scholarly journals An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4285 ◽  
Author(s):  
Shubha Sathyendranath ◽  
Robert Brewin ◽  
Carsten Brockmann ◽  
Vanda Brotas ◽  
Ben Calton ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Marine Ecosystem ◽  
Ocean Colour ◽  
Remote Sensing Reflectance ◽  
Resolution Imaging ◽  
In Situ Observations ◽  
Climate Studies ◽  
Reflectance Data

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.

scholarly journals Phytoplankton Phenology in the Coastal Zone of Cyprus, Based on Remote Sensing and In Situ Observations

2021 ◽  
Vol 14 (1) ◽  
pp. 12
Author(s):  
Monica Demetriou ◽  
Dionysios E. Raitsos ◽  
Antonia Kournopoulou ◽  
Manolis Mandalakis ◽  
Spyros Sfenthourakis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Phytoplankton Biomass ◽  
Trophic Levels ◽  
Data Availability ◽  
Ocean Colour ◽  
Chl A ◽  
In Situ Data

Alterations in phytoplankton biomass, community structure and timing of their growth (phenology), are directly implicated in the carbon cycle and energy transfer to higher trophic levels of the marine food web. Due to the lack of long-term in situ datasets, there is very little information on phytoplankton seasonal succession in Cyprus (eastern Mediterranean Sea). On the other hand, satellite-derived measurements of ocean colour can only provide long-term time series of chlorophyll (an index of phytoplankton biomass) up to the first optical depth (surface waters). The coupling of both means of observations is essential for understanding phytoplankton dynamics and their response to environmental change. Here, we use 23 years of remotely sensed, regionally tuned ocean-colour observations, along with a unique time series of in situ phytoplankton pigment composition data, collected in coastal waters of Cyprus during 2016. The satellite observations show an initiation of phytoplankton growth period in November, a peak in February and termination in April, with an overall mean duration of ~4 months. An in-depth exploration of in situ total Chl-a concentration and phytoplankton pigments revealed that pico- and nano-plankton cells dominated the phytoplankton community. The growth peak in February was dominated by nanophytoplankton and potentially larger diatoms (pigments of 19’ hexanoyloxyfucoxanthin and fucoxanthin, respectively), in the 0–20 m layer. The highest total Chl-a concentration was recorded at a station off Akrotiri peninsula in the south, where strong coastal upwelling has been reported. Another station in the southern part, located next to a fish farm, showed a higher contribution of picophytoplankton during the most oligotrophic period (summer). Our results highlight the importance of using available in situ data coupled to ocean-colour remote sensing, for monitoring marine ecosystems in areas with limited in situ data availability.

scholarly journals Dynamic time warping analysis of the evolution of SMOS surface and in-situ soil moisture time series

2020 ◽  
Author(s):  
Christoph Herbert ◽  
Miriam Pablos ◽  
Mercedes Vall-llossera ◽  
Adriano Camps
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Soil Moisture ◽  
Temporal Variability ◽  
Dynamic Time Warping ◽  
Time Lag ◽  
Time Warping ◽  
In Situ Observations ◽  
Dynamic Time

<p>A comprehensive understanding of temporal variability of root-zone and surface soil moisture (SM) and the relationship with the underlying soil characteristics is of great importance in hydrological and agricultural applications. For the last ten years, global and frequent satellite SM observations have been available to investigate SM dynamics. However, validating remote sensing retrievals against in-situ observations based on the comparison of collocated SM time series is complicated. While satellite retrievals are approximated from inversion models over an area, in-situ measurements are determined at point-scale. This usually produces different SM dynamic ranges and biases in the corresponding time series. Moreover, the influence of soil properties and meteorological conditions can cause SM time series obtained from indirect remote sensing techniques and direct in-situ observations to be non-linearly related. Dynamic Time Warping (DTW) is a dynamic programming technique, capable of coping with temporal distortions by aiming for finding the optimal match between time series.</p><p> </p><p>In this study, DTW was used to provide a time lag evolution as a continuous dissimilarity measure comprising the main temporal variability features of two time series. The DTW technique was applied to SM time series from the Soil Moisture and Ocean Salinity mission (SMOS) L4 product developed at Barcelona Expert Center (BEC) with in-situ measurements at top- and subsoil-representative depth levels, located in the Soil Moisture Measurements Station Network of the University of Salamanca (REMEDHUS) in Western Spain. DTW parameters were customized to the particular input time series to obtain a robust and meaningful time lag. Seasonal differences in SM dynamics were analyzed in a clustering approach by investigating the link between SM time series and SM-regime-related parameters including precipitation and categorical features such as soil type and land use. Since the technique resolves the non-linear behaviour of time series, it has the potential to generally assess major differences in SM acquisition techniques. It could also be useful to investigate spatial SM variability in heterogeneous regions and to make informed choices in future sensor deployment in SM networks.</p>

scholarly journals A Photometric Study of Regolith Intimate Mixing with Ice-Like Impurity

2021 ◽  
Author(s):  
Dwaipayan Deb ◽  
Pavan Chakraborty
Keyword(s):  
Solar System ◽  
Linear Trend ◽  
Geological Processes ◽  
Solar System Objects ◽  
Shadowing Effect ◽  
Mixing Proportion ◽  
In Situ Observations ◽  
End Members ◽  
Reflectance Data

