scholarly journals Variasi Fluks CO2 Udara-Laut di Perairan Pesisir Pulau Bintan

2020 ◽  
Vol 5 (3) ◽  
pp. 145
Author(s):  
Afdal Afdal ◽  
Hanif Budi Prayitno ◽  
A'an Johan Wahyudi ◽  
Suci Lastrini
Keyword(s):  
Surface Water ◽  
Partial Pressure ◽  
Coastal Water ◽  
Temporal Variability ◽  
Monsoon Season ◽  
Carbon Sources ◽  
Southwest Monsoon ◽  
Spatial And Temporal Variability ◽  
Coral Reef Ecosystems ◽  
Spatio Temporal

<strong>Variation of Air-Sea CO<sub>2</sub> Fluxes in Bintan Island Coastal Water. </strong>Eastern part of Bintan coastal water plays a major role as CO<sub>2</sub> sink. However, flux and partial pressure of CO<sub>2</sub> (<em>p</em>CO<sub>2</sub>) dynamically follows spatio-temporal variability. Spatio-temporal variability of CO<sub>2</sub> flux may shows the whole condition of Bintan Island coastal water, especially in correlation with the primary production. Systematic study on variability of CO<sub>2</sub> flux from or to the watern column is essential to understand the whole conditions of Bintan Island coastal water. This study aims to understand the spatio-temporal variation of CO<sub>2</sub> fluxes in Bintan Island coastal water, and the factors influencing it. This study was conducted in the eastern part of Bintan coastal water in April and August 2014. In addition, this study was also conducted in the southern and northern parts in April 2016. CO<sub>2</sub> fluxes dynamics were calculated from <em>p</em>CO<sub>2</sub> (surface water and atmosphere), temperature, salinity, and wind speed. The result showed that almost all parts of the Bintan coastal water were carbon sources during first transition season. The largest CO<sub>2</sub> emission was observed in the northern part (4.02 ± 1.92 mmol/m<sup>2</sup>/d) followed by the southern part (2.28 ± 0.80 mmol/m<sup>2</sup>/d) and then the eastern part (0.46 ± 0.28 mmol/m<sup>2</sup>/d). The eastern part temporally turned into CO<sub>2</sub> sink in the southwest monsoon season (-0.27 ± 0.10 mmol/m<sup>2</sup>/d). Temperature was the main factor causing spatial and temporal variability of air-sea CO<sub>2</sub> fluxes in the Bintan coastal water. Spatially, the presence of seagrass and coral reef ecosystems causes the partial pressure of surface water CO<sub>2</sub> in the eastern part of waters of Bintan is much lower compared to the waters of north and south Bintan, thus emitting less CO<sub>2</sub> to the atmosphere

scholarly journals SPATIO-TEMPORAL ESTIMATION OF INTEGRATED WATER VAPOUR OVER THE MALAYSIAN PENINSULA DURING MONSOON SEASON

2017 ◽  
Vol XLII-4/W5 ◽  
pp. 165-175
Author(s):  
S. Salihin ◽  
T. A. Musa ◽  
Z. Mohd Radzi
Keyword(s):  
Water Vapour ◽  
Monsoon Season ◽  
Temporal Distribution ◽  
Southwest Monsoon ◽  
Northeast Monsoon ◽  
Path Delay ◽  
Zenith Path Delay ◽  
Temporal Estimation ◽  
Integrated Water Vapour ◽  
Spatio Temporal

This paper provides the precise information on spatial-temporal distribution of water vapour that was retrieved from Zenith Path Delay (ZPD) which was estimated by Global Positioning System (GPS) processing over the Malaysian Peninsular. A time series analysis of these ZPD and Integrated Water Vapor (IWV) values was done to capture the characteristic on their seasonal variation during monsoon seasons. This study was found that the pattern and distribution of atmospheric water vapour over Malaysian Peninsular in whole four years periods were influenced by two inter-monsoon and two monsoon seasons which are First Inter-monsoon, Second Inter-monsoon, Southwest monsoon and Northeast monsoon.

