DataExpo GAKG DeepReport Navigation

Copyright©2015-2024 Acemap, Inc. Shanghai Jiao Tong University. All rights reserved.

沪ICP备18028330号

GD

Giovanna De Chiara

European Centre for Medium-Range Weather Forecasts

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Ad Stoffelen

Royal Netherlands Meteorological Institute

Marcos Portabella

Institut de Ciències del Mar

Wenming Lin

Nanjing University of Information Science and Technology

J. Vogelzang

Royal Netherlands Meteorological Institute

Anton Verhoef

Royal Netherlands Meteorological Institute

Massimo Bonavita

European Centre for Medium-Range Weather Forecasts

S. B. Healy

European Centre for Medium-Range Weather Forecasts

Raffaele Crapolicchio

European Space Research Institute

Linus Magnusson

European Centre for Medium-Range Weather Forecasts

Patricia de Rosnay

European Centre for Medium-Range Weather Forecasts

Cooperative Institutions

European Centre for Medium-Range Weather Forecasts

Centre National de la Recherche Scientifique

Met Office

NSF National Center for Atmospheric Research

Météo-France

Royal Netherlands Meteorological Institute

University of Reading

Centre National de Recherches Météorologiques

Scripps Institution of Oceanography

National Oceanic and Atmospheric Administration

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

Estimating Random Errors of Scatterometer, Altimeter, and Model Wind Speed Data

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2017)

Saleh Abdalla Giovanna De Chiara

Scatterometer and altimeter wind data are very important for data assimilation and verification of numerical weather prediction models. Standard deviation of absolute random errors can be estimated using the triple collocation technique. However, error correlations between various wind sources (e.g., due to data assimilation) complicate the error estimation. A method is used to alleviate the impact of error correlations between the scatterometer and the model that assimilates such data. Using twenty-two datasets of triplet composed of Jason-2 altimeter, Metop-A/B scatterometers (ASCAT-A/B, respectively), and ECMWF model analysis and forecasts (1 altimeter × 2 scatterometers × 11 model analysis and forecasts = 22 datasets) covering a period of two years from August 2013 to July 2015, the correlation coefficient between the errors of scatterometers and the model analysis was found to be about 0.33 for those datasets. This correlation reduces with forecast lead time until it almost vanishes at day seven. Altimeter and scatterometer errors are not correlated. The standard deviation of wind speed random errors of Jason-2, ASCAT-A/B, and the IFS analysis are estimated as 0.7, 0.8, and 0.9 m/s, respectively. As expected, there was no difference between ASCAT-A and ASCAT-B results.

Scatterometer

Collocation (remote sensing)

10.1109/jstars.2017.2659220

Cite

Citations (18)

The role of observations in ECMWF tropical cyclone initialisation and forecasting

Quarterly Journal of the Royal Meteorological Society (2025)

Linus Magnusson Sharanya J. Majumdar Mohamed Dahoui Niels Bormann Massimo Bonavita

Abstract In a unique undertaking, 13 Observing System Experiments (OSEs) were conducted at the European Centre for Medium‐range Weather Forecasts (ECMWF) during a 37‐day period in August–September 2020, using the same 9‐km resolution as the operational data assimilation. These OSEs provided a unified framework to evaluate and understand the role of different types of observational data for tropical cyclone (TC) forecasts, keeping in mind that removing or adding individual types is expected to have a limited effect due to resilience in the full observation system. The strongest impact came from withholding of microwave radiance observations, which on average degraded the TC position for all evaluated lead times and central‐pressure forecasts out to three days, with some further improvement from all‐sky assimilation of Advanced Microwave Sounding Unit (AMSU‐A) temperature sounders to the TC position forecasts. Scatterometer data improved the forecasts of both quantities, with further improvements from reduced spatial thinning. The impact for other satellite data such as Global Navigation Satellite System (GNSS)‐RO, atmospheric motion vectors (AMVs) and Aeolus were mixed/neutral. While the aircraft‐borne data (dropsonde, flight‐level data) were mostly beneficial, further investigations on how to best use this data in the TC core are needed. The assimilation of interpolated hourly central pressure and position data estimated by forecasters had an overall positive impact on both position and central pressure. While this study has illustrated the difficulties in obtaining strong results for observation impact on TCs for an operational data assimilation system, including new observations and improvements to the use of existing ones are necessary to keep improving the accumulated positive effect from the observation system. Additionally, future work is needed to advance diagnostic tools to judge the impact of individual observation systems on TCs.

10.1002/qj.4924

Cite

Citations (0)

Verification and Error Estimation of Altimeter and Scatterometer Surface Wind Speed

Giovanna De Chiara Saleh Abdalla

Scatterometer

Error Analysis

Radar altimeter

Cite

Citations (0)

Assessment of new ASCAT wind products for assimilation in global NWP

Giovanna De Chiara Wenming Lin Marcos Portabella Ad Stoffelen

European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteorological Satellite Conference, 17-21 September 2018, Tallinn, Estonia

Assimilation (phonology)

Cite

Citations (0)

Scientific Developments and the EPS-SG Scatterometer

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2017)

Ad Stoffelen Signe Aaboe Jean‐Christophe Calvet James Cotton Giovanna De Chiara

The second-generation exploitation of meteorological satellite polar system (EPS-SG) C-band-wavelength scatterometer instrument (called SCA), planned for launch in 2022, has a direct heritage from the successful advanced scatterometer (ASCAT) flown on the current EPS satellites. In addition, SCA will represent three major innovations with respect to ASCAT, namely: 1) Cross polarization and horizontal copolarization; 2) a nominal spatial resolution of 25 km; and 3) 20% greater spatial coverage than ASCAT. The associated expected science and application benefits that led the SCA design are discussed with respect to ocean, land, and sea ice applications for near-real time, climate monitoring, and research purposes. Moreover, an option to implement an ocean Doppler capability to retrieve the ocean motion vector is briefly discussed as well. In conclusion, the SCA instrument innovations are well set to provide timely benefits in all the main application areas of the scatterometer (winds, soil moisture, sea ice) and can be expected to contribute to new and more sophisticated meteorological, oceanographic, land, sea ice, and climate services in the forthcoming SCA era.

Scatterometer

10.1109/jstars.2017.2696424

Cite

Citations (42)

Towards a new ASCAT wind product for assimilation in global NWP

Marcos Portabella Wenming Lin Ad Stoffelen Giovanna De Chiara

European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteorological Satellite Conference, 2-6 October 2017, Rome, Italy

Assimilation (phonology)

Cite

Citations (0)

Evaluation of ASCAT superobbing products for NWP data assimilation

Giovanna De Chiara Wenming Lin Marcos Portabella J. Vogelzang Lars Isaksen

International Ocean Vector Winds Science Team Meeting (IOVWST), 29-31 May 2019, Portland, Maine

Assimilation (phonology)

Cite

Citations (1)

Towards an improved assimilation of ASCAT-derived winds into global NWP：Input preparation

Wenming Lin Giovanna De Chiara Marcos Portabella Ad Stoffelen J. Vogelzang

International Ocean Vector Winds Science Team Meeting (2016 IOVWST), 17-19 May 2016, Sapporo.-- 23 pages

Assimilation (phonology)

Cite

Citations (0)

Using spatial wind information in NWP data assimilation

Ad Stoffelen Giovanna De Chiara Wenming Lin Marcos Portabella J. Vogelzang

Assimilation (phonology)

Cite

Citations (0)

Towards an improved assimilation of ASCAT winds

Wenming Lin Giovanna De Chiara Marcos Portabella Ad Stoffelen J. Vogelzang

Assimilation (phonology)

Cite

Citations (0)