scholarly journals MORPHODYNAMIC PROCESSES IN ESTUARIES - COMPARISON OF MARINE AND LIMNIC TIDAL FLATS

2011 ◽  
Vol 1 (32) ◽  
pp. 77
Author(s):  
Thorsten Albers ◽  
Dagmar Much ◽  
Nino Ohle ◽  
Nicole Von Lieberman ◽  
Eva Falke
Keyword(s):  
Extreme Events ◽  
Tidal Flat ◽  
Large Scale ◽  
Spatial Scales ◽  
Field Measurements ◽  
Weather Conditions ◽  
Water Levels ◽  
Seasonal Effects ◽  
Data Set ◽  
Investigation Area

Tidal flat areas in estuaries are affected by strong morphodynamics. Changes of sedimentation and erosion occur on different temporal and spatial scales. These changes challenge the responsible authorities due to the high importance of sufficient navigation channel depths and the ecological importance of those unique zones. In cooperation with the Hamburg Port Authority the Hamburg University of Technology runs broad field measurements on tidal flat areas in the Elbe estuary. The results provide a fundamental data set to improve the knowledge about morphodynamic processes. For more than 3 years water levels, waves, current parameters and suspended sediment concentrations are being recorded continuously and in a high resolution at different positions on a marine investigation area. Therefore, ADCP’s, optical backscatter sensors (OBS) and pressure transducers (PT) are used. To observe the consequences of the morphodynamic processes, the bathymetry of the investigation areas is determined with a multi-beam echo sounder (MBES) in frequent intervals as well as after extreme events like storm surges. Derived from the field data certain patterns of erosion, sediment transport and sedimentation could be observed depending on tidal currents, waves and large scale weather conditions. Seasonal effects are analyzed as well as the influence of extreme events. The observed processes are compared with data from a limnic investigation area, where a second, shorter field study was carried out.

scholarly journals CREATING MULTI-TEMPORAL MAPS OF URBAN ENVIRONMENTS FOR IMPROVED LOCALIZATION OF AUTONOMOUS VEHICLES

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 317-323
Author(s):  
J. Schachtschneider ◽  
C. Brenner
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Weather Conditions ◽  
Point Clouds ◽  
Urban Environments ◽  
Seasonal Effects ◽  
Data Set ◽  
Multi Temporal ◽  
One Year

Abstract. The development of automated and autonomous vehicles requires highly accurate long-term maps of the environment. Urban areas contain a large number of dynamic objects which change over time. Since a permanent observation of the environment is impossible and there will always be a first time visit of an unknown or changed area, a map of an urban environment needs to model such dynamics.In this work, we use LiDAR point clouds from a large long term measurement campaign to investigate temporal changes. The data set was recorded along a 20 km route in Hannover, Germany with a Mobile Mapping System over a period of one year in bi-weekly measurements. The data set covers a variety of different urban objects and areas, weather conditions and seasons. Based on this data set, we show how scene and seasonal effects influence the measurement likelihood, and that multi-temporal maps lead to the best positioning results.

scholarly journals Regional-scale lateral carbon transport and CO<sub>2</sub> evasion in temperate stream catchments

2017 ◽  
Vol 14 (21) ◽  
pp. 5003-5014 ◽  
Author(s):  
Katrin Magin ◽  
Celia Somlai-Haase ◽  
Ralf B. Schäfer ◽  
Andreas Lorke
Keyword(s):  
Catchment Area ◽  
Large Scale ◽  
Net Primary Production ◽  
Spatial Scales ◽  
Regional Scale ◽  
Stream Network ◽  
Carbon Export ◽  
Data Set ◽  
Catchment Areas ◽  
Temperate Stream

