scholarly journals Hyplant-Derived Sun-Induced Fluorescence—A New Opportunity to Disentangle Complex Vegetation Signals from Diverse Vegetation Types

2019 ◽  
Vol 11 (14) ◽  
pp. 1691 ◽  
Author(s):  
Subhajit Bandopadhyay ◽  
Anshu Rastogi ◽  
Uwe Rascher ◽  
Patrick Rademske ◽  
Anke Schickling ◽  
...  
Keyword(s):  
Plant Communities ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Vegetation Indices ◽  
Spatial Diversity ◽  
Small Scale ◽  
Data Set ◽  
Area Index ◽  
Heterogeneous Landscape ◽  
Large Heterogeneity

Hyperspectral remote sensing (RS) provides unique possibilities to monitor peatland vegetation traits and their temporal dynamics at a fine spatial scale. Peatlands provide a vital contribution to ecosystem services by their massive carbon storage and wide heterogeneity. However, monitoring, understanding, and disentangling the diverse vegetation traits from a heterogeneous landscape using complex RS signal is challenging, due to its wide biodiversity and distinctive plant species composition. In this work, we aim to demonstrate, for the first time, the large heterogeneity of peatland vegetation traits using well-established vegetation indices (VIs) and Sun-Induced Fluorescence (SIF) for describing the spatial heterogeneity of the signals which may correspond to spatial diversity of biochemical and structural traits. SIF originates from the initial reactions in photosystems and is emitted at wavelengths between 650–780 nm, with the first peak at around 687 nm and the second peak around 760 nm. We used the first HyPlant airborne data set recorded over a heterogeneous peatland area and its surrounding ecosystems (i.e., forest, grassland) in Poland. We deployed a comparative analysis of SIF and VIs obtained from differently managed and natural vegetation ecosystems, as well as from diverse small-scale peatland plant communities. Furthermore, spatial relationships between SIF and VIs from large-scale vegetation ecosystems to small-scale peatland plant communities were examined. Apart from signal variations, we observed a positive correlation between SIF and greenness-sensitive VIs, whereas a negative correlation between SIF and a VI sensitive to photosynthesis was observed for large-scale vegetation ecosystems. In general, higher values of SIF were associated with higher biomass of vascular plants (associated with higher Leaf Area Index (LAI)). SIF signals, especially SIF760, were strongly associated with the functional diversity of the peatland vegetation. At the peatland area, higher values of SIF760 were associated with plant communities of high perennials, whereas, lower values of SIF760 indicated peatland patches dominated by Sphagnum. In general, SIF760 reflected the productivity gradient on the fen peatland, from Sphagnum-dominated patches with the lowest SIF and fAPAR values indicating lowest productivity to the Carex-dominated patches with the highest SIF and fAPAR values indicating highest productivity.

scholarly journals Multi-Scale Ionospheric Anomalies Monitoring and Spatio-Temporal Analysis during Intense Storm

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 215
Author(s):  
Na Cheng ◽  
Shuli Song ◽  
Wei Li
Keyword(s):  
Magnetic Storm ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Ionospheric Disturbance ◽  
Ionospheric Scintillation ◽  
Small Scale ◽  
Electron Content ◽  
Total Electron ◽  
Multi Scale ◽  
Intense Storm

The ionosphere is a significant component of the geospace environment. Storm-induced ionospheric anomalies severely affect the performance of Global Navigation Satellite System (GNSS) Positioning, Navigation, and Timing (PNT) and human space activities, e.g., the Earth observation, deep space exploration, and space weather monitoring and prediction. In this study, we present and discuss the multi-scale ionospheric anomalies monitoring over China using the GNSS observations from the Crustal Movement Observation Network of China (CMONOC) during the 2015 St. Patrick’s Day storm. Total Electron Content (TEC), Ionospheric Electron Density (IED), and the ionospheric disturbance index are used to monitor the storm-induced ionospheric anomalies. This study finally reveals the occurrence of the large-scale ionospheric storms and small-scale ionospheric scintillation during the storm. The results show that this magnetic storm was accompanied by a positive phase and a negative phase ionospheric storm. At the beginning of the main phase of the magnetic storm, both TEC and IED were significantly enhanced. There was long-duration depletion in the topside ionospheric TEC during the recovery phase of the storm. This study also reveals the response and variations in regional ionosphere scintillation. The Rate of the TEC Index (ROTI) was exploited to investigate the ionospheric scintillation and compared with the temporal dynamics of vertical TEC. The analysis of the ROTI proved these storm-induced TEC depletions, which suppressed the occurrence of the ionospheric scintillation. To improve the spatial resolution for ionospheric anomalies monitoring, the regional Three-Dimensional (3D) ionospheric model is reconstructed by the Computerized Ionospheric Tomography (CIT) technique. The spatial-temporal dynamics of ionospheric anomalies during the severe geomagnetic storm was reflected in detail. The IED varied with latitude and altitude dramatically; the maximum IED decreased, and the area where IEDs were maximum moved southward.

