scholarly journals Spatiotemporal Characterization of VIIRS Night Light

2021 ◽  
Vol 2 ◽  
Author(s):  
Christopher Small
Keyword(s):  
Time Scales ◽  
Infrared Imaging ◽  
Temporal Frequency ◽  
Full Range ◽  
Primary Objective ◽  
Skewed Distribution ◽  
Spatiotemporal Variability ◽  
Spatial And Temporal Variation ◽  
Light Change ◽  
Atmospheric Scattering

The Visible Infrared Imaging Radiometer Suite (VIIRS) Day Night Band (DNB) on board the Suomi NPP satellite now provides almost a decade of daily observations of night light. The temporal frequency of sampling, without the degree of temporal averaging of annual composites, makes it necessary to consider the distinction between apparent temporal changes of night light related to the imaging process and actual changes in the underlying sources of the night light being imaged. The most common approach to night light change detection involves direct attribution of observed changes to the phenomenon of interest. Implicit in this approach is the assumption that other forms of actual and apparent change in the light source are negligible or non-existent. An alternative approach is to characterize the spatiotemporal variability prior to deductive attribution of causation so that the attribution can be made in the context of the full range of spatial and temporal variation. The primary objective of this study is to characterize night light variability over a range of spatial and temporal scales to provide a context for interpretation of night light changes observed on both subannual and interannual time scales. This analysis is based on a combination of temporal moments, spatial correlation and Empirical Orthogonal Function (EOF) analysis. A key result of this study is the pervasive heteroskedasticity of VIIRS monthly mean night light. Specifically, the monotonic decrease of variability with increasing mean brightness. Anthropogenic night light is remarkably stable on subannual time scales while background luminance varies considerably. The variance partition from the eigenvalues of the spatiotemporal covariance matrix are 88, 2 and 2% for spatial, seasonal and interannual variance (respectively) in the most diverse region on Earth (Eurasia). Heteroskedasticity is pervasive in the monthly composites; present in all areas for all months of the year, suggesting that much, if not most, of the month-to-month variability may be related to luminance of otherwise stable sources subjected to multiple aspects of the imaging process varying in time. Given the skewed distribution of all night light arising from radial peripheral dimming of bright sources subject to atmospheric scattering, even aggregate metrics using thresholds must be interpreted in light of the fact that much larger numbers of more variable low luminance pixels may statistically overwhelm smaller numbers of stable higher luminance pixels and cause apparent changes related to the imaging process to be interpreted as actual changes in the light sources.

scholarly journals Spatiotemporal Variability of Lightning Flash Distribution over Sri Lanka

2019 ◽  
Vol 82 ◽  
pp. 1-13
Author(s):  
U.G.Dilaj Maduranga ◽  
Mahesh Edirisinghe ◽  
L. Vimukthi Gamage
Keyword(s):  
Sri Lanka ◽  
Monsoon Season ◽  
Tropical Rainfall Measuring Mission ◽  
Spatiotemporal Variability ◽  
Spatial And Temporal Variation ◽  
Lightning Flash ◽  
Northeast Monsoon ◽  
Time Period ◽  
Total Lightning ◽  
Imaging Sensor

The variation of the lightning activities over Sri Lanka and surrounded costal belt (5.750N-10.000N and 79.50E-89.000E) is studied using lightning flash data of Lightning Imaging Sensor (LIS) which was launched in November 1997 for NASA’s Tropical Rainfall Measuring Mission (TRMM). The LIS data for the period of 1998 to 2014 are considered for this study. The spatial and temporal variation of lightning activities is investigated and respective results are presented. The diurnal variation over the studied area presents that maximum and minimum flash count recorded at 1530-1630 Local Time (10-11UTC) and 0530-0630LT (00-01UTC) respectively. Maximum lightning activities over the observed area have occurred after the 1330LT (08UTC) in every year during the considered time period. The seasonal variation of the lightning activities shows that the maximum lightning activities happened in First inter monsoon season (March to April) with 30.90% total lightning flashes and minimum lightning activities recorded in Northeast monsoon season (December to February) with 8.51% of total lightning flashes. Maximum flash density of 14.37fl km-2year-1 was observed at 6.980N/80.160E in First inter monsoon season. These seasonal lighting activities are agree with seasonal convective activities and temperature variation base on propagation of Intra-Tropical Convection Zone over the studied particular area. Mean monthly flash count presents a maximum in the month of April with 29.12% of lightning flashes. Variation pattern of number of lightning activities in month of April shows a tiny increment during the time period of 1998 to 2014. Maximum annual flash density of 28.09fl km-2yr-1 was observed at 6.980N/80.170E. The latitudinal variation of the lightning flash density is depicted that extreme lightning activities have happened at the southern part of the county and results show that there is a noticeable lack of lightning activities over the surrounded costal belt relatively landmass.

