WorldWideScience

Sample records for satellite avhrr temperature

  1. Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

    Science.gov (United States)

    Comiso, Joey C.

    1995-01-01

    Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have

  2. A satellite-based climatology (1989-2012) of lake surface water temperature from AVHRR 1-km for Central European water bodies

    Science.gov (United States)

    Riffler, Michael; Wunderle, Stefan

    2013-04-01

    The temperature of lakes is an important parameter for lake ecosystems influencing the speed of physio-chemical reactions, the concentration of dissolved gazes (e.g. oxygen), and vertical mixing. Even small temperature changes might have irreversible effects on the lacustrine system due to the high specific heat capacity of water. These effects could alter the quality of lake water depending on parameters like lake size and volume. Numerous studies mention lake water temperature as an indicator of climate change and in the Global Climate Observing System (GCOS) requirements it is listed as an essential climate variable. In contrast to in situ observations, satellite imagery offers the possibility to derive spatial patterns of lake surface water temperature (LSWT) and their variability. Moreover, although for some European lakes long in situ time series are available, the temperatures of many lakes are not measured or only on a non-regular basis making these observations insufficient for climate monitoring. However, only few satellite sensors offer the possibility to analyze time series which cover more than 20 years. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown on the National Oceanic and Atmospheric Administration (NOAA) Polar Operational Environmental Satellites (POES) and on the Meteorological Operational Satellites (MetOp) from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) as a heritage instrument for almost 35 years. It will be carried on for at least ten more years finally offering a unique opportunity for satellite-based climate studies. Herein we present the results from a study initiated by the Swiss GCOS office to generate a satellite-based LSWT climatology for the pre-alpine water bodies in Switzerland. It relies on the extensive AVHRR 1-km data record (1985-2012) of the Remote Sensing Research Group at the University of Bern (RSGB) and has been derived from the AVHRR/2

  3. Estimation of the soil temperature from the AVHRR-NOAA satellite data applying split window algorithms; Estimacion de la temperatura de suelo desde datos satelitales AVHRR-NOAA aplicando algoritmos de split window

    Energy Technology Data Exchange (ETDEWEB)

    Parra, J.C.; Acevedo, P.S. [Depto. de Ciencias Fisicas, Universidad de la Frontera, Casilla 54-D, Temuco (Chile); Sobrino, J.A. [Dep. de Termodinamica, Universidad de Valencia, 46100 Burjassot, Valencia (Spain); Morales, L.J. [Dep. de Fisica, Universidad Tecnologica Metropolitana, Casilla 9845, Santiago (Chile)

    2006-07-01

    Four algorithms based on the technique of split-window, to estimate the land surface temperature starting from the data provided by the sensor Advanced Very High Resolution radiometer (AVHRR), on board the series of satellites of the National Oceanic and Atmospheric Administration (NOAA), are carried out. These algorithms consider corrections for atmospheric characteristics and emissivity of the different surfaces of the land. Fourteen images AVHRR-NOAA corresponding to the months of October of 2003, and January of 2004 were used. Simultaneously, measurements of soil temperature in the Carillanca hydro-meteorological station were collected in the Region of La Araucana, Chile (38 deg 41 min S; 72 deg 25 min W). Of all the used algorithms, the best results correspond to the model proposed by Sobrino and Raussoni (2000), with a media and standard deviation corresponding to the difference among the temperature of floor measure in situ and the estimated for this algorithm, of -0.06 and 2.11 K, respectively. (Author)

  4. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  5. GHRSST Level 3P Global Subskin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Level 3 Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A platform...

  6. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  7. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  8. GHRSST L3C global sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-B) (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR)...

  9. GHRSST Level 3P North Atlantic Regional Subskin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  10. GHRSST L3C global sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-A) (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR)...

  11. Lossless compression of NOAA-AVHRR satellite data

    Science.gov (United States)

    Takamura, Seishi; Takagi, Mikio

    1994-01-01

    A high-performance lossless compression system for satellite NOAA data is developed. The data is called 'high resolution picture transmission' (HRPT) data, and consists of around 93 percent advanced very high resolution radiometer (AVHRR) multi-channel image data and 7 percent of miscellaneous data. In compressing the image portion, we classify each pixel into 10 different groups and apply a multi-channel prediction and a non-linear error conversion. The entropy coder is an arithmetic coder which is adaptive and regenerates the approximation of the statistical properties of the source as an initial probability table. To compress the non-image part, we used the general compressor (gzip). From experimental results, the original information is compressed down to 25 percent to approx. 40 percent.

  12. GHRSST Level 2P Global Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite produced by NAVO (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  13. GHRSST Level 2P Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite produced by NAVO (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  14. GHRSST Level 2P Global Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset based on multi-channel sea surface temperature (SST) retrievals from the...

