scholarly journals Monitoring Reservoir Drought Dynamics with Landsat and Radar/Lidar Altimetry Time Series in Persistently Cloudy Eastern Brazil

2019 ◽  
Vol 11 (7) ◽  
pp. 827 ◽  
Author(s):  
Jamon Van Den Hoek ◽  
Augusto Getirana ◽  
Hahn Jung ◽  
Modurodoluwa Okeowo ◽  
Hyongki Lee
Keyword(s):  
Time Series ◽  
Surface Area ◽  
Regression Models ◽  
Goodness Of Fit ◽  
Volume Changes ◽  
Landsat Images ◽  
Reservoir Volume ◽  
Eastern Brazil

Tropical reservoirs are critical infrastructure for managing drinking and irrigation water and generating hydroelectric power. However, long-term spaceborne monitoring of reservoir storage is challenged by data scarcity from near-persistent cloud cover and drought, which may reduce volumes below those in the observational record. In evaluating our ability to accurately monitor long-term reservoir volume dynamics using spaceborne data and overcome such observational challenges, we integrated optical, lidar, and radar time series to estimate reservoir volume dynamics across 13 reservoirs in eastern Brazil over a 12-year (2003–2014) period affected by historic drought. We (i) used 1560 Landsat images to measure reservoir surface area; (ii) built reservoir-specific regression models relating surface area and elevation from ICESat GLAS and Envisat RA-2 data; (iii) modeled volume changes for each reservoir; and (iv) compared modeled and in situ reservoir volume changes. Regression models had high goodness-of-fit (median RMSE = 0.89 m and r = 0.88) across reservoirs. Even though 88% of an average reservoir’s volume time series was based on modeled area–elevation relationships, we found exceptional agreement (RMSE = 0.31 km3 and r = 0.95) with in situ volume time series, and accurately captured seasonal recharge/depletion dynamics and the drought’s prolonged drawdown. Disagreements in volume dynamics were neither driven by wet/dry season conditions nor reservoir capacity, indicating analytical efficacy across a range of monitoring scenarios.

scholarly journals Mediterranean Sea climatic indices: monitoring long term variability and climate changes

2018 ◽  
Author(s):  
Athanasia Iona ◽  
Athanasios Theodorou ◽  
Sarantis Sofianos ◽  
Sylvain Watelet ◽  
Charles Troupin ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Mediterranean Sea ◽  
Climate Changes ◽  
Salt Content ◽  
Climatic Indices ◽  
In Situ Observations ◽  
The Mediterranean

Abstract. We present a new product composed of a set of thermohaline climatic indices from 1950 to 2015 for the Mediterranean Sea such as decadal temperature and salinity anomalies, their mean values over selected depths, decadal ocean heat and salt content anomalies at selected depth layers as well as their long times series. It is produced from a new high-resolution climatology of temperature and salinity on a 1/8° regular grid based on historical high quality in situ observations. Ocean heat and salt content differences between 1980–2015 and 1950–1979 are compared for evaluation of the climate shift in the Mediterranean Sea. The spatial patterns of heat and salt content shifts demonstrate in greater detail than ever before that the climate changes differently in the several regions of the basin. Long time series of heat and salt content for the period 1950 to 2015 are also provided which indicate that in the Mediterranean Sea there is a net mean volume warming and salting since 1950 with acceleration during the last two decades. The time series also show that the ocean heat content seems to fluctuate on a cycle of about 40 years and seems to follow the Atlantic Multidecadal Oscillation climate cycle indicating that the natural large scale atmospheric variability could be superimposed on to the warming trend. This product is an observations-based estimation of the Mediterranean climatic indices. It relies solely on spatially interpolated data produced from in-situ observations averaged over decades in order to smooth the decadal variability and reveal the long term trends with more accuracy. It can provide a valuable contribution to the modellers' community, next to the satellite-based products and serve as a baseline for the evaluation of climate-change model simulations contributing thus to a better understanding of the complex response of the Mediterranean Sea to the ongoing global climate change. The product is available here: https://doi.org/10.5281/zenodo.1210100.

scholarly journals Evaluation of Seven Atmospheric Profiles from Reanalysis and Satellite-Derived Products: Implication for Single-Channel Land Surface Temperature Retrieval

2020 ◽  
Vol 12 (5) ◽  
pp. 791 ◽  
Author(s):  
Jingjing Yang ◽  
Si-Bo Duan ◽  
Xiaoyu Zhang ◽  
Penghai Wu ◽  
Cheng Huang ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Single Channel ◽  
Landsat 8 ◽  
Atmospheric Profiles ◽  
Atmospheric Profile

