Spatial and Temporal Variability of Grain Size and Small-Scale Mophology

2006 ◽  
Author(s):  
Edith L. Gallagher ◽  
Jamie MacMahan
Keyword(s):  
Grain Size ◽  
Temporal Variability ◽  
Small Scale ◽  
Spatial And Temporal Variability

scholarly journals Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

2017 ◽  
Vol 21 (7) ◽  
pp. 3859-3878 ◽  
Author(s):  
Elena Cristiano ◽  
Marie-Claire ten Veldhuis ◽  
Nick van de Giesen
Keyword(s):  
Temporal Variability ◽  
Urban Areas ◽  
Rainfall Variability ◽  
Urban Environments ◽  
Hydrological Processes ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Hydrological Response ◽  
Weather Radars ◽  
New Instruments

Abstract. In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

scholarly journals Approaches to evaluate spatial and temporal variability of deep marine sediment characteristics under the impact of dense water formation events

2020 ◽  
Author(s):  
XAVIER DURRIEU de MADRON ◽  
MARION STABHOLZ ◽  
LARS-ERIC HEIMBÜRGER-BOAVIDA ◽  
DOMINIQUE AUBERT ◽  
PHILIPPE KERHERVÉ ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Temporal Variability ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Geochemical Composition ◽  
Dense Water ◽  
Water Formation ◽  
Dense Water Formation ◽  
Northwestern Mediterranean Sea ◽  
The Impact

Dense shelf water cascading and open-ocean convection frequently occurs in the Gulf of Lions, northwestern Mediterranean Sea. These intense dense water formation events are capable of supplying large amounts of particulate matter as well as remobilizing and dispersing local sediments and, therefore, are thought to leave an imprint on superficial deposits. Here, we compared the spatial variability of the superficial sediment composition (grain size, organic parameters, and metals) at different scales (from decimetric to kilometric) on the continental slope and rise with the temporal variability linked to the occurrence of intense dense water formation events. The spatial and temporal variability of the geochemical composition of deep sediments was assessed using multivariate and geostatistical analysis. The results indicate that, on the outer reach of the Cap de Creus Canyon, where both processes interact, no clear relation was found between the temporal variability of the superficial sediment and the deep-water formation events, and that the small-scale spatial variability of the sediment is masking the temporal variability. Measurements across the southern slope indicate the presence of a somehow distinct geochemical signature that likely results from the influence of recurrent intense, dense water formation events as well as an unabating bottom trawling activity.

scholarly journals Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network

2013 ◽  
Vol 17 (6) ◽  
pp. 2195-2208 ◽  
Author(s):  
N. Peleg ◽  
M. Ben-Asher ◽  
E. Morin
Keyword(s):  
Temporal Variability ◽  
Rainfall Variability ◽  
Rain Gauge ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Radar Rainfall ◽  
Rain Gauges ◽  
Daily Scale ◽  
Rain Gauge Network ◽  
Hydrological Applications

Abstract. Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4 km2 study area near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar, located 63 km from the study area. The gauge–rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale) and increased as the timescale increased. The variance reduction factor (VRF), representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6% for the 1 min timescale to 0.07% for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF < 5%) on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20% to the total difference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27 dB for 3 min timescale to 3.21 dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for hydrological applications of the radar data. Rainfall measurements collected with this dense rain gauge network will be used for further examination of small-scale rainfall's spatial and temporal variability in the coming years.

scholarly journals Spatial and temporal variability in summer snow pack in the Dronning Maud Land, Antarctica

2010 ◽  
Vol 4 (3) ◽  
pp. 1107-1150
Author(s):  
T. Vihma ◽  
O.-P. Mattila ◽  
R. Pirazzini ◽  
M. M. Johansson
Keyword(s):  
Standard Deviation ◽  
Temporal Variability ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Snow Pack ◽  
Snow Density ◽  
Ice Shelf ◽  
Dronning Maud Land ◽  
Larsen Ice Shelf ◽  
Snow Temperature

