scholarly journals Build, measure, understand: Pupils contributing to meteorological measurement campaigns.

2021 ◽  
Author(s):  
Martin Göber ◽  
Henning Rust ◽  
Thomas Kox ◽  
Bianca Wentzel ◽  
Christopher Böttcher ◽  
...  
Keyword(s):  
Weather Forecasting ◽  
Cold Pool ◽  
Small Scale ◽  
Atmospheric Measurements ◽  
High Resolution Data ◽  
Representative Study ◽  
Spatio Temporal ◽  
Observed Damage ◽  
Weather Risks ◽  
Resolution Data

<p>Voluntary weather measurements have a long tradition and the opportunities have recently expanded with that the advent of the Internet of Things. Atmospheric measurements are prototypical examples for the maker community and popular means to strengthen interest in STEM subjects. In two projects in Germany  (in Brandenburg, within the FESSTVaL (Field Experiment on submesoscale spatio-temporal variability in Lindenberg) measurement campaign initiated by the Hans-Ertel-Center for Weather Research, and in Bavaria, in the KARE-Citizen Science  project), we use a weather station to be assembled by pupils as a participatory vehicle to increase interest in and understanding of weather and climate, as well as of weather forecasting, and to generate high resolution data for research.</p><p>The devices measure e.g. temperature, humidity, radiation, pressure and precipitation in the students' immediate environment. They can be placed in almost any location, since they operate independent of W-LAN and external power supply. The data is visualized directly via a web app. Students report weather impacts, such as observed damage or their own exposure to weather. Due to the pandemic, only a few dozens pupils were able to participate and building their devices had to be done with digital guidance and video support. Further online materials on understanding weather forecasting and its uncertainty were provided.</p><p>Understanding of weather risks was surveyed before and after participation to detect any changes. Students were asked questions about thunderstorm, rain and heat events and climatic changes since 1880. The results show a good understanding of weather risks compared to a population of all ages representative study. In online workshops pupils together with the scientists scetched and discussed the influence of the placement of their stations on their measurements. Interesting meteorological phenomena were discovered in the dataset, e.g. a cold pool that can form during a thunderstorm and trigger new ones. Thus, our network of higher spatial and temporal resolution data collected by the pupils has the potential to study these small-scale phenomena in more detail than with professional networks of about 25 km spacing.</p>

Objective Determination of Feature Resolution in Two Sea Surface Temperature Analyses

2013 ◽  
Vol 26 (8) ◽  
pp. 2514-2533 ◽  
Author(s):  
Richard W. Reynolds ◽  
Dudley B. Chelton ◽  
Jonah Roberts-Jones ◽  
Matthew J. Martin ◽  
Dimitris Menemenlis ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Data ◽  
Sea Surface ◽  
Small Scale ◽  
High Resolution Data ◽  
Data Coverage ◽  
Feature Resolution ◽  
Resolution Data

Abstract Considerable effort is presently being devoted to producing high-resolution sea surface temperature (SST) analyses with a goal of spatial grid resolutions as low as 1 km. Because grid resolution is not the same as feature resolution, a method is needed to objectively determine the resolution capability and accuracy of SST analysis products. Ocean model SST fields are used in this study as simulated “true” SST data and subsampled based on actual infrared and microwave satellite data coverage. The subsampled data are used to simulate sampling errors due to missing data. Two different SST analyses are considered and run using both the full and the subsampled model SST fields, with and without additional noise. The results are compared as a function of spatial scales of variability using wavenumber auto- and cross-spectral analysis. The spectral variance at high wavenumbers (smallest wavelengths) is shown to be attenuated relative to the true SST because of smoothing that is inherent to both analysis procedures. Comparisons of the two analyses (both having grid sizes of roughly ) show important differences. One analysis tends to reproduce small-scale features more accurately when the high-resolution data coverage is good but produces more spurious small-scale noise when the high-resolution data coverage is poor. Analysis procedures can thus generate small-scale features with and without data, but the small-scale features in an SST analysis may be just noise when high-resolution data are sparse. Users must therefore be skeptical of high-resolution SST products, especially in regions where high-resolution (~5 km) infrared satellite data are limited because of cloud cover.

