Gap-filling strategies for annual VOC flux data sets

Abstract. Up to now the limited knowledge about the exchange of volatile organic compounds (VOCs) between the biosphere and the atmosphere is one of the factors which hinders more accurate climate predictions. Complete long-term flux data sets of several VOCs to quantify the annual exchange and validate recent VOC models are basically not available. In combination with long-term VOC flux measurements the application of gap-filling routines is inevitable in order to replace missing data and make an important step towards a better understanding of the VOC ecosystem–atmosphere exchange on longer timescales. We performed VOC flux measurements above a mountain meadow in Austria during two complete growing seasons (from snowmelt in spring to snow reestablishment in late autumn) and used this data set to test the performance of four different gap-filling routines, mean diurnal variation (MDV), mean gliding window (MGW), look-up tables (LUT) and linear interpolation (LIP), in terms of their ability to replace missing flux data in order to obtain reliable VOC sums. According to our findings the MDV routine was outstanding with regard to the minimization of the gap-filling error for both years and all quantified VOCs. The other gap-filling routines, which performed gap-filling on 24 h average values, introduced considerably larger uncertainties. The error which was introduced by the application of the different filling routines increased linearly with the number of data gaps. Although average VOC fluxes measured during the winter period (complete snow coverage) were close to zero, these were highly variable and the filling of the winter period resulted in considerably higher uncertainties compared to the application of gap-filling during the measurement period. The annual patterns of the overall cumulative fluxes for the quantified VOCs showed a completely different behaviour in 2009, which was an exceptional year due to the occurrence of a severe hailstorm, compared to 2011. Methanol was the compound which, at 381.5 mg C m−2 and 449.9 mg C m−2, contributed most to the cumulative VOC carbon emissions in 2009 and 2011, respectively. In contrast to methanol emissions, however, considerable amounts of monoterpenes (−327.3 mg C m−2) were deposited onto the mountain meadow during 2009 caused by a hailstorm. Other quantified VOCs had considerably lower influences on the annual patterns.

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Gap-filling strategies for annual VOC flux data sets

Biogeosciences Discussions ◽

10.5194/bgd-10-17785-2013 ◽

2013 ◽

Vol 10 (11) ◽

pp. 17785-17818 ◽

Cited By ~ 1

Author(s):

I. Bamberger ◽

L. Hörtnagl ◽

M. Walser ◽

A. Hansel ◽

G. Wohlfahrt

Keyword(s):

Linear Interpolation ◽

Winter Period ◽

Data Sets ◽

Gap Filling ◽

Data Set ◽

Mountain Meadow ◽

Flux Data ◽

Flux Measurements ◽

Annual Patterns

Abstract. Up to now the limited knowledge about the exchange of volatile organic compounds (VOCs) between the biosphere and the atmosphere is one of the factors which hinders more accurate climate predictions. Complete long-term flux data sets of several VOCs to quantify the annual exchange and validate recent VOC models are basically not available. In combination with long-term VOC flux measurements the application of gap-filling routines is inevitable in order to replace missing data and make an important step towards a better understanding of the VOC ecosystem-atmosphere exchange on longer time scales. We performed VOC flux measurements above a mountain meadow in Austria during two complete growing seasons (from snowmelt in spring to snow reestablishment in late autumn) and used this data set to test the performance of four different gap-filling routines, mean diurnal variation (MDV), mean gliding window (MGW), look up tables (LUT) and linear interpolation (LIP), in terms of their ability to replace missing flux data in order to obtain reliable VOC sums. According to our findings the MDV routine was outstanding with regard to the minimization of the gap-filling error for both years and all quantified VOCs. The other gap-filling routines, which performed gap-filling on 24 h average values, introduced considerably larger uncertainties. The error which was introduced by the application of the different filling routines increased linearly with the number of data gaps. Although average VOC fluxes measured during the winter period (complete snow coverage) were close to zero, these were highly variable and the filling of the winter period resulted in considerably higher uncertainties compared to the application of gap-filling during the measurement period. The annual patterns of the overall cumulative fluxes for the quantified VOCs showed a completely different behavior in 2009, which was an exceptional year due to the occurrence of a severe hailstorm, compared to 2011. Methanol was the compound which contributed with 381.5 mg C m–2 and 449.9 mg C m–2 most to the cumulative VOC carbon emissions in 2009 and 2011, respectively. In contrast to methanol emissions, however, considerable amounts of monoterpenes (−327.3 mg C m–2) were deposited to the mountain meadow in consequence to the hailstorm in 2009. Other quantified VOCs had considerably lower influences on the annual patterns.

