In situ quantification of spatial and temporal variability of hyporheic exchange in static and mobile gravel-bed rivers

2011 ◽  
Vol 26 (4) ◽  
pp. 604-612 ◽  
Author(s):  
Donald O. Rosenberry ◽  
P. Zion Klos ◽  
Andrew Neal
Keyword(s):  
Temporal Variability ◽  
Hyporheic Exchange ◽  
Spatial And Temporal Variability ◽  
Gravel Bed ◽  
Gravel Bed Rivers

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 Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO<sub>2</sub> measurements

2021 ◽  
Vol 14 (7) ◽  
pp. 5241-5269
Author(s):  
Vinod Kumar ◽  
Julia Remmers ◽  
Steffen Beirle ◽  
Joachim Fallmann ◽  
Astrid Kerkweg ◽  
...  
Keyword(s):  
High Resolution ◽  
Atmospheric Chemistry ◽  
Temporal Variability ◽  
Model System ◽  
West Germany ◽  
Optical Absorption Spectroscopy ◽  
Anthropogenic Emissions ◽  
Spatial And Temporal Variability ◽  
Daily Variability

Abstract. We present high spatial resolution (up to 2.2×2.2 km2) simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n) (MESSy-fied ECHAM and COSMO models nested n times). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMRs) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly-resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS (Multiple AXis Differential Optical Absorption Spectroscopy) measurements performed at Mainz (49.99∘ N, 8.23∘ E) were used to evaluate the simulated tropospheric vertical column densities (VCDs) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles (≤8∘), small biases in the range of −14 % to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases, indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly-resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when vertical mixing is suppressed, and the atmospheric lifetime of NO2 is relatively long.

scholarly journals Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data

2020 ◽  
Vol 12 (15) ◽  
pp. 2415
Author(s):  
Tuuli Soomets ◽  
Kristi Uudeberg ◽  
Kersti Kangro ◽  
Dainis Jakovels ◽  
Agris Brauns ◽  
...  
Keyword(s):  
Primary Production ◽  
Temporal Variability ◽  
Carbon Fixation ◽  
Remote Sensing Data ◽  
Spatial And Temporal Variation ◽  
Spatial And Temporal Variability ◽  
Phytoplankton Primary Production ◽  
Spatio Temporal ◽  
Lake Size

Phytoplankton primary production (PP) in lakes play an important role in the global carbon cycle. However, monitoring the PP in lakes with traditional complicated and costly in situ sampling methods are impossible due to the large number of lakes worldwide (estimated to be 117 million lakes). In this study, bio-optical modelling and remote sensing data (Sentinel-3 Ocean and Land Colour Instrument) was combined to investigate the spatial and temporal variation of PP in four Baltic lakes during 2018. The model used has three input parameters: concentration of chlorophyll-a, the diffuse attenuation coefficient, and incident downwelling irradiance. The largest of our studied lakes, Võrtsjärv (270 km2), had the highest total yearly estimated production (61 Gg C y−1) compared to the smaller lakes Lubans (18 Gg C y−1) and Razna (7 Gg C y−1). However, the most productive was the smallest studied, Lake Burtnieks (40.2 km2); although the total yearly production was 13 Gg C y−1, the daily average areal production was 910 mg C m−2 d−1 in 2018. Even if lake size plays a significant role in the total PP of the lake, the abundance of small and medium-sized lakes would sum up to a significant contribution of carbon fixation. Our method is applicable to larger regions to monitor the spatial and temporal variability of lake PP.

scholarly journals Estimation of turbulence parameters from scanning lidars and in-situ instrumentation in the Perdigão 2017 campaign

2019 ◽  
Author(s):  
Norman Wildmann ◽  
Nicola Bodini ◽  
Julie K. Lundquist ◽  
Ludovic Bariteau ◽  
Johannes Wagner
Keyword(s):  
Temporal Variability ◽  
Shear Zones ◽  
Spectral Width ◽  
Early Morning ◽  
Spatial And Temporal Variability ◽  
Atmospheric Conditions ◽  
Sonic Anemometers ◽  
Spatio Temporal ◽  
Lifting System

