellation of RO receiving satellites is necessary to improve weather forecast skill globally. The largest impact from reducing COSMIC-2B from six to four satellites was to slightly degrade weather forecast skill in the Northern Hemisphere extratropics. The impact of degrading COSMIC-2B to the COSMIC level of accuracy, in terms of penetration into the lower troposphere, was mostly neutral.

scholarly journals Parameter Sensitivity of the WRF–LETKF System for Assimilation of Radar Observations: Imperfect-Model Observing System Simulation Experiments

2020 ◽  
Vol 35 (4) ◽  
pp. 1345-1362 ◽  
Author(s):  
Paula Maldonado ◽  
Juan Ruiz ◽  
Celeste Saulo
Keyword(s):  
Data Assimilation ◽  
Short Range ◽  
System Simulation ◽  
Weather Prediction ◽  
Doppler Velocity ◽  
Convective System ◽  
Model Errors ◽  
Spatiotemporal Resolution ◽  
Simulation Experiments ◽  
The Impact

AbstractSpecification of suitable initial conditions to accurately forecast high-impact weather events associated with intense thunderstorms still poses a significant challenge for convective-scale forecasting. Radar data assimilation has been showing encouraging results to produce an accurate estimate of the state of the atmosphere at the mesoscale, as it combines high-spatiotemporal-resolution observations with convection-permitting numerical weather prediction models. However, many open questions remain regarding the configuration of state-of-the-art data assimilation systems at the mesoscale and their potential impact upon short-range weather forecasts. In this work, several observing system simulation experiments of a mesoscale convective system were performed to assess the sensitivity of the local ensemble transform Kalman filter to both relaxation-to-prior spread (RTPS) inflation and horizontal localization of the error covariance matrix. Realistic large-scale forcing and model errors have been taken into account in the simulation of reflectivity and Doppler velocity observations. Overall, the most accurate analyses in terms of RMSE were produced with a relatively small horizontal localization cutoff radius (~3.6–7.3 km) and large RTPS inflation parameter (~0.9–0.95). Additionally, the impact of horizontal localization on short-range ensemble forecast was larger compared to inflation, almost doubling the lead times up to which the effect of using a more accurate state to initialize the forecast persisted.

Observing System Simulation Experiments (OSSEs) to Evaluate the Potential Impact of an Optical Autocovariance Wind Lidar (OAWL) on Numerical Weather Prediction

2015 ◽  
Vol 32 (9) ◽  
pp. 1593-1613 ◽  
Author(s):  
Robert Atlas ◽  
Ross N. Hoffman ◽  
Zaizhong Ma ◽  
G. David Emmitt ◽  
Sidney A. Wood ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sampling Error ◽  
System Simulation ◽  
Weather Prediction ◽  
Simulation Experiments ◽  
Wind Lidar ◽  
Potential Impact ◽  
The Impact ◽  
Data Assimilation System ◽  
Assimilation System

AbstractThe potential impact of Doppler wind lidar (DWL) observations from a proposed optical autocovariance wind lidar (OAWL) instrument is quantified in observing system simulation experiments (OSSEs). The OAWL design would provide profiles of useful wind vectors along a ground track to the left of the International Space Station (ISS), which is in a 51.6° inclination low-Earth orbit (LEO). These observations are simulated realistically, accounting for cloud and aerosol distributions inferred from the OSSE nature runs (NRs), and measurement and sampling error sources. The impact of the simulated observations is determined in both global and regional OSSE frameworks. The global OSSE uses the ECMWF T511 NR and the NCEP operational Global Data Assimilation System at T382 resolution. The regional OSSE uses an embedded hurricane NR and the NCEP operational HWRF data assimilation system with outer and inner domains of 9- and 3-km resolution, respectively.The global OSSE results show improved analyses and forecasts of tropical winds and extratropical geopotential heights. The tropical wind RMSEs are significantly reduced in the analyses and in short-term forecasts. The tropical wind improvement decays as the forecasts lengthen. The regional OSSEs are limited but show some improvements in hurricane track and intensity forecasts.

scholarly journals Data assimilation of satellite-retrieved ozone, carbon monoxide and nitrogen dioxide with ECMWF's Composition-IFS

2015 ◽  
Vol 15 (9) ◽  
pp. 5275-5303 ◽  
Author(s):  
A. Inness ◽  
A.-M. Blechschmidt ◽  
I. Bouarar ◽  
S. Chabrillat ◽  
M. Crepulja ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Data Assimilation ◽  
Nitrogen Dioxide ◽  
Initial Conditions ◽  
Stratospheric Ozone ◽  
Lower Troposphere ◽  
Atmospheric Composition ◽  
Reactive Gases ◽  
The Impact ◽  
Total Column

Abstract. Daily global analyses and 5-day forecasts are generated in the context of the European Monitoring Atmospheric Composition and Climate (MACC) project using an extended version of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The IFS now includes modules for chemistry, deposition and emission of reactive gases, aerosols, and greenhouse gases, and the 4-dimensional variational data assimilation scheme makes use of multiple satellite observations of atmospheric composition in addition to meteorological observations. This paper describes the data assimilation setup of the new Composition-IFS (C-IFS) with respect to reactive gases and validates analysis fields of ozone (O3), carbon monoxide (CO), and nitrogen dioxide (NO2) for the year 2008 against independent observations and a control run without data assimilation. The largest improvement in CO by assimilation of Measurements of Pollution in the Troposphere (MOPITT) CO columns is seen in the lower troposphere of the Northern Hemisphere (NH) extratropics during winter, and during the South African biomass-burning season. The assimilation of several O3 total column and stratospheric profile retrievals greatly improves the total column, stratospheric and upper tropospheric O3 analysis fields relative to the control run. The impact on lower tropospheric ozone, which comes from the residual of the total column and stratospheric profile O3 data, is smaller, but nevertheless there is some improvement particularly in the NH during winter and spring. The impact of the assimilation of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI) is small because of the short lifetime of NO2, suggesting that NO2 observations would be better used to adjust emissions instead of initial conditions. The results further indicate that the quality of the tropospheric analyses and of the stratospheric ozone analysis obtained with the C-IFS system has improved compared to the previous "coupled" model system of MACC.

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