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Gap filling strategies for long term energy flux data sets

Agricultural and Forest Meteorology ◽

10.1016/s0168-1923(00)00235-5 ◽

2001 ◽

Vol 107 (1) ◽

pp. 71-77 ◽

Cited By ~ 364

Author(s):

Eva Falge ◽

Dennis Baldocchi ◽

Richard Olson ◽

Peter Anthoni ◽

Marc Aubinet ◽

...

Keyword(s):

Energy Flux ◽

Data Sets ◽

Gap Filling ◽

Flux Data ◽

Term Energy

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Trophic Level Relationships in Pelagic Food Webs: Comparisons Derived from Long-Term Data Sets for Oneida Lake, New York (USA), and Lake St. George, Ontario (Canada)

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f92-177 ◽

1992 ◽

Vol 49 (8) ◽

pp. 1588-1596 ◽

Cited By ~ 19

Author(s):

Donald J. McQueen ◽

Edward L. Mills ◽

John L. Forney ◽

Mark R. S. Johannes ◽

John R. Post

Keyword(s):

New York ◽

Total Phosphorus ◽

Trophic Level ◽

Data Sets ◽

Phytoplankton Abundance ◽

Data Set ◽

Oneida Lake ◽

Pelagic Food Webs ◽

Term Data

We used standardized methods to analyze a 14-yr data set from Oneida Lake and a 10-yr data set from Lake St. George. We estimated mean summer concentrations of several trophic level indicators including piscivores, planktivores, zooplankton, phytoplankton, and total phosphorus, and we then investigated the relationships between these variables. Both data sets yielded similar long-term and short-term trends. The long-term mean annual trends were that (1) the relationships between concentrations of planktivores and zooplankton (including daphnids) were always negative, (2) the relationships between concentrations of zooplankton and various measures of phytoplankton abundance were unpredictable and never statistically significant, and (3) the relationships between total phosphorus and various measures of phytoplankton abundance were always positive. Over short periods, the data from both lakes showed periodic, strong top-down relationships between concentrations of zooplankton (especially large Daphnia) and chlorophyll a, but these events were unpredictable and were seldom related to piscivore abundance.

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Intention, Principle, Outputs and Aims of the Experimental Pavilion Research of Building Envelopes Including Windows for Wooden Buildings

Civil and Environmental Engineering ◽

10.1515/cee-2017-0005 ◽

2017 ◽

Vol 13 (1) ◽

pp. 42-51 ◽

Cited By ~ 3

Author(s):

Daniela Štaffenová ◽

Ján Rybárik ◽

Miroslav Jakubčík

Keyword(s):

Experimental Research ◽

Climatic Conditions ◽

Point Of View ◽

Physical Parameters ◽

Data Sets ◽

Data Set ◽

Building Envelopes ◽

Climate Conditions ◽

Time Period

AbstractThe aim of experimental research in the area of exterior walls and windows suitable for wooden buildings was to build special pavilion laboratories. These laboratories are ideally isolated from the surrounding environment, airtight and controlled by the constant internal climate. The principle of experimental research is measuring and recording of required physical parameters (e.g. temperature or relative humidity). This is done in layers of experimental fragment sections in the direction from exterior to interior, as well as in critical places by stable interior and real exterior climatic conditions. The outputs are evaluations of experimental structures behaviour during the specified time period, possibly during the whole year by stable interior and real exterior boundary conditions. The main aim of this experimental research is processing of long-term measurements of experimental structures and the subsequent analysis. The next part of the research consists of collecting measurements obtained with assistance of the experimental detached weather station, analysis, evaluation for later setting up of reference data set for the research locality, from the point of view of its comparison to the data sets from Slovak Hydrometeorological Institute (SHMU) and to localities with similar climate conditions. Later on, the data sets could lead to recommendations for design of wooden buildings.