scholarly journals Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

2015 ◽  
Vol 8 (10) ◽  
pp. 3033-3053 ◽  
Author(s):  
S. Garrigues ◽  
A. Olioso ◽  
D. Carrer ◽  
B. Decharme ◽  
J.-C. Calvet ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Surface Model ◽  
Data Sets ◽  
Data Set ◽  
Area Index ◽  
Hydrodynamic Parameters ◽  
Land Surface Parameter ◽  
Crop Succession

Abstract. Generic land surface models are generally driven by large-scale data sets to describe the climate, the soil properties, the vegetation dynamic and the cropland management (irrigation). This paper investigates the uncertainties in these drivers and their impacts on the evapotranspiration (ET) simulated from the Interactions between Soil, Biosphere, and Atmosphere (ISBA-A-gs) land surface model over a 12-year Mediterranean crop succession. We evaluate the forcing data sets used in the standard implementation of ISBA over France where the model is driven by the SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) high spatial resolution atmospheric reanalysis, the leaf area index (LAI) time courses derived from the ECOCLIMAP-II land surface parameter database and the soil texture derived from the French soil database. For climate, we focus on the radiations and rainfall variables and we test additional data sets which include the ERA-Interim (ERA-I) low spatial resolution reanalysis, the Global Precipitation Climatology Centre data set (GPCC) and the MeteoSat Second Generation (MSG) satellite estimate of downwelling shortwave radiations. The evaluation of the drivers indicates very low bias in daily downwelling shortwave radiation for ERA-I (2.5 W m−2) compared to the negative biases found for SAFRAN (−10 W m−2) and the MSG satellite (−12 W m−2). Both SAFRAN and ERA-I underestimate downwelling longwave radiations by −12 and −16 W m−2, respectively. The SAFRAN and ERA-I/GPCC rainfall are slightly biased at daily and longer timescales (1 and 0.5 % of the mean rainfall measurement). The SAFRAN rainfall is more precise than the ERA-I/GPCC estimate which shows larger inter-annual variability in yearly rainfall error (up to 100 mm). The ECOCLIMAP-II LAI climatology does not properly resolve Mediterranean crop phenology and underestimates the bare soil period which leads to an overall overestimation of LAI over the crop succession. The simulation of irrigation by the model provides an accurate irrigation amount over the crop cycle but the timing of irrigation occurrences is frequently unrealistic. Errors in the soil hydrodynamic parameters and the lack of irrigation in the simulation have the largest influence on ET compared to uncertainties in the large-scale climate reanalysis and the LAI climatology. Among climate variables, the errors in yearly ET are mainly related to the errors in yearly rainfall. The underestimation of the available water capacity and the soil hydraulic diffusivity induce a large underestimation of ET over 12 years. The underestimation of radiations by the reanalyses and the absence of irrigation in the simulation lead to the underestimation of ET while the overall overestimation of LAI by the ECOCLIMAP-II climatology induces an overestimation of ET over 12 years. This work shows that the key challenges to monitor the water balance of cropland at regional scale concern the representation of the spatial distribution of the soil hydrodynamic parameters, the variability of the irrigation practices, the seasonal and inter-annual dynamics of vegetation and the spatiotemporal heterogeneity of rainfall.