  15. GHRSST Level 2P Global Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset based on multi-channel sea surface temperature (SST) retrievals from the...

  16. GHRSST Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite produced by NAVO (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  17. GHRSST Level 2P Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the Atlantic Ocean and nearby regions based on multi-channel sea surface...

  18. GHRSST Level 2P Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the Atlantic Ocean and nearby regions based on multi-channel sea surface...

  19. Long-Term High-Latitude Sea and Ice Surface Temperature Record from AVHRR GAC Data

    Science.gov (United States)

    Luis, C. S.; Dybkjær, G.; Eastwood, S.; Tonboe, R. T.; Høyer, J. L.

    2014-12-01

    Surface temperature is among the most important variables in the surface energy balance equation and it significantly affects the atmospheric boundary layer structure, the turbulent heat exchange and, over ice, the ice growth rate. Here we measure the surface temperature using thermal infrared sensors from 10-12 μm wavelength, a method whose primary limitation over sea ice is the detection of clouds. However, in the Arctic and around Antarctica there are very few conventional observations of surface temperature from buoys, and it is sometimes difficult to determine if the temperature is measured at the surface or within the snowpack, the latter of which often results in a warm bias. To reduce this bias, much interest is being paid to alternative remote sensing methods for monitoring high latitude surface temperature. We used Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) data to produce a high latitude sea surface temperature (SST), ice surface temperature (IST) and ice cap skin temperature dataset spanning 27 years (1982-2009). This long-term climate record is the first of its kind for IST. In this project we used brightness temperatures from the infrared channels of AVHRR sensors aboard NOAA and Metop polar-orbiting satellites. Surface temperatures were calculated using separate split window algorithms for day SST, night SST, and IST. The snow surface emissivity across all angles of the swath were simulated specifically for all sensors using an emission model. Additionally, all algorithms were tuned to the Arctic using simulated brightness temperatures from a radiative transfer model with atmospheric profiles and skin temperatures from European Centre for Medium-Range Forecasts (ECMWF) re-analysis data (ERA-Interim). Here we present the results of product quality as compared to in situ measurements from buoys and infrared radiometers, as well as a preliminary analysis of climate trends revealed by the record.

  20. Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

    Directory of Open Access Journals (Sweden)

    G. Dybkjær

    2012-11-01

    Full Text Available The ice surface temperature (IST is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions prevail during spring in the Arctic, while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveals that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C and that the different in situ measurements complicate the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic, the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere.

  1. Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

    Directory of Open Access Journals (Sweden)

    G. Dybkjær

    2012-03-01

    Full Text Available The ice surface temperature (IST is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions are prevailing during spring in the Arctic while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveal that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C and that the different in situ measures complicates the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere.

  2. OW NOAA AVHRR-GAC Sea-Surface Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains satellite-derived sea-surface temperature measurements collected by means of the Advanced Very High Resolution Radiometer - Global Area Coverage...

  3. Surface Temperature Trends in the Arctic and the Antarctic from AVHRR and In Situ Data

    Science.gov (United States)

    Perez, G. J. P.; Comiso, J. C.

    2015-12-01

    The earliest signals of a climate change are expected to be observed in the polar regions in part because of the high reflectively of snow and ice. Because of general inaccessibility, there is a paucity of in situ data and hence the need to use satellite data to observe the large-scale variability and trends in surface temperature in the two regions. The sensor with the longest satellite record on temperature has been the NOAA/Advanced Very High Resolution Radiometer (AVHRR) that has provided continuous thermal infrared data for more than 33 years. The results of analysis of the data show that there is indeed a strong signal coming from the Arctic with the trend in surface temperature (for the region > 64°N) being 0.6°C per decade which is about 3 times the global trend of 0.2°C per decade for the same period. It appeared surprising when the results from a similar region (> 64 °S) in the Antarctic show a much lower trend and comparable to the global trend. The primary source of error in the temperature data is cloud masking associated with the similar signatures of clouds and snow/ice covered surfaces. However, the derived AVHRR data show good consistency with in situ data with standard deviation less than 1°C. The AVHRR time series has also been compared and showed compatibility with data from the Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) which have been available from 2000 to the present. Some differences in the trends from the two hemispheres are expected because of very different geographical environments in the two regions. The relationships of the trend with the atmospheric global circulation in the north, as defined by the Northern Annular Mode (NAM), and that in the south, as defined by the Southern Annular Mode (SAM), have been observed to be generally weak. The occurrences of the Antarctic Circumpolar Wave (ACW) and ENSO were also studied and not considered a significant factor. It is intriguing that the observed variability in

  4. Retrieval of Atmospheric Horizontal Visibility by Statistical Regression from NOAA/AVHRR Satellite Data

    Institute of Scientific and Technical Information of China (English)