scholarly journals Impact of Atmospheric Moisture Storage on Precipitation Recycling

2006 ◽  
Vol 19 (8) ◽  
pp. 1513-1530 ◽  
Author(s):  
Francina Dominguez ◽  
Praveen Kumar ◽  
Xin-Zhong Liang ◽  
Mingfang Ting
Keyword(s):  
United States ◽  
Time Scales ◽  
Analytical Models ◽  
Spatiotemporal Variability ◽  
Spatial And Temporal Variability ◽  
Monthly Precipitation ◽  
Computationally Efficient ◽  
Precipitation Recycling ◽  
Moisture Storage ◽  
Storage Term

Abstract Computations of precipitation recycling using analytical models are generally performed under the assumption of negligible change in moisture storage in the atmospheric column. Because the moisture storage term is nonnegligible at smaller time scales, most recycling studies using analytical models are done at monthly or longer time scales. A dynamic precipitation recycling model, which incorporates the change in moisture storage, is developed. It is derived formally from the conservation of mass equation and is presented in a simple and computationally efficient form. This model allows for recycling analysis at a range of temporal scales, from daily to monthly and longer. In comparison to the traditional models that do not include the storage term, the new model presents almost identical spatial and temporal variability, but predicts recycling ratios that are 12%–33% larger at a monthly level. The dynamic model is used to study the variability of monthly precipitation recycling over the conterminous United States using Reanalysis-II data from 1979 to 2000. On average, the southeastern and southwestern parts of the country exhibit high summer recycling ratios, contrasting with the low values in the northeastern and northwestern United States. The Colorado region also presents high recycling ratios. Dominant modes of spatiotemporal variability in recycling are identified using EOF analysis. The first mode captures strong recycling ratios over the western United States during the summers of 1986, 1992, and 1998. The second mode captures anomalous high recycling ratios during 1988 and 1989 over the central part of the country, and anomalous low ratios during 1980 and 1993.

Paleoecology and high-resolution paleohydrology of a kettle peatland in upper Michigan

2004 ◽  
Vol 61 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Robert K. Booth ◽  
Stephen T. Jackson ◽  
Catherine E.D. Gray
Keyword(s):  
High Resolution ◽  
Climate Variability ◽  
Time Scales ◽  
Plant Macrofossils ◽  
Testate Amoebae ◽  
Climatic Changes ◽  
Primary Objective ◽  
History Of ◽  
Past Climate Variability

We investigated the developmental and hydrological history of a Sphagnum-dominated, kettle peatland in Upper Michigan using testate amoebae, plant macrofossils, and pollen. Our primary objective was to determine if the paleohydrological record of the peatland represents a record of past climate variability at subcentennial to millennial time scales. To assess the role of millennial-scale climate variability on peatland paleohydrology, we compared the timing of peatland and upland vegetation changes. To investigate the role of higher-frequency climate variability on peatland paleohydrology, we used testate amoebae to reconstruct a high-resolution, hydrologic history of the peatland for the past 5100 years, and compared this record to other regional records of paleoclimate and vegetation. Comparisons revealed coherent patterns of hydrological, vegetational, and climatic changes, suggesting that peatland paleohydrology responded to climate variability at millennial to sub-centennial time scales. Although ombrotrophic peatlands have been the focus of most high-resolution peatland paleoclimate research, paleohydrological records from Sphagnum-dominated, closed-basin peatlands record high-frequency and low-magnitude climatic changes and thus represent a significant source of unexplored paleoclimate data.

scholarly journals Spatiotemporal variability of snow depth across the Eurasian continent from 1966 to 2012

