scholarly journals Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea

2017 ◽  
Vol 18 (1) ◽  
pp. 22 ◽  
Author(s):  
D. KASSIS ◽  
G. KORRES ◽  
A. KONSTANTINIDOU ◽  
L. PERIVOLIOTIS
Keyword(s):  
High Resolution ◽  
Hydrodynamic Model ◽  
Numerical Models ◽  
Regional Scale ◽  
Model Performance ◽  
Temporal Analysis ◽  
In Situ Monitoring ◽  
Ionian Sea ◽  
Nested Models

In-situ monitoring is an essential component for the development of hydrodynamic numerical models. Argo expansion into marginal seas has enabled the advancement of high resolution regional nested models through initialization, assimilation and validation processes. The SANI (Southern Adriatic-Northern Ionian) hydrodynamic model is a regional nested model producing high resolution outputs for the period 2008-2012. For the corresponding time period, 21 free drifting Argo floats recorded Temperature –Salinity (T/S) profiles throughout the region. This study presents the inter-comparison of the two data sets whilst noting interesting aspects of the model performance regarding the representation of the major water masses characteristics of the SANI area. Aside from the inter-comparison in a basin’s scale, a spatio-temporal analysis is also performed. The results indicate an adequate response of the model simulations regarding the basic hydrographic features of the region. Nevertheless, important differences are highlighted mainly in the upper and deep layers of the study area. At a regional scale, inter-annual variability of the model’s performance is observed reflecting the hydrographic changes occurred in the wider area during the study period. Overall, the results present the strong points but also highlight the weaknesses of the model. They also confirm the challenging task of producing high resolution numerical simulations in transitional areas such as the Ionian Sea.

scholarly journals Presentation and discussion of the high resolution atmosphere-land surface subsurface simulation dataset of the virtual Neckar catchment for the period 2007–2015

2020 ◽  
Author(s):  
Bernd Schalge ◽  
Gabriele Baroni ◽  
Barbara Haese ◽  
Daniel Erdal ◽  
Gernot Geppert ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Overland Flow ◽  
Water Cycle ◽  
Numerical Models ◽  
Model Performance ◽  
Surface Model ◽  
Meteorological Model ◽  
The Real ◽  
Terrestrial System

Abstract. Coupled numerical models, which simulate water and energy fluxes in the subsurface-land surface-atmosphere system in a physically consistent way are a prerequisite for the analysis and a better understanding of heat and matter exchange fluxes at compartmental boundaries and interdependencies of states across these boundaries. Complete state evolutions generated by such models may be regarded as a proxy of the real world, provided they are run at sufficiently high resolution and incorporate the most important processes. Such a virtual reality can be used to test hypotheses on the functioning of the coupled terrestrial system. Coupled simulation systems, however, face severe problems caused by the vastly different scales of the processes acting in and between the compartments of the terrestrial system, which also hinders comprehensive tests of their realism. We used the Terrestrial Systems Modeling Platform TerrSysMP, which couples the meteorological model COSMO, the land-surface model CLM, and the subsurface model ParFlow, to generate a virtual catchment for a regional terrestrial system mimicking the Neckar catchment in southwest Germany. Simulations for this catchment are made for the period 2007–2015, and at a spatial resolution of 400 m for the land surface and subsurface and 1.1 km for the atmosphere. Among a discussion of modelling challenges, the model performance is evaluated based on real observations covering several variables of the water cycle. We find that the simulated (virtual) catchment behaves in many aspects quite close to observations of the real Neckar catchment, e.g. concerning atmospheric boundary-layer height, precipitation, and runoff. But also discrepancies become apparent, both in the ability of the model to correctly simulate some processes which still need improvement such as overland flow, and in the realism of some observation operators like the satellite based soil moisture sensors. The whole raw dataset is available for interested users. The dataset described here is available via the CERA database (Schalge et al., 2020): https://doi.org/10.26050/WDCC/Neckar_VCS_v1.

scholarly journals Multiscale observations of NH<sub>3</sub> around Toronto, Canada

2021 ◽  
Vol 14 (2) ◽  
pp. 905-921
Author(s):  
Shoma Yamanouchi ◽  
Camille Viatte ◽  
Kimberly Strong ◽  
Erik Lutsch ◽  
Dylan B. A. Jones ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Grid Point ◽  
Regional Scale ◽  
Model Performance ◽  
In Situ Measurements ◽  
Coefficient Of Determination ◽  
Spatial And Temporal Variability ◽  
Predictive Capacity ◽  
Total Column

