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

BALTIC+ Theme 3 Baltic+ SEAL (Sea Level) Product Handbook

This handbook is designed to support both novice and more advanced users. It is a reference guide for users of the ESA Baltic SEAL suite of products. It provides fundamental information on the theory underpinning the products, and the technical specifications of the data you can access. It also provides links to the more in-depth literature and information on the theory and technical aspects of the product you are using. Newcomers to satellite altimetry data can find basic information on altimetry, and how to interpret and understand the data files you have obtained. There are also helpful basic codes to display and explore your newly acquired data. For more expert users, the overview information is presented here, with more technical, and in-depth information available in the referenced literature

Comparison of sea-ice freeboard distributions from aircraft data and cryosat-2

The only remote sensing technique capable of obtain- ing sea-ice thickness on basin-scale are satellite altime- ter missions, such as the 2010 launched CryoSat-2. It is equipped with a Ku-Band radar altimeter, which mea- sures the height of the ice surface above the sea level. This method requires highly accurate range measure- ments. During the CryoSat Validation Experiment (Cry- oVEx) 2011 in the Lincoln Sea, Cryosat-2 underpasses were accomplished with two aircraft, which carried an airborne laser-scanner, a radar altimeter and an electro- magnetic induction device for direct sea-ice thickness re- trieval. Both aircraft flew in close formation at the same time of a CryoSat-2 overpass. This is a study about the comparison of the sea-ice freeboard and thickness dis- tribution of airborne validation and CryoSat-2 measure- ments within the multi-year sea-ice region of the Lincoln Sea in spring, with respect to the penetration of the Ku- Band signal into the snow

The optimal coastal retracked sea levels from saral/altika satellite altimetry over the southeast asia

The current demand for accurate coastal altimetry data, particularly for the sea level has increased since human activities have become increasingly concentrated along coastal areas. Over coastal region, particularly within 10 km from the coastline, the altimeter footprint is severely contaminated by land and rough coastal sea states. The contamination leads to the low quality observations, thus creating a significant gap in data availability over the coast. The aim of this study is to evaluate the quality of coastal retracked sea level data from AltiKa satellite altimetry over the Southeast Asia region. In this study, high resolution (40 Hz) sea levels derived from the advanced AltiKa satellite altimetry are validated over the Southeast Asia coastal regions. The parameter of sea level is derived based on three standard retracking algorithms which are MLE-4, Ice-1 and Ice-2. The assessments of quantity and quality of the retracked sea levels data are conducted to identify the optimum retracker over the study regions, which are Andaman Sea, Strait of Malacca, South China Sea, Gulf of Thailand and Sulu Sea. The quantitative analysis involves the comparison between AltiKa and Jason-2 waveforms, the computation of percentage of data availability, and the minimum distance of Sea Level Anomaly (SLA) to the coastline. The qualitative analysis involves the relative validation with geoid height and absolute validation with tide gauge. In general, AltiKa measurement can obtain as close as 1 km to the coastline with =85% data availability. The Ice-1 retracker has shown an excellent performance with percentage of data availability at =90% and minimum distance as close as 0.9 km to the coastline. In term of quality, Ice-1 retracker shows the highest improvement of percentage (IMP) values over Andaman Sea, Sulu Sea and Strait of Malacca with IMPs of 19%, 16% and 43%, respectively. The Ice-1 retracker also shows the highest temporal correlation (up to 0.95) and the lowest root mean square (RMS) error up to 8 cm over distance less than 10 km for those three regions. Contrary, over the South China Sea, Ice-2 retracker has better performance when compared to other retrackers with IMP values of 43%. Over distance less than 10 km to the shore, the temporal correlation and RMS error reach up to 0.88 and 7 cm respectively. Over the Gulf of Thailand, the optimum retracker cannot be concluded due to unavailable tide gauge data. The Ice-1 is the optimum retracker over three out of four regions. Therefore, it is used to study the seasonal variability of sea levels over the Southeast Asia. The seasonal variability shows that the mean amplitude is up to 25 cm during the Northeast Monsoon and decreased by 9 cm during the Southwest Monsoon and between 2 to 9 cm during inter-monsoon seasons. In conclusion, the research has significantly contributed in defining the quantity and quality of the AltiKa SLAs in the coastal region of Southeast Asia. The results from comprehensive validation obtained in this research present a significant improvement in identifying the reliability and applicability of the AltiKa datasets and retracking algorithms over the coastal area of the study region

