Improving the altimetric rain record from Jason-1 & Jason-2

Dual-frequency rain-flagging has long been a standard part of altimetric data analysis, both for quality control of the data and for the study of rain itself, because altimeters can provide a finer spatial sampling of rain than can passive microwave instruments. However, there have been many varied implementations, using different records of the surface backscatter and different thresholds. This paper compares four different measures available for the recently-launched Jason-2. The evaluation compares these measures against clearly desired properties, finding that in most cases the adjusted backscatter and that from the ice retracker perform much better than that recommended in the users' handbook. The adjusted backscatter measure also provides a much better link to observations from Jason-1, opening up a much longer period for consistent rain investigations, and enabling greatly improved analysis of the short-scale variability of precipitation. Initial analysis shows that although the spatial and temporal gradients of backscatter increase at very low winds, the spatial gradients in rain attenuation are concentrated where rainfall is greatest, whilst the temporal changes have a simple broad latitudinal pattern

Optimal estimation of sea surface temperature from AMSR-E

The Optimal Estimation (OE) technique is developed within the European Space Agency Climate Change Initiative (ESA-CCI) to retrieve subskin Sea Surface Temperature (SST) from AQUA’s Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E). A comprehensive matchup database with drifting buoy observations is used to develop and test the OE setup. It is shown that it is essential to update the first guess atmospheric and oceanic state variables and to perform several iterations to reach an optimal retrieval. The optimal number of iterations is typically three to four in the current setup. In addition, updating the forward model, using a multivariate regression model is shown to improve the capability of the forward model to reproduce the observations. The average sensitivity of the OE retrieval is 0.5 and shows a latitudinal dependency with smaller sensitivity for cold waters and larger sensitivity for warmer waters. The OE SSTs are evaluated against drifting buoy measurements during 2010. The results show an average difference of 0.02 K with a standard deviation of 0.47 K when considering the 64% matchups, where the simulated and observed brightness temperatures are most consistent. The corresponding mean uncertainty is estimated to 0.48 K including the in situ and sampling uncertainties. An independent validation against Argo observations from 2009 to 2011 shows an average difference of 0.01 K, a standard deviation of 0.50 K and a mean uncertainty of 0.47 K, when considering the best 62% of retrievals. The satellite versus in situ discrepancies are highest in the dynamic oceanic regions due to the large satellite footprint size and the associated sampling effects. Uncertainty estimates are available for all retrievals and have been validated to be accurate. They can thus be used to obtain very good retrieval results. In general, the results from the OE retrieval are very encouraging and demonstrate that passive microwave observations provide a valuable alternative to infrared satellite observations for retrieving SST

An Improved Ocean Vector Winds Retrieval Approach Using C- And Ku-band Scatterometer And Multi-frequency Microwave Radiometer Measurements

This dissertation will specifically address the issue of improving the quality of satellite scatterometer retrieved ocean surface vector winds (OVW), especially in the presence of strong rain associated with tropical cyclones. A novel active/passive OVW retrieval algorithm is developed that corrects Ku-band scatterometer measurements for rain effects and then uses them to retrieve accurate OVW. The rain correction procedure makes use of independent information available from collocated multi-frequency passive microwave observations provided by a companion sensor and also from simultaneous C-band scatterometer measurements. The synergy of these active and passive measurements enables improved correction for rain effects, which enhances the utility of Ku-band scatterometer measurements in extreme wind events. The OVW retrieval algorithm is based on the next generation instrument conceptual design for future US scatterometers, i.e. the Dual Frequency Scatterometer (DFS) developed by NASA’s Jet Propulsion Laboratory. Under this dissertation research, an end-to-end computer simulation was developed to evaluate the performance of this active/passive technique for retrieving hurricane force winds in the presence of intense rain. High-resolution hurricane wind and precipitation fields were simulated for several scenes of Hurricane Isabel in 2003 using the Weather Research and Forecasting (WRF) Model. Using these numerical weather model environmental fields, active/passive measurements were simulated for instruments proposed for the Global Change Observation Mission- Water Cycle (GCOM-W2) satellite series planned by the Japanese Aerospace Exploration Agency. Further, the quality of the simulation was evaluated using actual hurricane measurements from the Advanced Microwave Scanning Radiometer and iv SeaWinds scatterometer onboard the Advanced Earth Observing Satellite-II (ADEOS-II). The analysis of these satellite data provided confidence in the capability of the simulation to generate realistic active/passive measurements at the top of the atmosphere. Results are very encouraging, and they show that the new algorithm can retrieve accurate ocean surface wind speeds in realistic hurricane conditions using the rain corrected Ku-band scatterometer measurements. They demonstrate the potential to improve wind measurements in extreme wind events for future wind scatterometry missions such as the proposed GCOM-W2