2018 ◽  
Vol 12 (1) ◽  
pp. 227-245 ◽  
Author(s):  
Xinyue Zhong ◽  
Tingjun Zhang ◽  
Shichang Kang ◽  
Kang Wang ◽  
Lei Zheng ◽  
...  
Keyword(s):  
Land Surface ◽  
Snow Depth ◽  
Local Community ◽  
Water Cycle ◽  
Primary Objective ◽  
Spatiotemporal Variability ◽  
Physical Parameters ◽  
Large Area ◽  
Eurasian Continent

Abstract. Snow depth is one of the key physical parameters for understanding land surface energy balance, soil thermal regime, water cycle, and assessing water resources from local community to regional industrial water supply. Previous studies by using in situ data are mostly site specific; data from satellite remote sensing may cover a large area or global scale, but uncertainties remain large. The primary objective of this study is to investigate spatial variability and temporal change in snow depth across the Eurasian continent. Data used include long-term (1966–2012) ground-based measurements from 1814 stations. Spatially, long-term (1971–2000) mean annual snow depths of >20 cm were recorded in northeastern European Russia, the Yenisei River basin, Kamchatka Peninsula, and Sakhalin. Annual mean and maximum snow depth increased by 0.2 and 0.6 cm decade−1 from 1966 through 2012. Seasonally, monthly mean snow depth decreased in autumn and increased in winter and spring over the study period. Regionally, snow depth significantly increased in areas north of 50° N. Compared with air temperature, snowfall had greater influence on snow depth during November through March across the former Soviet Union. This study provides a baseline for snow depth climatology and changes across the Eurasian continent, which would significantly help to better understanding climate system and climate changes on regional, hemispheric, or even global scales.

scholarly journals The Portable Ice Nucleation Experiment (PINE): a new online instrument for laboratory studies and automated long-term field observations of ice-nucleating particles

2021 ◽  
Vol 14 (2) ◽  
pp. 1143-1166
Author(s):  
Ottmar Möhler ◽  
Michael Adams ◽  
Larissa Lacher ◽  
Franziska Vogel ◽  
Jens Nadolny ◽  
...  
Keyword(s):  
Pure Water ◽  
Full Range ◽  
Field Measurements ◽  
Ice Nucleation ◽  
Spatial And Temporal Variation ◽  
Expansion Chamber ◽  
Predictive Capacity ◽  
Field Campaign ◽  
New Instrument ◽  
Term Field

Abstract. Atmospheric ice-nucleating particles (INPs) play an important role in determining the phase of clouds, which affects their albedo and lifetime. A lack of data on the spatial and temporal variation of INPs around the globe limits our predictive capacity and understanding of clouds containing ice. Automated instrumentation that can robustly measure INP concentrations across the full range of tropospheric temperatures is needed in order to address this knowledge gap. In this study, we demonstrate the functionality and capacity of the new Portable Ice Nucleation Experiment (PINE) to study ice nucleation processes and to measure INP concentrations under conditions pertinent for mixed-phase clouds, with temperatures from about −10 to about −40 ∘C. PINE is a cloud expansion chamber which avoids frost formation on the cold walls and thereby omits frost fragmentation and related background ice signals during the operation. The development, working principle and treatment of data for the PINE instrument is discussed in detail. We present laboratory-based tests where PINE measurements were compared with those from the established AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber. Within experimental uncertainties, PINE agreed with AIDA for homogeneous freezing of pure water droplets and the immersion freezing activity of mineral aerosols. Results from a first field campaign conducted at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory in Oklahoma, USA, from 1 October to 14 November 2019 with the latest PINE design (a commercially available PINE chamber) are also shown, demonstrating PINE's ability to make automated field measurements of INP concentrations at a time resolution of about 8 min with continuous temperature scans for INP measurements between −10 and −30 ∘C. During this field campaign, PINE was continuously operated for 45 d in a fully automated and semi-autonomous way, demonstrating the capability of this new instrument to also be used for longer-term field measurements and INP monitoring activities in observatories.

scholarly journals Seasonal and spatial variability of methane emissions from a subtropical reservoir in Eastern China

