Statistical analysis and combination of active and passive microwave remote sensing methods for soil moisture retrieval

Knowledge about soil moisture and its spatio-temporal dynamics is essential for the improvement of climate and hydrological modeling, including drought and flood monitoring and forecasting, as well as weather forecasting models. In recent years, several soil moisture products from active and passive microwave remote sensing have become available with high temporal resolution and global coverage. Thus, the validation and evaluation of spatial and temporal soil moisture patterns are of great interest, for improving soil moisture products as well as for their proper use in models or other applications. This thesis analyzes the different accuracy levels of global soil moisture products and identifies the major influencing factors on this accuracy based on a small catchment example. Furthermore, on global scale, structural differences betweenthe soil moisture products were investigated. This includes in particular the representation of spatial and temporal patterns, as well as a general scaling law of soil moisture variability with extent scale. The results of the catchment scale as well as the global scale analyses identified vegetation to have a high impact on the accuracy of remotely sensed soil moisture products. Therefore, an improved method to consider vegetation characteristics in pasive soil moisture retrieval from active radar satellite data was developed and tested. The knowledge gained by this thesis will contribute to improve soil moisture retrieval of current and future microwave remote sensors (e.g. SMOS or SMAP)

Statistical analysis and combination of active and passive microwave remote sensing methods for soil moisture retrieval

Knowledge about soil moisture and its spatio-temporal dynamics is essential for the improvement of climate and hydrological modeling, including drought and flood monitoring and forecasting, as well as weather forecasting models. In recent years, several soil moisture products from active and passive microwave remote sensing have become available with high temporal resolution and global coverage. However, for the improvement of a soil moisture product and for its proper use in models or other applications, validation and evaluation of its spatial and temporal patterns are of great importance. In chapter 2 the Level 2 Soil Moisture and Ocean Salinity (SMOS) soil moisture product and the Advanced Scatterometer (ASCAT) surface soil moisture product are validated in the Rur and Erft catchments in western Germany for the years 2010 to 2012 against a soil moisture reference created by a hydrological model, which was calibrated by in situ observations. Correlation with the modeled soil moisture reference results in an overall correlation coefficient of 0.28 for the SMOS product and 0.50 for ASCAT. While the correlation of both products with the reference is highly dependent ontopography and vegetation, SMOS is also strongly influenced by radiofrequency interferences in the study area. Both products exhibit dry biases as compared to the reference. The bias of the SMOS product is constant in time, while the ASCAT bias is more variable. For the investigation of spatio temporal soil moisture patterns in the study area, a new validation method based on the temporal stability analysis is developed. Through investigation of mean relative differences of soil moisture for every pixel the temporal persistence of spatial patterns is analyzed. Results indicate a lower temporal persistence for both SMOS and ASCAT soil moisture products as compared to modeled soil moisture. ASCAT soil moisture, converted to absolute values, shows highest consistence of ranks and therefore most similar spatio-temporal patterns with the soil moisture reference, while the correlation of ranks of mean relative differences is low for SMOS and relative ASCAT soil moisture products. Chapter 3 investigates the spatial and temporal behavior of the SMOS and ASCAT soil moisture products and additionally of the ERA Interim product from a weather forecast model reanalysis on global scale. Results show similar temporal patterns of the soil moisture products, but high impact of sensor and retrieval types and therefore higher deviations in absolute soil moisture values. Results are more variable for the spatial patterns of the soil moisture products: While the global patterns are similar, a ranking of mean relative differences reveals that ASCAT and ERA Interim products show most similar spatial soil moisture patterns, while ERA and SMOS products show least similarities. Patterns are generally more similar between the products in regions with low vegetation. [...

Half a century of satellite remote sensing of sea-surface temperature

Sea-surface temperature (SST) was one of the first ocean variables to be studied from earth observation satellites. Pioneering images from infrared scanning radiometers revealed the complexity of the surface temperature fields, but these were derived from radiance measurements at orbital heights and included the effects of the intervening atmosphere. Corrections for the effects of the atmosphere to make quantitative estimates of the SST became possible when radiometers with multiple infrared channels were deployed in 1979. At the same time, imaging microwave radiometers with SST capabilities were also flown. Since then, SST has been derived from infrared and microwave radiometers on polar orbiting satellites and from infrared radiometers on geostationary spacecraft. As the performances of satellite radiometers and SST retrieval algorithms improved, accurate, global, high resolution, frequently sampled SST fields became fundamental to many research and operational activities. Here we provide an overview of the physics of the derivation of SST and the history of the development of satellite instruments over half a century. As demonstrated accuracies increased, they stimulated scientific research into the oceans, the coupled ocean-atmosphere system and the climate. We provide brief overviews of the development of some applications, including the feasibility of generating Climate Data Records. We summarize the important role of the Group for High Resolution SST (GHRSST) in providing a forum for scientists and operational practitioners to discuss problems and results, and to help coordinate activities world-wide, including alignment of data formatting and protocols and research. The challenges of burgeoning data volumes, data distribution and analysis have benefited from simultaneous progress in computing power, high capacity storage, and communications over the Internet, so we summarize the development and current capabilities of data archives. We conclude with an outlook of developments anticipated in the next decade or so