Abstract. Inland waters play an important role in regional to global-scale carbon cycling by transporting, processing and emitting substantial amounts of carbon, which originate mainly from their catchments. In this study, we analyzed the relationship between terrestrial net primary production (NPP) and the rate at which carbon is exported from the catchments in a temperate stream network. The analysis included more than 200 catchment areas in southwest Germany, ranging in size from 0.8 to 889 km2 for which CO2 evasion from stream surfaces and downstream transport with stream discharge were estimated from water quality monitoring data, while NPP in the catchments was obtained from a global data set based on remote sensing. We found that on average 13.9 g C m−2 yr−1 (corresponding to 2.7 % of terrestrial NPP) are exported from the catchments by streams and rivers, in which both CO2 evasion and downstream transport contributed about equally to this flux. The average carbon fluxes in the catchments of the study area resembled global and large-scale zonal mean values in many respects, including NPP, stream evasion and the carbon export per catchment area in the fluvial network. A review of existing studies on aquatic–terrestrial coupling in the carbon cycle suggests that the carbon export per catchment area varies in a relatively narrow range, despite a broad range of different spatial scales and hydrological characteristics of the study regions.

scholarly journals Improving pan-european hydrological simulation of extreme events through statistical bias correction of RCM-driven climate simulations

2011 ◽  
Vol 8 (2) ◽  
pp. 3883-3936 ◽  
Author(s):  
R. Rojas ◽  
L. Feyen ◽  
A. Dosio ◽  
D. Bavera
Keyword(s):  
Impact Assessment ◽  
Extreme Events ◽  
Bias Correction ◽  
Large Scale ◽  
Transfer Functions ◽  
Time Window ◽  
Control Period ◽  
Maximum Temperature ◽  
Data Set ◽  
Climate Simulations

Abstract. In this work we asses the benefits of removing bias in climate forcing data used for hydrological climate change impact assessment at pan-European scale, with emphasis on floods. Climate simulations from the HIRHAM5-ECHAM5 model driven by the SRES-A1B emission scenario are corrected for bias using a histogram equalization method. As predictand for the bias correction we employ gridded interpolated observations of precipitation, average, minimum, and maximum temperature from the E-OBS data set. Bias removal transfer functions are derived for the control period 1961–1990. These are subsequently used to correct the climate simulations for the control period, and, under the assumption of a stationary error model, for the future time window 2071–2100. Validation against E-OBS climatology in the control period shows that the correction method performs successfully in removing bias in average and extreme statistics relevant for flood simulation over the majority of the European domain in all seasons. This translates into considerably improved simulations with the hydrological model of observed average and extreme river discharges at a majority of 554 validation river stations across Europe. Probabilities of extreme events derived employing extreme value techniques are also more closely reproduced. Results indicate that projections of future flood hazard in Europe based on uncorrected climate simulations, both in terms of their magnitude and recurrence interval, are likely subject to large errors. Notwithstanding the inherent limitations of the large-scale approach used herein, this study strongly advocates the removal of bias in climate simulations prior to their use in hydrological impact assessment.

scholarly journals Regional-scale lateral carbon transport and CO<sub>2</sub> evasion in temperate stream catchments

2017 ◽  
Author(s):  
Katrin Magin ◽  
Celia Somlai-Haase ◽  
Ralf B. Schäfer ◽  
Andreas Lorke
Keyword(s):  
Large Scale ◽  
Net Primary Production ◽  
Spatial Scales ◽  
Regional Scale ◽  
Water Quality Monitoring ◽  
Stream Network ◽  
Data Set ◽  
Mean Values ◽  
Catchment Areas ◽  
Temperate Stream

Abstract. Inland waters play an important role in regional to global scale carbon cycling by transporting, processing and emitting substantial amounts of carbon, which originate mainly from their catchments. In this study, we analyzed the relationship between terrestrial net primary production (NPP) and the rate at which carbon is exported from the catchments in a temperate stream network. The analysis included more than 200 catchment areas in southwest Germany, ranging in size from 0.8 to 889 km2 for which CO2 evasion from stream surfaces and downstream transport with stream discharge were estimated from water quality monitoring data, while NPP in the catchments was obtained from a global data set based on remote sensing. We found that on average 2.7 % of terrestrial NPP (13.9 g C m2 yr−1) are exported from the catchments by streams and rivers, in which both CO2 evasion and downstream transport contributed about equally to this flux. The average carbon fluxes in the catchments of the study area resembled global and large-scale zonal mean values in many respects, including NPP, stream evasion as well as the catchment-specific total export rate of carbon in the fluvial network. A review of existing studies on aquatic-terrestrial coupling in the carbon cycle suggests that the catchment-specific carbon export varies in a relatively narrow range, despite a broad range of different spatial scales and hydrological characteristics of the study regions.

