Global energy and water cycle experiment (GEWEX) continental-scale international project (GCIP); reference data sets CD-ROM

Earth atmosphere is almost opaque in the infrared: about 374 W/m2 is absorbed by the atmosphere out of 396 W/m2 surface upward longwave radiation, and only about 22 W/m2 leaves the system unabsorbed in the atmospheric window. This makes rise to the idea to approximate the annual global mean energy flow system from a simple idealized greenhouse model, where the surface is surrounded by a single-layer shortwave (SW) transparent, longwave (LW) opaque, non-turbulent atmosphere. The energy flows in this geometry can be described by elementary arithmetic relationships. Starting from this model, the realistic Earth’s atmosphere can be achieved by introducing partial atmospheric SW opacity, partial atmospheric LW transparency and turbulent fluxes during the course of the deduction. The resulted global mean energy flow system is then compared to several data sets such as satellite observations from the CERES mission; estimates using direct surface observations and climate models; global energy and water cycle assessments; and independent detailed clear-sky radiative transfer computations. We find that the deduction from this idealized model approximates the real values in Earth energy budget with reasonable accuracy: the deduced fluxes and the observed ones are consistent within the acknowledged error of observations; while fundamental features of the initial geometry like special ratios and definite relationships between the fluxes are preserved.

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Multiple data parameter identification for nonlinear conceptual models

Water Science & Technology ◽

10.2166/wst.1997.0165 ◽

1997 ◽

Vol 36 (5) ◽

pp. 61-68 ◽

Cited By ~ 1

Author(s):

Hermann Eberl ◽

Amar Khelil ◽

Peter Wilderer

Keyword(s):

Optimization Problem ◽

Conceptual Models ◽

Reference Data ◽

Transport Model ◽

Calibration Method ◽

Data Sets ◽

Multiple Data ◽

Marquardt Algorithm ◽

Multicriteria Optimization Problem ◽

Higher Order Differential Equations

A numerical method for the identification of parameters of nonlinear higher order differential equations is presented, which is based on the Levenberg-Marquardt algorithm. The estimation of the parameters can be performed by using several reference data sets simultaneously. This leads to a multicriteria optimization problem, which will be treated by using the Pareto optimality concept. In this paper, the emphasis is put on the presentation of the calibration method. As an example identification of the parameters of a nonlinear hydrological transport model for urban runoff is included, but the method can be applied to other problems as well.

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Critical Aspects of Person Counting and Density Estimation

Journal of Imaging ◽

10.3390/jimaging7020021 ◽

2021 ◽

Vol 7 (2) ◽

pp. 21

Author(s):

Roland Perko ◽

Manfred Klopschitz ◽

Alexander Almer ◽

Peter M. Roth

Keyword(s):

Density Estimation ◽

Network Architecture ◽

Reference Data ◽

State Of The Art ◽

Limit State ◽

Ground Truth ◽

Data Sets ◽

Ground Truth Generation ◽

Baseline Approach ◽

Critical Aspects

Many scientific studies deal with person counting and density estimation from single images. Recently, convolutional neural networks (CNNs) have been applied for these tasks. Even though often better results are reported, it is often not clear where the improvements are resulting from, and if the proposed approaches would generalize. Thus, the main goal of this paper was to identify the critical aspects of these tasks and to show how these limit state-of-the-art approaches. Based on these findings, we show how to mitigate these limitations. To this end, we implemented a CNN-based baseline approach, which we extended to deal with identified problems. These include the discovery of bias in the reference data sets, ambiguity in ground truth generation, and mismatching of evaluation metrics w.r.t. the training loss function. The experimental results show that our modifications allow for significantly outperforming the baseline in terms of the accuracy of person counts and density estimation. In this way, we get a deeper understanding of CNN-based person density estimation beyond the network architecture. Furthermore, our insights would allow to advance the field of person density estimation in general by highlighting current limitations in the evaluation protocols.

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Transferability Intercomparison: An Opportunity for New Insight on the Global Water Cycle and Energy Budget

Bulletin of the American Meteorological Society ◽

10.1175/bams-88-3-375 ◽

2007 ◽

Vol 88 (3) ◽

pp. 375-384 ◽

Cited By ~ 39

Author(s):

E. S. Takle ◽

J. Roads ◽

B. Rockel ◽

W. J. Gutowski ◽

R. W. Arritt ◽

...

Keyword(s):

Energy Budget ◽

Climate Models ◽

Climate Model ◽

Water Cycle ◽

Regional Climate ◽

Climate Conditions ◽

Continental Scale ◽

Global Water Cycle ◽

Wide Range ◽

Global Water

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.

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From pole to pole: 33 years of physical oceanography onboard R/V <i>Polarstern</i>

Earth System Science Data ◽

10.5194/essd-9-211-2017 ◽

2017 ◽

Vol 9 (1) ◽

pp. 211-220 ◽

Cited By ~ 7

Author(s):

Amelie Driemel ◽

Eberhard Fahrbach ◽

Gerd Rohardt ◽

Agnieszka Beszczynska-Möller ◽

Antje Boetius ◽

...