    HUANG Fei; WANG Hong; QIAN Junping; WANG Guofu

    2006-01-01

    Based on the atmospheric horizontal visibility data from forty-seven observational stations along the eastern coast of China near the Taiwan Strait and simultaneous NOAA/AVHRR multichannel satellite data during January 2001 to December 2002, the spectral characters associated with visibility were investigated.Successful retrieval of visibility from multichannel NOAA/AVHRR data was performed using the principal component regression (PCR) method.A sample of retrieved visibility distribution was discussed with a sea fog process.The correlation coefficient between the observed and retrieved visibility was about 0.82, which is far higher than the 99.9% confidence level by statistical test.The rate of successful retrieval is 94.98% of the 458 cases during 2001- 2002.The error distribution showed that high visibilities were usually under-estimated and low visibilities were over-estimated and the relative error between the observed and retrieved visibilities was about 21.4%.

  5. Effect of NOAA satellite orbital drift on AVHRR-derived phenological metrics

    Science.gov (United States)

    Ji, Lei; Brown, Jesslyn F.

    2017-10-01

    The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center routinely produces and distributes a remote sensing phenology (RSP) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) 1-km data compiled from a series of National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-11, -14, -16, -17, -18, and -19). Each NOAA satellite experienced orbital drift during its duty period, which influenced the AVHRR reflectance measurements. To understand the effect of the orbital drift on the AVHRR-derived RSP dataset, we analyzed the impact of solar zenith angle (SZA) on the RSP metrics in the conterminous United States (CONUS). The AVHRR weekly composites were used to calculate the growing-season median SZA at the pixel level for each year from 1989 to 2014. The results showed that the SZA increased towards the end of each NOAA satellite mission with the highest increasing rate occurring during NOAA-11 (1989-1994) and NOAA-14 (1995-2000) missions. The growing-season median SZA values (44°-60°) in 1992, 1993, 1994, 1999, and 2000 were substantially higher than those in other years (28°-40°). The high SZA in those years caused negative trends in the SZA time series, that were statistically significant (at α = 0.05 level) in 76.9% of the CONUS area. A pixel-based temporal correlation analysis showed that the phenological metrics and SZA were significantly correlated (at α = 0.05 level) in 4.1-20.4% of the CONUS area. After excluding the 5 years with high SZA (>40°) from the analysis, the temporal SZA trend was largely reduced, significantly affecting less than 2% of the study area. Additionally, significant correlation between the phenological metrics and SZA was observed in less than 7% of the study area. Our study concluded that the NOAA satellite orbital drift increased SZA, and in turn, influenced the phenological metrics. Elimination of the years with high median SZA reduced the influence of orbital drift

  6. Effect of NOAA satellite orbital drift on AVHRR-derived phenological metrics

    Science.gov (United States)

    Ji, Lei; Brown, Jesslyn

    2017-01-01

    The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center routinely produces and distributes a remote sensing phenology (RSP) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) 1-km data compiled from a series of National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-11, −14, −16, −17, −18, and −19). Each NOAA satellite experienced orbital drift during its duty period, which influenced the AVHRR reflectance measurements. To understand the effect of the orbital drift on the AVHRR-derived RSP dataset, we analyzed the impact of solar zenith angle (SZA) on the RSP metrics in the conterminous United States (CONUS). The AVHRR weekly composites were used to calculate the growing-season median SZA at the pixel level for each year from 1989 to 2014. The results showed that the SZA increased towards the end of each NOAA satellite mission with the highest increasing rate occurring during NOAA-11 (1989–1994) and NOAA-14 (1995–2000) missions. The growing-season median SZA values (44°–60°) in 1992, 1993, 1994, 1999, and 2000 were substantially higher than those in other years (28°–40°). The high SZA in those years caused negative trends in the SZA time series, that were statistically significant (at α = 0.05 level) in 76.9% of the CONUS area. A pixel-based temporal correlation analysis showed that the phenological metrics and SZA were significantly correlated (at α = 0.05 level) in 4.1–20.4% of the CONUS area. After excluding the 5 years with high SZA (>40°) from the analysis, the temporal SZA trend was largely reduced, significantly affecting less than 2% of the study area. Additionally, significant correlation between the phenological metrics and SZA was observed in less than 7% of the study area. Our study concluded that the NOAA satellite orbital drift increased SZA, and in turn, influenced the phenological metrics. Elimination of the years with high median SZA reduced the

  7. Validation of the modified Becker's split-window approach for retrieving land surface temperature from AVHRR

    Science.gov (United States)