Assessing spatio-temporal variability and biases of climate models

2020 ◽  
Author(s):  
Nedjeljka Žagar
Keyword(s):  
Temporal Variability ◽  
Prediction Models ◽  
Climate Model ◽  
Weather Prediction ◽  
Ocean Model ◽  
Spatial And Temporal Variability ◽  
Dynamical Regime ◽  
Temporal Variance ◽  
Slab Ocean ◽  
Spatio Temporal

&lt;div&gt;Atmospheric spatial and temporal variability are closely related with the former being relatively well observed compared to the latter. The former is also regularly assessed in the validation of numerical weather prediction models while the latter is more difficult to estimate. Likewise, thermodynamical fields and circulation are closely coupled calling for an approach that considers them simultaneously. &amp;#160;&lt;/div&gt; &lt;div&gt;In this contribution, spatio-temporal variability spectra of the four major reanalysis datasets are discussed and applied for the validation of a climate model prototype. &amp;#160;A relationship between deficiencies in simulated variability and model biases is derived. The underlying method includes dynamical regime decomposition thereby providing a better understanding of the role of tropical variability in global circulation.&amp;#160;&lt;/div&gt; &lt;div&gt;Results of numerical simulations are validated by a 20th century reanalysis. A climate model was forced either with the prescribed SST or with a slab ocean model that updates SST in each forecast step.&amp;#160; Scale-dependent validation shows that missing temporal variance in the model relative to verifying reanalysis increases as the spatial scale reduces that appears associated with an increasing lack of spatial variance at smaller scales. Similar to variability, bias is strongly scale dependent; the larger the scale, the greater the bias. Biases present in the SST-forced simulation increase in the simulation using the slab ocean. The comparison of biases computed as a systematic difference between the model and reanalysis and between the SST-forced model and slab-ocean model (a perfect-model scenario) suggests that improving the atmospheric model increases the variance in the model on synoptic and subsynoptic scales but large biases associated with a poor SST remain at planetary scales.&lt;/div&gt; &lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Spatio-temporal trends in observed and downscaled precipitation over Ganga Basin

2017 ◽  
Author(s):  
Himanshu Arora ◽  
Chandra Shekhar Prasad Ojha ◽  
Wouter Buytaert ◽  
Gujjunadu Suryaprakash Kaushika ◽  
Chetan Sharma
Keyword(s):  
Monsoon Season ◽  
Temporal Trends ◽  
Winter Season ◽  
Southwest Monsoon ◽  
Historical Period ◽  
Precipitation Series ◽  
Emission Scenarios ◽  
Test Statistic ◽  
Ganga Basin ◽  
Spatio Temporal

Abstract. This paper focuses on the spatio-temporal trends of precipitation over the Ganga Basin in India for over 2 centuries. Trends in precipitation amounts are detected using observed data for historical period in 20th century and using downscaled precipitation data from 37 GCMs for 21st century. The ranking of 37 GCMs (from CMIP5 archive) is done employing a statistics based skill score. The best ranked GCM output is then bias corrected with observed precipitation prior to further analysis. The direction and magnitude of trend in annual and seasonal precipitation series is determined using Mann Kendall’s test statistic (ZMK) and Thiel Sen’s Slope estimator (β). The plots depicting the spatial variation of ZMK and β are prepared which provides a comprehensive inter-scenario comparison of spatio-temporal trends in precipitation series. Highly non-uniform spatio-temporal trends are detected for observed precipitation series. It is observed that the precipitation for annual and southwest monsoon season is indicating a rising trend for all future emission scenarios in the region adjacent to Himalayas (northeast side of study area) but shows falling trends in the plains away from the Himalayas. Insignificant trends are observed in pre-monsoon and winter season precipitation. An inter-emission-scenario comparison shows that for higher emission scenarios the annual and southwest monsoon precipitation is showing rising trends with increasing spatial dominance i.e. the area under rising trends increases as we observe it from low to high emission scenarios.

scholarly journals Spatial and temporal variability of snow depth and SWE in a small mountain catchment

2010 ◽  
Vol 4 (1) ◽  
pp. 1-30 ◽  
Author(s):  
T. Grünewald ◽  
M. Schirmer ◽  
R. Mott ◽  
M. Lehning
Keyword(s):  
Temporal Variability ◽  
Snow Depth ◽  
Energy Transport ◽  
Snow Water Equivalent ◽  
Laser Scanner ◽  
Ablation Rate ◽  
Spatial And Temporal Variability ◽  
M Cell ◽  
Snow Water ◽  
Spatio Temporal

