scholarly journals High-frequency productivity estimates for a lake from free-water CO<sub>2</sub> concentration measurements

2017 ◽  
Author(s):  
Maria Provenzale ◽  
Anne Ojala ◽  
Jouni Heiskanen ◽  
Kukka-Maaria Erkkilä ◽  
Ivan Mammarella ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
High Frequency ◽  
Free Water ◽  
Co2 Concentration ◽  
Freshwater Ecosystems ◽  
High Temporal Resolution ◽  
Net Ecosystem Productivity ◽  
Data Set ◽  
Fully Integrated ◽  
Typical Summer

Abstract. Lakes are important actors in biogeochemical cycles and a powerful natural source of CO2. However, they are not yet fully integrated in carbon budgets, and the carbon cycle in the water is still poorly understood. In freshwater ecosystems, productivity studies have usually been carried out with traditional methods (bottle incubations, 14C technique), which are imprecise and have a poor temporal resolution. Consequently, our ability to quantify and predict the net ecosystem productivity (NEP) is limited: the estimates are prone to errors and the NEP cannot be parameterized from environmental variables. Here we expand the testing of a free-water method based on the direct measurement of the CO2 concentration in the water. The approach was proposed already in 2008, but was tested on a very short data set (3 days) under specific conditions (autumn turnover); despite showing promising results, it has not been used ever since. We tested the method under different conditions (summer stratification, typical summer conditions for boreal dark-water lakes) and on a much longer data set (40 days), and quantitatively validated it comparing our data and productivity models. We were able to evaluate the NEP with a high temporal resolution (minutes) and found an excellent agreement with the models. We also estimated the parameters of the productivity-irradiance (PI) curves that allow the calculation of the NEP from irradiance and water temperature. Overall, our work shows that the approach is suitable for productivity studies under a wider range of conditions, and is an important step towards developing it so that it becomes even more general.

scholarly journals High-frequency productivity estimates for a lake from free-water CO<sub>2</sub> concentration measurements

2018 ◽  
Vol 15 (7) ◽  
pp. 2021-2032 ◽  
Author(s):  
Maria Provenzale ◽  
Anne Ojala ◽  
Jouni Heiskanen ◽  
Kukka-Maaria Erkkilä ◽  
Ivan Mammarella ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Free Water ◽  
Co2 Concentration ◽  
Freshwater Ecosystems ◽  
High Temporal Resolution ◽  
Data Set ◽  
Fully Integrated ◽  
Global Budgets ◽  
Typical Summer ◽  
Good Agreement

Abstract. Lakes are important actors in biogeochemical cycles and a powerful natural source of CO2. However, they are not yet fully integrated in carbon global budgets, and the carbon cycle in the water is still poorly understood. In freshwater ecosystems, productivity studies have usually been carried out with traditional methods (bottle incubations, 14C technique), which are imprecise and have a poor temporal resolution. Consequently, our ability to quantify and predict the net ecosystem productivity (NEP) is limited: the estimates are prone to errors and the NEP cannot be parameterised from environmental variables. Here we expand the testing of a free-water method based on the direct measurement of the CO2 concentration in the water. The approach was first proposed in 2008, but was tested on a very short data set (3 days) under specific conditions (autumn turnover); despite showing promising results, this method has been neglected by the scientific community. We tested the method under different conditions (summer stratification, typical summer conditions for boreal dark-water lakes) and on a much longer data set (40 days), and quantitatively validated it comparing our data and productivity models. We were able to evaluate the NEP with a high temporal resolution (minutes) and found a very good agreement (R2≥0.71) with the models. We also estimated the parameters of the productivity–irradiance (PI) curves that allow the calculation of the NEP from irradiance and water temperature. Overall, our work shows that the approach is suitable for productivity studies under a wider range of conditions, and is an important step towards developing this method so that it becomes more widely used.

scholarly journals Harmonizing Multi-Source Remote Sensing Images for Summer Corn Growth Monitoring