    Quan, Weijun; Chen, Hongbin; Han, Xiuzhen; Ma, Zhiqiang

    2015-10-01

    To further verify the modified Becker's split-window approach for retrieving land surface temperature (LST) from long-term Advanced Very High Resolution Radiometer (AVHRR) data, a cross-validation and a radiance-based (R-based) validation are performed and examined in this paper. In the cross-validation, 3481 LST data pairs are extracted from the AVHRR LST product retrieved with the modified Becker's approach and compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (MYD11A1) for the period 2002-2008, relative to the positions of 548 weather stations in China. The results show that in most cases, the AVHRR LST values are higher than the MYD11A1. When the AVHRR LSTs are adjusted with a linear regression, the values are close to the MYD11A1, showing a good linear relationship between the two datasets ( R 2 = 0.91). In the R-based validation, comparison is made between AVHRR LST retrieved from the modified Becker's approach and the inversed LST from the Moderate Resolution Transmittance Model (MODTRAN) consolidated with observed temperature and humidity profiles at four radiosonde stations. The results show that the retrieved AVHRR LST deviates from the MODTRAN inversed LST by-1.3 (-2.5) K when the total water vapor amount is less (larger) than 20 mm. This provides useful hints for further improvement of the LST retrieval algorithms' accuracy and consistency.

  8. Estimation of Land Surface Temperature from 1-km AVHRR data

    Science.gov (United States)

    Frey, Corinne

    2016-04-01

    In order to re-process DLRs 1km AVHRR data archive to different geophysical and descriptive parameters of the land surface and the atmosphere, a series of scientific data processors are being developed in the framework of the TIMELINE project. The archive of DLR ranges back to the 80ies. One of the data processors is SurfTemp, which processes L2 LST and emissivity datasets from AVHRR L1b data. The development of the data processor included the selection of statistical procedures suitable for time series processing, including four mono-window and six split window algorithms. For almost all of these algorithms, new constants were generated, which better account for different atmospheric and geometric acquisition situations. The selection of optimal algorithms for SurfTemp is based on a round robin approach, in which the selected mono-window and split window algorithms are tested on the basis of a large number of TOA radiance/LST pairs, which were generated using a radiative transfer model and the SeeBorV5 profile database. The original LSTs are thereby compared to the LSTs derived from the TOA radiances using the mono- and split window algorithms. The algorithm comparison includes measures of precision, as well as the sensitivity of a method to the accuracy of its input data. The results of the round robin are presented, as well as the implementation of selected algorithms into SurfTemp. Further, first cross-validation results between the AVHRR LST and MODIS LST are shown.

  9. Alpine cloud climatology using long-term NOAA-AVHRR satellite data

    Energy Technology Data Exchange (ETDEWEB)

    Kaestner, M.; Kriebel, K.T.

    2000-07-01

    Three different climates have been identified by our evaluation of AVHRR (advanced very high resolution radiometer) data using APOLLO (AVHRR processing scheme over land, clouds and ocean) for a five-years cloud climatology of the Alpine region. The cloud cover data from four layers were spatially averaged in boxes of 15 km by 14 km. The study area only comprises 540 km by 560 km, but contains regions with moderate, Alpine and Mediterranean climate. Data from the period July 1989 until December 1996 have been considered. The temporal resolution is one scene per day, the early afternoon pass, yielding monthly means of satellite derived cloud coverages 5% to 10% above the daily mean compared to conventional surface observation. At nonvegetated sites the cloudiness is sometimes significantly overestimated. Averaging high resolution cloud data seems to be superior to low resolution measurements of cloud properties and averaging is favourable in topographical homogeneous regions only. The annual course of cloud cover reveals typical regional features as foehn or temporal singularities as the so-called Christmas thaw. The cloud cover maps in spatially high resolution show local luff/lee features which outline the orography. Less cloud cover is found over the Alps than over the forelands in winter, an accumulation of thick cirrus is found over the High Alps and an accumulation of thin cirrus north of the Alps. (orig.)

  10. Satellite remote sensing of rangelands in Botswana. II - NOAA AVHRR and herbaceous vegetation

    Science.gov (United States)

    Prince, S. D.; Tucker, C. J.

    1986-01-01

    The relation between the normalized difference vegetation index (NDVI) and the herbaceous vegetation in Tamasane, Shakwe, and Masama in eastern Botswana is studied using 1983-1984 AVHRR data. The procedures for Landsat MSS interpolation of ground measurements and the data processing of the AVHRR data are described. The temporal sequence AVHRR global-area coverage (GAC) composite NDVI is examined. The AVHRR GAC composite NDVI and biomass and Landsat MSS interpolations of field measurements are analyzed and compared.

  11. Lake Surface Water Temperature of European Lakes retrieved from AVHRR Data - Time Series and Quality Assessment

    Science.gov (United States)

    Wunderle, S.; Lieberherr, G.; Riffler, M.