Mangroves as Fish Habitat

2015 ◽  
Keyword(s):  
Numerical Modeling ◽  
Quantitative Data ◽  
Large Scale ◽  
Scientific Literature ◽  
Spatial Scales ◽  
Fish Habitat ◽  
Systematic Search ◽  
Small Scale ◽  
Data Set ◽  
Subsistence Fishing

<em>Abstract</em>.—Mangroves are widely understood to be important habitats for fisheries, supporting resident fish, crustacean, and mollusk populations as well as acting as nursery grounds for species that are targeted by offshore fisheries. There is, however, a lack of quantitative data on fisheries that operate in and around mangroves. We carried out a systematic search to gather data on mangrove fisheries from the scientific literature. We filtered the 4,358 studies returned by the search based on their title and abstract and extracted data from 169 of these. Despite the abundance of literature on mangrove fisheries, we were unable to build a data set of comparable, quantitative data of sufficient size to support numerical modeling approaches. In part, this is due to the variety of mangrove fisheries, which range from small-scale subsistence fishing for mollusks and crabs to large-scale industrialized prawn trawling. This is compounded by the broad range of reporting methods and metrics encountered in the literature. We make a number of recommendations to guide the future reporting of mangrove fisheries to allow for better quantification and comparison of fisheries values at large spatial scales.

scholarly journals Differences between downscaling with spectral and grid nudging using WRF

2012 ◽  
Vol 12 (8) ◽  
pp. 3601-3610 ◽  
Author(s):  
P. Liu ◽  
A. P. Tsimpidi ◽  
Y. Hu ◽  
B. Stone ◽  
A. G. Russell ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Regional Climate ◽  
Wrf Model ◽  
Global Climate Models ◽  
Small Scale ◽  
Data Set ◽  
Spectral Nudging

Abstract. Dynamical downscaling has been extensively used to study regional climate forced by large-scale global climate models. During the downscaling process, however, the simulation of regional climate models (RCMs) tends to drift away from the driving fields. Developing a solution that addresses this issue, by retaining the large scale features (from the large-scale fields) and the small-scale features (from the RCMs) has led to the development of "nudging" techniques. Here, we examine the performance of two nudging techniques, grid and spectral nudging, in the downscaling of NCEP/NCAR data with the Weather Research and Forecasting (WRF) Model. The simulations are compared against the results with North America Regional Reanalysis (NARR) data set at different scales of interest using the concept of similarity. We show that with the appropriate choice of wave numbers, spectral nudging outperforms grid nudging in the capacity of balancing the performance of simulation at the large and small scales.

scholarly journals Log Data Real Time Analysis Using Big Data Analytic Framework with Storm and Hadoop

2018 ◽  
Vol 246 ◽  
pp. 03009
Author(s):  
Jia-Ke Lv ◽  
Yang Li ◽  
Xuan Wang
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Knowledge Extraction ◽  
Streaming Data ◽  
Small Scale ◽  
Global Knowledge ◽  
Data Set ◽  
Log Data ◽  
Real Time Processing ◽  
Real Time Analysis

The log data real-time processing platform which is built using Storm On YARN integrated MapReduce and Storm that use MapReduce to complete large-scale off-line data global knowledge extraction, sudden knowledge extraction of small-scale data in Kafka buffers through Storm, and continuous real-time calculation of streaming data in combination with global knowledge. We tested our technique with the well-known KDD99 CUP data set. The experimentation results prove the system to be effective and efficient.

scholarly journals Observed small spatial scale and seasonal variability of the CO<sub>2</sub> system in the Southern Ocean

2014 ◽  
Vol 11 (1) ◽  
pp. 75-90 ◽  
Author(s):  
L. Resplandy ◽  
J. Boutin ◽  
L. Merlivat
Keyword(s):  
Southern Ocean ◽  
Spatial Scale ◽  
Large Scale ◽  
Carbon Budget ◽  
Spatial Scales ◽  
Mixed Layer Depth ◽  
Small Scale ◽  
Spatiotemporal Resolution ◽  
Small Spatial Scale ◽  
Data Set