Remote Sensing of Environmental Changes in Cold Regions

This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing

Snow observations from Arctic Ocean Soviet drifting stations: legacy and new directions

The Arctic Ocean is one of the most rapidly changing regions on the planet. Its warming climate has driven reductions in the region's sea ice cover which are likely unprecedented in recent history, with many of the environmental impacts being mediated by the overlying snow cover. As well as impacting energetic and material fluxes, the snow cover also obscures the underlying ice from direct satellite observation. While the radar waves emitted from satellite-mounted altimeters have some ability to penetrate snow cover, an understanding of snow geophysical properties remains critical to remote sensing of sea ice thickness. The paucity of Arctic Ocean snow observations was recently identified as a key knowledge gap and uncertainty by the Intergovernmental Panel on Climate Change's Special Report on Oceans and Cryosphere in a Changing Climate. This thesis aims to address that knowledge gap. Between 1937 and 1991 the Soviet Union operated a series of 31 crewed stations which drifted around the Arctic Ocean. During their operation, scientists took detailed observations of the atmospheric conditions, the physical oceanography, and the snow cover on the sea ice. This thesis contains four projects that feature these observations. The first two consider a well known snow depth and density climatology that was compiled from observations at the stations between 1954 & 1991. Specifically, Chapter two considers the role of seasonally evolving snow density in sea ice thickness retrievals, and Chapter three considers the impact of the climatological treatment itself on satellite estimates of sea ice thickness variability and trends. Chapter four presents a statistical model for the sub-kilometre distribution of snow depth on Arctic sea ice through analysis of snow depth transect data. Chapter five then compares the characteristics of snow melt onset at the stations with satellite observations and results from a recently developed model

Aquarius Sea Surface Salinity Gridding Method Based on Dual Quality–Distance Weighting

A new method for improving the accuracy of gridded sea surface salinity (SSS) fields is proposed in this paper. The method mainly focuses on dual quality–distance weighting of the Aquarius level 2 along-track SSS data according to quality flags, which represent nonnominal data conditions for measurements. In the weighting progress, 14 data conditions were considered, and their geospatial distributions and influences on the SSS were also visualized and evaluated. Three interpolation methods were employed, and weekly gridded SSS maps were produced for the period from September 2011 to May 2015. These maps were evaluated via comparisons with concurrent Argo buoy measurements. The results show that the proposed method improved the accuracy of the SSS fields by approximately 36% compared to the officially released weekly level 3 products and yielded root mean squared difference (RMSD), correlation and bias values of 0.19 psu, 0.98 and 0.01 psu, respectively. These findings indicate a significant improvement in the accuracy of the SSS fields and provide a better understanding of the influences of different conditions on salinity