    2016-12-01

    Data analysis of the recent years showed an increase of lake surface water temperature for many lakes around the world. But due to sparse in-situ measurements, which are often not well documented, only satellite data can provide the needed information of the last decades. The importance of lakes for climate research was also highlighted by the Global Climate Observing System (GCOS) defining lakes as Essential Climate Variables (ECVs). Within the frame of a research project funded by the Swiss National Science Foundation a procedure was developed to retrieve lake surface water temperature with high accuracy based on our archived AVHRR data at the University of Bern, Switzerland. The data archive starts in 1985 and is continuously filled with NOAA-/MetOp-AVHRR data received by our antenna resulting in a time series of more than 30 years (WMO definition of a climate period). The data set covering Europe is also used by other teams for climate related studies resulting in improved pre-processing to guarantee precise calibration and geocoding. The first part of our presentation will be dedicated to the quality of the LSWT retrieval comparing various in-situ measurements from lakes in Switzerland with varying sizes (150km2 - 9km2). The quality of the used split-window approach is sensitive to the derived split-window coefficients. The influence of water vapor, view angle, temporal and spatial validity and day vs. night data will be shown. In addition, some information will be presented about the influence of topography and climatic regions (e.g. Scandinavia vs. Greece) on the quality of the LSWT product. Based on these findings compiling time series for different lakes in Europe will be the focus of the second part of our presentation with details of the applied quality assessment to avoid erroneous signals. Hence, some information is given about hierarchical quality checks which are needed to guarantee a dataset without artefacts. Finally, some results of time series

  12. NOAA Climate Data Record (CDR) of Reflectance and Brightness Temperatures from AVHRR Pathfinder Atmospheres - Extended (PATMOS-x), Version 5.3

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This NOAA Climate Data Record (CDR) of AVHRR reflectance and brightness temperatures was produced by the University of Wisconsin using the AVHRR Pathfinder...

  13. NOAA Climate Data Record (CDR) of Sea Surface Temperature (SST) from AVHRR Pathfinder, Version 5.2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The AVHRR Pathfinder Version 5.2 Sea Surface Temperature data set (PFV52) is a collection of global, twice-daily 4km sea surface temperature data produced in a...

  14. The use of NOAA/AVHRR satellite data for monitoring and assessment of forest fires and floods

    Directory of Open Access Journals (Sweden)

    C. Domenikiotis

    2003-01-01

    Full Text Available The increasing number of extreme natural phenomena, which are related to the climate variability and are mainly caused by anthropogenic factors, escalate the frequency and severity of natural disasters. Operational monitoring of natural hazards and assessment of the affected area impose quick and efficient methods based on large-scale data, readily available to the agencies. The growing number of satellite systems and their capabilities give rise to remote sensing applications to all types of natural disasters, including forest fires and floods. Remote sensing techniques can be used in all three aspects of disaster management viz: forecasting, monitoring and damage assessment. The purpose of this paper is to highlight the importance of satellite remote sensing for monitoring and near-real time assessment of the affected by forest fires and floods areas. As a tool, two satellite indices are presented, namely the Normalized Difference Vegetation Index (NDVI and the Surface Temperature (ST, extracted by the meteorological satellite NOAA/AVHRR. In the first part of the paper, a review of utilized techniques using NDVI and ST is given. In the second part, the application of various methodologies to three case studies are presented: the forest fire of 21–24 July 1995 in Penteli Mountain near Athens and 16 September 1994 in Pelion Mountain in Thessaly region, central Greece, and finally the flood of 17–23 October 1994 in Thessaly region, central Greece. For all studies the NDVI has been utilized for hazard assessment. The method of ST has been applied to the flood event in Thessaly, for the estimation of the areal extent of the floods. As emerged from the studies, remote sensing data can be decisive for monitoring and damage assessment, caused by forest fires and floods.

  15. GHRSST Level 2P Global 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite produced by NAVO (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  16. GHRSST Level 2P Regional 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 satellite produced by NAVO (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  17. GHRSST Level 2P Global 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 satellite produced by NAVO (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  18. GHRSST Level 2P Global 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite produced by NAVO (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  19. GHRSST Level 2P Global 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-B satellite produced by NAVO (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  20. GHRSST Level 2P Global Skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite produced by EUMETSAT (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global 1 km Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated...

  1. GHRSST Level 2P sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-A) (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global 1 km Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated...

  2. GHRSST Level 2P sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-B) (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global 1 km Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated...

  3. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite produced by NEODAAS (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Level 2P swath-based Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic area from the Advanced Very High Resolution...

  4. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite produced by NEODAAS (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Level 2P swath-based Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic area from the Advanced Very High Resolution...

  5. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 satellite produced by NEODAAS (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Level 2P swath-based Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic area from the Advanced Very High Resolution...

  6. A Satellite Time Slots Climatology of the Urban Heat Island of Guadalajara Megacity in Mexico from NOAA ¡/AVHRR THERMAL Infrared Monitoring (TIR)

    Science.gov (United States)

    Galindo, I.

