scholarly journals The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather radar network

2013 ◽  
Vol 6 (6) ◽  
pp. 10699-10730
Author(s):  
A. Devasthale ◽  
L. Norin
Keyword(s):  
Temporal Variability ◽  
High Intensity ◽  
Large Scale ◽  
Weather Radar ◽  
Radar Data ◽  
The Arctic ◽  
Northern Sweden ◽  
Late Night ◽  
Spatio Temporal ◽  
Precipitation Events

Abstract. Using measurements from the national network of 12 weather radar stations for the last decade (2000–2010), we investigate the large-scale spatio-temporal variability of precipitation over Sweden. These statistics provide useful information to evaluate regional climate models as well as for hydrology and energy applications. A strict quality control is applied to filter out noise and artifacts from the radar data. We focus on investigating four distinct aspects namely, the diurnal cycle of precipitation and its seasonality, the dominant time scale (diurnal vs. seasonal) of variability, precipitation response to different wind directions, and the correlation of precipitation events with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO). When classified based on their intensity, moderate to high intensity events (precipitation > 0.34 mm (3 h)−1) peak distinctly during late afternoon over the majority of radar stations in summer and during late night or early morning in winter. Precipitation variability is highest over the southwestern parts of Sweden. It is shown that the high intensity events (precipitation > 1.7mm (3 h)−1) are positively correlated with NAO and AO (esp. over northern Sweden), while the low intensity events are negatively correlated (esp. over southeastern parts). It is further observed that southeasterly winds often lead to intense precipitation events over central and northern Sweden, while southwesterly winds contribute most to the total accumulated precipitation for all radar stations. Apart from its operational applications, the present study demonstrates the potential of the weather radar data set for studying climatic features of precipitation over Sweden.

scholarly journals The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather radar network

2014 ◽  
Vol 7 (6) ◽  
pp. 1605-1617 ◽  
Author(s):  
A. Devasthale ◽  
L. Norin
Keyword(s):  
Temporal Variability ◽  
High Intensity ◽  
Large Scale ◽  
Weather Radar ◽  
Radar Data ◽  
The Arctic ◽  
Northern Sweden ◽  
Late Night ◽  
Spatio Temporal ◽  
Precipitation Events

Abstract. Using measurements from the national network of 12 weather radar stations for the 11-year period 2000–2010, we investigate the large-scale spatio-temporal variability of precipitation over Sweden. These statistics provide useful information to evaluate regional climate models as well as for hydrology and energy applications. A strict quality control is applied to filter out noise and artifacts from the radar data. We focus on investigating four distinct aspects: the diurnal cycle of precipitation and its seasonality, the dominant timescale (diurnal versus seasonal) of variability, precipitation response to different wind directions, and the correlation of precipitation events with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO). When classified based on their intensity, moderate- to high-intensity events (precipitation > 0.34 mm/3 h) peak distinctly during late afternoon over the majority of radar stations in summer and during late night or early morning in winter. Precipitation variability is highest over the southwestern parts of Sweden. It is shown that the high-intensity events (precipitation > 1.7 mm/3 h) are positively correlated with NAO and AO (esp. over northern Sweden), while the low intensity events are negatively correlated (esp. over southeastern parts). It is further observed that southeasterly winds often lead to intense precipitation events over central and northern Sweden, while southwesterly winds contribute most to the total accumulated precipitation for all radar stations. Apart from its operational applications, the present study demonstrates the potential of the weather radar data set for studying climatic features of precipitation over Sweden.