scholarly journals Recurrent Generative Networks for Multi-Resolution Satellite Data: An Application in Cropland Monitoring

2019 ◽  
Author(s):  
Xiaowei Jia ◽  
Mengdie Wang ◽  
Ankush Khandelwal ◽  
Anuj Karpatne ◽  
Vipin Kumar
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Temporal Patterns ◽  
Small Scale ◽  
High Resolution Data ◽  
Sensing Data ◽  
Coarse Resolution ◽  
Sequential Models ◽  
Resolution Data

Effective and timely monitoring of croplands is critical for managing food supply. While remote sensing data from earth-observing satellites can be used to monitor croplands over large regions, this task is challenging for small-scale croplands as they cannot be captured precisely using coarse-resolution data. On the other hand, the remote sensing data in higher resolution are collected less frequently and contain missing or disturbed data. Hence, traditional sequential models cannot be directly applied on high-resolution data to extract temporal patterns, which are essential to identify crops. In this work, we propose a generative model to combine multi-scale remote sensing data to detect croplands at high resolution. During the learning process, we leverage the temporal patterns learned from coarse-resolution data to generate missing high-resolution data. Additionally, the proposed model can track classification confidence in real time and potentially lead to an early detection. The evaluation in an intensively cultivated region demonstrates the effectiveness of the proposed method in cropland detection.

Participation of pupils in atmospheric measurements -- Potential for increasing climate change risk awareness and data availability for weather and climate research

2021 ◽  
Author(s):  
Henning Rust ◽  
Bianca Wentzel ◽  
Thomas Kox ◽  
Jonas Lehmke ◽  
Christopher Böttcher ◽  
...  
Keyword(s):  
Climate Change ◽  
Data Availability ◽  
Smart Devices ◽  
Cold Pool ◽  
Atmospheric Measurements ◽  
School Students ◽  
High Resolution Data ◽  
Main Site ◽  
Weather And Climate ◽  
Set Up

<p>Voluntarily measuring atmospheric characteristics by citizens has a long tradition. Possibilities has been increasing in the last years with the rise of smart devices and the internet-of-things (IoT). Atmospheric measurements are also prototypical project examples within the Maker community. Maker projects (i.e. IoT-/technology-oriented projects) are popular means of strengthening interest in STEM subjects among pupils. In the frame of two projects, we use an IoT-based weather station to be assembled by pupils as a participatory vehicle to a) raise interest in and understanding of weather and climate, as well as weather forecasts, and b) obtain additional data to be used in scientific projects.  </p><p>In the project KARE-CS  (funding: German Ministry for Education and Research, BMBF), a lay weather network has been set up together with pupils in the Bavarian Oberland south of Munich in 2020 and 2021. The students' devices measure temperature, pressure, humidity, solar radiation and precipitation in their direct environment, data is visualized on their smartphones (or any device running a browser) and updated every few minutes. Pupils also report weather impacts such as observed damages or their own concernment about weather events. These data are evaluated in workshops involving the students, their teachers, local partners and scientists. Atmospheric as well as impact data is evaluated for further use in scientifc studies, such as within the mother project KARE (). KARE-CS focuses on upper secondary school students as participants and aim at a development of competences among teachers as multipliers and pupils, particularly in terms of climate change adaptation, understanding natural hazards and risks and in taking personal precautions.</p><p>A similar setup is used for supporting the measurement campaing FESSTVaL ( initiated for 2021 by the Hans-Ertel-Centre for Weather Research ( ). The pupils' network will consist of 100 instruments within and close to the campaign's main site. Additionally to the communication and education-oriented goals mentioned above, the resulting spatially and temporally high-resolution data is used for research on thunderstorm development and cold pool characteristics within the Hans-Ertel-Centre.</p>

scholarly journals Inclusion of Narrow Flow Paths between Buildings in Coarser Grids for Urban Flood Modeling: Virtual Surface Links