    2009-04-01

    The urban heat island (UHI) of the metropolitan area of the second megacity of Mexico, named Guadalajara in Mexico is studied using thermal infrared data (TIR) (10 £ l £ 12 mm) obtained from the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbitters whose signals are received on real time at our ground station for the period 1996-2006. The TIR data are selected by means of a software, since they depend on natural causes (e.g., atmospheric transparency, surface temperature, spectral emissivity and topography) and observational (time and incidence angle of the satellite pass, season of the year, etc.). The above conditions have a variable contribution to the measurements which it can be so high that they simulate the temporal-space fluctuations considered as thermal anomalies. Using a Geographic Information System and spatial analysis techniques temperatures are obtained for diofferent times of the day (satellite slots) and dropped into a grid with a 2.5 km distance between points (latitude, longitude). The temperatures obtained for each satellite pass slot (four per day) are monthly averaged and the temperature anomalies are represented in thermal isolines for the study area. The temperature difference usually is larger at night than during the day, reaching a thermal gradient of 9 °C.

  7. Comparison of AVHRR and ECMWF ERA-Interim data with buoy observational data for sea surface temperature over the Southern Coast of the Caspian Sea

    Science.gov (United States)

    Ghafarian, Parvin; Pegahfar, Nafiseh

    2016-07-01

    Sea surface temperature plays an important role in formation or intensification of many atmospheric phenomena such as tropical storms, lake-effect snow and sea breeze. Also, this variable is one of the input data in atmospheric, climate and oceanic models and also used climate change interpretation. According to the sparse location of observational stations over the ocean basins and seas, so satellite products can play an important role over such areas. The southern coast of the Caspian Sea (CS) is a prone area to experience some extreme challenging events forming due to sea surface temperature (SST) variation. In this research, SST data obtained by the AVHRR (Advanced Very High Resolution Radiometer) and those modeled by ECMWF data have been compared with observational data from buoy instrument. The horizontal resolution of AVHRR data is 0.125 degree, while that is 0.75 degree for ECMWF. The comparison process has been done in various seasons especially for some stormy days in winter and spring led to the lake-effect snow and waterspout. Analysis has been done applying nearest-neighbor interpolation and statistical methods. Our findings indicated that SST measured by AVHRR, comparing with ECMWF data, is more close to the observational data.

  8. A Simple Statistical Model to Estimate Incident Solar Radiation at the Surface from NOAA AVHRR Satellite Data

    Directory of Open Access Journals (Sweden)

    Mst. Ashrafunnahar Hena

    2013-01-01

    Full Text Available Processing of meteorological satellite image data provides a wealth of information useful in earth surface and environmental applications. Particularly, it is important for the estimation of different parameters of surface energy budget. In this work, a method has been developed to estimation of hourly incoming solar radiation on the surface of Bangladesh using NOAA-AVHRR satellite digital images. The model is based on the statistical regressions between the ground truth and satellite estimated values. Hundreds of full resolution images (1.1 km for two months of the year have been processed using ERDAS IMAGINE software. Ground solar global irradiation for one place has been estimated for two months through this application. The efficiency of this method for calculating surface insolation has been checked by estimating the relative deviation between the estimated Irradiation and measured Irradiation. The method can be used for calculation of hourly irradiation over areas in a tropical environment.

  9. Recent History of Large-Scale Ecosystem Disturbances in North America Derived from the AVHRR Satellite Record

    Science.gov (United States)

    Potter, Christopher; Tan, Pang-Ning; Kumar, Vipin; Kicharik, Chris; Klooster, Steven; Genovese, Vanessa

    2004-01-01

    Ecosystem structure and function are strongly impacted by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the Advanced Very High Resolution Radiometer (AVHRR) as a means to characterize major ecosystem disturbance events and regimes. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8-km globally. Potential disturbance events were identified in the FPAR time series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We can find verifiable evidence of numerous disturbance types across North America, including major regional patterns of cold and heat waves, forest fires, tropical storms, and large-scale forest logging. Summed over 19 years, areas potentially influenced by major ecosystem disturbances (one FPAR-LO event over the period 1982-2000) total to more than 766,000 km2. The periods of highest detection frequency were 1987-1989, 1995-1997, and 1999. Sub- continental regions of Alaska and Central Canada had the highest proportion (greater than 90%) of FPAR-LO pixels detected in forests, tundra shrublands, and wetland areas. The Great Lakes region showed the highest proportion (39%) of FPAR-LO pixels detected in cropland areas, whereas the western United States showed the highest proportion (16%) of FPAR-LO pixels detected in grassland areas. Based on this analysis, an historical picture is emerging of periodic droughts and heat waves, possibly coupled with herbivorous insect outbreaks, as among the most important causes of ecosystem disturbance in North America.

