scholarly journals An Effective Similar-Pixel Reconstruction of the High-Frequency Cloud-Covered Areas of Southwest China

2019 ◽  
Vol 11 (3) ◽  
pp. 336 ◽  
Author(s):  
Wenping Yu ◽  
Junlei Tan ◽  
Mingguo Ma ◽  
Xiaolu Li ◽  
Xiaojun She ◽  
...  
Keyword(s):  
Land Surface ◽  
High Frequency ◽  
Southwest China ◽  
Global Climate ◽  
Average Error ◽  
Balance Theory ◽  
High Temporal Resolution ◽  
Retrieval Accuracy ◽  
Southwest Region

With advantages of multispatial resolutions, a high retrieval accuracy, and a high temporal resolution, the satellite-derived land surface temperature (LST) products are very important LST sources. However, the greatest barrier to their wide application is the invalid values produced by large quantities of cloudy pixels, especially for regions frequently swathed in clouds. In this study, an effective method based on the land energy balance theory and similar pixels (SP) method was developed to reconstruct the LSTs over cloudy pixels for the widely used MODIS LST (MOD11A1). The southwest region of China was selected as the study area, where extreme drought has frequently occurred in recent years in the context of global climate change and which commonly exhibits cloudy and foggy weather. The validation results compared with in situ LSTs showed that the reconstructed LSTs have an average error < 1.00 K (0.57 K at night and -0.14 K during the day) and an RMSE < 3.20 K (1.90 K at night and 3.16 K in the daytime). The experiment testing the SP interpolation indicated that the spatial structure of the LST has a greater effect on the SP performance than the size of the data-missing area, which benefits the LST reconstruction in the area frequently covered by large clouds.

scholarly journals How runoff components affect the export of DOC and nitrate: a long-term and high-frequency analysis

2017 ◽  
Author(s):  
Michael P. Schwab ◽  
Julian Klaus ◽  
Laurent Pfister ◽  
Markus Weiler
Keyword(s):  
High Frequency ◽  
Initial Conditions ◽  
Shallow Groundwater ◽  
High Temporal Resolution ◽  
Near Surface ◽  
Nitrate Concentrations ◽  
Nitrate Export ◽  
Dry Conditions

Abstract. We monitored dissolved organic carbon (DOC) and nitrate concentrations and fluxes in situ with a UV-Vis spectrometer for two years at a high temporal resolution of 15 minutes in the forested Weierbach headwater catchment. The catchment exhibits a characteristic double peak runoff response to incident rainfall during periods with wet initial conditions. When initial conditions are dry, only the first discharge peak occurs. During our observations, both DOC and nitrate concentrations increased during the first discharge peak, while only nitrate concentrations were elevated during the second discharge peak. Relying on additional biweekly end-member data of precipitation, throughfall, soil water and groundwater, we linked the first peak to near surface flowpaths and the second peak to shallow groundwater reactions and subsurface flowpaths. The mass export of DOC and nitrate is largely controlled by the discharge yield. Nevertheless, this relationship is altered by changing flowpaths during different wetness conditions in the catchment. Due to the absence of second discharge peaks during dry conditions, the DOC export is more relevant and the nitrate export is less relevant during dry catchment states. The study highlights the benefits of in-situ, long-term, and high-frequency monitoring for comparing DOC and nitrate export with runoff components that are changing rapidly during events as well as gradually between seasons.

Ice-nucleating Macromolecules from Alpine Forests as Possible Contributors to Cloud Glaciation Processes

2020 ◽  
Author(s):  
Teresa M. Seifried ◽  
Paul Bieber ◽  
Laura Felgitsch ◽  
Hinrich Grothe
Keyword(s):  
Land Surface ◽  
Global Climate ◽  
Life Time ◽  
Ice Nucleation ◽  
Radiative Properties ◽  
Small Scale ◽  
Emission Rates ◽  
Sampling Systems ◽  
Rain Fall

&lt;p&gt;Ice nucleation in the atmosphere leads to the formation of mixed-phase as well as cirrus clouds in the upper troposphere. Cloud glaciation can either occur homogeneously at temperatures below -38&amp;#176;C or heterogeneously in the presence of ice-nucleating particles (INPs) at temperatures higher than -38&amp;#176;C. Depending on the aggregate state of a cloud, it&amp;#8217;s life time and radiative properties vary and thus affect regional and global climate. The influence of biogenic INPs on atmospheric processes as well as the transport of these particles from the land surface to the atmosphere remains elusive. Several plants from boreal and alpine forests are known to contain ice-nucleating macromolecules (INMs) to survive in extreme conditions. However, less is known about chemical characteristics and actual emission rates of such INMs.&lt;/p&gt;&lt;p&gt;We present here our investigation of surface extracts from different tree tissues (Betula pendula and Pinus sylvestris). We were able to extract INMs from nearly all samples. Furthermore, we analyzed the ability of these INMs to be released during rain fall events in-situ. To investigate possible transport mechanisms of INMs from the canopy of studied tree species to the atmosphere we sampled aerosols with two small scale drones, carrying our self-build sampling systems called DAPSI (Drone-based Aerosol Particles Sampling Impinger/Impactor). Results indicate that birches and pines outline an important source of airborne biogenic INPs.&lt;/p&gt;

scholarly journals Filling the gaps in meteorological continuous data measured at FLUXNET sites with ERA-interim reanalysis

