91 research outputs found

    Google Earth Engine Open-Source Code for Land Surface Temperature Estimation from the Landsat Series

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    Land Surface Temperature (LST) is increasingly important for various studies assessing land surface conditions, e.g., studies of urban climate, evapotranspiration, and vegetation stress. The Landsat series of satellites have the potential to provide LST estimates at a high spatial resolution, which is particularly appropriate for local or small-scale studies. Numerous studies have proposed LST retrieval algorithms for the Landsat series, and some datasets are available online. However, those datasets generally require the users to be able to handle large volumes of data. Google Earth Engine (GEE) is an online platform created to allow remote sensing users to easily perform big data analyses without increasing the demand for local computing resources. However, high spatial resolution LST datasets are currently not available in GEE. Here we provide a code repository that allows computing LSTs from Landsat 4, 5, 7, and 8 within GEE. The code may be used freely by users for computing Landsat LST as part of any analysis within GEE

    Impact of High Concentrations of Saharan Dust Aerosols on Infrared-Based Land Surface Temperature Products

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    An analysis of three operational satellite-based thermal-infrared land surface temperature (LST) products is presented for conditions of heavy dust aerosol loading. The LST products are compared against ERA5’s skin temperature (SKT) across the Sahara Desert and Sahel region, where high concentrations of dust aerosols are prevalent. Large anomalous differences are found between satellite LST and ERA5’s SKT during the periods of highest dust activity, and satellite–ERA5 differences are shown to be strongly related to dust aerosol optical depth (DuAOD) at 550 nm, indicating an underestimation of LST in conditions of heavy dust aerosol loading. In situ measurements from two ground stations in the Sahel region provide additional evidence of this underestimation, showing increased biases of satellite LST with DuAOD, and no significant dependence of ERA5’s SKT biases on dust aerosol concentrations. The impact of atmospheric water vapor content on LST and SKT is also examined, but dust aerosols are shown to be the primary driver of the inaccurate LSTs observed. Based on comparisons with in situ data, we estimate an aerosol-induced underestimation of LST of approximately 0.9 K for every 0.1 increase in DuAOD. Analysis of brightness temperatures (BTs) in the thermal infrared atmospheric window reveals that dust aerosols have the opposite effect on BT differences compared to water vapor, leading to an underestimation of atmospheric correction by the LST retrieval algorithms. This article highlights a shortcoming of current operational LST retrieval algorithms that must be addressed

    a consensus view among methods with different system identification and tracking criteria

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    The Mediterranean storm track constitutes a well-defined branch of the North Hemisphere storm track and is characterised by small but intense features and frequent cyclogenesis. The goal of this study is to assess the level of consensus among cyclone detection and tracking methods (CDTMs), to identify robust features and to explore sources of disagreement. A set of 14 CDTMs has been applied for computing the climatology of cyclones crossing the Mediterranean region using the ERA-Interim dataset for the period 1979–2008 as common testbed. Results show large differences in actual cyclone numbers identified by different methods, but a good level of consensus on the interpretation of results regarding location, annual cycle and trends of cyclone tracks. Cyclogenesis areas such as the north-western Mediterranean, North Africa, north shore of the Levantine basin, as well as the seasonality of their maxima are robust features on which methods show a substantial agreement. Differences among methods are greatly reduced if cyclone numbers are transformed to a dimensionless index, which, in spite of disagreement on mean values and interannual variances of cyclone numbers, reveals a consensus on variability, sign and significance of trends. Further, excluding ‘weak’ and ‘slow’ cyclones from the computation of cyclone statistics improves the agreement among CDTMs. Results show significant negative trends of cyclone frequency in spring and positive trends in summer, whose contrasting effects compensate each other at annual scale, so that there is no significant long- term trend in total cyclone numbers in the Mediterranean basin in the 1979–2008 period

    Quality assessment of S-NPP VIIRS land surface temperature product

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    The VIIRS Land Surface Temperature (LST) Environmental Data Record (EDR) has reached validated (V1 stage) maturity in December 2014. This study compares VIIRS v1 LST with the ground in situ observations and with heritage LST product from MODIS Aqua and AATSR. Comparisons against U.S. SURFRAD ground observations indicate a similar accuracy among VIIRS, MODIS and AATSR LST, in which VIIRS LST presents an overall accuracy of −0.41 K and precision of 2.35 K. The result over arid regions in Africa suggests that VIIRS and MODIS underestimate the LST about 1.57 K and 2.97 K, respectively. The cross comparison indicates an overall close LST estimation between VIIRS and MODIS. In addition, a statistical method is used to quantify the VIIRS LST retrieval uncertainty taking into account the uncertainty from the surface type input. Some issues have been found as follows: (1) Cloud contamination, particularly the cloud detection error over a snow/ice surface, shows significant impacts on LST validation; (2) Performance of the VIIRS LST algorithm is strongly dependent on a correct classification of the surface type; (3) The VIIRS LST quality can be degraded when significant brightness temperature difference between the two split window channels is observed; (4) Surface type dependent algorithm exhibits deficiency in correcting the large emissivity variations within a surface type