Selection of the key earth observation sensors and platforms focusing on applications for Polar Regions in the scope of Copernicus system 2020-2030

An optimal payload selection conducted in the frame of the H2020 ONION project (id 687490) is presented based on the ability to cover the observation needs of the Copernicus system in the time period 2020–2030. Payload selection is constrained by the variables that can be measured, the power consumption, and weight of the instrument, and the required accuracy and spatial resolution (horizontal or vertical). It involved 20 measurements with observation gaps according to the user requirements that were detected in the top 10 use cases in the scope of Copernicus space infrastructure, 9 potential applied technologies, and 39 available commercial platforms. Additional Earth Observation (EO) infrastructures are proposed to reduce measurements gaps, based on a weighting system that assigned high relevance for measurements associated to Marine for Weather Forecast over Polar Regions. This study concludes with a rank and mapping of the potential technologies and the suitable commercial platforms to cover most of the requirements of the top ten use cases, analyzing the Marine for Weather Forecast, Sea Ice Monitoring, Fishing Pressure, and Agriculture and Forestry: Hydric stress as the priority use cases.Peer ReviewedPostprint (published version

Gaps analysis and requirements specification for the evolution of Copernicus system for polar regions monitoring: addressing the challenges in the horizon 2020-2030

This work was developed as part of the European H2020 ONION (Operational Network of Individual Observation Nodes) project, aiming at identifying the technological opportunity areas to complement the Copernicus space infrastructure in the horizon 2020–2030 for polar region monitoring. The European Earth Observation (EO) infrastructure is assessed through of comprehensive end-user need and data gap analysis. This review was based on the top 10 use cases, identifying 20 measurements with gaps and 13 potential EO technologies to cover the identified gaps. It was found that the top priority is the observation of polar regions to support sustainable and safe commercial activities and the preservation of the environment. Additionally, an analysis of the technological limitations based on measurement requirements was performed. Finally, this analysis was used for the basis of the architecture design of a potential polar mission.Peer ReviewedPostprint (published version