2019 ◽  
Vol 11 (11) ◽  
pp. 1266 ◽  
Author(s):  
Mingzheng Zhang ◽  
Dehai Zhu ◽  
Wei Su ◽  
Jianxi Huang ◽  
Xiaodong Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Kalman Filter ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Meteorological Data ◽  
High Temporal Resolution ◽  
Growth Monitoring ◽  
Landsat 8 ◽  
Data Set

Continuous monitoring of crop growth status using time-series remote sensing image is essential for crop management and yield prediction. The growing season of summer corn in the North China Plain with the period of rain and hot, which makes the acquisition of cloud-free satellite imagery very difficult. Therefore, we focused on developing image datasets with both a high temporal resolution and medium spatial resolution by harmonizing the time-series of MOD09GA Normalized Difference Vegetation Index (NDVI) images and 30-m-resolution GF-1 WFV images using the improved Kalman filter model. The harmonized images, GF-1 images, and Landsat 8 images were then combined and used to monitor the summer corn growth from 5th June to 6th October, 2014, in three counties of Hebei Province, China, in conjunction with meteorological data and MODIS Evapotranspiration Data Set. The prediction residuals ( Δ P R K ) in NDVI between the GF-1 observations and the harmonized images was in the range of −0.2 to 0.2 with Gauss distribution. Moreover, the obtained phenological curves manifested distinctive growth features for summer corn at field scales. Changes in NDVI over time were more effectively evaluated and represented corn growth trends, when considered in conjunction with meteorological data and MODIS Evapotranspiration Data Set. We observed that the NDVI of summer corn showed a process of first decreasing and then rising in the early growing stage and discuss how the temperature and moisture of the environment changed with the growth stage. The study demonstrated that the synthesized dataset constructed using this methodology was highly accurate, with high temporal resolution and medium spatial resolution and it was possible to harmonize multi-source remote sensing imagery by the improved Kalman filter for long-term field monitoring.

scholarly journals Diurnal aerosol variations do affect daily averaged radiative forcing under heavy aerosol loading observed in Hefei, China

2015 ◽  
Vol 8 (7) ◽  
pp. 2901-2907 ◽  
Author(s):  
Z. Wang ◽  
D. Liu ◽  
Y. Wang ◽  
Z. Wang ◽  
G. Shi
Keyword(s):  
Temporal Resolution ◽  
Radiative Forcing ◽  
Single Scattering ◽  
High Temporal Resolution ◽  
Diurnal Changes ◽  
Data Set ◽  
Time Resolved ◽  
Aerosol Radiative Forcing ◽  
Aerosol Loading

Abstract. A strong diurnal variation of aerosol has been observed in many heavily polluted regions in China. This variation could affect the direct aerosol radiative forcing (DARF) evaluation if the daily averaged value is used as normal rather than the time-resolved values. To quantify the effect of using the daily averaged DARF, 196 days of high temporal resolution ground-based data collected in SKYNET Hefei site during the period from 2007 to 2013 is used to perform an assessment. We demonstrate that strong diurnal changes of heavy aerosol loading have an impact on the 24-h averaged DARF when daily averaged optical properties are used to retrieve this quantity. The DARF errors varying from −7.6 to 15.6 W m−2 absolutely and from 0.1 to 28.5 % relatively were found between the calculations using daily average aerosol properties, and those using time-resolved aerosol observations. These errors increase with increasing daily aerosol optical depth (AOD) and decreasing daily single-scattering albedo (SSA), indicating that the high temporal resolution DARF data set should be used in the model instead of the normal daily-averaged one, especially under heavy aerosol loading conditions for regional campaign studies. We also found that statistical errors (0.3 W m−2 absolutely and 11.8 % relatively) will be less, which means that the effect of using the daily averaged DARF can be weakened by using a long-term observational data set.

scholarly journals Efficient Bootstrap Estimates for Tail Statistics

2016 ◽  
Author(s):  
Øyvind Breivik ◽  
Ole Johan Aarnes
Keyword(s):  
Confidence Intervals ◽  
Temporal Resolution ◽  
Small Subset ◽  
High Temporal Resolution ◽  
Data Set ◽  
Empirical Distributions ◽  
Bootstrap Techniques ◽  
Entire Sequence ◽  
Bootstrap Estimates ◽  
Return Value