Dynamics of Aeolian Sand Streamers and Airflow Turbulence over a Beach Surface

2021 ◽  
Author(s):  
Andreas Baas
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Temporal Variability ◽  
Large Scale ◽  
Sonic Anemometer ◽  
Dynamic Structure ◽  
Sand Transport ◽  
Video Imagery ◽  
Spatio Temporal ◽  
The Impact

<p>Sand transport by wind over granular beds displays dynamic structure and organisation in the form of streamers (aka ‘sand snakes’) that appear, meander and intertwine, and then dissipate as they are advected downwind. These patterns of saltating grain populations are thought to be initiated and controlled by coherent flow structures in the turbulent boundary layer wind that scrape over the bed surface raking up sand into entrainment. Streamer behaviour is thus fundamental to understanding sand transport dynamics, in particular its strong spatio-temporal variability, and is equally relevant to granular transport in other geophysical flows (fluvial, submarine).</p><p>This paper presents findings on streamer dynamics and associated wind turbulence observed in a field experiment on a beach, with measurements from 30Hz video-imagery using Large-Scale Particle Image Velocimetry (LS-PIV), combined with 50Hz wind measurements from 3D sonic anemometry and co-located sand transport rate monitoring using an array of laser particle counters (‘Wenglors’), all taking place over an area of ~10 m<sup>2</sup> and over periods of several minutes. The video imagery was used to identify when and where streamers advected past the sonic anemometer and laser sensors so that relationships could be detected between the passage of turbulence structures in the airflow and the length- and time-scales, propagation speeds, and sand transport intensities of associated streamers. The findings form the basis for a phenomenological model of streamer dynamics under turbulent boundary layer flows that predicts the impact of spatio-temporal variability on local measurement of sand transport.</p>

scholarly journals Arctic avian predators synchronise their spring migration with the northern progression of snowmelt

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Teja Curk ◽  
Ivan Pokrovsky ◽  
Nicolas Lecomte ◽  
Tomas Aarvak ◽  
David F. Brinker ◽  
...  
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
The Arctic ◽  
Migratory Species ◽  
Migration Patterns ◽  
Predator Species ◽  
Movement Data ◽  
Breeding Grounds ◽  
Spatio Temporal ◽  
Spring Snowmelt

Abstract Migratory species display a range of migration patterns between irruptive (facultative) to regular (obligate), as a response to different predictability of resources. In the Arctic, snow directly influences resource availability. The causes and consequences of different migration patterns of migratory species as a response to the snow conditions remains however unexplored. Birds migrating to the Arctic are expected to follow the spring snowmelt to optimise their arrival time and select for snow-free areas to maximise prey encounter en-route. Based on large-scale movement data, we compared the migration patterns of three top predator species of the tundra in relation to the spatio-temporal dynamics of snow cover. The snowy owl, an irruptive migrant, the rough-legged buzzard, with an intermediary migration pattern, and the peregrine falcon as a regular migrant, all followed, as expected, the spring snowmelt during their migrations. However, the owl stayed ahead, the buzzard stayed on, and the falcon stayed behind the spatio-temporal peak in snowmelt. Although none of the species avoided snow-covered areas, they presumably used snow presence as a cue to time their arrival at their breeding grounds. We show the importance of environmental cues for species with different migration patterns.

scholarly journals Combining citizen science and weather radar data to study large‐scale bird movements

Ibis ◽  
2020 ◽  
Author(s):  
Nadja Weisshaupt ◽  
Teemu Lehtiniemi ◽  
Jarmo Koistinen
Keyword(s):  
Citizen Science ◽  
Large Scale ◽  
Weather Radar ◽  
Radar Data

scholarly journals Detecting and Tracking Communal Bird Roosts in Weather Radar Data

2020 ◽  
Vol 34 (01) ◽  
pp. 378-385
Author(s):  
Zezhou Cheng ◽  
Saadia Gabriel ◽  
Pankaj Bhambhani ◽  
Daniel Sheldon ◽  
Subhransu Maji ◽  
...  
Keyword(s):  
Latent Variable ◽  
Weather Radar ◽  
Radar Data ◽  
Learning System ◽  
Variable Model ◽  
Detection Model ◽  
Radar Images ◽  
Biological Phenomena ◽  
The Us ◽  
Spatio Temporal