Abstract. The considerable uncertainties in the carbon budget of the Southern Ocean are largely attributed to unresolved variability, in particular at a seasonal timescale and small spatial scale (~ 100 km). In this study, the variability of surface pCO2 and dissolved inorganic carbon (DIC) at seasonal and small spatial scales is examined using a data set of surface drifters including ~ 80 000 measurements at high spatiotemporal resolution. On spatial scales of 100 km, we find gradients ranging from 5 to 50 μatm for pCO2 and 2 to 30 μmol kg−1 for DIC, with highest values in energetic and frontal regions. This result is supported by a second estimate obtained with sea surface temperature (SST) satellite images and local DIC–SST relationships derived from drifter observations. We find that dynamical processes drive the variability of DIC at small spatial scale in most regions of the Southern Ocean and the cascade of large-scale gradients down to small spatial scales, leading to gradients up to 15 μmol kg−1 over 100 km. Although the role of biological activity is more localized, it enhances the variability up to 30 μmol kg−1 over 100 km. The seasonal cycle of surface DIC is reconstructed following Mahadevan et al. (2011), using an annual climatology of DIC and a monthly climatology of mixed layer depth. This method is evaluated using drifter observations and proves to be a reasonable first-order estimate of the seasonality in the Southern Ocean that could be used to validate model simulations. We find that small spatial-scale structures are a non-negligible source of variability for DIC, with amplitudes of about a third of the variations associated with the seasonality and up to 10 times the magnitude of large-scale gradients. The amplitude of small-scale variability reported here should be kept in mind when inferring temporal changes (seasonality, interannual variability, decadal trends) of the carbon budget from low-resolution observations and models.

scholarly journals Large Interstellar Polarisation Survey

2018 ◽  
Vol 611 ◽  
pp. A5 ◽  
Author(s):  
R. Siebenmorgen ◽  
N. V. Voshchinnikov ◽  
S. Bagnulo ◽  
N. L. J. Cox ◽  
J. Cami ◽  
...  
Keyword(s):  
High Resolution ◽  
Interstellar Medium ◽  
Southern Hemisphere ◽  
Large Scale ◽  
Small Scale ◽  
Data Set ◽  
Carbon Particles ◽  
Prolate Shape ◽  
Multiple Clouds ◽  
H 20

It is well known that the dust properties of the diffuse interstellar medium exhibit variations towards different sight-lines on a large scale. We have investigated the variability of the dust characteristics on a small scale, and from cloud-to-cloud. We use low-resolution spectro-polarimetric data obtained in the context of the Large Interstellar Polarisation Survey (LIPS) towards 59 sight-lines in the Southern Hemisphere, and we fit these data using a dust model composed of silicate and carbon particles with sizes from the molecular to the sub-micrometre domain. Large (≥6 nm) silicates of prolate shape account for the observed polarisation. For 32 sight-lines we complement our data set with UVES archive high-resolution spectra, which enable us to establish the presence of single-cloud or multiple-clouds towards individual sight-lines. We find that the majority of these 35 sight-lines intersect two or more clouds, while eight of them are dominated by a single absorbing cloud. We confirm several correlations between extinction and parameters of the Serkowski law with dust parameters, but we also find previously undetected correlations between these parameters that are valid only in single-cloud sight-lines. We find that interstellar polarisation from multiple-clouds is smaller than from single-cloud sight-lines, showing that the presence of a second or more clouds depolarises the incoming radiation. We find large variations of the dust characteristics from cloud-to-cloud. However, when we average a sufficiently large number of clouds in single-cloud or multiple-cloud sight-lines, we always retrieve similar mean dust parameters. The typical dust abundances of the single-cloud cases are [C]/[H] = 92 ppm and [Si]/[H] = 20 ppm.

scholarly journals Study of a prototypical convective boundary layer observed during BLLAST: contributions by large-scale forcings

2014 ◽  
Vol 14 (13) ◽  
pp. 19247-19291 ◽  
Author(s):  
H. Pietersen ◽  
J. Vilà-Guerau de Arellano ◽  
P. Augustin ◽  
O. de Coster ◽  
H. Delbarre ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Large Scale ◽  
Surface Heterogeneity ◽  
Small Scale ◽  
Mountain Range ◽  
Convective Boundary ◽  
Good Correspondence ◽  
Data Set ◽  
Boundary Layer Height ◽  
Boundary Layer Dynamics