Abstract. Bootstrap resamples can be used to investigate the tail of empirical distributions as well as return value estimates based on the extremal behaviour of the distribution. Specifically, the confidence intervals on return value estimates or bounds on in-sample tail statistics can be estimated using bootstrap techniques. However, bootstrapping from the entire data set is expensive. It is shown here that it suffices to bootstrap from a small subset consisting of the highest entries in the sequence to make estimates that are essentially identical to bootstraps from the entire sequence. Similarly, bootstrap estimates of confidence intervals of threshold return estimates are found to be well approximated by using a subset consisting of the highest entries. This has practical consequences in fields such as meteorology, oceanography and hydrology where return estimates are routinely made from very large gridded model integrations spanning decades at high temporal resolution. In such cases the computational savings are substantial.

A high temporal resolution data set of ERS scatterometer radar backscatter for research in Arctic and sub-Arctic regions

Polar Record ◽  
2002 ◽  
Vol 38 (205) ◽  
pp. 115-120 ◽  
Author(s):  
Yongwei Sheng ◽  
Laurence C. Smith ◽  
Karen E. Frey ◽  
Douglas E. Alsdorf
Keyword(s):  
Temporal Resolution ◽  
Incident Angle ◽  
High Temporal Resolution ◽  
Grid Spacing ◽  
Radar Backscatter ◽  
Data Set ◽  
Arctic Regions ◽  
Full Resolution ◽  
Data Products ◽  
Resolution Data

AbstractRadar backscatter in Arctic and sub-Arctic regions is temporally dynamic and reflects changes in sea ice, glacier facies, soil thaw state, vegetation cover, and moisture content. Wind scatterometers on the ERS-1 and ERS-2 satellites have amassed a global archive of C-band radar backscatter data since 1991. This paper derives three high temporal resolution data products from this archive that are designed to facilitate scatterometer research in high-latitude environments. Radar backscatter data have a grid spacing of 25 km and are mapped northwards from 60°N latitude over intervals of one, three, and seven days for the period 1991–2000. Data are corrected to a normalized incident angle of 40°. Animations and full-resolution data products are freely available for scientific use at http://merced.gis.ucla.edu/scatterometer/index.htm.

scholarly journals A NEW SPATIAL AND TEMPORAL FUSION MODEL

2016 ◽  
Vol III-7 ◽  
pp. 203-206
Author(s):  
Jing Wang ◽  
Bo Huang
Keyword(s):  
Temporal Resolution ◽  
Visual Analysis ◽  
High Temporal Resolution ◽  
Fusion Model ◽  
Data Set ◽  
Regression Error ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Temporal Model ◽  
Moderate Resolution Imaging Spectroradiometer

As Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) has a tradeoff between the high temporal resolution and high spatial resolution, this paper proposed a spatial and temporal model with auto-regression error correction (AREC) method to blend the two types of images in order to obtain the composed image with both high spatial and temporal resolution. Experiments and validation were conducted on a data set located in Shenzhen, China and compared with Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in several objective indexes and visual analysis. It was found that AREC could effectively predict the land cover changes and the fusion results had better performances versus the ones of STARFM.

scholarly journals A NEW SPATIAL AND TEMPORAL FUSION MODEL

2016 ◽  
Vol III-7 ◽  
pp. 203-206
Author(s):  
Jing Wang ◽  
Bo Huang
Keyword(s):  
Temporal Resolution ◽  
Visual Analysis ◽  
High Temporal Resolution ◽  
Fusion Model ◽  
Data Set ◽  
Regression Error ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Temporal Model ◽  
Moderate Resolution Imaging Spectroradiometer

As Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) has a tradeoff between the high temporal resolution and high spatial resolution, this paper proposed a spatial and temporal model with auto-regression error correction (AREC) method to blend the two types of images in order to obtain the composed image with both high spatial and temporal resolution. Experiments and validation were conducted on a data set located in Shenzhen, China and compared with Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in several objective indexes and visual analysis. It was found that AREC could effectively predict the land cover changes and the fusion results had better performances versus the ones of STARFM.

