M. Joana Fernandes
University of Porto
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by M. Joana Fernandes.
Remote Sensing | 2014
M. Joana Fernandes; Clara Lázaro; Alexandra L. Nunes; Remko Scharroo
Originally designed for applications over the ocean, satellite altimetry has been proven to be a useful tool for hydrologic studies. Altimeter products, mainly conceived for oceanographic studies, often fail to provide atmospheric corrections suitable for inland water studies. The focus of this paper is the analysis of the main issues related with the atmospheric corrections that need to be applied to the altimeter range to get precise water level heights. Using the corrections provided on the Radar Altimeter Database System, the main errors present in the dry and wet tropospheric corrections and in the ionospheric correction of the various satellites are reported. It has been shown that the model-based tropospheric corrections are not modeled properly and in a consistent way in the various altimetric products. While over the ocean, the dry tropospheric correction (DTC) is one of the most precise range corrections, in some of the present altimeter products, it is the correction with the largest errors over continental water regions, causing large biases of several decimeters, and along-track interpolation errors up to several centimeters, both with small temporal variations. The wet tropospheric correction (WTC) from the on-board microwave radiometers is hampered by the contamination on the radiometer measurements of the surrounding lands, making it usable only in the central parts of large lakes. In addition, the WTC from atmospheric models may also have large errors when it is provided at sea level instead of surface height. These errors cannot be corrected by the user, since no accurate expression exists for the height variation of the WTC. Alternative and accurate corrections can be computed from in situ data, e.g., DTC from surface pressure at barometric stations and WTC from Global Navigation Satellite System permanent stations. The latter approach is particularly favorable for small lakes and reservoirs, where GNSS-derived WTC at a single location can be representative of the whole lake. For non-timely critical studies, for consistency and stability, model-derived tropospheric corrections from European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis ERA Interim, properly computed at surface height, are recommended. The instrument-based dual-frequency ionospheric correction may have errors related with the land contamination in the Ku and C/S bands, making it more suitable to use a model-based correction. The most suitable model-based ionospheric correction is the Jet Propulsion Laboratory (JPL) global ionosphere map (GIM) model, available after 1998, properly scaled to the altimeter height. Most altimeter products provide the GIM correction unreduced for the total electron content extending above the altitude of these satellites, thus overestimating the ionospheric correction by about 8%. Prior to 1998, the NIC09 (NOAA Ionosphere Climatology 2009) climatology provides the best accuracy.
IEEE Geoscience and Remote Sensing Letters | 2010
M. Joana Fernandes; Clara Lázaro; Alexandra L. Nunes; Nelson Pires; L. Bastos; Virgilio B Mendes
This letter presents an innovative method for computing the wet tropospheric correction for altimetry measurements in the coastal regions, where the measurements from the microwave radiometers (MWRs) onboard altimetric missions become invalid. The method, called Global Navigation Satellite System (GNSS)-derived Path Delay, gives an estimation of the correction, along with the associated mapping error, from the combination of independent zenith wet delay (ZWD) values obtained from the tropospheric delays derived at a network of coastal GNSS stations, from the MWR measurements acquired before land degradation, and from the European Centre for Medium-Range Weather Forecasts Deterministic Atmospheric Model. The wet tropospheric correction is estimated at each altimeter point with an invalid MWR value using a linear space-time objective analysis technique that takes into account the spatial and temporal variability of the ZWD field and the accuracy of each data set used. The method was applied in the South West European region for the whole Envisat data series, and the results are presented here. The uncertainty of the wet-delay estimates is below 1 cm, provided they are obtained for points at distances shorter than ~ 50 km from a GNSS station, and/or valid MWR measurements are available for the estimation. The method can be implemented globally and foster the use of satellite altimetry in coastal studies.
Remote Sensing | 2013
M. Joana Fernandes; Alexandra L. Nunes; Clara Lázaro
Unlike most altimetric missions, CryoSat-2 is not equipped with an onboard microwave radiometer (MWR) to provide wet tropospheric correction (WTC) to radar altimeter measurements, thus, relying on a model-based one provided by the European Center for Medium-range Weather Forecasts (ECMWF). In the ambit of ESA funded project CP4O, an improved WTC for CryoSat-2 data over ocean is under development, based on a data combination algorithm (DComb) through objective analysis of WTC values derived from all existing global-scale data types. The scope of this study is the analysis and inter-calibration of the large dataset of total column water vapor (TCWV) products from scanning MWR aboard Remote Sensing (RS) missions for use in the WTC computation for CryoSat-2. The main issues regarding the computation of the WTC from all TCWV products are discussed. The analysis of the orbital parameters of CryoSat-2 and all other considered RS missions, their sensor characteristics and inter-calibration is presented, providing an insight into the expected impact of these datasets on the WTC estimation. The most suitable approach for calculating the WTC from TCWV is investigated. For this type of application, after calibration with respect to an appropriate reference, two approaches were found to give very similar results, with root mean square differences of 2 mm.