Ocean surface currents reconstruction from microwave radiometers measurements

Premi Extraordinari de Doctorat, promoció 2014-2015. Àmbit d'Enginyeria de les TICOcean currents are a key component to understanding many oceanic and climatic phenomena and knowledge of them is crucial for both navigation and operational applications. Therefore, a key problem in oceanography is the estimation of the synoptic velocity field. Currently, global ocean surface velocities are routinely estimated from Sea Surface Height (SSH) measurements provided by altimeters. However, the separation between passes, as well as and the limited number of available altimeters leads to errors in the accurate location of oceanic currents when these measurements are used exclusively. Contrarily, satellite images of Sea Surface Temperature (SST) provide a good qualitative view of the location of ocean patterns, which has encouraged the investigation of alternative methodologies to reconstruct the velocity field based on these observations. This Ph.D. thesis has assessed the capability of SST microwave radiometers observations to retrieve ocean surface currents. The reconstruction of the ocean surface currents from SST observations can be expressed in terms of a transfer function notation, that allows to convert SST maps into SSH, and thus into currents. Because under geostrophic balance, the slope of SSH is proportional to ocean surface currents. This transfer function can be theoretically derived using the Surface Quasi-Geostrophic equations (SQG). Two different approaches were analyzed at a global scale: on one side, the analysis of the validity of the SQG approach has been performed, and on the other, an approach based on the synergetic properties between simultaneous SST and SSH observations has been analyzed. Both approaches have been compared with ocean surface currents retrieved from merged altimetric observations. The study has been focused on the period from October 2002 to May 2005, since during that period there were available four different altimeters, and the quality of the merged altimetric observations was enhanced. The analysis of the validity of SQG at a global scale revealed that this dynamical model is valid near the major extratropic current system such us the Gulf Stream, the Antartic Circumpolar Current, Kuroshio currents. Besides, the potential of MW SST observations to reconstruct ocean surface currents was analyzed using a synergetic approach: the combination of the SST phase with the SSH spectra. Actually, we explored under which environmental conditions the phase of the MW SST is close to the SSH phase. Results showed that the phase of the MW SST can be used to retrieve ocean currents during winter, near the major extratropical current systems, which are characterized by an intense mesoscale activity and the presence of strong thermal gradients, and deep ML. Furthermore, the reconstruction of the velocity fields from an ideal transfer function built up from simultaneous SST and SSH observations revealed that the SQG approach can be enhanced. The spectral properties of this ideal transfer function derived from simultaneous SST and SSH observations were characterized at a global scale. The analysis of spectral properties of the transfer function between SST and SSH observations revealed that despite daily spectral can be flatter or steeper than the k^{-1} predicted by SQG theory, in mean eSQG is a good statistically approach to retrieve ocean currents, when no simultaneous observations of SSH and SST are available.Las corrientes oceánicas son clave en muchos procesos oceánicos y climáticos, y su conocimiento es crucial para aplicaciones operacionales y de navegación. Por lo tanto, un aspecto importante en oceanografía es la estimación de campos sinópticos del campo de velocidades superficiales del mar. Actualmente, las velocidades superficiales el mar se estiman rutinariamente a partir de medidas del nivel del mar proporcionadas por altimetros, denotadas a partir de ahora con sus siglas en inglés SSH. Sin embargo, la llocalización de las corrientes puede no ser la correcta si solo se utilizan este tipo de medidas para su estimación, debido a la separación entre trazas del satélite. Por contra, las imágenes de temperatura superficial del mar, SST, proporiconan una visión cualitativa de la localización de las estructruas oceánicas. Este hecho ha motivado la investigación de metodologías alternativas para reconstruir los campos de velocidades superficiales del mar basados en estas observaciones. Esta tesis doctoral ha investigado la capacidad de las observaciones de SST proporcionadas por radiometros de microondas para recuperar las corrientes oceánicas superficiales. La reconstrucción de estas velocidades a partir de observaciones de SST se puede expresar en términos de una función de transferencia que relacione las observaciones de SST con las observaciones de SSH. Con lo que la estimación del campo de velocidades es directa, puesto que bajo la condición de equilibrio geostrófico la pendiente de la SSH es proporcional a las corrientes oceánicas. Esta función de transferencia se puede derivar teóricamente mediante las equaciones superficiales cuasi-geotróficas, denotadas con sus siglas en inglés SQG a partir de ahora. Una pregunta clave, es si las ecuaciones de este modelo dinámico son válidas. En esta tesis, se han llevado a cabo dos aproximaciones diferentes para la reconstrucción del campo de velocidades superficiales del mar: por un lado, el análisis de la validez de las ecuaciones SQG, y por otro, una aproximación basada en las propiedades espectrales de medidas simultáneas de SST y SSH. El estudio se ha centrado en el período comprendido entre Octubre del 2002 y Mayo del 2005, puesto que durante este período había disponibles hasta cuatro altmímetros, y consecuentemente la calidad de las observaciones es mayor. El análisis de la validez de SQG a escala global reveló que este modelo dinámico es válido en las regiones cerca de los sistemas de corrientes extratropicales, como la corriente del Golfo, la Corriente Circumpolar Antártica (ACC), o la Kuroshio. Además, el potencial de las observaciones de SST en el rango de las microondas para la recuperación del campo de velocidades superficiales del mar, ha sido analizado utilizando un método que combina la fase de la SST con el espectro de SSH. En realidad, se ha investigado bajo que condiciones la SST y SSH están en fase. Los resultados mostraron que la fase de la SST de microondas puede utilizarse para para la reconstrucción en invierno, cerca de los sistemas de corrientes extratropicales, caracterizados por una intensa actividad de mesoscala y la presencia de fuertes gradientes termales, así como de capas de mezcla profundas. Asimismo, la reconstrucción del campo de velocidades a partir de una función de transferencia ideal, construida a partir de imágenes simultaneas de SST y SSH, reveló que la aproximación SQG puede ser mejorada. Las propiedades espectrales de esta función de tranferencia ideal han sido estudiadas., así como su variabilidad temporal. Este análisis desveló que para escalas pequeñas y zonas enegéticas, la aproximación SQG es una buena aproximación, al menos, desde un punto de vista estádistico.Award-winningPostprint (published version