Le niveau de la mer actuel : variations globale et régionales

Sea level is an integrated climate parameter that involves interactions of all components of the climate system (oceans, ice sheets, glaciers, atmosphere, and land water reservoirs) on a wide range of spatial and temporal scales. Over the 20th century, tide gauge records indicate a rise in global sea level between 1.6 mm/yr and 1.8 mm/yr. Since 1993, sea level variations have been measured precisely by satellite altimetry. They indicate a faster sea level rise of 3.3 mm/yr over 1993-2015. Owing to their global coverage, they also reveal a strong regional sea level variability that sometimes is several times greater than the global mean sea level rise. Considering the highly negative impact of sea level rise for society, monitoring sea level change and understanding its causes are henceforth high priorities.In this thesis, we first validate the sea level variations measured by the new satellite altimetry mission, SARAL-AltiKa by comparing the measurements with Jason-2 and tide gauge records. We then attempt to close the global mean sea level budget since 2003 and estimate the deep ocean contribution by making use of observational data from satellite altimetry, Argo profiles and GRACE mission. We show that uncertainties due to data processing approaches and systematic errors of different observing systems still prevent us from obtaining accurate results. In the second part of the thesis, by making use of past sea level reconstruction, we study the patterns of the regional sea level variability and estimate climate related (global mean plus regional component) sea level change over 1950-2009 at three vulnerable regions: Indian Ocean, South China and Caribbean Sea. For the sites where vertical crustal motion monitoring is available, we compute the total relative sea level (i.e. total sea level rise plus the local vertical crustal motion) since 1950. On comparing the results from these three regions with already existing results in tropical Pacific, we find that tropical Pacific displays the highest magnitude of sea level variations.In the last part of the thesis, we therefore focus on the tropical Pacific and analyze the respective roles of ocean dynamic processes, internal climate modes and external anthropogenic forcing on tropical Pacific sea level spatial trend patterns since 1993. Building up on the relationship between thermocline and sea level in the tropical region, we show that most of the observed sea level spatial trend pattern in the tropical Pacific can be explained by the wind driven vertical thermocline movement. By performing detection and attribution study on sea level spatial trend patterns in the tropical Pacific and attempting to eliminate signal corresponding to the main internal climate mode, we further show that the remaining residual sea level trend pattern does not correspond to externally forced anthropogenic sea level signal. In addition, we also suggest that satellite altimetry measurement may not still be accurate enough to detect the anthropogenic signal in the 20-year tropical Pacific sea level trends.Le niveau de la mer est une des variables climatiques essentielles dont la variabilité résulte de nombreuses interactions complexes entre toutes les composantes du système climatique sur une large gamme d'échelles spatiales et temporelles. Au cours du XXème siècle, les mesures marégraphiques ont permis d’estimer la hausse du niveau de la mer global entre 1,6 mm/an et 1,8 mm/an. Depuis 1993, les observations faites par les satellites altimétriques indiquent une hausse du niveau de la mer plus rapide de 3,3 mm/an. Grâce à leur couverture quasi-globale, elles révèlent aussi une forte variabilité du niveau de la mer à l’échelle régionale, parfois plusieurs fois supérieure à la moyenne globale du niveau de la mer. Compte tenu de l'impact très négatif de l’augmentation du niveau de la mer pour la société, sa surveillance, la compréhension de ses causes ainsi que sa prévision sont désormais considérées comme des priorités scientifiques et sociétales majeures.Dans cette thèse, nous validons d’abord les variations du niveau de la mer mesurées par la nouvelle mission d'altimétrie satellitaire, SARAL-AltiKa, en comparant les mesures avec celles de Jason-2 et des marégraphes. Un autre volet de cette première partie de thèse a consisté à estimer les parts respectives des facteurs responsables des variations du niveau de la mer depuis 2003 en utilisant des observations issues de l'altimétrie satellitaire (missions altimétrique Jason-1, Jason-2 et Envisat), de la mission GRACE, et des profils de température et salinité de l’océan par les flotteurs Argo. Une attention particulière est portée à la contribution de l’océan profond non ‘vue’ par Argo. Nous montrons que les incertitudes dues aux approches du traitement des données et aux erreurs systématiques des différents systèmes d'observation nous empêchent encore d'obtenir des résultats précis sur cette contribution.Dans la deuxième partie de la thèse, en utilisant les données de reconstruction du niveau de la mer dans le passé, nous étudions la variabilité régionale du niveau de la mer et estimons sa hausse totale (composante régionale plus moyenne globale) de 1950 à 2009 dans trois régions vulnérables : l’océan Indien, la mer de Chine méridionale et la mer des Caraïbes. Pour les sites où l’on dispose de mesures du mouvement de la croûte terrestre par GPS, nous évaluons la hausse locale du niveau de la mer relatif (hausse du niveau de la mer totale plus mouvement de la croûte locale) depuis 1950. En comparant les résultats de ces trois régions avec une étude précédente sur le Pacifique tropical, nous constatons que le Pacifique tropical présente la plus forte amplitude des variations du niveau de la mer sur la période d’étude.Dans la dernière partie de la thèse, nous nous concentrons par conséquent sur le Pacifique tropical. Nous analysons les rôles respectifs de la dynamique océanique, des modes de variabilité interne du climat et du forçage anthropique sur les structures de la variabilité régionale du niveau de la mer du Pacifique tropical depuis 1993. Nous montrons qu’une partie importante de la variabilité régionale du niveau de la mer du Pacifique tropical peut être expliquée par le mouvement vertical de la thermocline en réponse à l’action du vent. En tentant de séparer le signal correspondant au mode de variabilité interne du climat de celui de la hausse régionale du niveau de la mer dans le Pacifique tropical, nous montrons également que le signal résiduel restant (c’est-à-dire le signal total moins le signal de variabilité interne) ne correspond probablement pas à l’empreinte externe du forçage anthropique

Status of the Global Observing System for Climate

Status of the Global Observing System for Climat