Abstract. We study the disturbances of CBL dynamics due to large-scale atmospheric contributions for a representative day observed during the Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) campaign. We first reproduce the observed boundary-layer dynamics by combining the Dutch Atmospheric Large-Eddy Simulation (DALES) model with a mixed-layer theory based model. We find that by only taking surface and entrainment fluxes into account, the boundary-layer height is overestimated by 70%. If we constrain our numerical experiments with the BLLAST comprehensive data set, we are able to quantify the contributions of advection of heat and moisture, and subsidence. We find that subsidence has a clear diurnal pattern. Supported by the presence of a nearby mountain range, this pattern suggests that not only synoptic scales exert their influence on the boundary layer, but also mesoscale circulations. Finally, we study whether the vertical and temporal evolution of turbulent variables are influenced by these large-scale forcings. Our model results show good correspondence of the vertical structure of turbulent variables with observations. Our findings further indicate that when large-scale advection and subsidence are applied, the values for turbulent kinetic are lower than without these large-scale forcings. We conclude that the prototypical CBL can still be used as a valid representation of the boundary-layer dynamics near regions characterized by complex topography and small-scale surface heterogeneity, provided that surface- and large-scale forcings are well characterized.

scholarly journals Spatial Diversity Deconstruct of C-band Scatter Components in Multistatic RaDaR Datasets using Machine Learning Techniques

2021 ◽  
Author(s):  
Shanmugha Sundaram G A ◽  
Harun Surej I ◽  
Karthic S ◽  
Gandhiraj R ◽  
Binoy B N ◽  
...  
Keyword(s):  
Machine Learning ◽  
Communication Systems ◽  
Large Scale ◽  
Spatial Diversity ◽  
Machine Learning Techniques ◽  
Line Of Sight ◽  
Propagation Channel ◽  
Data Set ◽  
Band Frequency ◽  
Analytical Approaches

In complex application wherein the signal propagating through free space is subject to multipath interference due to scatter by line-of-sight and non-line-of-sight objects in the propagation channel. The aims is to identify scatter centers in the propagation channel and characterize them based on their subjective characteristics, interpreted based on machine learning algorithm operations. Data-driven models are employed, replacing the traditional analytical approaches, in order to profile the scatter centers as either of absorbing or reflecting types based on the manner in which the signals are affected. A typical multistatic detection scenario is reconstructed under controlled laboratory conditions in order to create spatially independent data sets, while operating in the C-band frequency. The outcomes of this study are then applied to identify the scatter centers based on the distinct signatures they register in the experimental data set. As a converse argument, the process of antenna pattern estimation can now be performed free of an anechoic chamber setup, which is time and cost insensitive. A greater relevance shall be in the context of mid-band 5G-NR cellular communication systems that need to optimize the distributed antenna location attributes on time and cost constrained scales before attempting a large-scale deployment.

scholarly journals Study of a prototypical convective boundary layer observed during BLLAST: contributions by large-scale forcings

2015 ◽  
Vol 15 (8) ◽  
pp. 4241-4257 ◽  
Author(s):  
H. P. Pietersen ◽  
J. Vilà-Guerau de Arellano ◽  
P. Augustin ◽  
A. van de Boer ◽  
O. de Coster ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Convective Boundary Layer ◽  
Large Scale ◽  
Surface Heterogeneity ◽  
Small Scale ◽  
Mountain Range ◽  
Convective Boundary ◽  
Data Set ◽  
Local Boundary ◽  
Heat And Moisture

Abstract. We study the influence of the large-scale atmospheric contribution to the dynamics of the convective boundary layer (CBL) in a situation observed during the Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. We employ two modeling approaches, the mixed-layer theory and large-eddy simulation (LES), with a complete data set of surface and upper-air atmospheric observations, to quantify the contributions of the advection of heat and moisture, and subsidence. We find that by only taking surface and entrainment fluxes into account, the boundary-layer height is overestimated by 70%. Constrained by surface and upper-air observations, we infer the large-scale vertical motions and horizontal advection of heat and moisture. Our findings show that subsidence has a clear diurnal pattern. Supported by the presence of a nearby mountain range, this pattern suggests that not only synoptic scales exert their influence on the boundary layer, but also mesoscale circulations. LES results show a satisfactory correspondence of the vertical structure of turbulent variables with observations. We also find that when large-scale advection and subsidence are included in the simulation, the values for turbulent kinetic energy are lower than without these large-scale forcings. We conclude that the prototypical CBL is a valid representation of the boundary-layer dynamics near regions characterized by complex topography and small-scale surface heterogeneity, provided that surface- and large-scale forcings are representative for the local boundary layer.

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