Keyword(s):

Data Collection ◽

Water Cycle ◽

Heat Budget ◽

Ocean Dynamics ◽

The Arctic ◽

Sensor Calibration ◽

Data Sets ◽

Calibration Data ◽

Data Set ◽

Different Characteristics

Abstract. Measuring temperature and salinity profiles in the world's oceans is crucial to understanding ocean dynamics and its influence on the heat budget, the water cycle, the marine environment and on our climate. Since 1983 the German research vessel and icebreaker Polarstern has been the platform of numerous CTD (conductivity, temperature, depth instrument) deployments in the Arctic and the Antarctic. We report on a unique data collection spanning 33 years of polar CTD data. In total 131 data sets (1 data set per cruise leg) containing data from 10 063 CTD casts are now freely available at doi:10.1594/PANGAEA.860066. During this long period five CTD types with different characteristics and accuracies have been used. Therefore the instruments and processing procedures (sensor calibration, data validation, etc.) are described in detail. This compilation is special not only with regard to the quantity but also the quality of the data – the latter indicated for each data set using defined quality codes. The complete data collection includes a number of repeated sections for which the quality code can be used to investigate and evaluate long-term changes. Beginning with 2010, the salinity measurements presented here are of the highest quality possible in this field owing to the introduction of the OPTIMARE Precision Salinometer.

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An updated global COI barcode reference data set for Fall Armyworm (Spodoptera frugiperda) and first record of this species in Bhutan

10.1101/2020.05.17.100883 ◽

2020 ◽

Author(s):

Kiran Mahat ◽

Andrew Mitchell ◽

Tshelthrim Zangpo

Keyword(s):

Spodoptera Frugiperda ◽

Reference Data ◽

Dna Barcode ◽

Fall Armyworm ◽

First Record ◽

Molecular Techniques ◽

Data Sets ◽

Pest Species ◽

Maize Crop ◽

Data Set

AbstractWe report the first detection of Fall Armyworm (FAW), Spodoptera frugiperda (Smith, 1797), in Bhutan. FAW feeds on more than 300 plant species and is a serious pest of many. It has been spreading through Africa since 2016 and Asia since 2018. In Bhutan, this species was first detected in maize fields in the western part of the country in September 2019 and subsequently found infesting maize crop in southern parts of the country in December 2019 and April 2020. Using morphological and molecular techniques the presence of the first invading populations of S. frugiperda in Bhutan is confirmed through this study. We present an updated reference DNA barcode data set for FAW comprising 374 sequences, which can be used to reliably identify this serious pest species, and discuss some of the reasons why such compiled reference data sets are necessary, despite the publicly availability of the underlying data. We also report on a second armyworm species, the Northern Armyworm, Mythimna separata (Walker, 1865), in rice, maize and other crops in eighteen districts of Bhutan.

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Demonstrated Wavelength Portability of Raman Reference Data for Explosives and Chemical Detection

International Journal of Spectroscopy ◽

10.1155/2012/297056 ◽

2012 ◽

Vol 2012 ◽

pp. 1-11 ◽

Cited By ~ 10

Author(s):

Timothy J. Johnson ◽

Yin-Fong Su ◽

Kristin H. Jarman ◽

Brenda M. Kunkel ◽

Jerome C. Birnbaum ◽

...

Keyword(s):

Near Infrared ◽

Reference Data ◽

Current Sensor ◽

Data Sets ◽

Reference Library ◽

Wavelength Calibration ◽

Intensity Response ◽

Excitation Laser ◽

Key Issues ◽

Infrared Excitation

As Raman spectroscopy continues to evolve, questions arise as to the portability of Raman data: dispersive versus Fourier transform, wavelength calibration, intensity calibration, and in particular the frequency of the excitation laser. While concerns about fluorescence arise in the visible or ultraviolet, most modern (portable) systems use near-infrared excitation lasers, and many of these are relatively close in wavelength. We have investigated the possibility of porting reference data sets from one NIR wavelength system to another: We have constructed a reference library consisting of 145 spectra, including 20 explosives, as well as sundry other compounds and materials using a 1064 nm spectrometer. These data were used as a reference library to evaluate the same 145 compounds whose experimental spectra were recorded using a second 785 nm spectrometer. In 128 cases of 145 (or 88.3% including 20/20 for the explosives), the compounds were correctly identified with a mean “hit score” of 954 of 1000. Adding in criteria for when to declare a correct match versus when to declare uncertainty, the approach was able to correctly categorize 134 out of 145 spectra, giving a 92.4% accuracy. For the few that were incorrectly identified, either the matched spectra were spectroscopically similar to the target or the 785 nm signal was degraded due to fluorescence. The results indicate that imported data recorded at a different NIR wavelength can be successfully used as reference libraries, but key issues must be addressed: the reference data must be of equal or higher resolution than the resolution of the current sensor, the systems require rigorous wavelength calibration, and wavelength-dependent intensity response should be accounted for in the different systems.

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