  10. Polar Geophysics Products Derived from AVHRR: The "AVHRR Polar Pathfinder

    Science.gov (United States)

    Maslanik, James; Fowler, Charles; Scambos, Theodore

    1999-01-01

    This NOAA/NASA Pathfinder effort was established to locate, acquire, and process Advanced Very High Resolution Radiometer (AVHRR) imagery into geo-located and calibrated radiances, cloud masks, surface clear-sky broadband albedo, clear-sky skin temperatures, satellite viewing times, and viewing and solar geometry for the, high-latitude portions of the northern and southern hemispheres (all area north of 48N and south of 53S). AVHRR GAC data for August 1981 - July 1998 were acquired, with some gaps remaining, and processed into twice-daily 5-km grids, with some products also provided at 25-km resolution. AVHRR LAC data for 3.5 years of coverage in the northern hemisphere and 2.75 years of coverage in the southern hemisphere were processed into 1.25-km grids for the same suite of products. The resulting data sets are presently being transferred to the National Snow and Ice Data Center (NSIDC) for archiving and distribution. Using these data, researchers now have at their disposal an extensive AVHRR data set for investigations of high-latitude processes. In addition, the data lend themselves to development and testing of algorithms. The products are particularly relevant for climate research and algorithm development as applied to relatively long time periods and large areas.

  11. NOAA Daily 25km Global Optimally Interpolated Sea Surface Temperature (OISST) in situ and AVHRR analysis supplemented with AVHRR Pathfinder Version 5.0 climatological SST for inland and coastal pixels, 1981-09-01 through 2010-12-31 (NODC Accession 0071180)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This accession contains the daily 25km global Optimally Interpolated Sea Surface Temperature (OISST) in situ and AVHRR analysis, supplemented with AVHRR Pathfinder...

  12. AVHRR Pathfinder version 5.3 level 3 collated (L3C) global 4km sea surface temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The AVHRR Pathfinder Version 5.3 (PFV53) L3C Sea Surface Temperature data set is a collection of global, twice-daily (Day and Night) 4km sea surface temperature...

  13. Comparison between remotely-sensed sea-surface temperature (AVHRR and in situ records in San Matías Gulf (Patagonia, Argentina

    Directory of Open Access Journals (Sweden)

    Gabriela N Williams

    2014-03-01

    Full Text Available In situ records of sea surface temperature collected between 2005 and 2009 were used to compare, for the first time, the temperature estimated by the Multichannel algorithms (MCSST of the Advanced Very High Resolution Radiometer (AVHRR sensors in San Matías Gulf, in the north of the Argentinean Patagonian Continental Shelf (between 40°47'-42°13'S. Match-ups between in situ records and satellite sea surface temperature (SST were analyzed. In situ records came from fixed stations and oceanographic cruises, while satellite data came from different NOAA satellites. The fitting of temperature data to a Standard Major Axis (SMA type II regression model indicated that a high proportion of the total variance (0.53< r² <0.99 was explained by this model showing a high correlation between in situ data and satellite estimations. The mean differences between satellite and in situ data for the full data set were 1.64 ± 1.49°C. Looking separately into in situ data from different sources and day and night estimates from different NOAA satellites, the differences were between 0.30 ± 0.60°C and 2.60 ± 1.50°C. In this paper we discuss possible reasons for the above-mentioned performance of the MCSST algorithms in the study area.

  14. Letter to the EditorRetrieval of land surface temperature from combined AVHRR data

    Directory of Open Access Journals (Sweden)

    H. Fischer

    Full Text Available Accurate retrievals of land surface temperature (LST from space are of high interest for studies of land surface processes. Here, an operationally applicable method to retrieve LST from NOAA/AVHRR data is proposed, which combines a split-window technique (SWT for atmospheric correction with a Normalised Difference Vegetation Index threshold method for the retrieval of land surface emissivity. Preliminary results of LST retrievals with this "combined method" are in good agreement with ground truth measurements for bare soil and wheat crops. The results are also compared with results from the same SWT but using emissivities from laboratory measurements.Key words. Meteorology and atmospheric dynamics (radiation processes; instruments and techniques – Radio science (remote sensing

  15. Comparison of satellite-derived land surface temperature and air temperature from meteorological stations on the Pan-Arctic scale

    NARCIS (Netherlands)

    Urban, M.; Eberle, J.; Hüttich, C.; Schmullius, C.; Herold, M.

    2013-01-01

    Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR) and (Advanced) Along Track Scanning Radiometer ((A)ATSR) are pr

  16. AVHRR Pathfinder Version 5.2 Level 3 Collated (L3C) Global 4km Sea Surface Temperature for 1981-2012

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The AVHRR Pathfinder Version 5.2 Sea Surface Temperature data set (PFV52) is a collection of global, twice-daily 4km sea surface temperature data produced in a...