The US weather radar archive holds detailed information about biological phenomena in the atmosphere over the last 20 years. Communally roosting birds congregate in large numbers at nighttime roosting locations, and their morning exodus from the roost is often visible as a distinctive pattern in radar images. This paper describes a machine learning system to detect and track roost signatures in weather radar data. A significant challenge is that labels were collected opportunistically from previous research studies and there are systematic differences in labeling style. We contribute a latent-variable model and EM algorithm to learn a detection model together with models of labeling styles for individual annotators. By properly accounting for these variations we learn a significantly more accurate detector. The resulting system detects previously unknown roosting locations and provides comprehensive spatio-temporal data about roosts across the US. This data will provide biologists important information about the poorly understood phenomena of broad-scale habitat use and movements of communally roosting birds during the non-breeding season.

scholarly journals Comparison of the GPM IMERG Final Precipitation Product to RADOLAN Weather Radar Data over the Topographically and Climatically Diverse Germany

2018 ◽  
Vol 10 (12) ◽  
pp. 2029 ◽  
Author(s):  
Thomas Ramsauer ◽  
Thomas Weiß ◽  
Philip Marzahn
Keyword(s):  
Spatial Variability ◽  
Winter Season ◽  
Weather Radar ◽  
Radar Data ◽  
Probability Of Detection ◽  
Statistical Measures ◽  
Weather Events ◽  
Precipitation Measurement ◽  
Spatio Temporal ◽  
Global Precipitation

Precipitation measurements provide crucial information for hydrometeorological applications. In regions where typical precipitation measurement gauges are sparse, gridded products aim to provide alternative data sources. This study examines the performance of NASA’s Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement Mission (IMERG, GPM) satellite precipitation dataset in capturing the spatio-temporal variability of weather events compared to the German weather radar dataset RADOLAN RW. Besides quantity, also timing of rainfall is of very high importance when modeling or monitoring the hydrologic cycle. Therefore, detection metrics are evaluated along with standard statistical measures to test both datasets. Using indices like “probability of detection” allows a binary evaluation showing the basic categorical accordance of the radar and satellite data. Furthermore, a pixel-by-pixel comparison is performed to assess the ability to represent the spatial variability of rainfall and precipitation quantity. All calculations are additionally carried out for seasonal subsets of the data to assess potentially different behavior due to differences in precipitation schemes. The results indicate significant differences between the datasets. Overall, GPM IMERG overestimates the quantity of precipitation compared to RADOLAN, especially in the winter season. Moreover, shortcomings in detection performance arise in this season with significant erroneously-detected, yet also missed precipitation events compared to the weather radar data. Additionally, along secondary mountain ranges and the Alps, topographically-induced precipitation is not represented in GPM data, which generally shows a lack of spatial variability in rainfall and snowfall estimates due to lower resolution.

scholarly journals Radar vision in the mapping of forest biodiversity from space

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Soyeon Bae ◽  
Shaun R. Levick ◽  
Lea Heidrich ◽  
Paul Magdon ◽  
Benjamin F. Leutner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Large Scale ◽  
External Validation ◽  
Predictive Ability ◽  
Radar Data ◽  
Forest Regions ◽  
Local Species ◽  
Spatio Temporal ◽  
Derived Data

Abstract Recent progress in remote sensing provides much-needed, large-scale spatio-temporal information on habitat structures important for biodiversity conservation. Here we examine the potential of a newly launched satellite-borne radar system (Sentinel-1) to map the biodiversity of twelve taxa across five temperate forest regions in central Europe. We show that the sensitivity of radar to habitat structure is similar to that of airborne laser scanning (ALS), the current gold standard in the measurement of forest structure. Our models of different facets of biodiversity reveal that radar performs as well as ALS; median R² over twelve taxa by ALS and radar are 0.51 and 0.57 respectively for the first non-metric multidimensional scaling axes representing assemblage composition. We further demonstrate the promising predictive ability of radar-derived data with external validation based on the species composition of birds and saproxylic beetles. Establishing new area-wide biodiversity monitoring by remote sensing will require the coupling of radar data to stratified and standardized collected local species data.

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