Abstract. The spatio-temporal variability of the mountain snow cover determines the avalanche danger, snow water storage, permafrost distribution and the local distribution of fauna and flora. Using a new type of terrestrial laser scanner (TLS), which is particularly suited for measurements of snow covered surfaces, snow depth, snow water equivalent (SWE) and melt rates have been monitored in a high alpine catchment during an ablation period. This allowed for the first time to get a high resolution (2.5 m cell size) picture of spatial variability and its temporal development. A very high variability in which maximum snow depths between 0–9 m at the end of the accumulation season was found. This variability decreased during the ablation phase, although the dominant snow deposition features remained intact. The spatial patterns of calculated SWE were found to be similar to snow depth. Average daily melt rate was between 15 mm/d at the beginning of the ablation period and 30 mm/d at the end. The spatial variation of melt rates increased during the ablation rate and could not be explained in a simple manner by geographical or meteorological parameters, which suggests significant lateral energy fluxes contributing to observed melt. It could be qualitatively shown that the effect of the lateral energy transport must increase as the fraction of snow free surfaces increases during the ablation period.

scholarly journals Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data

2020 ◽  
Vol 12 (15) ◽  
pp. 2415
Author(s):  
Tuuli Soomets ◽  
Kristi Uudeberg ◽  
Kersti Kangro ◽  
Dainis Jakovels ◽  
Agris Brauns ◽  
...  
Keyword(s):  
Primary Production ◽  
Temporal Variability ◽  
Carbon Fixation ◽  
Remote Sensing Data ◽  
Spatial And Temporal Variation ◽  
Spatial And Temporal Variability ◽  
Phytoplankton Primary Production ◽  
Spatio Temporal ◽  
Lake Size

Phytoplankton primary production (PP) in lakes play an important role in the global carbon cycle. However, monitoring the PP in lakes with traditional complicated and costly in situ sampling methods are impossible due to the large number of lakes worldwide (estimated to be 117 million lakes). In this study, bio-optical modelling and remote sensing data (Sentinel-3 Ocean and Land Colour Instrument) was combined to investigate the spatial and temporal variation of PP in four Baltic lakes during 2018. The model used has three input parameters: concentration of chlorophyll-a, the diffuse attenuation coefficient, and incident downwelling irradiance. The largest of our studied lakes, Võrtsjärv (270 km2), had the highest total yearly estimated production (61 Gg C y−1) compared to the smaller lakes Lubans (18 Gg C y−1) and Razna (7 Gg C y−1). However, the most productive was the smallest studied, Lake Burtnieks (40.2 km2); although the total yearly production was 13 Gg C y−1, the daily average areal production was 910 mg C m−2 d−1 in 2018. Even if lake size plays a significant role in the total PP of the lake, the abundance of small and medium-sized lakes would sum up to a significant contribution of carbon fixation. Our method is applicable to larger regions to monitor the spatial and temporal variability of lake PP.

scholarly journals Effects of Spring–Neap Tidal Cycle on Spatial and Temporal Variability of Satellite Chlorophyll-A in a Macrotidal Embayment, Ariake Sea, Japan

2020 ◽  
Vol 12 (11) ◽  
pp. 1859
Author(s):  
Mengmeng Yang ◽  
Joaquim I. Goes ◽  
Hongzhen Tian ◽  
Elígio de R. Maúre ◽  
Joji Ishizaka
Keyword(s):  
Chlorophyll A ◽  
Temporal Variability ◽  
Tidal Cycle ◽  
Ocean Color ◽  
Spatial And Temporal Variability ◽  
Ariake Sea ◽  
Chl A ◽  
Moderate Resolution ◽  
Spatio Temporal ◽  
Moderate Resolution Imaging Spectroradiometer

We investigated the spatio-temporal variability of chlorophyll-a (Chl-a) and total suspended matter (TSM) associated with spring–neap tidal cycles in the Ariake Sea, Japan. Our study relied on significantly improved, regionally-tuned datasets derived from the ocean color sensor Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua over a 16-year period (2002–2017). The results revealed that spring–neap tidal variations in Chl-a and TSM within this macrotidal embayment (the Ariake Sea) are clearly different regionally and seasonally. Generally, the spring–neap tidal variability of Chl-a in the inner part of the Ariake Sea was controlled by TSM for seasons other than summer, whereas it was controlled by river discharge for summer. On the other hand, the contribution of TSM to the variability of Chl-a was not large for two areas in the middle of Ariake Sea where TSM was not abundant. This study demonstrates that ocean color satellite observations of Chl-a and TSM in the macrotidal embayment offer strong advantages for understanding the variations during the spring–neap tidal cycle.

