Lake surface water temperatures of European Alpine lakes (1989–2013) based on the Advanced Very High Resolution Radiometer (AVHRR) 1 km data set

Riffler, Michael; Lieberherr, Gian-Duri; Wunderle, Stefan

doi:10.5194/essd-7-1-2015

Cited by 123 publications

(83 citation statements)

References 42 publications

(71 reference statements)

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“…For more details on thermal calibration, refer to [9] and [34]. The aforementioned calibration techniques are successfully implemented in operation for generating historical AVHRR baseline data records over Canada by [18] and more recently to develop LSWT time series for Alpine lakes in Europe by [21]. In Pytroll, pygac library has implemented thermal calibration procedure as per [8,10] followed by a Fourier transform filtering to remove high frequency fluctuations [34]; which we used to successfully calibrate the thermal channels ( Figure 3).…”

Section: Pre-processingmentioning

confidence: 99%

“…For the validation of the calibrated AVHRR LAC time series data, we compared the LSWT of the Lake Garda estimated from all the valid thermal channels, irrespective of the NOAA instrument, after pre-processing, geo-rectification and orbital drift correction [21]. Figure 7 shows boxplots of absolute lake mean LSWT differences between pair of NOAA instruments.…”

Section: Quality Assessment Of the Time Series Using Estimated Lswtmentioning

confidence: 99%

“…In the original study, North American regional reanalysis is used. Here we replaced it with the European regional analysis interim dataset developed by the European Center for Medium-range Weather Forecasts(ECMWF) [37] following the successful implementation over Europe by [21]. The SPARC algorithm is implemented using raster processing tools in GRASS GIS 7.0 ( Figure 3).…”

Section: Pre-processingmentioning

confidence: 99%

“…As a proof of concept, geo-rectified time series (1986-2014) of brightness temperature from the two thermal bands (channels 4 and 5) of AVHRR are developed, which is then intended to be used for estimating the historical surface temperature of sub-alpine lakes [21]. The quality of the developed time series is validated for the automatic geo-rectification and thermal calibration.…”

Section: Introductionmentioning

confidence: 99%

“…Numerous studies in the past deal with the accurate geolocation of the AVHRR LAC data to develop continuous time series irrespective of the NOAA instrument [1,[14][15][16][17][18][19][20][21]. One of the earlier methods is the automatic adjustment of the AVHRR images by applying a physical deformation model of the actual image using the ephemeral elements followed by landmark adjustment using reference Ground Control Points (GCP) along coastal lines [1,15].…”

Section: Introductionmentioning

confidence: 99%

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New Automated Method to Develop Geometrically Corrected Time Series of Brightness Temperatures from Historical AVHRR LAC Data

et al. 2016

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Analyzing temporal series of satellite data for regional scale studies demand high accuracy in calibration and precise geo-rectification at higher spatial resolution. The Advanced Very High Resolution Radiometer (AVHRR) sensor aboard the National Oceanic and Atmospheric Administration (NOAA) series of satellites provide daily observations for the last 30 years at a nominal resolution of 1.1 km at nadir. However, complexities due to on-board malfunctions and orbital drifts with the earlier missions hinder the usage of these images at their original resolution. In this study, we developed a new method using multiple open source tools which can read level 1B radiances, apply solar and thermal calibration to the channels, remove bow-tie effects on wider zenith angles, correct for clock drifts on earlier images and perform precise geo-rectification by automated generation and filtering of ground control points using a feature matching technique. The entire workflow is reproducible and extendable to any other geographical location. We developed a time series of brightness temperature maps from AVHRR local area coverage images covering the sub alpine lakes of Northern Italy at 1 km resolution (1986-2014; 28 years). For the validation of derived brightness temperatures, we extracted Lake Surface Water Temperature (LSWT) for Lake Garda in Northern Italy and performed inter-platform (NOAA-x vs. NOAA-y) and cross-platform (NOAA-x vs. MODIS/ATSR/AATSR) comparisons. The MAE calculated over available same day observations between the pairs-NOAA-12/14, NOAA-17/18 and NOAA-18/19 are 1.18 K, 0.67 K, 0.35 K, respectively. Similarly, for cross-platform pairs, the MAE varied between 0.5 to 1.5 K. The validation of LSWT from various NOAA instruments with in-situ data shows high accuracy with mean R 2 and RMSE of 0.97 and 0.91 K respectively.

