How complex climate networks complement eigen techniques for the statistical analysis of climatological data

Eigen techniques such as empirical orthogonal function (EOF) or coupled pattern (CP) / maximum covariance analysis have been frequently used for detecting patterns in multivariate climatological data sets. Recently, statistical methods originating from the theory of complex networks have been employed for the very same purpose of spatio-temporal analysis. This climate network (CN) analysis is usually based on the same set of similarity matrices as is used in classical EOF or CP analysis, e.g., the correlation matrix of a single climatological field or the cross-correlation matrix between two distinct climatological fields. In this study, formal relationships as well as conceptual differences between both eigen and network approaches are derived and illustrated using exemplary global precipitation, evaporation and surface air temperature data sets. These results allow to pinpoint that CN analysis can complement classical eigen techniques and provides additional information on the higher-order structure of statistical interrelationships in climatological data. Hence, CNs are a valuable supplement to the statistical toolbox of the climatologist, particularly for making sense out of very large data sets such as those generated by satellite observations and climate model intercomparison exercises.Comment: 18 pages, 11 figure

Influence of Monolayer-Monolayer Coupling on the Phase Behavior of a Fluid Lipid Bilayer

AbstractWe suggest a minimal model for the coupling of the lateral phase behavior in an asymmetric lipid membrane across its two monolayers. Our model employs one single order parameter for each monolayer leaflet, namely its composition. Regular solution theory on the mean-field level is used to describe the free energy in each individual leaflet. Coupling between monolayers entails an energy penalty for any local compositional differences across the membrane. We calculate and analyze the phase behavior of this model. It predicts a range of possible scenarios. A monolayer with a propensity for phase separation is able to induce phase separation in the apposed monolayer. Conversely, a monolayer without this propensity is able to prevent phase separation in the apposed monolayer. If there is phase separation in the membrane, it may lead to either complete or partial registration of the monolayer domains across the membrane. The latter case which corresponds to a three-phase coexistence is only found below a critical coupling strength. We calculate that critical coupling strength. Above the critical coupling strength, the membrane adopts a uniform compositional difference between its two monolayers everywhere in the membrane, implying phase coexistence between only two phases and thus perfect spatial registration of all domains on the apposed membrane leafs. We use the lattice Boltzmann simulation method to also study the morphologies that form during phase separation within the three-phase coexistence region. Generally, domains in one monolayer diffuse but remain fully enclosed within domains in the other monolayer

Soil moisture retrieval through a merging of multi-temporal L-band SAR data and hydrologic modelling

he objective of the study is to investigate the potential of retrieving superficial soil moisture content (m(v)) from multi-temporal L-band synthetic aperture radar (SAR) data and hydrologic modelling. The study focuses on assessing the performances of an L-band SAR retrieval algorithm intended for agricultural areas and for watershed spatial scales (e. g. from 100 to 10 000 km(2)). The algorithm transforms temporal series of L-band SAR data into soil moisture contents by using a constrained minimization technique integrating a priori information on soil parameters. The rationale of the approach consists of exploiting soil moisture predictions, obtained at coarse spatial resolution ( e. g. 1530 km2) by point scale hydrologic models ( or by simplified estimators), as a priori information for the SAR retrieval algorithm that provides soil moisture maps at high spatial resolution (e. g. 0.01 km(2)). In the present form, the retrieval algorithm applies to cereal fields and has been assessed on simulated and experimental data. The latter were acquired by the airborne E-SAR system during the AgriSAR campaign carried out over the Demmin site (Northern Germany) in 2006. Results indicate that the retrieval algorithm always improves the a priori information on soil moisture content though the improvement may be marginal when the accuracy of prior mv estimates is better than 5%

Integration of L-band SAR data into Land Surface Models

Abstract—Land surface process modelling might be limited due to lack of reliable model input data. Key surface variables as land cover information or soil moisture conditions have been proven to be observable by remote sensing systems. The integration of remote sensing data into land surface process models might therefore help to improve their simulations results. Longer wavelength SAR data has a higher sensitivity to soil moisture content than higher frequency systems. Recent (ALOS) and planed (e.g. TerraSAR-L) SAR systems are therefore expected to provide valuable information about soil moisture dynamics. The present study investigates the potential to retrieve land cover information and geophysical parameters from L-band SAR data. The retrieval results are assimilated into a state-of-the-art land surface model to evaluate the merit of L-band SAR data assimilation

Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau

The Tibetan Plateau (TP) plays a major role in regional and global climate. The understanding of latent heat (LE) flux can help to better describe the complex mechanisms and interactions between land and atmosphere. Despite its importance, accurate estimation of evapotranspiration (ET) over the TP remains challenging. Satellite observations allow for ET estimation at high temporal and spatial scales. The purpose of this paper is to provide a detailed cross-comparison of existing ET products over the TP. Six available ET products based on different approaches are included for comparison. Results show that all products capture the seasonal variability well with minimum ET in the winter and maximum ET in the summer. Regarding the spatial pattern, the High resOlution Land Atmosphere surface Parameters from Space (HOLAPS) ET demonstrator dataset is very similar to the LandFlux-EVAL dataset (a benchmark ET product from the Global Energy and Water Cycle Experiment), with decreasing ET from the south-east to northwest over the TP. Further comparison against the LandFlux-EVAL over different sub-regions that are decided by different intervals of normalised difference vegetation index (NDVI), precipitation, and elevation reveals that HOLAPS agrees best with LandFlux-EVAL having the highest correlation coefficient (R) and the lowest root mean square difference (RMSD). These results indicate the potential for the application of the HOLAPS demonstrator dataset in understanding the land-atmosphere-biosphere interactions over the TP. In order to provide more accurate ET over the TP, model calibration, high accuracy forcing dataset, appropriate in situ measurements as well as other hydrological data such as runoff measurements are still needed