Land surface temperature (LST) is vital for studies of hydrology, ecology, climatology, and environmental monitoring. The radiative-transfer-equation-based single-channel algorithm, in conjunction with the atmospheric profile, is regarded as the most suitable one with which to produce long-term time series LST products from Landsat thermal infrared (TIR) data. In this study, the performances of seven atmospheric profiles from different sources (the MODerate-resolution Imaging Spectroradiomete atmospheric profile product (MYD07), the Atmospheric Infrared Sounder atmospheric profile product (AIRS), the European Centre for Medium-range Weather Forecasts (ECMWF), the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2), the National Centers for Environmental Prediction (NCEP)/Global Forecasting System (GFS), NCEP/Final Operational Global Analysis (FNL), and NCEP/Department of Energy (DOE)) were comprehensively evaluated in the single-channel algorithm for LST retrieval from Landsat 8 TIR data. Results showed that when compared with the radio sounding profile downloaded from the University of Wyoming (UWYO), the worst accuracies of atmospheric parameters were obtained for the MYD07 profile. Furthermore, the root-mean-square error (RMSE) values (approximately 0.5 K) of the retrieved LST when using the ECMWF, MERRA2, NCEP/GFS, and NCEP/FNL profiles were smaller than those but greater than 0.8 K when the MYD07, AIRS, and NCEP/DOE profiles were used. Compared with the in situ LST measurements that were collected at the Hailar, Urad Front Banner, and Wuhai sites, the RMSE values of the LST that were retrieved by using the ECMWF, MERRA2, NCEP/GFS, and NCEP/FNL profiles were approximately 1.0 K. The largest discrepancy between the retrieved and in situ LST was obtained for the NCEP/DOE profile, with an RMSE value of approximately 1.5 K. The results reveal that the ECMWF, MERRA2, NCEP/GFS, and NCEP/FNL profiles have great potential to perform accurate atmospheric correction and generate long-term time series LST products from Landsat TIR data by using a single-channel algorithm.

scholarly journals Automated Extraction of Consistent Time-Variable Water Surfaces of Lakes and Reservoirs Based on Landsat and Sentinel-2

2019 ◽  
Vol 11 (9) ◽  
pp. 1010 ◽  
Author(s):  
Christian Schwatke ◽  
Daniel Scherer ◽  
Denise Dettmering
Keyword(s):  
Time Series ◽  
Surface Area ◽  
Time Variable ◽  
New Approach ◽  
Data Gaps ◽  
Lakes And Reservoirs ◽  
Variable Water ◽  
Land Water ◽  
Sentinel 2

In this study, a new approach for the automated extraction of high-resolution time-variable water surfaces is presented. For that purpose, optical images from Landsat and Sentinel-2 are used between January 1984 and June 2018. The first part of this new approach is the extraction of land-water masks by combining five water indexes and using an automated threshold computation. In the second part of this approach, all data gaps caused by voids, clouds, cloud shadows, or snow are filled by using a long-term water probability mask. This mask is finally used in an iterative approach for filling remaining data gaps in all monthly masks which leads to a gap-less surface area time series for lakes and reservoirs. The results of this new approach are validated by comparing the surface area changes with water level time series from gauging stations. For inland waters in remote areas without in situ data water level time series from satellite altimetry are used. Overall, 32 globally distributed lakes and reservoirs of different extents up to 2482.27 km 2 are investigated. The average correlation coefficients between surface area time series and water levels from in situ and satellite altimetry have increased from 0.611 to 0.862 after filling the data gaps which is an improvement of about 41%. This new approach clearly demonstrates the quality improvement for the estimated land-water masks but also the strong impact of a reliable data gap-filling approach. All presented surface area time series are freely available on the Database of Hydrological Time Series of Inland (DAHITI).

scholarly journals Effect of electrode shape on grounding resistances — Part 2: Experimental results and cryospheric monitoring

Geophysics ◽  
2016 ◽  
Vol 81 (1) ◽  
pp. WA169-WA182 ◽  
Author(s):  
Soňa Tomaškovičová ◽  
Thomas Ingeman-Nielsen ◽  
Anders V. Christiansen ◽  
Inooraq Brandt ◽  
Torleif Dahlin ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Area ◽  
Winter Season ◽  
Frozen Ground ◽  
Resistivity Tomography ◽  
Grounding Resistance ◽  
Electrode Shape ◽  
Standard Tool ◽  
Ground Conditions