Abstract. The understanding of the sources, spatial distribution and temporal variability of turbulence in the atmospheric boundary layer (ABL) and improved simulation of its forcing processes require observations in a broad range of terrain types and atmospheric conditions. In this study, we estimate turbulence kinetic energy (TKE) dissipation rate using multiple techniques, including traditional in-situ measurements of sonic anemometers on meteorological towers, a hot-wire anemometer on a tethered lifting system (TLS), as well as remote-sensing retrievals from a vertically staring lidar and two lidars performing range-height indicator (RHI) scans. For the retrieval of ε from the lidar RHI scans, we introduce a modification of the Doppler Spectral Width (DSW) method. This method uses spatio-temporal averages of the variance of the line-of-sight (LOS) velocity and the turbulent broadening of the Doppler backscatter spectrum. We validate this method against the observations from the other instruments, also including uncertainty estimations for each method. The synthesis of the results from all instruments enables a detailed analysis of the spatial and temporal variability of ε across a valley between two parallel ridges at the Perdigão 2017 campaign. We find that the shear zones above and below nighttime low-level jets (LLJ) experience turbulence enhancements, as does the wake of a wind turbine (WT). We analyze in detail how ε varies in the early morning of 14 June 2017, when the turbulence in the valley, approximately eleven rotor diameters downstream of the WT, is still significantly enhanced by the WT wake.

scholarly journals Spatial–Temporal Variability of Snow Cover and Depth in the Qinghai–Tibetan Plateau

2017 ◽  
Vol 30 (4) ◽  
pp. 1521-1533 ◽  
Author(s):  
Wenfang Xu ◽  
Lijuan Ma ◽  
Minna Ma ◽  
Haicheng Zhang ◽  
Wenping Yuan
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Snow Cover ◽  
Temporal Variability ◽  
Snow Depth ◽  
Initial Increase ◽  
Spatial And Temporal Variability ◽  
Important Challenge ◽  
In Situ Observations

Abstract Changes in snow cover over the Qinghai–Tibetan Plateau have attracted much attention in recent years owing to climate change. Because of the limitations of in situ observations, only a few studies have analyzed the dynamics of snow cover. Using observations from 103 meteorological stations across the Qinghai–Tibetan Plateau, this study investigated the spatial and temporal variability of snow depth and the number of snow-cover days. The results show a very weak negative trend for the snow depth and the number of snow-cover days in spring and winter from 1961 to 2010, but two different trends were found: an initial increase followed by a decrease. In summer and autumn, snow depth and the number of snow-cover days show a significant decreasing trend for most sites. The duration of snow cover exhibits a significant decreasing trend (−3.5 ± 1.2 days decade−1), which was jointly controlled by a later snow starting time (1.6 ± 0.8 days decade−1) and an earlier snow ending time (−1.9 ± 0.8 days decade−1) consistent with a response to climate change. This study highlights the competing effects of rising temperatures and changing precipitation, which remain an important challenge in understanding and interpreting the observed changes in snow depth and the number of snow-cover days for the Qinghai–Tibetan Plateau.

scholarly journals Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO<sub>2</sub> measurements

2021 ◽  
Author(s):  
Vinod Kumar ◽  
Julia Remmers ◽  
Steffen Beirle ◽  
Joachim Fallmann ◽  
Astrid Kerkweg ◽  
...  
Keyword(s):  
High Resolution ◽  
Atmospheric Chemistry ◽  
Temporal Variability ◽  
Pearson Correlation ◽  
Model System ◽  
West Germany ◽  
Anthropogenic Emissions ◽  
Spatial And Temporal Variability ◽  
Daily Variability

Abstract. We present high spatial resolution (up to 2.2 × 2.2 km2 simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMR) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability, and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS measurements performed at Mainz (49.99° N, 8.23° E) were used to evaluate the simulated tropospheric vertical column densities (VCD) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles ≤ 8°), small biases in the range of −14 to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when the atmospheric lifetime of NO2 is relatively long.