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2629
Author(s):  
Sebastian Ramsauer ◽  
Jorge Leandro ◽  
Qing Lin
Keyword(s):  
High Resolution ◽  
Computational Time ◽  
Water Volume ◽  
Small Scale ◽  
Flood Modeling ◽  
Flow Paths ◽  
Urban Flood ◽  
High Resolution Data ◽  
Simulation Results ◽  
Resolution Data

Urban flood modeling benefits from new remote sensing technologies, which provide high-resolution data and allow the consideration of small-scale urban key features. Since high-resolution data often result in large simulation runtimes, coarsening of the 2D grid via resampling techniques can be used to achieve a good balance between accuracy and computation time. However, the representation of urban features and topographical properties degrades, since small-scale features are blurred. Therefore, narrow flow paths between buildings are often not considered, building’s sizes are overestimated, and their arrangement in the grid changes. Thus, flow paths change and waterways are blocked, leading to incorrect inundations around buildings. This paper develops a method to improve the simulation results of coarser grids by adding virtual surface links (VSL) between buildings. The VSL mimic the flow paths of a high-resolution model in the areas of interest. The approach is developed for dual-drainage 1D/2D models. The approach shows a visible improvement at the localized level where the VSL are applied, in terms of under/overestimating flooding and a moderate overall improvement of the simulation results. Relatively to the model resolution of 2 m, the computational time, by applying this method, is reduced by 93.6% when using a 5 m grid and by 99% when using a 10 m grid. For a small test case, where the local effects are investigated, the error in the maximum water volume, relative to a grid size of 2 m, is reduced from 69.63% to 5.03% by using a 5 m grid and from 152.75% to 22.92% for a 10 m grid.

Using high resolution data to reveal depth-dependent mechanisms that drive land subsidence: The Venice coast, Italy

2009 ◽  
Vol 474 (1-2) ◽  
pp. 271-284 ◽  
Author(s):  
L. Tosi ◽  
P. Teatini ◽  
L. Carbognin ◽  
G. Brancolini
Keyword(s):  
High Resolution ◽  
Land Subsidence ◽  
High Resolution Data ◽  
Resolution Data

scholarly journals Small-scale spatio-temporal characteristics of accumulation rates in western Dronning Maud Land, Antarctica

2008 ◽  
Vol 54 (185) ◽  
pp. 315-323 ◽  
Author(s):  
Helgard Anschütz ◽  
Daniel Steinhage ◽  
Olaf Eisen ◽  
Hans Oerter ◽  
Martin Horwath ◽  
...  
Keyword(s):  
Accumulation Rate ◽  
Temporal Variations ◽  
Spatial Variations ◽  
Small Scale ◽  
Accumulation Rates ◽  
Order Of Magnitude ◽  
Dronning Maud Land ◽  
Spatio Temporal ◽  
Ground Penetrating ◽  
Firn Core

AbstractSpatio-temporal variations of the recently determined accumulation rate are investigated using ground-penetrating radar (GPR) measurements and firn-core studies. The study area is located on Ritscherflya in western Dronning Maud Land, Antarctica, at an elevation range 1400–1560 m. Accumulation rates are derived from internal reflection horizons (IRHs), tracked with GPR, which are connected to a dated firn core. GPR-derived internal layer depths show small relief along a 22 km profile on an ice flowline. Average accumulation rates are about 190 kg m−2 a−1 (1980–2005) with spatial variability (1σ) of 5% along the GPR profile. The interannual variability obtained from four dated firn cores is one order of magnitude higher, showing 1σ standard deviations around 30%. Mean temporal variations of GPRderived accumulation rates are of the same magnitude or even higher than spatial variations. Temporal differences between 1980–90 and 1990–2005, obtained from two dated IRHs along the GPR profile, indicate temporally non-stationary processes, linked to spatial variations. Comparison with similarly obtained accumulation data from another coastal area in central Dronning Maud Land confirms this observation. Our results contribute to understanding spatio-temporal variations of the accumulation processes, necessary for the validation of satellite data (e.g. altimetry studies and gravity missions such as Gravity Recovery and Climate Experiment (GRACE)).

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