Although electric resistivity tomography (ERT) is now regarded as a standard tool in permafrost monitoring, high grounding resistances continue to limit the acquisition of time series over complete freeze-thaw cycles. In an attempt to alleviate the grounding resistance problem, we have tested three electrode designs featuring increasing sizes and surface area, in the laboratory and at three different field sites in Greenland. Grounding resistance measurements showed that changing the electrode shape (using plates instead of rods) reduced the grounding resistances at all sites by 28%–69% during unfrozen and frozen ground conditions. Using meshes instead of plates (the same rectangular shape and a larger effective surface area) further improved the grounding resistances by 29%–37% in winter. Replacement of rod electrodes of one entire permanent permafrost monitoring array by meshes resulted in an immediate reduction of the average grounding resistance by 73% from [Formula: see text] to [Formula: see text] (unfrozen conditions); in addition, the length of the acquisition period during the winter season was markedly prolonged. Grounding resistance time series from the three ERT monitoring stations in Greenland showed that the electrodes were rarely perfectly grounded and that grounding resistances exceeding [Formula: see text] may occur in severe cases. We concluded that the temperature, electrode shape, and lithology at the sites have a marked impact on electrode performance. Choosing an optimized electrode design may be the deciding factor for successful data acquisition, and should therefore be considered when planning a long-term monitoring project.

scholarly journals Comparison of in situ time-series of temperature with gridded sea surface temperature datasets in the North Atlantic

2009 ◽  
Vol 66 (7) ◽  
pp. 1467-1479 ◽  
Author(s):  
Sarah L. Hughes ◽  
N. Penny Holliday ◽  
Eugene Colbourne ◽  
Vladimir Ozhigin ◽  
Hedinn Valdimarsson ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Sea Surface ◽  
The North ◽  
Spatial Coverage ◽  
The North Atlantic

Abstract Hughes, S. L., Holliday, N. P., Colbourne, E., Ozhigin, V., Valdimarsson, H., Østerhus, S., and Wiltshire, K. 2009. Comparison of in situ time-series of temperature with gridded sea surface temperature datasets in the North Atlantic. – ICES Journal of Marine Science, 66: 1467–1479. Analysis of the effects of climate variability and climate change on the marine ecosystem is difficult in regions where long-term observations of ocean temperature are sparse or unavailable. Gridded sea surface temperature (SST) products, based on a combination of satellite and in situ observations, can be used to examine variability and long-term trends because they provide better spatial coverage than the limited sets of long in situ time-series. SST data from three gridded products (Reynolds/NCEP OISST.v2., Reynolds ERSST.v3, and the Hadley Centre HadISST1) are compared with long time-series of in situ measurements from ICES standard sections in the North Atlantic and Nordic Seas. The variability and trends derived from the two data sources are examined, and the usefulness of the products as a proxy for subsurface conditions is discussed.

Towards a long term global snow climate data record from satellite data generated within the Snow Climate Change Initiative

2020 ◽  
Author(s):  
Gabriele Schwaizer ◽  
Lars Keuris ◽  
Thomas Nagler ◽  
Chris Derksen ◽  
Kari Luojus ◽  
...  
Keyword(s):  
Time Series ◽  
Satellite Data ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Process Models ◽  
Climate Data ◽  
Seasonal Snow ◽  
Snow Water

<p>Seasonal snow is an important component of the global climate system. It is highly variable in space and time and sensitive to short term synoptic scale processes and long term climate-induced changes of temperature and precipitation. Current snow products derived from various satellite data applying different algorithms show significant discrepancies in extent and snow mass, a potential source for biases in climate monitoring and modelling. The recently launched ESA CCI+ Programme addresses seasonal snow as one of 9 Essential Climate Variables to be derived from satellite data.</p><p>In the snow_cci project, scheduled for 2018 to 2021 in its first phase, reliable fully validated processing lines are developed and implemented. These tools are used to generate homogeneous multi-sensor time series for the main parameters of global snow cover focusing on snow extent and snow water equivalent. Using GCOS guidelines, the requirements for these parameters are assessed and consolidated using the outcome of workshops and questionnaires addressing users dealing with different climate applications. Snow extent product generation applies algorithms accounting for fractional snow extent and cloud screening in order to generate consistent daily products for snow on the surface (viewable snow) and snow on the surface corrected for forest masking (snow on ground) with global coverage. Input data are medium resolution optical satellite images (AVHRR-2/3, AATSR, MODIS, VIIRS, SLSTR/OLCI) from 1981 to present. An iterative development cycle is applied including homogenisation of the snow extent products from different sensors by minimizing the bias. Independent validation of the snow products is performed for different seasons and climate zones around the globe from 1985 onwards, using as reference high resolution snow maps from Landsat and Sentinel- 2as well as in-situ snow data following standardized validation protocols.</p><p>Global time series of daily snow water equivalent (SWE) products are generated from passive microwave data from SMMR, SSM/I, and AMSR from 1978 onwards, combined with in-situ snow depth measurements. Long-term stability and quality of the product is assessed using independent snow survey data and by intercomparison with the snow information from global land process models.</p><p>The usability of the snow_cci products is ensured through the Climate Research Group, which performs case studies related to long term trends of seasonal snow, performs evaluations of CMIP-6 and other snow-focused climate model experiments, and applies the data for simulation of Arctic hydrological regimes.</p><p>In this presentation, we summarize the requirements and product specifications for the snow extent and SWE products, with a focus on climate applications. We present an overview of the algorithms and systems for generation of the time series. The 40 years (from 1980 onwards) time series of daily fractional snow extent products from AVHRR with 5 km pixel spacing, and the 20-year time series from MODIS (1 km pixel spacing) as well as the coarse resolution (25 km pixel spacing) of daily SWE products from 1978 onwards will be presented along with first results of the multi-sensor consistency checks and validation activities.</p>