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Prediction of Progestin Affinity for the Human Progesterone Receptor Based on Corrected RBA Data

Biomedical Chemistry Research and Methods ◽

10.18097/bmcrm00080 ◽

2018 ◽

Vol 1 (4) ◽

pp. e00080

Author(s):

A.V. Mikurova ◽

V.S. Skvortsov

Keyword(s):

Progesterone Receptor ◽

Prediction Equation ◽

Binding Activity ◽

Data Sets ◽

Data Set ◽

The Third ◽

Relative Binding ◽

Human Progesterone Receptor ◽

Nuclear Progesterone Receptor

The modeling of complexes of 3 sets of steroid and nonsteroidal progestins with the ligand-binding domain of the nuclear progesterone receptor was performed. Molecular docking procedure, long-term simulation of molecular dynamics and subsequent analysis by MM-PBSA (MM-GBSA) were used to model the complexes. Using the characteristics obtained by the MM-PBSA method two data sets of steroid compounds obtained in different scientific groups a prediction equation for the value of relative binding activity (RBA) was constructed. The RBA value was adjusted so that in all samples the actual activity was compared with the progesterone activity. The third data set of nonsteroidal compounds was used as a test. The resulted equation showed that the prediction results could be applied to both steroid molecules and nonsteroidal progestins.

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Long-Term Rainfall Forecast Model Based on The TabNet and LightGbm Algorithm

10.21203/rs.3.rs-107107/v1 ◽

2020 ◽

Author(s):

Tianyu Xu ◽

Yongchuan Yu ◽

Jianzhuo Yan ◽

Hongxia Xu

Keyword(s):

Prediction Model ◽

Feature Fusion ◽

Forecast Model ◽

Data Sets ◽

Good Prediction ◽

Data Set ◽

Rainfall Prediction ◽

Improve Model ◽

Probability Prediction

Abstract Due to the problems of unbalanced data sets and distribution differences in long-term rainfall prediction, the current rainfall prediction model had poor generalization performance and could not achieve good prediction results in real scenarios. This study uses multiple atmospheric parameters (such as temperature, humidity, atmospheric pressure, etc.) to establish a TabNet-LightGbm rainfall probability prediction model. This research uses feature engineering (such as generating descriptive statistical features, feature fusion) to improve model accuracy, Borderline Smote algorithm to improve data set imbalance, and confrontation verification to improve distribution differences. The experiment uses 5 years of precipitation data from 26 stations in the Beijing-Tianjin-Hebei region of China to verify the proposed rainfall prediction model. The test set is to predict the rainfall of each station in one month. The experimental results shows that the model has good performance with AUC larger than 92%. The method proposed in this study further improves the accuracy of rainfall prediction, and provides a reference for data mining tasks.

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Calibration methods for rotating shadowband irradiometers and optimizing the calibration duration

Atmospheric Measurement Techniques ◽

10.5194/amt-9-1601-2016 ◽

2016 ◽

Vol 9 (4) ◽

pp. 1601-1612 ◽

Cited By ~ 4

Author(s):

Wilko Jessen ◽

Stefan Wilbert ◽

Bijan Nouri ◽

Norbert Geuder ◽

Holger Fritz

Keyword(s):

Spectral Response ◽

Atmospheric Condition ◽

Resource Assessment ◽

Data Sets ◽

Data Set ◽

Direct Normal Irradiance ◽

Calibration Methods ◽

Long Term Result ◽

Time Of Year

Abstract. Resource assessment for concentrated solar power (CSP) needs accurate direct normal irradiance (DNI) measurements. An option for such measurement campaigns is the use of thoroughly calibrated rotating shadowband irradiometers (RSIs). Calibration of RSIs and Si-sensors is complex because of the inhomogeneous spectral response of these sensors and incorporates the use of several correction functions. One calibration for a given atmospheric condition and air mass might not be suitable under different conditions. This paper covers procedures and requirements of two calibration methods for the calibration of rotating shadowband irradiometers. The necessary duration of acquisition of test measurements is examined with regard to the site-specific conditions at Plataforma Solar de Almería (PSA) in Spain. Seven data sets of long-term test measurements were collected. For each data set, calibration results of varying durations were compared to its respective long-term result. Our findings show that seasonal changes of environmental conditions are causing small but noticeable fluctuation of calibration results. Calibration results within certain periods (i.e. November to January and April to May) show a higher likelihood of deviation. These effects can partially be attenuated by including more measurements from outside these periods. Consequently, the duration of calibrations at PSA can now be selected depending on the time of year in which measurements commence.