2015 ◽  
Vol 8 (1) ◽  
pp. 23-55 ◽  
Author(s):  
N. Vuichard ◽  
D. Papale
Keyword(s):  
Standard Deviation ◽  
Land Surface ◽  
Meteorological Data ◽  
Internal Variability ◽  
Fair Use ◽  
Meteorological Variable ◽  
Continuous Data ◽  
High Temporal Resolution ◽  
In Situ Data

Abstract. Exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 sites registered and up to 250 of them sharing data (Free Fair Use dataset). Many modelling groups use the FLUXNET dataset for evaluating ecosystem model's performances but it requires uninterrupted time series for the meteorological variables used as input. Because original in-situ data often contain gaps, from very short (few hours) up to relatively long (some months), we develop a new and robust method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-interim) and high temporal resolution spanning from 1989 to today. These data are however not measured at site level and for this reason a method to downscale and correct the ERA-interim data is needed. We apply this method on the level 4 data (L4) from the LaThuile collection, freely available after registration under a Fair-Use policy. The performances of the developed method vary across sites and are also function of the meteorological variable. On average overall sites, the bias correction leads to cancel from 10 to 36% of the initial mismatch between in-situ and ERA-interim data, depending of the meteorological variable considered. In comparison to the internal variability of the in-situ data, the root mean square error (RMSE) between the in-situ data and the un-biased ERA-I data remains relatively large (on average overall sites, from 27 to 76% of the standard deviation of in-situ data, depending of the meteorological variable considered). The performance of the method remains low for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations. The ERA-interim reanalysis data debiased at FLUXNET sites can be downloaded from the PANGAEA data center (http://doi.pangaea.de/10.1594/PANGAEA.838234).

scholarly journals Filling the gaps in meteorological continuous data measured at FLUXNET sites with ERA-Interim reanalysis

2015 ◽  
Vol 7 (2) ◽  
pp. 157-171 ◽  
Author(s):  
N. Vuichard ◽  
D. Papale
Keyword(s):  
Standard Deviation ◽  
Land Surface ◽  
Meteorological Data ◽  
Fair Use ◽  
Meteorological Variable ◽  
Continuous Data ◽  
High Temporal Resolution ◽  
Data Set ◽  
In Situ Data

Abstract. Exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 registered sites, and up to 250 of them share data (free fair-use data set). Many modelling groups use the FLUXNET data set for evaluating ecosystem models' performance, but this requires uninterrupted time series for the meteorological variables used as input. Because original in situ data often contain gaps, from very short (few hours) up to relatively long (some months) ones, we develop a new and robust method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-Interim) and a high temporal resolution spanning from 1989 to today. These data are, however, not measured at site level, and for this reason a method to downscale and correct the ERA-Interim data is needed. We apply this method to the level 4 data (L4) from the La Thuile collection, freely available after registration under a fair-use policy. The performance of the developed method varies across sites and is also function of the meteorological variable. On average over all sites, applying the bias correction method to the ERA-Interim data reduced the mismatch with the in situ data by 10 to 36 %, depending on the meteorological variable considered. In comparison to the internal variability of the in situ data, the root mean square error (RMSE) between the in situ data and the unbiased ERA-I (ERA-Interim) data remains relatively large (on average over all sites, from 27 to 76 % of the standard deviation of in situ data, depending on the meteorological variable considered). The performance of the method remains poor for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations. The ERA-Interim reanalysis data de-biased at FLUXNET sites can be downloaded from the PANGAEA data centre (http://doi.pangaea.de/10.1594/PANGAEA.838234).

In-situ compaction and sintering of Al2O3 – GNP nanoparticles using a high-frequency induction system

2018 ◽  
Vol 60 (7-8) ◽  
pp. 727-732
Author(s):  
Uğur Çavdar ◽  
İ. Murat Kusoglu ◽  
Ayberk Altintas
Keyword(s):  
High Frequency ◽  
Induction System ◽  
High Frequency Induction

Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

2020 ◽  
Vol 3 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Abdulla Al Kafy ◽  
Abdullah Al-Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Md. Soumik Sikdar ◽  
Mohammad Hasib Hasan Khan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Agricultural Land ◽  
Global Climate ◽  
Urban Expansion ◽  
Water Bodies ◽  
Landsat 8 ◽  
Lulc Changes ◽  
The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

scholarly journals A Fused Variable by Night Light Images and MODIS Products for Improving Urban Built-Up Area Extraction

Technologies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 40
Author(s):  
Guang Yang ◽  
Yuntao Ma ◽  
Jiaqi Hu
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Extraction Methods ◽  
Average Error ◽  
Geographic Coordinate System ◽  
Optimal Thresholds ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Spatial Locations

The boundary of urban built-up areas is the baseline data of a city. Rapid and accurate monitoring of urban built-up areas is the prerequisite for the boundary control and the layout of urban spaces. In recent years, the night light satellite sensors have been employed in urban built-up area extraction. However, the existing extraction methods have not fully considered the properties that directly reflect the urban built-up areas, like the land surface temperature. This research first converted multi-source data into a uniform projection, geographic coordinate system and resampling size. Then, a fused variable that integrated the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) night light images, the Moderate-resolution Imaging Spectroradiometer (MODIS) surface temperature product and the normalized difference vegetation index (NDVI) product was designed to extract the built-up areas. The fusion results showed that the values of the proposed index presented a sharper gradient within a smaller spatial range, compared with the only night light images. The extraction results were tested in both the area sizes and the spatial locations. The proposed index performed better in both accuracies (average error rate 1.10%) and visual perspective. We further discussed the regularity of the optimal thresholds in the final boundary determination. The optimal thresholds of the proposed index were more stable in different cases on the premise of higher accuracies.

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