Influence of the Fermi Surface Morphology on the Magnetic Field-Driven Vortex Lattice Structure Transitions in YBa2_{2}Cu3_{3}O7−δ:δ=_{7-\delta}:\delta=0, 0.15

We report small-angle neutron scattering measurements of the vortex lattice (VL) structure in single crystals of the lightly underdoped cuprate superconductor YBa2Cu3O6.85. At 2 K, and for fields of up to 16 T applied parallel to the crystal c-axis, we observe a sequence of field-driven and first-order transitions between different VL structures. By rotating the field away from the c-axis, we observe each structure transition to shift to either higher or lower field dependent on whether the field is rotated towards the [100] or [010] direction. We use this latter observation to argue that the Fermi surface morphology must play a key role in the mechanisms that drive the VL structure transitions. Furthermore, we show this interpretation is compatible with analogous results obtained previously on lightly overdoped YBa2Cu3O7. In that material, it has long-been suggested that the high field VL structure transition is driven by the nodal gap anisotropy. In contrast, the results and discussion presented here bring into question the role, if any, of a nodal gap anisotropy on the VL structure transitions in both YBa2Cu3O6.85 and YBa2Cu3O7

Precipitation from Space: Advancing Earth System Science

Of the three primary sources of spatially contiguous precipitation observations (surface networks, ground-based radar, and satellite-based radar/radiometers), only the last is a viable source over ocean and much of the Earth's land. As recently as 15 years ago, users needing quantitative detail of precipitation on anything under a monthly time scale relied upon products derived from geostationary satellite thermal infrared (IR) indices. The Special Sensor Microwave Imager (SSMI) passive microwave (PMW) imagers originated in 1987 and continue today with the SSMI sounder (SSMIS) sensor. The fortunate longevity of the joint National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) Tropical Rainfall Measuring Mission (TRMM) is providing the environmental science community a nearly unbroken data record (as of April 2012, over 14 years) of tropical and sub-tropical precipitation processes. TRMM was originally conceived in the mid-1980s as a climate mission with relatively modest goals, including monthly averaged precipitation. TRMM data were quickly exploited for model data assimilation and, beginning in 1999 with the availability of near real time data, for tropical cyclone warnings. To overcome the intermittently spaced revisit from these and other low Earth-orbiting satellites, many methods to merge PMW-based precipitation data and geostationary satellite observations have been developed, such as the TRMM Multisatellite Precipitation Product and the Climate Prediction Center (CPC) morphing method (CMORPH. The purpose of this article is not to provide a survey or assessment of these and other satellite-based precipitation datasets, which are well summarized in several recent articles. Rather, the intent is to demonstrate how the availability and continuity of satellite-based precipitation data records is transforming the ways that scientific and societal issues related to precipitation are addressed, in ways that would not be otherwise possible. These developments have taken place in parallel with the growth of an increasingly interconnected scientific environment. Scientists from different disciplines can easily interact with each other via information and materials they encounter online, and collaborate remotely without ever meeting each other in person. Likewise, these precipitation datasets are quickly and easily available via various data portals and are widely used. Within the framework of the NASA/JAXA Global Precipitation Measurement (GPM mission, these applications will become increasingly interconnected. We emphasize that precipitation observations by themselves provide an incomplete picture of the state of the atmosphere. For example, it is unlikely that a richer understanding of the global water cycle will be possible by standalone missions and algorithms, but must also involve some component of data, where model analyses of the physical state are constrained alongside multiple observations (e.g., precipitation, evaporation, radiation). The next section provides examples extracted from the many applications that use various high-resolution precipitation products. The final section summarizes the future system for global precipitation processing

Unconventional quantum vortex matter state hosts quantum oscillations in the underdoped high-temperature cuprate superconductors.

A central question in the underdoped cuprates pertains to the nature of the pseudogap ground state. A conventional metallic ground state of the pseudogap region has been argued to host quantum oscillations upon destruction of the superconducting order parameter by modest magnetic fields. Here, we use low applied measurement currents and millikelvin temperatures on ultrapure single crystals of underdoped [Formula: see text] to unearth an unconventional quantum vortex matter ground state characterized by vanishing electrical resistivity, magnetic hysteresis, and nonohmic electrical transport characteristics beyond the highest laboratory-accessible static fields. A model of the pseudogap ground state is now required to explain quantum oscillations that are hosted by the bulk quantum vortex matter state without experiencing sizable additional damping in the presence of a large maximum superconducting gap; possibilities include a pair density wave.Royal Society Winton Programme for the Physics of Sustainability Engineering and Physical Sciences Research Council (EPSRC; studentship and grant numbers EP/R513180/1, EP/M506485/1 and EP/P024947/1) European Research Council under the European Unions Seventh Framework Programme (Grant Agreement numbers 337425 and 772891). EPSRC Strategic Equipment Grant EP/M000524/1 Leverhulme Trust by way of the award of a Philip Leverhulme Prize. National Key Research and Development Program of China (grant no. 2016YFA0401704). Work performed at the National High Magnetic Field Laboratory (NHMFL) supported by NSF Cooperative Agreement DMR-1157490, the State of Florida, and the Department of Energy (DOE) DOE Basic Energy Sciences project: ‘Science of 100 tesla’