Evaluation of the Harmful Algal Bloom Mapping System (HABMapS) and Bulletin

The National Oceanic and Atmospheric Administration (NOAA) Harmful Algal Bloom (HAB) Mapping System and Bulletin provide a Web-based geographic information system (GIS) and an e-mail alert system that allow the detection, monitoring, and tracking of HABs in the Gulf of Mexico. NASA Earth Science data that potentially support HABMapS/Bulletin requirements include ocean color, sea surface temperature (SST), salinity, wind fields, precipitation, water surface elevation, and ocean currents. Modeling contributions include ocean circulation, wave/currents, along-shore current regimes, and chlorophyll modeling (coupled to imagery). The most immediately useful NASA contributions appear to be the 1-km Moderate Resolution Imaging Spectrometer (MODIS) chlorophyll and SST products and the (presently used) SeaWinds wind vector data. MODIS pigment concentration and SST data are sufficiently mature to replace imagery currently used in NOAA HAB applications. The large file size of MODIS data is an impediment to NOAA use and modified processing schemes would aid in NOAA adoption of these products for operational HAB forecasting

Inter-comparison and evaluation of Arctic sea ice type products

oai:publications.copernicus.org:tc102910Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. However, systematic inter-comparison and analysis for SITY products are lacking. This study analysed eight daily SITY products from five retrieval approaches covering the winters of 1999–2019, including purely radiometer-based (C3S-SITY), scatterometer-based (KNMI-SITY and IFREMER-SITY) and combined ones (OSISAF-SITY and Zhang-SITY). These SITY products were inter-compared against a weekly sea ice age product (i.e. NSIDC-SIA – National Snow and Ice Data Center sea ice age) and evaluated with five synthetic aperture radar (SAR) images. The average Arctic multiyear ice (MYI) extent difference between the SITY products and NSIDC-SIA varies from -1.32×106 to 0.49×106 km2. Among them, KNMI-SITY and Zhang-SITY in the QuikSCAT (QSCAT) period (2002–2009) agree best with NSIDC-SIA and perform the best, with the smallest bias of -0.001×106 km2 in first-year ice (FYI) extent and -0.02×106 km2 in MYI extent. In the Advanced Scatterometer (ASCAT) period (2007–2019), KNMI-SITY tends to overestimate MYI (especially in early winter), whereas Zhang-SITY and IFREMER-SITY tend to underestimate MYI. C3S-SITY performs well in some early winter cases but exhibits large temporal variabilities like OSISAF-SITY. Factors that could impact performances of the SITY products are analysed and summarized. (1) The Ku-band scatterometer generally performs better than the C-band scatterometer for SITY discrimination, while the latter sometimes identifies FYI more accurately, especially when surface scattering dominates the backscatter signature. (2) A simple combination of scatterometer and radiometer data is not always beneficial without further rules of priority. (3) The representativeness of training data and efficiency of classification are crucial for SITY classification. Spatial and temporal variation in characteristic training datasets should be well accounted for in the SITY method. (4) Post-processing corrections play important roles and should be considered with caution.</p

Retrieval of Wintertime Sea Ice Production in Arctic Polynyas Using Thermal Infrared and Passive Microwave Remote Sensing Data

Precise knowledge of wintertime sea ice production in Arctic polynyas is not only required to enhance our understanding of atmosphere‐sea ice‐ocean interactions but also to verify frequently utilized climate and ocean models. Here, a high‐resolution (2‐km) Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared satellite data set featuring spatial and temporal characteristics of 17 Arctic polynya regions for the winter seasons 2002/2003 to 2017/2018 is directly compared to an akin low‐resolution Advanced Microwave Scanning Radiometer‐EOS (AMSR‐E) passive microwave data set for 2002/2003 to 2010/2011. The MODIS data set is purely based on a 1‐D energy‐balance model, where thin‐ice thicknesses (≤ 20 cm) are directly derived from ice‐surface temperature swath data and European Centre for Medium‐Range Weather Forecasts Re‐Analysis‐Interim atmospheric reanalysis data on a quasi‐daily basis. Thin‐ice thicknesses in the AMSR‐E data set are derived empirically. Important polynya properties such as areal extent and potential thermodynamic ice production can be estimated from both pan‐Arctic data sets. Although independently derived, our results show that both data sets feature quite similar spatial and temporal variations of polynya area (POLA) and ice production (IP), which suggests a high reliability. The average POLA (average accumulated IP) for all Arctic polynyas combined derived from both MODIS and AMSR‐E are 1.99×105 km2 (1.34×103 km3) and 2.29×105 km2 (1.31×103 km3), respectively. Narrow polynyas in areas such as the Canadian Arctic Archipelago are notably better resolved by MODIS. Analysis of 16 winter seasons provides an evaluation of long‐term trends in POLA and IP, revealing the significant increase of ice formation in polynyas along the Siberian coast