Abstract. Ammonia (NH3) is a major source of nitrates in the atmosphere and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, 3 years of surface in situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the representativeness of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.89 %/yr from 2002 to 2018 in the FTIR columns, 8.88 ± 5.08 %/yr from 2013 to 2017 in the surface in situ data, and 8.38 ± 1.54 %/yr from 2008 to 2018 in the IASI columns. To assess the representative scale of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤25 km and ≤20 min, with r=0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in situ measurements were standardized and correlated. Comparison of 24 d averages and monthly averages resulted in correlation coefficients of r=0.72 and r=0.75, respectively, although correlation without averaging to reduce high-frequency variability led to a poorer correlation, with r=0.39. The GEOS-Chem model, run at 2∘ × 2.5∘ resolution, was compared to FTIR and IASI to assess model performance and investigate the correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35 to 53∘ N and 93.75 to 63.75∘ W) resulted in r=0.57 and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2=0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2=0.13, indicating that a finer spatial resolution is needed for modeling NH3.

scholarly journals A Cost-Effective In Situ Zooplankton Monitoring System Based on Novel Illumination Optimization

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3471
Author(s):  
Zhiqiang Du ◽  
Chunlei Xia ◽  
Longwen Fu ◽  
Nan Zhang ◽  
Bowei Li ◽  
...  
Keyword(s):  
High Resolution ◽  
Imaging System ◽  
Physiological State ◽  
Cost Effective ◽  
In Situ Monitoring ◽  
Measuring System ◽  
Target Area ◽  
Image Processing Algorithm ◽  
Led Array

A cost-effective and low-power-consumption underwater microscopic imaging system was developed to capture high-resolution zooplankton images in real-time. In this work, dark-field imaging was adopted to reduce backscattering and background noise. To produce an accurate illumination, a novel illumination optimization scheme for the light-emitting diode (LED) array was proposed and applied to design a lighting system for the underwater optical imaging of zooplankton. A multiple objective genetic algorithm was utilized to find the best location of the LED array, which resulted in the specific illumination level and most homogeneous irradiance in the target area. The zooplankton imaging system developed with the optimal configuration of LEDs was tested with Daphnia magna under laboratory conditions. The maximal field of view was 16 mm × 13 mm and the optical resolution was 15 μm. The experimental results showed that the imaging system developed could capture high-resolution and high-definition images of Daphnia. Subsequently, Daphnia individuals were accurately segmented and their geometrical characters were measured by using a classical image processing algorithm. This work provides a cost-effective zooplankton measuring system based on an optimization illumination configuration of an LED array, which has a great potential for minimizing the investment and operating costs associated with long-term in situ monitoring of the physiological state and population conditions of zooplankton.

3D Simulation of Tunnel Collapse Consolidation and In Situ Monitoring Analysis

2011 ◽  
Vol 243-249 ◽  
pp. 3551-3555
Author(s):  
Zhi Min Chen ◽  
De An Zhao
Keyword(s):  
Numerical Models ◽  
Three Dimensional ◽  
In Situ Monitoring ◽  
3D Simulation ◽  
Actual Situation ◽  
Consolidation Effect ◽  
Tunnel Collapse ◽  
Simulation Results ◽  
Shallow Buried Tunnel

A shallow buried tunnel was collapsed during construction. According to the actual situation of the tunnel, different collapse consolidation schemes were put forward and corresponding three-dimensional finite difference numerical models were established and analyzed using FLAC3D software. Base on the 3D Simulation results, a collapse consolidation scheme was determined and constructed. The in-situ monitoring results of vault subsidence and convergence displacement were consistent approximately with the 3D Simulation results. The in-situ measured results were in line with the specification’s allowance and show that the consolidation effect of reinforced concrete casing arch and ahead grouting method is good. This could be referenced for similar engineering.

scholarly journals Multiscale observations of NH3 around Toronto, Canada

2020 ◽  
Author(s):  
Shoma Yamanouchi ◽  
Camille Viatte ◽  
Kimberly Strong ◽  
Dylan B. A. Jones ◽  
Cathy Clerbaux ◽  
...  
Keyword(s):  
Case Studies ◽  
Biomass Burning ◽  
Grid Point ◽  
Fine Particulate Matter ◽  
Regional Scale ◽  
Model Performance ◽  
In Situ Measurements ◽  
Coefficient Of Determination ◽  
Predictive Capacity

&lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;p&gt;Ammonia (NH&lt;sub&gt;3&lt;/sub&gt;) is a major source of nitrates in the atmosphere, and a major source of fine particulate matter. As such, there have been increasing efforts to monitor NH&lt;sub&gt;3&lt;/sub&gt;. This study examines long-term measurements of NH&lt;sub&gt;3&lt;/sub&gt; around Toronto, Canada, derived from three multiscale datasets: 16 years of total column measurements using ground-based Fourier transform infrared (FTIR) spectroscopy, three years of surface in-situ measurements, and ten years of total columns from the Infrared Atmospheric Sounding Interferometer (IASI) sensor onboard the Metop satellites. These datasets were used to quantify NH&lt;sub&gt;3&lt;/sub&gt; temporal variabilities (trends, inter-annual, seasonal) over Toronto to assess the observational footprint of the FTIR measurements, and two case studies of pollution events due to transport of biomass burning plumes.&lt;/p&gt; &lt;p&gt;All three timeseries showed increasing trends in NH&lt;sub&gt;3&lt;/sub&gt; over Toronto: 3.34 &amp;#177; 0.44 %/year from 2002 to 2018 in the FTIR columns, 8.88 &amp;#177; 2.49 %/year from 2013 to 2017 in the surface in-situ data, and 8.78 &amp;#177; 0.84 %/year from 2008 to 2018 in the IASI columns. To assess the observational footprint of the FTIR NH&lt;sub&gt;3&lt;/sub&gt; columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was found for coincidence criterion of &amp;#8804; 50 km and &amp;#8804; 20 minutes, with r = 0.66 and a slope of 0.988 &amp;#177; 0.058. The FTIR column and in-situ measurements were standardized and correlated, with 24-day averages and monthly averages yielding correlation coefficients of r = 0.72 and r = 0.75, respectively.&lt;br&gt;FTIR and IASI were also compared against the GEOS-Chem model, run at 2&amp;#176; by 2.5&amp;#176; resolution, to assess model performance and investigate correlation of the model output with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (domain spanning from 35&amp;#176;N to 53&amp;#176;N, and 93.75&amp;#176;W to 63.75&amp;#176;W) resulted in r = 0.62, and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r&lt;sup&gt;2&lt;/sup&gt; = 0.38, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r&lt;sup&gt;2&lt;/sup&gt; = 0.26, indicating that a finer spatial resolution is needed to adequately model the variability of NH&lt;sub&gt;3&lt;/sub&gt;. This study also examines two case studies of NH&lt;sub&gt;3&lt;/sub&gt; enhancements due to biomass burning plumes, in August 2014 and May 2016. In these events, enhancements in both the total columns and surface NH3, were observed.&lt;/p&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt;

A data-driven approach for mapping global surface soil moisture at 100 m using high-resolution remote sensing data and land surface parameters

2021 ◽  
Author(s):  
Jingyi Huang ◽  
Ankur Desai ◽  
Jun Zhu ◽  
Alfred Hartemink ◽  
Paul Stoy ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
High Resolution ◽  
Land Surface ◽  
Regional Scale ◽  
Remote Sensing Data ◽  
Field Scale ◽  
Land Surface Parameters ◽  
Global Surface

&lt;p&gt;Current in situ soil moisture monitoring networks are sparsely distributed while remote sensing satellite soil moisture maps have a very coarse spatial resolution. In this study, an empirical global surface soil moisture (SSM) model was established via fusion of in situ continental and regional scale soil moisture networks, remote sensing data (SMAP and Sentinel-1) and high-resolution land surface parameters (e.g., soil texture, terrain) using a quantile random forest (QRF) algorithm. The model had a spatial resolution of 100m and performed moderately well under cultivated, herbaceous, forest, and shrub soils (R&lt;sup&gt;2&lt;/sup&gt; = 0.524, RMSE = 0.07 m&lt;sup&gt;3&lt;/sup&gt; m&lt;sup&gt;&amp;#8722;3&lt;/sup&gt;). It has a relatively good transferability at the regional scale among different continental and regional networks (mean RMSE = 0.08&amp;#8211;0.10 m&lt;sup&gt;3&lt;/sup&gt; m&lt;sup&gt;&amp;#8722;3&lt;/sup&gt;). The global model was then applied to map SSM dynamics at 30&amp;#8211;100m across a field-scale network (TERENO-W&amp;#252;stebach) in Germany and an 80-ha irrigated cropland in Wisconsin, USA. Without local training data, the model was able to delineate the variations in SSM at the field scale but contained large bias. With the addition of 10% local training datasets (&amp;#8220;spiking&amp;#8221;), the bias of the model was significantly reduced. The QRF model was also affected by the resolution and accuracy of soil maps. It was concluded that the empirical model has the potential to be applied elsewhere across the globe to map SSM at the regional to field scales for research and applications. Future research is required to improve the performance of the model by incorporating more field-scale soil moisture sensor networks and high-resolution soil maps as well as assimilation with process-based water flow models.&lt;/p&gt;

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