Archive | 2011
Stefano Vignudelli; Paolo Cipollini; Christine Gommenginger; Scott Gleason; Helen M. Snaith; Henrique Coelho; M. Joana Fernandes; Clara Lázaro; Alexandra L. Nunes; Jesus Gomez-Enri; Cristina Martin-Puig; Philip L. Woodworth; Salvatore Dinardo; Jérôme Benveniste
In this chapter we review the history of coastal altimetry. We illustrate the challenges associated with data processing, improvement and exploitation, including: (1) what altimeter data are available today and what are the issues in coastal zones; (2) what efforts are underway to fill the gaps in coastal altimetry and what still needs to be done; (3) how coastal altimetry can be used in support of coastal oceanography. After nearly two decades of data collection near coasts, the planned reprocessing of the multi-mission global record now appears to be necessary for full exploitation of satellite altimetry for coastal oceanography. We will focus on the European research efforts, in particular the main outcomes of the COASTALT project, by showcasing improved corrections (with special emphasis on the wet tropospheric effect), waveform analysis and novel retracking techniques, as well as the structure of the new processor for Envisat RA-2 coastal records. This is of interest to a broad range of data integrators who will be able to use the improved altimeter data in their operational products or services.
Science of The Total Environment | 2017
Isabel Iglesias; M. Nieves Lorenzo; Clara Lázaro; M. Joana Fernandes; L. Bastos
Sea level anomaly (SLA), provided globally by satellite altimetry, is considered a valuable proxy for detecting long-term changes of the global ocean, as well as short-term and annual variations. In this manuscript, monthly sea level anomaly grids for the period 1993-2013 are used to characterise the North Atlantic Ocean variability at inter-annual timescales and its response to the North Atlantic main patterns of atmospheric circulation variability (North Atlantic Oscillation, Eastern Atlantic, Eastern Atlantic/Western Russia, Scandinavian and Polar/Eurasia) and main driven factors as sea level pressure, sea surface temperature and wind fields. SLA variability and long-term trends are analysed for the North Atlantic Ocean and several sub-regions (North, Baltic and Mediterranean and Black seas, Bay of Biscay extended to the west coast of the Iberian Peninsula, and the northern North Atlantic Ocean), depicting the SLA fluctuations at basin and sub-basin scales, aiming at representing the regions of maximum sea level variability. A significant correlation between SLA and the different phases of the teleconnection patterns due to the generated winds, sea level pressure and sea surface temperature anomalies, with a strong variability on temporal and spatial scales, has been identified. Long-term analysis reveals the existence of non-stationary inter-annual SLA fluctuations in terms of the temporal scale. Spectral density analysis has shown the existence of long-period signals in the SLA inter-annual component, with periods of ~10, 5, 4 and 2years, depending on the analysed sub-region. Also, a non-uniform increase in sea level since 1993 is identified for all sub-regions, with trend values between 2.05mm/year, for the Bay of Biscay region, and 3.98mm/year for the Baltic Sea (no GIA correction considered). The obtained results demonstrated a strong link between the atmospheric patterns and SLA, as well as strong long-period fluctuations of this variable in spatial and temporal scales.
Remote Sensing of Environment | 2005
Clara Lázaro; M. Joana Fernandes; A. Miguel P. Santos; Paulo B. Oliveira
Remote Sensing of Environment | 2015
M. Joana Fernandes; Clara Lázaro; Michael Ablain; Nelson Pires
Advances in Space Research | 2013
M. Joana Fernandes; Nelson Pires; Clara Lázaro; Alexandra L. Nunes
Earth System Science Data | 2017
Jean-François Legeais; Michael Ablain; Lionel Zawadzki; Hao Zuo; Johnny A. Johannessen; Martin G. Scharffenberg; Luciana Fenoglio-Marc; M. Joana Fernandes; Ole Baltazar Andersen; S Rudenko; Paolo Cipollini; Graham D. Quartly; M Passaro; Anny Cazenave; Jérôme Benveniste
Earth System Science Data | 2017
Graham D. Quartly; Jean-François Legeais; Michael Ablain; Lionel Zawadzki; M. Joana Fernandes; S Rudenko; Loren Carrère; P. N. Garcia; Paolo Cipollini; Ole Baltazar Andersen; Jean-Christophe Poisson; Sabrina Mbajon Njiche; Anny Cazenave; Jérôme Benveniste