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High resolution atmospheric reconstruction for Europe 1948–2012: coastDat2

Earth System Science Data Discussions ◽

10.5194/essdd-6-779-2013 ◽

2013 ◽

Vol 6 (2) ◽

pp. 779-809 ◽

Cited By ~ 2

Author(s):

B. Geyer

Keyword(s):

Climate Model ◽

Numerical Models ◽

Regional Climate ◽

Reanalysis Data ◽

Data Sets ◽

Data Set ◽

Horizontal Grid ◽

Global Reanalysis ◽

Marine Climate

Abstract. The coastDat data sets were produced to give a consistent and homogeneous database mainly for assessing weather statistics and long-term changes for Europe, especially in data sparse regions. A sequence of numerical models was employed to reconstruct all aspects of marine climate (such as storms, waves, surges etc.) over many decades. Here, we describe the atmospheric part of coastDat2 (Geyer and Rockel, 2013, doi:10.1594/WDCC/coastDat-2_COSMO-CLM). It consists of a regional climate reconstruction for entire Europe, including Baltic and North Sea and parts of the Atlantic. The simulation was done for 1948 to 2012 with a regional climate model and a horizontal grid size of 0.22° in rotated coordinates. Global reanalysis data were used as forcing and spectral nudging was applied. To meet the demands on the coastDat data set about 70 variables are stored hourly.

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Revising the retrieval technique of a long-term stratospheric HNO<sub>3</sub> data set: from a constrained matrix inversion to the optimal estimation algorithm

Annales Geophysicae ◽

10.5194/angeo-29-1317-2011 ◽

2011 ◽

Vol 29 (7) ◽

pp. 1317-1330 ◽

Cited By ~ 3

Author(s):

I. Fiorucci ◽

G. Muscari ◽

R. L. de Zafra

Keyword(s):

Optimal Estimation ◽

Matrix Inversion ◽

The Arctic ◽

Inversion Method ◽

Data Sets ◽

Vertical Profiles ◽

Mixing Ratio ◽

Data Set ◽

The Antarctic

Abstract. The Ground-Based Millimeter-wave Spectrometer (GBMS) was designed and built at the State University of New York at Stony Brook in the early 1990s and since then has carried out many measurement campaigns of stratospheric O3, HNO3, CO and N2O at polar and mid-latitudes. Its HNO3 data set shed light on HNO3 annual cycles over the Antarctic continent and contributed to the validation of both generations of the satellite-based JPL Microwave Limb Sounder (MLS). Following the increasing need for long-term data sets of stratospheric constituents, we resolved to establish a long-term GMBS observation site at the Arctic station of Thule (76.5° N, 68.8° W), Greenland, beginning in January 2009, in order to track the long- and short-term interactions between the changing climate and the seasonal processes tied to the ozone depletion phenomenon. Furthermore, we updated the retrieval algorithm adapting the Optimal Estimation (OE) method to GBMS spectral data in order to conform to the standard of the Network for the Detection of Atmospheric Composition Change (NDACC) microwave group, and to provide our retrievals with a set of averaging kernels that allow more straightforward comparisons with other data sets. The new OE algorithm was applied to GBMS HNO3 data sets from 1993 South Pole observations to date, in order to produce HNO3 version 2 (v2) profiles. A sample of results obtained at Antarctic latitudes in fall and winter and at mid-latitudes is shown here. In most conditions, v2 inversions show a sensitivity (i.e., sum of column elements of the averaging kernel matrix) of 100 ± 20 % from 20 to 45 km altitude, with somewhat worse (better) sensitivity in the Antarctic winter lower (upper) stratosphere. The 1σ uncertainty on HNO3 v2 mixing ratio vertical profiles depends on altitude and is estimated at ~15 % or 0.3 ppbv, whichever is larger. Comparisons of v2 with former (v1) GBMS HNO3 vertical profiles, obtained employing the constrained matrix inversion method, show that v1 and v2 profiles are overall consistent. The main difference is at the HNO3 mixing ratio maximum in the 20–25 km altitude range, which is smaller in v2 than v1 profiles by up to 2 ppbv at mid-latitudes and during the Antarctic fall. This difference suggests a better agreement of GBMS HNO3 v2 profiles with both UARS/ and EOS Aura/MLS HNO3 data than previous v1 profiles.

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