Parameter estimation for peaky altimetric waveforms

Much attention has been recently devoted to the analysis of coastal altimetric waveforms. When approaching the coast, altimetric waveforms are sometimes corrupted by peaks caused by high reflective areas inside the illuminated land surfaces or by the modification of the sea state close to the shoreline. This paper introduces a new parametric model for these peaky altimetric waveforms. This model assumes that the received altimetric waveform is the sum of a Brown echo and an asymmetric Gaussian peak. The asymmetric Gaussian peak is parameterized by a location, an amplitude, a width, and an asymmetry coefficient. A maximum-likelihood estimator is studied to estimate the Brown plus peak model parameters. The Cramér–Rao lower bounds of the model parameters are then derived providing minimum variances for any unbiased estimator, i.e., a reference in terms of estimation error. The performance of the proposed model and the resulting estimation strategy are evaluated via many simulations conducted on synthetic and real data. Results obtained in this paper show that the proposed model can be used to retrack efficiently standard oceanic Brown echoes as well as coastal echoes corrupted by symmetric or asymmetric Gaussian peaks. Thus, the Brown with Gaussian peak model is useful for analyzing altimetric easurements closer to the coast

Controls on satellite altimetry over inland water surfaces for hydrological purposes

The global available and freely accessible in situ measurements of hydrological cycles is unsatisfactory, limited and has been on the decline, lately. This together with large modeling error for hydrological cycles, support the efforts to seek for alternative measuring techniques. In the recent past, satellite altimetry has been used to measure non-ocean water level variations for hydrological purposes. Due to the effect of topography and heterogeneity of reflecting surface and atmospheric propagation, the expected echo shape for altimeter returns over land differs from that over ocean surfaces. As a result, altimetry measurements over inland waters are erroneous and include missing data. In the present study, we have developed an algorithm to improve the quality of water level time series over non-ocean surfaces. This algorithm contains an outlier identification and elimination process, an algorithm for excluding the noisy waveforms, an unsupervised classification of the satellite waveforms and finally a retracking procedure. The two preliminary steps of outlier identification and noisy waveforms exclusion allow to achieve better results for further classification and retracking steps. We have employed data snooping algorithm to identify and eliminate outliers in the water level time series. Further, an algorithm based on comparing each waveform with fitted waveform from 5β algorithm is developed to identify the noisy waveforms. An unsupervised classification algorithm is implemented to classify the waveforms into consistent groups, for which the appropriate retracking algorithms are performed. The classification algorithm is based on computing the heterogeneity of data sets, which is computed through the difference between median and modal waveforms. We have employed the algorithm to improve the water level time series in Balaton (Hungary) and Urmia (Iran) lakes. After then, we validated the results of proposed algorithm against the available in situ measurements.In letzter Zeit ist die global verfügbare und frei zugängliche in situ-Messungen von hydrologischen Zyklen unbefriedigend, beschränkt und rückgängig geworden. Dies zusammen mit großen Modellierungsfehler der hydrologischen Zyklen unterstützen die Suche nach alternativen Messverfahren. In der jüngsten Vergangenheit hat die Satellitenaltimetrie verwendet worden, um die Variationen des kontinentalen Wasserstands für hydrologische Zwecke zu messen. Aufgrund der Wirkung der Topographie und der Heterogenität der reflektierenden Oberfläche und atmosphärische Ausbreitung unterscheidet sich die erwartete Echoform des Höhenmessers über das Land vom Echoform über die Ozeanoberflächen. In der vorliegenden Arbeit haben wir einen Algorithmus entwickelt, um die Qualität der Wasserstandszeitreihen über die kontinentale Oberflächen zu verbessern. Dieser Algorithmus enthält: • eine Ausreißer-Identifikation und einen Beseitigungsprozess • einen Algorithmus zum Ausschluss der gestörten Echoform • eine unüberwachten Klassifizierung der Echoform • ein „retracking“ Verfahren Die vorbereitende Schritte zur Ermittlung von Ausreißern und verrauschten Echoformen ermöglichen bessere Ergebnisse zur weiteren Klassifizierung und retracking Schritte. Wir haben Daten-Snooping-Algorithmus zur Identifizierung und Beseitigung von Ausreißern in der Wasserstand Zeitreihen verwendet. Um die verrauschten Echoformen zu identifizieren ist ein Algorithmus entwickelt, der sich auf den Vergleich jeder Echoform mit gepasster Echoform aus 5β-Algorithmus basiert. Ein überwachten Klassifizierungsalgorithmus ist implementiert, um die Echoformen in kohärente Gruppen zu klassifizieren. Für jede kohärente Gruppe ist ein entsprechender retracking-Algorithmus durchgeführt worden. Die Klassifizierung Algorithmus basiert sich auf der Berechnung der Heterogenität der Datensätze, die durch die Differenz zwischen Median und Modal-Echoformen berechnet wird. Wir haben diese Algorithmen verwendet, um die Wasserstandszeitreihen im Balaton (Ungarn) und Urmia (Iran) Seen zu verbessern. Danach haben wir die Ergebnisse der vorgeschlagenen Algorithmen gegen lokalen Daten geprüft