scholarly journals Projected Seasonal Changes in Large-Scale Global Precipitation and Temperature Extremes Based on the CMIP5 Ensemble

2020 ◽  
Vol 33 (13) ◽  
pp. 5651-5671 ◽  
Author(s):  
Wang Zhan ◽  
Xiaogang He ◽  
Justin Sheffield ◽  
Eric F. Wood
Keyword(s):  
Extreme Events ◽  
Large Scale ◽  
Climate Models ◽  
Spatial Scales ◽  
Extreme Temperature ◽  
Economic Losses ◽  
Temperature And Precipitation ◽  
Extreme Precipitation Events ◽  
The Future ◽  
Precipitation Events

AbstractOver the past decades, significant changes in temperature and precipitation have been observed, including changes in the mean and extremes. It is critical to understand the trends in hydroclimatic extremes and how they may change in the future as they pose substantial threats to society through impacts on agricultural production, economic losses, and human casualties. In this study, we analyzed projected changes in the characteristics, including frequency, seasonal timing, and maximum spatial and temporal extent, as well as severity, of extreme temperature and precipitation events, using the severity–area–duration (SAD) method and based on a suite of 37 climate models archived in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Comparison between the CMIP5 model estimated extreme events and an observation-based dataset [Princeton Global Forcing (PGF)] indicates that climate models have moderate success in reproducing historical statistics of extreme events. Results from the twenty-first-century projections suggest that, on top of the rapid warming indicated by a significant increase in mean temperature, there is an overall wetting trend in the Northern Hemisphere with increasing wet extremes and decreasing dry extremes, whereas the Southern Hemisphere will have more intense wet extremes. The timing of extreme precipitation events will change at different spatial scales, with the largest change occurring in southern Asia. The probability of concurrent dry/hot and wet/hot extremes is projected to increase under both RCP4.5 and RCP8.5 scenarios, whereas little change is detected in the probability of concurrent dry/cold events and only a slight decrease of the joint probability of wet/cold extremes is expected in the future.

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 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 Improving pan-European hydrological simulation of extreme events through statistical bias correction of RCM-driven climate simulations

2011 ◽  
Vol 15 (8) ◽  
pp. 2599-2620 ◽  
Author(s):  
R. Rojas ◽  
L. Feyen ◽  
A. Dosio ◽  
D. Bavera
Keyword(s):  
Impact Assessment ◽  
Extreme Events ◽  
Bias Correction ◽  
Large Scale ◽  
Transfer Functions ◽  
Time Window ◽  
Control Period ◽  
Maximum Temperature ◽  
Data Set ◽  
Climate Simulations

Abstract. In this work we asses the benefits of removing bias in climate forcing data used for hydrological climate change impact assessment at pan-European scale, with emphasis on floods. Climate simulations from the HIRHAM5-ECHAM5 model driven by the SRES-A1B emission scenario are corrected for bias using a histogram equalization method. As target for the bias correction we employ gridded interpolated observations of precipitation, average, minimum, and maximum temperature from the E-OBS data set. Bias removal transfer functions are derived for the control period 1961–1990. These are subsequently used to correct the climate simulations for the control period, and, under the assumption of a stationary error model, for the future time window 2071–2100. Validation against E-OBS climatology in the control period shows that the correction method performs successfully in removing bias in average and extreme statistics relevant for flood simulation over the majority of the European domain in all seasons. This translates into considerably improved simulations with the hydrological model of observed average and extreme river discharges at a majority of 554 validation river stations across Europe. Probabilities of extreme events derived employing extreme value techniques are also more closely reproduced. Results indicate that projections of future flood hazard in Europe based on uncorrected climate simulations, both in terms of their magnitude and recurrence interval, are likely subject to large errors. Notwithstanding the inherent limitations of the large-scale approach used herein, this study strongly advocates the removal of bias in climate simulations prior to their use in hydrological impact assessment.