2018 ◽  
Author(s):  
Le Yang ◽  
Hepeng Li ◽  
Chunlei Yue ◽  
Jun Wang
Keyword(s):  
Spatial Variability ◽  
Time Scales ◽  
Seasonal Variability ◽  
Eastern China ◽  
Methane Emissions ◽  
Spatiotemporal Variability ◽  
Ch4 Emission ◽  
Atmospheric Methane ◽  
Ch4 Flux ◽  
Minimum Value

Abstract. Subtropical reservoirs are important source of atmospheric methane (CH4). This study aims to investigate the spatiotemporal variability of CH4 emission, using the methods of static floating chambers and bubble traps, from the water surfaces of Xin'anjiang Reservoir. Seasonal variability showed that CH4 emission from the main reservoir body was high in autumn and low in spring, with medium values in summer and winter. The dynamics of CH4 emission was flat from February to June, but fluctuated dramatically from July to January in the upstream river, which was interrupted by the bubbles in the second half year. However, CH4 emission was largely influenced by the streamflow in the downstream river, with a minimum value in February due to an extreme low streamflow (275 m3 s−1). Spatial variability showed the upstream river had the highest CH4 flux (3.90 ± 7.80 mg CH4 m−2 h−1), followed by the downstream river (0.50 ± 0.41 mg CH4 m−2 h−1), and the main reservoir body stood the last place (0.01 ± 0.07 mg CH4 m−2 h−1). Therefore, it was necessary to capture the variation of CH4 emission from reservoirs in the space and time scales to avoid the error of estimating the CH4 emission incorrectly.

Estimation of spatiotemporal transmission dynamics and analysis of management scenarios for sea lice of farmed and wild salmon

2020 ◽  
Vol 77 (1) ◽  
pp. 55-68 ◽  
Author(s):  
Stephanie J. Peacock ◽  
Martin Krkošek ◽  
Andrew W. Bateman ◽  
Mark A. Lewis
Keyword(s):  
Transmission Dynamics ◽  
Spatiotemporal Variability ◽  
Sea Lice ◽  
Spatial And Temporal Variation ◽  
Oncorhynchus Keta ◽  
Juvenile Salmon ◽  
Management Scenarios ◽  
Wild Salmon ◽  
Farmed Salmon ◽  
Parameterized Model

Parasite transmission between farmed and wild salmon affects the sustainability of salmon aquaculture in Pacific Canada. Understanding and managing parasites in aquaculture is challenged by spatial and temporal variation in transmission dynamics. We developed a mechanistic model that connects sea louse (Lepeoptheirus salmonis) outbreak and control on farmed salmon (Salmo salar) to spatiotemporal dynamics of sea lice on migrating wild juvenile salmon (Oncorhynchus keta and Oncorhynchus gorbuscha). We fitted the model to time series of sea lice on farmed salmon and spatial surveys of juvenile wild salmon in the Broughton Archipelago. We used the parameterized model to evaluate alternative management scenarios based on the resulting sea louse infestations and predicted mortality of wild salmon. Early and coordinated management of sea lice on salmon farms was most effective for controlling outbreaks in wild salmon, while uncoordinated treatments led to a resurgence of sea lice on salmon farms during the juvenile salmon migration. This study highlights the importance of incorporating spatiotemporal variability when considering infectious disease dynamics shared by farmed and wild hosts, particularly when migratory wildlife are involved.

Character, spatial and temporal variation of turbidity currents on a source-to-sink scale.

2020 ◽  
Author(s):  
Kate Heerema ◽  
Peter Talling ◽  
Matthieu Cartigny ◽  
Gwyn Lintern ◽  
Cooper Stacey ◽  
...  
Keyword(s):  
Full Range ◽  
Turbidity Current ◽  
Spatial And Temporal Variation ◽  
Turbidity Currents ◽  
Deep Basin ◽  
Data Set ◽  
Sedimentary Deposits ◽  
Submarine Channel ◽  
Direct Measurements ◽  
Adcp Data