scholarly journals Aerosol decadal trends – Part 2: In-situ aerosol particle number concentrations at GAW and ACTRIS stations

2013 ◽  
Vol 13 (2) ◽  
pp. 895-916 ◽  
Author(s):  
A. Asmi ◽  
M. Collaud Coen ◽  
J. A. Ogren ◽  
E. Andrews ◽  
P. Sheridan ◽  
...  
Keyword(s):  
Time Series ◽  
Aerosol Particle ◽  
Particle Number ◽  
Cloud Condensation Nuclei ◽  
Temperature Changes ◽  
Long Time ◽  
Modelling Studies ◽  
Infrastructure Project

Abstract. We have analysed the trends of total aerosol particle number concentrations (N) measured at long-term measurement stations involved either in the Global Atmosphere Watch (GAW) and/or EU infrastructure project ACTRIS. The sites are located in Europe, North America, Antarctica, and on Pacific Ocean islands. The majority of the sites showed clear decreasing trends both in the full-length time series, and in the intra-site comparison period of 2001–2010, especially during the winter months. Several potential driving processes for the observed trends were studied, and even though there are some similarities between N trends and air temperature changes, the most likely cause of many northern hemisphere trends was found to be decreases in the anthropogenic emissions of primary particles, SO2 or some co-emitted species. We could not find a consistent agreement between the trends of N and particle optical properties in the few stations with long time series of all of these properties. The trends of N and the proxies for cloud condensation nuclei (CCN) were generally consistent in the few European stations where the measurements were available. This work provides a useful comparison analysis for modelling studies of trends in aerosol number concentrations.

scholarly journals A comparison of empirical and physically based glacier surface melt models for long-term simulations of glacier response

2014 ◽  
Vol 60 (224) ◽  
pp. 1140-1154 ◽  
Author(s):  
Jeannette Gabbi ◽  
Marco Carenzo ◽  
Francesca Pellicciotti ◽  
Andreas Bauder ◽  
Martin Funk
Keyword(s):  
Shortwave Radiation ◽  
Radiation Balance ◽  
Volume Changes ◽  
Glacier Surface ◽  
Surface Evolution ◽  
Ice Volume ◽  
In Situ Data ◽  
Physically Based

AbstractWe investigate the performance of five glacier melt models over a multi-decadal period in order to assess their ability to model future glacier response. The models range from a simple degree-day model, based solely on air temperature, to more-sophisticated models, including the full shortwave radiation balance. In addition to the empirical models, the performance of a physically based energy-balance (EB) model is examined. The melt models are coupled to an accumulation and a surface evolution model and applied in a distributed manner to Rhonegletscher, Switzerland, over the period 1929–2012 at hourly resolution. For calibration, seasonal mass-balance measurements (2006–12) are used. Decadal ice volume changes for six periods in the years 1929–2012 serve for model validation. Over the period 2006–12, there are almost no differences in performance between the models, except for EB, which is less consistent with observations, likely due to lack of meteorological in situ data. However, simulations over the long term (1929–2012) reveal that models which include a separate term for shortwave radiation agree best with the observed ice volume changes, indicating that their melt relationships are robust in time and thus suitable for long-term modelling, in contrast to more empirical approaches that are oversensitive to temperature fluctuations.

scholarly journals Spatial-temporal analysis of temperature in Lake Shira based on long-term observations

2021 ◽  
Author(s):  
O.S. Volodko ◽  
L.A. Kompaniets ◽  
L.V. Gavrilova
Keyword(s):  
Principal Component Analysis ◽  
Time Series ◽  
Principal Component ◽  
Temporal Analysis ◽  
Temperature Time Series ◽  
Lake Shira ◽  
Temperature Time ◽  
Spatial Temporal Analysis

Long-term in-situ measurements of temperature were conducted in lake Shira during 2013-2015. The principal component analysis of temperature time series allowed to identify period of generation and propagation of internal waves. The spectral analysis revealed the dominance of the oscillations with periods of 21.3, 10.6 and 5.3 h.

Sign in / Sign up

Export Citation Format

Share Document