scholarly journals A Bayesian approach to exploring the influence of climate variability modes on fire weather conditions and lightning-ignited wildfires

2021 ◽  
Author(s):  
Bryson C. Bates ◽  
Andrew J. Dowdy ◽  
Lachlan McCaw
Keyword(s):  
Climate Variability ◽  
Network Architecture ◽  
Large Scale ◽  
Weather Prediction ◽  
Weather Conditions ◽  
Fire Weather ◽  
Prescribed Burn ◽  
Data Set ◽  
Climate Modes

AbstractUnderstanding the relationships between large-scale, low-frequency climate variability modes, fire weather conditions and lighting-ignited wildfires has implications for fire-weather prediction, fire management and conservation. This article proposes a Bayesian network framework for quantifying the influence of climate modes on fire weather conditions and occurrence of lightning-ignited wildfires. The main objectives are to describe and demonstrate a probabilistic framework for identifying and quantifying the joint and individual relationships that comprise the climate-wildfire system; gain insight into potential causal mechanisms and pathways; gauge the influence of climate modes on fire weather and lightning-ignition relative to that of local-scale conditions alone; assess the predictive skill of the network; and motivate the use of techniques that are intuitive, flexible and for which user‐friendly software is freely available. A case study illustrates the application of the framework to a forested region in southwest Australia. Indices for six climate variability modes are considered along with two hazard variables (observed fire weather conditions and prescribed burn area), and a 41-year record of lightning-ignited wildfire counts. Using the case study data set, we demonstrate that the proposed framework: (1) is based on reasonable assumptions provided the joint density of the variables is converted to multivariate normal; (2) generates a parsimonious and interpretable network architecture; (3) identifies known or partially known relationships between the variables; (4) has potential to be used in a predictive setting for fire weather conditions; and (5) climate modes are more directly related to fire weather conditions than to lightning-ignition counts.

Measuring gravity on ice: An example from Wanapitei Lake, Ontario, Canada

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. J23-J29 ◽  
Author(s):  
Hernan A. Ugalde ◽  
Elizabeth L’Heureux ◽  
Richard Lachapelle ◽  
Bernd Milkereit
Keyword(s):  
Large Scale ◽  
Field Measurements ◽  
Noise Sources ◽  
Large Lakes ◽  
Data Set ◽  
Long Time ◽  
Calm Wind ◽  
Regional Gravity ◽  
The Impact

Large lakes have always represented a problem for regional gravity databases; the difficulty of access means gaps or coarse spacing in the sampling. Satellite, airborne, and shipborne gravity techniques are options, but the resolution and/or cost of these systems make them impractical or inaccurate for exploration or environmental studies, where the required resolution is [Formula: see text]. In this study, the feasibility of a ground gravity survey over a frozen lake where ice moves because of windy conditions is assessed. Lake Wanapitei, widely accepted as resulting from the impact of a meteorite 37 million years ago, is one of these cases in which the necessity of expanding coverage over poorly sampled regions arose from a significant gap between surface and airborne geophysical maps. Two gravity surveys were completed on the ice of Lake Wanapitei in the winters of 2003 and 2004. To study the structure, longtime series of gravity field measurements were recorded for 98 stations, allowing for improved control over the noise sources in the data. Final processing and integration with an existing regional data set in the area and the application of terrain corrections reduced the amplitude of the circular anomaly from 15 to [Formula: see text] and its diameter from 11 to [Formula: see text]. The feasibility of gravity surveys on ice was assessed, and we determined that for large-scale studies such as this one, the quality of the data, even under noisy conditions, was acceptable. However, for more detailed mapping, calm wind conditions and long time series are required.

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