scholarly journals Evaluation of four years continuous δ<sup>13</sup>C(CO<sub>2</sub>) data using a running Keeling approach

2016 ◽  
Author(s):  
Sanam Noreen Vardag ◽  
Samuel Hammer ◽  
Ingeborg Levin
Keyword(s):  
Fossil Fuel ◽  
Co2 Concentration ◽  
High Temporal Resolution ◽  
Data Set ◽  
Additional Information ◽  
Hourly Data ◽  
The Mean ◽  
Carbon Dioxide Co2 ◽  
End Members ◽  
Different Sources

Abstract. As different carbon dioxide (CO2) emitters have different carbon isotope ratios, measurements of atmospheric δ13C(CO2) and CO2 concentration contain information on the CO2 source mix in the catchment area of an atmospheric measurement site. Often, this information is illustratively presented as mean isotopic source signature. Recently an increasing number of continuous measurements of δ13C(CO2) and CO2 have become available, opening the door to quantification of CO2 shares from different sources at high temporal resolution. Here, we present a method to compute the CO2 source signature (δS) continuously without introducing biases and evaluate our result using model data. We find that biases in δS are smaller than 0.2 ‰ with uncertainties of about 1.2 ‰ for hourly data. Applying the method to a four year data set of CO2 and δ13C(CO2) measured in Heidelberg, Germany, yields a distinct seasonal cycle of δS. Disentangling this seasonal source signature into its source components is, however, only possible if the isotopic end members of these sources, i.e., the biosphere, δbio, and the fuel mix, δF, are known. From the mean source signature record in 2012, δbio could be reliably estimated only for summer to (−25 ± 1) ‰ and δF only for winter to (−32.5 ± 2.5) ‰. As the isotopic end members δbio and δF were shown to change over the season, no year-round estimation of the fossil fuel or biosphere share is possible from the measured mean source signature record without additional information from emission inventories or other tracer measurements, such as Δ14C(CO2).

scholarly journals A unified code for conventional and disjunct eddy covariance analysis of trace gas measurements: An urban test case

2019 ◽  
Author(s):  
Marcus Striednig ◽  
Martin Graus ◽  
Tilmann Märk ◽  
Thomas G. Karl
Keyword(s):  
Eddy Covariance ◽  
High Frequency ◽  
Urban Canopy ◽  
Lag Time ◽  
Trace Gas ◽  
High Temporal Resolution ◽  
Eddy Covariance Method ◽  
Data Set ◽  
Wide Range ◽  
Gas Measurements

Abstract. We describe and test a new versatile software tool for processing eddy covariance and disjunct eddy covariance data. We present an evaluation based on urban NMVOC measurements using a Proton-transfer-reaction quadrupole interface time of flight mass spectrometer (PTR-QiTOFMS) at the Innsbruck Atmospheric Observatory. The code is based on MATLAB ® and can be easily configured to process high frequency, low frequency and disjunct data. It can be applied to a wide range of analytical setups for NMVOC as well as other trace gas measurements, and is tailored towards the application of noisy data, where lag-time corrections become challenging. Several corrections and quality control routines are implemented to obtain the most reliable results. The software is open-source, so it can be extended and adjusted to specific purposes. We demonstrate the capabilities of the code based on a large urban dataset collected in Innsbruck, Austria, where ambient concentrations of non-methane volatile organic compounds (NMVOC) and auxiliary trace gases were sampled with high temporal resolution above an urban canopy. Concomitant measurements of 12C and 13C isotopic NMVOC fluxes allow testing algorithms used for determinations of flux LODs and lag time analysis. We use the high frequency NMVOC data set to generate a set of disjunct data and compare these results with the true eddy covariance method. The presented analysis allows testing the theory of DEC in an urban environment. Our findings confirm that the disjunct eddy covariance method can be a reliable tool, even in complex urban environments, when fast sensors are not available, but that the increase in random error impedes the ability to detect small fluxes due to higher flux LODs.

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