    Long Term Validation of Land Surface Temperature Retrieved from MSG/SEVIRI with Continuous in-Situ Measurements in Africa

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    Since 2005, the Land Surface Analysis Satellite Application Facility (LSA SAF) operationally retrieves Land Surface Temperature (LST) for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat Second Generation (MSG). The high temporal resolution of the Meteosat satellites and their long term availability since 1977 make their data highly valuable for climate studies. In order to ensure that the LSA SAF LST product continuously meets its target accuracy of 2 °C, it is validated with in-situ measurements from four dedicated LST validation stations. Three stations are located in highly homogenous areas in Africa (semiarid bush, desert, and Kalahari semi-desert) and typically provide thousands of monthly match-ups with LSA SAF LST, which are used to perform seasonally resolved validations. An uncertainty analysis performed for desert station Gobabeb yielded an estimate of total in-situ LST uncertainty of 0.8 ± 0.12 °C. Ignoring rainy seasons, the results for the period 2009–2014 show that LSA SAF LST consistently meets its target accuracy: the highest mean root-mean-square error (RMSE) for LSA SAF LST over the African stations was 1.6 °C while mean absolute bias was 0.1 °C. Nighttime and daytime biases were up to 0.7 °C but had opposite signs: when evaluated together, these partially compensated each other

    Long-term effects of tafamidis for the treatment of transthyretin familial amyloid polyneuropathy

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    Tafamidis, a transthyretin (TTR) kinetic stabilizer, delayed neuropathic progression in patients with Val30Met TTR familial amyloid polyneuropathy (TTR-FAP) in an 18-month randomized controlled trial (study Fx-005). This 12-month, open-label extension study evaluated the long-term safety, tolerability, and efficacy of tafamidis 20 mg once daily in 86 patients who earlier received blinded treatment with tafamidis or placebo. Efficacy measures included the Neuropathy Impairment Score in the Lower Limbs (NIS-LL), Norfolk Quality of Life-Diabetic Neuropathy total quality of life (TQOL) score, and changes in neurologic function and nutritional status. We quantified the monthly rates of change in efficacy measures, and TTR stabilization, and monitored adverse events (AEs). Patients who continued on tafamidis had stable rates of change in NIS-LL (from 0.08 to 0.11/month; p = 0.60) and TQOL (from −0.03 to 0.25; p = 0.16). In patients switched from placebo, the monthly rate of change in NIS-LL declined (from 0.34 to 0.16/month; p = 0.01), as did TQOL score (from 0.61 to −0.16; p < 0.001). Patients treated with tafamidis for 30 months had 55.9 % greater preservation of neurologic function as measured by the NIS-LL than patients in whom tafamidis was initiated later. Plasma TTR was stabilized in 94.1 % of patients treated with tafamidis for 30 months. AEs were similar between groups; no patients discontinued because of an AE. Long-term tafamidis was well tolerated, with the reduced rate of neurologic deterioration sustained over 30 months. Tafamidis also slowed neurologic impairment in patients previously given placebo, but treatment benefits were greater when tafamidis was begun earlier

    Are greenhouse gas signals of Northern Hemisphere winter extra-tropical cyclone activity dependent on the identification and tracking algorithm?

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    For Northern Hemisphere extra-tropical cyclone activity, the dependency of a potential anthropogenic climate change signal on the identification method applied is analysed. This study investigates the impact of the used algorithm on the changing signal, not the robustness of the climate change signal itself. Using one single transient AOGCM simulation as standard input for eleven state-of-the-art identification methods, the patterns of model simulated present day climatologies are found to be close to those computed from re-analysis, independent of the method applied. Although differences in the total number of cyclones identified exist, the climate change signals (IPCC SRES A1B) in the model run considered are largely similar between methods for all cyclones. Taking into account all tracks, decreasing numbers are found in the Mediterranean, the Arctic in the Barents and Greenland Seas, the mid-latitude Pacific and North America. Changing patterns are even more similar, if only the most severe systems are considered: the methods reveal a coherent statistically significant increase in frequency over the eastern North Atlantic and North Pacific. We found that the differences between the methods considered are largely due to the different role of weaker systems in the specific methods

    IMILAST: a community effort to intercompare extratropical cyclone detection and tracking algorithms

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    The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases
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