<p>Seafloor avalanches of sediment called turbidity currents are one of the principle mechanisms for moving sediments across our planet. However, turbidity currents are notoriously difficult to monitor directly in action, and we still mainly depend on their sedimentary deposits as well as physical and numerical models to understand their temporal and spatial evolution. In recent years, multiple studies have successfully made direct measurements within active turbidity currents at multiple sites along their pathway. However, these direct measurements are often limited to the upper reaches of submarine systems, only cover relatively short (few months to a couple of years) time scales, or have very few measurement stations (<3). To capture the full range of turbidity current types and recurrence times we need to combine direct monitoring with longer-term archives in sedimentary deposits. Here we present an unusual data set that extends from the submarine channel on the delta, to the final deposits in the deep basin. The dataset combines short-term (< 1 year) direct measurements of flows with long-term sediment deposits (dating back to about 100 years). This combination of data types allows us to understand turbidity current frequencies, runouts, heights and characteristics along an entire submarine system.  </p><p>We analyse data from Bute Inlet, which is a fjord in British Colombia, Canada. The entire turbidity current system stretches out for 80 km, with an incised submarine channel extending for 45 km. 46 Cores have been collected between 2015 and 2018. Simultaneously, direct measurements of the currents have been obtained in 2016 and 2018 using Acoustic Doppler Current Profilers (ADCPs) in the submarine channel.</p><p>Our objective is two-fold. First, we look at flow frequency over time and space. Visual logs of the sediment cores, as well as sediment accumulation rates for a selection of cores, are used to infer flow frequencies. We then use the ADCP data to understand more frequent and recent flows at 6 places along the channel. These ADCP measurements are used to infer frequencies which are not necessarily recorded in the deposits, and give additional insights into current-day activity. This allows us to reconstruct the change in frequency over space and time.</p><p>Second, we consider the variation in turbidity current character to understand how flows evolve along the channel. Facies determination and grain size data are used to infer turbidity current character. Cores along the channel, on terraces and in the deep basin are used to understand the spatial variation. Finally, comparison of deposits and monitoring (ADCP) data shows how submarine flows are recorded by their deposits.</p>

scholarly journals High spatiotemporal variability of bacterial diversity over short time scales with unique hydrochemical associations within a shallow aquifer

2019 ◽  
Vol 164 ◽  
pp. 114917 ◽  
Author(s):  
Anna J. Zelaya ◽  
Albert E. Parker ◽  
Kathryn L. Bailey ◽  
Ping Zhang ◽  
Joy Van Nostrand ◽  
...  
Keyword(s):  
Bacterial Diversity ◽  
Time Scales ◽  
Shallow Aquifer ◽  
Spatiotemporal Variability ◽  
Short Time

scholarly journals Sea Level Expression of Intrinsic and Forced Ocean Variabilities at Interannual Time Scales

2011 ◽  
Vol 24 (21) ◽  
pp. 5652-5670 ◽  
Author(s):  
Thierry Penduff ◽  
Mélanie Juza ◽  
Bernard Barnier ◽  
Jan Zika ◽  
William K. Dewar ◽  
...  
Keyword(s):  
Sea Level ◽  
Time Scales ◽  
General Circulation ◽  
Large Scale ◽  
Full Range ◽  
Circulation Model ◽  
Global Ocean ◽  
Western Boundary ◽  
Intrinsic Variability ◽  
Boundary Current

Abstract This paper evaluates in a realistic context the local contributions of direct atmospheric forcing and intrinsic oceanic processes on interannual sea level anomalies (SLAs). A ¼° global ocean–sea ice general circulation model, driven over 47 yr by the full range of atmospheric time scales, is quantitatively assessed against altimetry and shown to reproduce most observed features of the interannual SLA variability from 1993 to 2004. Comparing this simulation with a second driven only by the climatological annual cycle reveals that the intrinsic part of the total interannual SLA variance exceeds 40% over half of the open-ocean area and exceeds 80% over one-fifth of it. This intrinsic contribution is particularly strong in eddy-active regions (more than 70%–80% in the Southern Ocean and western boundary current extensions) as predicted by idealized studies, as well as within the 20°–35° latitude bands. The atmosphere directly forces most of the interannual SLA variance at low latitudes and in most midlatitude eastern basins, in particular north of about 40°N in the Pacific. The interannual SLA variance is almost entirely due to intrinsic processes south of the Antarctic Circumpolar Current in the Indian Ocean sector, while half of this variance is forced by the atmosphere north of it. The same simulations were performed and analyzed at 2° resolution as well: switching to this laminar regime yields a comparable forced variability (large-scale distribution and magnitude) but almost suppresses the intrinsic variability. This likely explains why laminar ocean models largely underestimate the interannual SLA variance.

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