scholarly journals Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign

2019 ◽  
Vol 12 (12) ◽  
pp. 6401-6423 ◽  
Author(s):  
Norman Wildmann ◽  
Nicola Bodini ◽  
Julie K. Lundquist ◽  
Ludovic Bariteau ◽  
Johannes Wagner
Keyword(s):  
Wind Turbine ◽  
Temporal Variability ◽  
Dissipation Rate ◽  
Shear Zones ◽  
Spectral Width ◽  
Energy Dissipation Rate ◽  
Spatial And Temporal Variability ◽  
Atmospheric Conditions ◽  
Sonic Anemometers

Abstract. The understanding of the sources, spatial distribution and temporal variability of turbulence in the atmospheric boundary layer, and improved simulation of its forcing processes require observations in a broad range of terrain types and atmospheric conditions. In this study, we estimate turbulence kinetic energy dissipation rate ε using multiple techniques, including in situ measurements of sonic anemometers on meteorological towers, a hot-wire anemometer on a tethered lifting system and remote-sensing retrievals from a vertically staring lidar and two lidars performing range–height indicator (RHI) scans. For the retrieval of ε from the lidar RHI scans, we introduce a modification of the Doppler spectral width method. This method uses spatiotemporal averages of the variance in the line-of-sight velocity and the turbulent broadening of the Doppler backscatter spectrum. We validate this method against the observations from the other instruments, also including uncertainty estimations for each method. The synthesis of the results from all instruments enables a detailed analysis of the spatial and temporal variability in ε across a valley between two parallel ridges at the Perdigão 2017 campaign. We analyze in detail how ε varies in the night from 13 to 14 June 2017. We find that the shear zones above and below a nighttime low-level jet experience turbulence enhancements. We also show that turbulence in the valley, approximately 11 rotor diameters downstream of an operating wind turbine, is still significantly enhanced by the wind turbine wake.

scholarly journals Evaluación de dos modelos para la estimación de la evapotranspiración de referencia con datos CERES

2018 ◽  
pp. 87 ◽  
Author(s):  
F. Carmona ◽  
M. Holzman ◽  
R. Rivas ◽  
M.F. Degano ◽  
E. Kruse ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Reference Evapotranspiration ◽  
Important Variable ◽  
Spatial And Temporal Variability ◽  
Suitable Alternative ◽  
Pampean Region ◽  
Daily Scale ◽  
Weather Stations ◽  
Good Agreement

<p>Evapotranspiration is the most important variable in the Pampas plain. Information provided by sensors onboard satellite missions allows represent the spatial and temporal variability of evapotranspiration, which cannot be achieved using only measurements of weather stations. In this work, the Priestley and Taylor (PT) and FAO Penman Monteith (FAO PM) equations were adapted to estimate the reference evapotranspiration, ET<sub>0</sub> , using only CERES satellite products (SYN1 and CldTypHist). In order to evaluate the reference evapotranspiration from CERES, a comparison with in situ measurements was conducted. We used ET data provided by the Oficina de Riesgo Agropecuario, corresponding to 24 stations placed in the Pampean Region of Argentina (2001-2016). Results showed very good agreement between the estimates with CERES products and in situ values, with errors between ±0.8 and ±1.1 mm d–<sup>1 </sup>and r<sup>2</sup>  greater than 0.75  at daily scale, and errors between ±14  and ±19  mm month<sup>–1</sup>  and r<sup>2</sup>   greater than 0.9, at monthly scale better results were obtained with adapted model FAO PM than PT. Finally, ET<sub>0</sub> monthly maps for the Pampean Region of Argentina were elaborated, which allowed knowing the temporal-spatial variation in the validation area. In conclusion, the methods presented here are a suitable alternative to estimate the reference evapotranspiration without requiring ground measurements.</p>

Spatial and Temporal Variability of Benthic Respiration in a Scottish Sea Loch Impacted by Fish Farming: A Combination of In Situ Techniques

2012 ◽  
Vol 18 (6) ◽  
pp. 515-541 ◽  
Author(s):  
Cécile Cathalot ◽  
Bruno Lansard ◽  
Per O. J. Hall ◽  
Anders Tengberg ◽  
Elin Almroth-Rosell ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Fish Farming ◽  
Spatial And Temporal Variability ◽  
In Situ Techniques ◽  
Benthic Respiration
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