scholarly journals Estimation of turbulence parameters from scanning lidars and in-situ instrumentation in the Perdigão 2017 campaign

2019 ◽  
Author(s):  
Norman Wildmann ◽  
Nicola Bodini ◽  
Julie K. Lundquist ◽  
Ludovic Bariteau ◽  
Johannes Wagner
Keyword(s):  
Temporal Variability ◽  
Shear Zones ◽  
Spectral Width ◽  
Early Morning ◽  
Spatial And Temporal Variability ◽  
Atmospheric Conditions ◽  
Sonic Anemometers ◽  
Spatio Temporal ◽  
Lifting System

Abstract. The understanding of the sources, spatial distribution and temporal variability of turbulence in the atmospheric boundary layer (ABL) and improved simulation of its forcing processes require observations in a broad range of terrain types and atmospheric conditions. In this study, we estimate turbulence kinetic energy (TKE) dissipation rate using multiple techniques, including traditional in-situ measurements of sonic anemometers on meteorological towers, a hot-wire anemometer on a tethered lifting system (TLS), as well as remote-sensing retrievals from a vertically staring lidar and two lidars performing range-height indicator (RHI) scans. For the retrieval of ε from the lidar RHI scans, we introduce a modification of the Doppler Spectral Width (DSW) method. This method uses spatio-temporal averages of the variance of the line-of-sight (LOS) velocity and the turbulent broadening of the Doppler backscatter spectrum. We validate this method against the observations from the other instruments, also including uncertainty estimations for each method. The synthesis of the results from all instruments enables a detailed analysis of the spatial and temporal variability of ε across a valley between two parallel ridges at the Perdigão 2017 campaign. We find that the shear zones above and below nighttime low-level jets (LLJ) experience turbulence enhancements, as does the wake of a wind turbine (WT). We analyze in detail how ε varies in the early morning of 14 June 2017, when the turbulence in the valley, approximately eleven rotor diameters downstream of the WT, is still significantly enhanced by the WT wake.

scholarly journals Spatio-temporal heterogeneity of the snow cover from data of the penetrometer SnowMicroPen

2018 ◽  
Vol 58 (4) ◽  
pp. 473-485
Author(s):  
A. Y. Komarov ◽  
Y. G. Seliverstov ◽  
P. B. Grebennikov ◽  
S. A. Sokratov
Keyword(s):  
Snow Cover ◽  
Temporal Variability ◽  
Climatic Conditions ◽  
Spatial And Temporal Variability ◽  
State University ◽  
Direct Data ◽  
Homogeneous Area ◽  
Spatio Temporal ◽  
University City ◽  
Moscow State University

Te paper presents the results of studies aimed at investigation of the spatial and temporal variability of snow coverstructure on the basis of strength values and its variations obtained by means of the high-resolution penetrometer SnowMicroPen. Te possibilities of fast and independent from the observer identifcation of layers (including identifcation of weakened, potentially avalanche-dangerous layers) were estimated under the climatic conditions of Moscow and the Khibiny mountains. Horizontal areas with homogeneous underlying surface and vegetation were selected for the stratigraphic studies that made it possible to avoid a possible influence of slope relief and exposure from the obtained data on the spatial and temporal variability of the snow depth structure. Te analysis of the information obtained in winter seasons 2014/15 and 2016/17 allowed constructing detailed schemes of the snow cover evolution at the Moscow site as well as assessing the inter-annual and intra-seasonal variability of its structure. Afer the SnowMicroPen data were recorded in the course of the feld works carried out in winter 2015/16 on the Khibiny educational and scientifc base of the Lomonosov Moscow State University (city of Kirovsk), the 10-meter trench on the same profle was described in details, and direct data on the snow cover structure were obtained. Te strength values resulted from the above studies characterize the layers composed of crystals of various shapes and sizes, and they are considered as the frst step to methodology of operational defnition of the spatially-inhomogeneous stratigraphy and stability of snowpack without snowpit observations. Te data analysis showed high spatial and temporal variability of the structure and properties of snow cover even at a homogeneous area, usually described by a single snowpit.

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