Abstract. Snow temperature, density, and layering were measured in four summers in the Dronning Maud Land, Antarctica. Data from a 310-km-long transect showed that the most homogeneous snow pack located in the Riiser-Larsen Ice Shelf, while horizontal gradients in snow density, temperature, and hardness were larger in the escarpment region. In the local scale, day-to-day temporal variability dominated the standard deviation of snow temperature, while the diurnal cycle was next important, and horizontal variability in the scale of 0.4 to 10 m was the smallest component. The day-to-day and total small-scale variability decreased exponentially with depth with an e-folding depth at 0.25 to 0.30 m. Snow temperature depended on the cloud cover in the uppermost 0.30 m and snow density in the uppermost 0.10 m. Both in the intra-pit and transect scales, the ratio of horizontal to temporal variability increased with depth. In the intra-pit scale the temporal variability in snow density exceeded the horizontal variability throughout the uppermost 0.50 m layer, but in the 100-km scale only in the uppermost centimetres. The horizontal standard deviation of snow density increased rapidly between the scales of 0.4 and 2 m, and much more gradually from 101 to 102 m.

Evaluation of a WRF model in forecasting extreme rainfall in the urban data-scarce coastal city of Alexandria, Egypt

2021 ◽  
Author(s):  
Adele Young ◽  
Biswa Bhattacharya ◽  
Emma Daniels ◽  
Chris Zevenbergen
Keyword(s):  
High Resolution ◽  
Boundary Conditions ◽  
Temporal Variability ◽  
Weather Prediction ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Small Scale ◽  
Lead Times ◽  
Spatial And Temporal Variability ◽  
Urban Drainage

&lt;p&gt;High-resolution precipitation models are essential to forecast urban pluvial floods. Global Numerical Weather Prediction Models (NWPs) are considered too coarse to accurately forecast flooding at the city scale. High-resolution radar nowcasting can be either unavailable or insufficient to forecast at the required lead-times. &amp;#160;Downscaling models are used to increase the resolution and extend forecast by several days when initialised with global NWPs. However, resolving weather processes at smaller spatial scales and sub-daily temporal resolutions has its challenges and does not necessarily result in more accurate forecast but instead only increase the computational requirements. Additionally, in ungauged regions, forecast verification is a challenge as in-situ measurements and radar estimates remain scarce or non-existent. This research evaluates the ability of a dynamically downscaled WRF model to capture the spatial and temporal variability of rainfall suitable for an urban drainage flood forecast model and evaluated against IMERG Global Precipitation Model (GPM) Satellite Precipitation Products (SPPs).&lt;br&gt;&amp;#160;A WRF model was set-up with one-way nesting, three nested domains at horizontal grid resolutions 10km, 3.33km and 1km, a 1hourly temporal output, a spin-up time of 12 hours and evaluated at different lead times up to 48 hrs. The analysis was performed for three (3) &amp;#160;winter frontal systems during the period 2015-2019 in the highly urbanised coastal Mediterranean city of Alexandria in Egypt which experiences floods from extreme precipitation. The Global Forecast System (GFS), and European Centre for Medium Range (ECMWF) forecast were used as initial and lateral boundary conditions.&amp;#160;&lt;br&gt;Initial results indicate the WRF models could capture extreme rainfall for all events. There is some agreement with the IMERG data and the model correctly forecasted a decrease in rainfall as the systems transition from coastal to inland areas. In general, GFS and ECMWF initialised WRF models overestimated rainfall estimates compared to IMERG data. Differences in GFS and ECMWF initialised models (multi-model approach) highlight the sensitivity of models to initial and boundary conditions and emphasises the need for post-processing and data assimilation when possible to generate accurate small-scale features. A study such as this provides knowledge for understanding, future applications and limitations of using Quantitative Precipitation Forecasts (QPFs) in urban drainage models. Additionally, the potential use of IMERG GPM to verify spatial and temporal variability of forecast in ungauged and data-scarce regions. Future analysis will evaluate the skill of ensembles precipitation systems in characterising forecast uncertainty in such applications.&amp;#160;&lt;/p&gt;

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