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Section: Pre-processingmentioning

confidence: 99%

Section: Quality Assessment Of the Time Series Using Estimated Lswtmentioning

confidence: 99%

Section: Pre-processingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

New Automated Method to Develop Geometrically Corrected Time Series of Brightness Temperatures from Historical AVHRR LAC Data

et al. 2016

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Global and regional fluxes of carbon from land use and land cover change 1850–2015

Houghton

Nassikas

2017

Global Biogeochemical Cycles

490

401

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The net flux of carbon from land use and land cover change (LULCC) is an important term in the global carbon balance. Here we report a new estimate of annual fluxes from 1850 to 2015, updating earlier analyses with new estimates of both historical and current rates of LULCC and including emissions from draining and burning of peatlands in Southeast Asia. For most of the 186 countries included we relied on data from Food and Agriculture Organization to document changes in the areas of croplands and pastures since 1960 and changes in the areas of forests and “other land” since 1990. For earlier years we used other sources of information. We used a bookkeeping model that prescribed changes in carbon density of vegetation and soils for 20 types of ecosystems and five land uses. The total net flux attributable to LULCC over the period 1850–2015 is calculated to have been 145 ± 16 Pg C (1 standard deviation). Most of the emissions were from the tropics (102 ± 5.8 Pg C), generally increasing over time to a maximum of 2.10 Pg C yr−1 in 1997. Outside the tropics emissions were roughly constant at 0.5 Pg C yr−1 until 1940, declined to zero around 1970, and then became negative. For the most recent decade (2006–2015) global net emissions from LULCC averaged 1.11 (±0.35) Pg C yr−1, consisting of a net source from the tropics (1.41 ± 0.17 Pg C yr−1), a net sink in northern midlatitudes (−0.28 ± 0.21 Pg C yr−1), and carbon neutrality in southern midlatitudes.

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Seasonality of change: Summer warming rates do not fully represent effects of climate change on lake temperatures

Winslow

Read

Hansen

et al. 2017

Limnology & Oceanography

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Responses in lake temperatures to climate warming have primarily been characterized using seasonal metrics of surface-water temperatures such as summertime or stratified period average temperatures. However, climate warming may not affect water temperatures equally across seasons or depths. We analyzed a longterm dataset of biweekly water temperature data in six temperate lakes in Wisconsin, U.S.A. to understand (1) variability in monthly rates of surface-and deep-water warming, (2) how those rates compared to summertime average trends, and (3) if monthly heterogeneity in water temperature trends can be predicted by heterogeneity in air temperature trends. Monthly surface-water temperature warming rates varied across the open-water season, ranging from 0.013 in August to 0.0738C yr 21 in September (standard deviation [SD]: 0.0258C yr 21 ). Deep-water trends during summer varied less among months (SD: 0.0068C yr 21 ), but varied broadly among lakes (-0.0568C yr 21 to 0.0358C yr 21 , SD: 0.0348C yr 21 ). Trends in monthly surface-water temperatures were well correlated with air temperature trends, suggesting monthly air temperature trends, for which data exist at broad scales, may be a proxy for seasonal patterns in surface-water temperature trends during the open water season in lakes similar to those studied here. Seasonally variable warming has broad implications for how ecological processes respond to climate change, because phenological events such as fish spawning and phytoplankton succession respond to specific, seasonal temperature cues. 2168LIMNOLOGY and OCEANOGRAPHY

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Lake surface water temperatures of European Alpine lakes (1989–2013) based on the Advanced Very High Resolution Radiometer (AVHRR) 1 km data set

Cited by 123 publications

References 42 publications

New Automated Method to Develop Geometrically Corrected Time Series of Brightness Temperatures from Historical AVHRR LAC Data

New Automated Method to Develop Geometrically Corrected Time Series of Brightness Temperatures from Historical AVHRR LAC Data

Global and regional fluxes of carbon from land use and land cover change 1850–2015

Seasonality of change: Summer warming rates do not fully represent effects of climate change on lake temperatures

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