Abstract Surfaces of solid solar system objects are covered by layers of particulate materials called regolith originated from their surface bedrock. They preserve important information about surface geological processes. Often regolith is composed of more than one type of particle in terms of composition, maturity, size, etc. Experiments and theoretical works are being carried out to constrain the result of mixing and extract the abundance of compositional end-members from regolith spectra. In this work we have studied, photometric light scattering from simulated surfaces made of two different materials – one is highly bright quartz particles ≈ 80µm and the other moderately bright sandstone particles ≈ 250µm. The samples were mixed with varying proportions and investigated at normal illumination conditions to avoid the shadowing effect. Said combinations may resemble ice mixed regolith on various solar system objects and therefore important for in situ observations. We find that the combinations show a linear trend in the corresponding reflectance data in terms of their mixing proportion and some interesting facts come out when compared to previous studies.

scholarly journals Mediterranean Sea climatic indices: monitoring long term variability and climate changes

2018 ◽  
Author(s):  
Athanasia Iona ◽  
Athanasios Theodorou ◽  
Sarantis Sofianos ◽  
Sylvain Watelet ◽  
Charles Troupin ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Mediterranean Sea ◽  
Climate Changes ◽  
Salt Content ◽  
Climatic Indices ◽  
In Situ Observations ◽  
The Mediterranean

Abstract. We present a new product composed of a set of thermohaline climatic indices from 1950 to 2015 for the Mediterranean Sea such as decadal temperature and salinity anomalies, their mean values over selected depths, decadal ocean heat and salt content anomalies at selected depth layers as well as their long times series. It is produced from a new high-resolution climatology of temperature and salinity on a 1/8° regular grid based on historical high quality in situ observations. Ocean heat and salt content differences between 1980–2015 and 1950–1979 are compared for evaluation of the climate shift in the Mediterranean Sea. The spatial patterns of heat and salt content shifts demonstrate in greater detail than ever before that the climate changes differently in the several regions of the basin. Long time series of heat and salt content for the period 1950 to 2015 are also provided which indicate that in the Mediterranean Sea there is a net mean volume warming and salting since 1950 with acceleration during the last two decades. The time series also show that the ocean heat content seems to fluctuate on a cycle of about 40 years and seems to follow the Atlantic Multidecadal Oscillation climate cycle indicating that the natural large scale atmospheric variability could be superimposed on to the warming trend. This product is an observations-based estimation of the Mediterranean climatic indices. It relies solely on spatially interpolated data produced from in-situ observations averaged over decades in order to smooth the decadal variability and reveal the long term trends with more accuracy. It can provide a valuable contribution to the modellers' community, next to the satellite-based products and serve as a baseline for the evaluation of climate-change model simulations contributing thus to a better understanding of the complex response of the Mediterranean Sea to the ongoing global climate change. The product is available here: https://doi.org/10.5281/zenodo.1210100.

scholarly journals Estudo do ciclo diário da Camada Limite Planetária durante a estação cChuvosa da Amazônia (GOAmazon 2014/15)

2018 ◽  
Vol 40 ◽  
pp. 63 ◽  
Author(s):  
Rayonil Gomes Carneiro ◽  
Alice Henkes ◽  
Gilberto Fisch ◽  
Camilla Kassar Borges
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Remote Sensing Data ◽  
Great Depth ◽  
Wet Season ◽  
Daily Cycle ◽  
Convective Boundary ◽  
In Situ Observations

In the present study, the evolution the diurnal cycle of planetary boundary layer in the wet season at Amazon region during a period of intense observations carried out in the GOAmazon Project 2014/2015 (Green Ocean Amazon).The analysis includes radiosonde and remote sensing data. In general case, the results of the daily cycle in the wet season indicate a Nocturnal boundary layer with a small oscillation in its depth and with a tardy erosion. The convective boundary layer did not present great depth, responding to the low values of sensible heat of the wet season. A comparison between the different techniques(in situ observations and remote sensing)  for estimating the planetary boundary layer is also presented.

Characterization of Remote Sensing Albedo Over Sloped Surfaces Based on DART Simulations and In Situ Observations

2018 ◽  
Vol 123 (16) ◽  
pp. 8599-8622 ◽  
Author(s):  
Shengbiao Wu ◽  
Jianguang Wen ◽  
Dongqin You ◽  
Dalei Hao ◽  
Xingwen Lin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
In Situ Observations

scholarly journals Three-phase Evolution of a Coronal Hole. I. 360° Remote Sensing and In Situ Observations

2018 ◽  
Vol 861 (2) ◽  
pp. 151 ◽  
Author(s):  
Stephan G. Heinemann ◽  
Manuela Temmer ◽  
Stefan J. Hofmeister ◽  
Astrid M. Veronig ◽  
Susanne Vennerstrøm
Keyword(s):  
Remote Sensing ◽  
Coronal Hole ◽  
Phase Evolution ◽  
Three Phase ◽  
In Situ Observations

Application of the active learning method to the retrieval of pigment from spectral remote sensing reflectance data

2009 ◽  
Vol 30 (4) ◽  
pp. 1045-1065 ◽  
Author(s):  
H. Taheri Shahraiyni ◽  
S. Bagheri Shouraki ◽  
F. Fell ◽  
M. Schaale ◽  
J. Fischer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Active Learning ◽  
Learning Method ◽  
Remote Sensing Reflectance ◽  
Active Learning Method ◽  
Reflectance Data
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