Impact of new aircraft observations Mode‐S MRAR in a mesoscale NWP model

Strajnar, Benedikt; Žagar, Nedjeljka; Berre, Loïk

doi:10.1002/2014jd022654

Cited by 23 publications

(23 citation statements)

References 29 publications

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“…The results above explain the verification scores of Strajnar et al (), who assimilated Mode‐S observations and demonstrated positive scores when using Mode‐S for verification, but neutral impact when using radiosondes for verification (their Figures and ). Also, their results for the summer period are less positive than the winter period, possibly because the latter contains a stable high pressure period with reduced advection, thus yielding higher correlations between increments and evolved increments.…”

Section: Observation Impact Assessmentsupporting

confidence: 69%

“…That is, model forecast quality is not uniform over the verification area and forecast skill scores highly depend on the sampling of the verifying observing system. This explains the inconsistent skill scores found in Strajnar et al (2015) and to a less extent in de Haan and Stoffelen (2012) who assimilated Mode-S EHS in their respective mesoscale models and showed better skill scores when verifying against Mode-S EHS rather than against radiosondes. The results demonstrate that one has to be careful when using observations for forecast verification when assessing the added value of new observing systems for NWP.…”

Section: Summary Discussion Conclusion and Outlookmentioning

confidence: 85%

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Assessment and tuning of data assimilation systems using passive observations

Marseille

Barkmeijer

Haan

et al. 2016

Quart J Royal Meteoro Soc

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Independent observations can be used to diagnose and tune a data assimilation (DA) system. Analysis increments generally improve the model state near assimilated observations but degrade it further away. High‐resolution aircraft observations from Mode‐S Enhanced Surveillance (Mode‐S EHS) are used as an independent data source to verify increment degradation as a function of distance from assimilated observations. An adaptation of the inherently imperfect gain matrix in DA is proposed such that resulting analyses better fit the independent data source and as such draw model simulations closer to the true atmospheric state. It is found that the structure functions of the background‐error covariance matrix of the experimental mesoscale HARMONIE model are appropriate but too much weight is given to observations relative to the model background. The ECMWF model is well tuned with a slight overestimation of temperature information in the upper troposphere. Finally, a caveat is highlighted when comparing model forecasts from different experiments against observations. It is common practice to use the same observing system both in the analysis and for forecast verification. However, forecast verification is prone to sampling errors, yielding less favourable scores when using an independent data source. Avoidance of biased conclusions on the impact of observing systems, e.g. in observing system experiments (OSE), requires an independent data source (best practice) or a data source used in all experiments (best pragmatic practice) for verification of forecasts from different experiments.

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Section: Observation Impact Assessmentsupporting

confidence: 69%

Section: Summary Discussion Conclusion and Outlookmentioning

confidence: 85%

Assessment and tuning of data assimilation systems using passive observations

Marseille

Barkmeijer

Haan

et al. 2016

Quart J Royal Meteoro Soc

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“…The physics package used in the model uses Modular, Multi-scale, Microphysics and Transport (3MT) structure (Gerard et al, 2009). Initial conditions for the model are provided by atmospheric analysis with 3-hourly threedimensional variational assimilation (3D-Var) (Fischer et al, 2005;Strajnar et al, 2015) and optimal interpolation for surface and soil variables. Most of the conventional and satellite observations are assimilated, including surface stations (Synop) and ship reports, radiosondes, Automated Meteorological Data Relay (AMDAR), atmospheric motion vectors (AMV), Advanced Microwave Sounding Unit (AMSU)-A and -B, Metop-A and -B polar orbiters and water vapor channels from the geostationary Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager (SE-VIRI).…”

Section: Introductionmentioning

confidence: 99%

Modeling the ocean and atmosphere during an extreme bora event in northern Adriatic using one-way and two-way atmosphere–ocean coupling

et al. 2016

Self Cite

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Abstract.We have studied the performances of (a) a two-way coupled atmosphere-ocean modeling system and (b) one-way coupled ocean model (forced by the atmosphere model), as compared to the available in situ measurements during and after a strong Adriatic bora wind event in February 2012, which led to extreme air-sea interactions. The simulations span the period between January and March 2012. The models used were ALADIN (Aire Limitée Adaptation dynamique Développement InterNational) (4.4 km resolution) on the atmosphere side and an Adriatic setup of Princeton ocean model (POM) (1 • /30 × 1 • /30 angular resolution) on the ocean side. The atmosphere-ocean coupling was implemented using the OASIS3-MCT model coupling toolkit. Two-way coupling ocean feedback to the atmosphere is limited to sea surface temperature. We have compared modeled atmosphere-ocean fluxes and sea temperatures from both setups to platform and CTD (conductivity, temperature, and depth) measurements from three locations in the northern Adriatic. We present objective verification of 2 m atmosphere temperature forecasts using mean bias and standard deviation of errors scores from 23 meteorological stations in the eastern part of Italy. We show that turbulent fluxes from both setups differ up to 20 % during the bora but not significantly before and after the event. When compared to observations, two-way coupling ocean temperatures exhibit a 4 times lower root mean square error (RMSE) than those from one-way coupled system. Two-way coupling improves sensible heat fluxes at all stations but does not improve latent heat loss. The spatial average of the two-way coupled atmosphere component is up to 0.3 • C colder than the one-way coupled setup, which is an improvement for prognostic lead times up to 20 h. Daily spatial average of the standard deviation of air temperature errors shows 0.15 • C improvement in the case of coupled system compared to the uncoupled. Coupled and uncoupled circulations in the northern Adriatic are predominantly wind-driven and show no significant mesoscale differences.

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“…Strajnar et al (, fig. ) showed that meteorological routine air reports (MRAR) of ambient temperature, obtained from the secondary surveillance radar (SSR) using Mode‐S, centred around Ljubljana airport, Slovenia, have a spatial and temporal resolution sufficient to locate a temperature inversion at around 1,000 m above the surface.…”

Section: Introductionmentioning

confidence: 99%

Towards operational use of aircraft‐derived observations: a case study at London Heathrow airport

Mirza

Ballard

Dance

et al. 2019

Meteorological Applications

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Mode‐Selective Enhanced Surveillance (Mode‐S EHS) aircraft reports can be collected at a low cost and are readily available around busy airports. The new work presented here demonstrates that observations derived from Mode‐S EHS reports can be used to study the evolution of temperature inversions since the data have a high spatial and temporal frequency. This is illustrated by a case study centred around London Heathrow airport for the period January 4–5, 2015. Using Mode‐S EHS reports from multiple aircraft and after applying quality control criteria, vertical temperature profiles are constructed by aggregating these reports at discrete intervals between the surface and 3,000 m. To improve these derived temperatures, four smoothing methods using low‐pass filters are evaluated. The effect of smoothing reduces the variance in the aircraft derived temperature by approximately half. After smoothing, the temperature variance between the altitudes 3,000 and 1,000 m is 1–2 K; below 1,000 m, it is 2–4 K. Although the differences between the four smoothing methods are small, exponential smoothing is favoured because it uses all available Mode‐S EHS reports. The resulting vertical profiles may be useful in operational meteorology for identifying elevated temperature inversions above 1,000 m. However, below 1,000 m they are less useful because of the reduced precision of the reported Mach number. A better source of in situ temperature observations would be for aircraft to use the meteorological reporting function of their automatic dependent surveillance system.

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Impact of new aircraft observations Mode‐S MRAR in a mesoscale NWP model

Cited by 23 publications

References 29 publications

Assessment and tuning of data assimilation systems using passive observations

Assessment and tuning of data assimilation systems using passive observations

Modeling the ocean and atmosphere during an extreme bora event in northern Adriatic using one-way and two-way atmosphere–ocean coupling

Towards operational use of aircraft‐derived observations: a case study at London Heathrow airport

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