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

    Directory of Open Access Journals (Sweden)

    M. Riffler

    2014-05-01

    Full Text Available Lake water temperature (LWT is an important driver of lake ecosystems and it has been identified as an indicator of climate change. Thus, the Global Climate Observing System (GCOS lists LWT as an Essential Climate Variable (ECV. Although for some European lakes long in situ time series of LWT do exist, many lakes are not observed or only on a non-regular basis making these observations insufficient for climate monitoring. Satellite data can provide the information needed. However, only few satellite sensors offer the possibility to analyse time series which cover 25 years or more. The Advanced Very High Resolution Radiometer (AVHRR is among these and has been flown as a heritage instrument for almost 35 years. It will be carried on for at least ten more years finally offering a unique opportunity for satellite-based climate studies. Herein we present a satellite-based lake surface water temperature (LSWT data set for European (pre-alpine water bodies based on the extensive AVHRR 1 km data record (1989–2013 of the Remote Sensing Research Group at the University of Bern. It has been compiled out of AVHRR/2 (NOAA-07, -09, -11, -14 and AVHRR/3 (NOAA-16, -17, -18, -19 and Metop-A data. The high accuracy needed for climate related studies requires careful pre-processing and consideration of the atmospheric state. Especially data from NOAA-16 and prior satellites were prone to noise, e.g., due to transmission errors or fluctuations in the instrument's thermal state. This has resulted in partly corrupted thermal calibration data and may cause errors of up to several Kelvin in the final resulting LSWT. Thus, a multi-stage correction scheme has been applied to the data to minimize these artefacts. The LSWT retrieval is based on a simulation-based scheme making use of the Radiative Transfer for TOVS (RTTOV Version 10 together with operational analysis and reanalysis data from the European Centre for Medium Range Weather Forecasts. The resulting LSWTs

  18. Temperature, All Surface, NOAA POES AVHRR, LAC, 0.0125 degrees, West US, Daytime

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides surface temperature products derived from NOAA's Polar Operational Environmental Satellites (POES). This data is provided at high resolution...

  19. Temperature, All Surface, NOAA POES AVHRR, LAC, 0.0125 degrees, Alaska, Daytime

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides surface temperature products derived from NOAA's Polar Operational Environmental Satellites (POES). This data is provided at high resolution...

  20. Temperature, All Surface, NOAA POES AVHRR, LAC, 0.0125 degrees, West US, Nighttime

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides surface temperature products derived from NOAA's Polar Operational Environmental Satellites (POES). This data is provided at high resolution...

  1. Validation of Fractional Snow Cover from AVHRR using Landsat TM

    Science.gov (United States)

    McKenzie, C.; Rittger, K.; Dozier, J.; Davis, R.

    2008-12-01

    The suite of NOAA satellites carrying the AVHRR sensor provides daily coverage of the world's snowpack. While another satellite-borne sensor, MODIS, may provide more accurate estimates of snow cover for operational forecasting, AVHRR provides a retrospective view, gaining a perspective of historical snowpack, which in turn can supplement operational forecasting. Here we validate a fractional snow cover algorithm for AVHRR in use by the Cold Regions Research and Engineering Laboratory. The approach uses a binary decision tree trained from the theoretical reflectance of snow and non-snow spectra convolved to AVHRR bandwidths. The binary decision tree, which estimates fractional snow cover, uses bands 1 and 2 calibrated with an atmosphere optical model 6S, and a derived band 3, which estimates a reflectance component separated from the emitance component by using temperature data from channel 4, and assumptions about the surface emissivity. Using 26 Landsat TM scenes we validate 79 scenes from NOAA 9, 11, 12 and 14. We investigate the absolute differences from the fine resolution data as well as the relative differences between sensors on the two satellites. Errors of commission are eliminated with a temperature and/or elevation mask. Like most moderate resolution satellite data, georegistration errors contribute to the overall error and can be accounted for when comparing images. The AVHRR algorithm demonstrates sensitivity to fractional snow cover and performs well in comparison to TM.

  2. Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

    Science.gov (United States)

    Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.; Xi, B.

    2016-01-01

    Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary satellites, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting satellite imagers, MODIS, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; satellite and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.

  3. Seasonal variation of sea surface temperature in the Bay of Bengal during 1992 as derived from NOAA-AVHRR SST data

    Digital Repository Service at National Institute of Oceanography (India)

    Murty, V.S.N.; Subrahmanyam, B.; Rao, L.V.G.; Reddy, G.V.

    Monthly maps of sea surface temperature (SST) derived for NOAA (National Oceanic and Atmospheric Administration)-AVHRR (Advanced Very High Resolution Radiometer) data during 1992 for the Bay of Bengal are analysed and compared with the available...

  4. 4 km AVHRR Pathfinder v5.0 Global Day-Night Sea Surface Temperature Monthly and Yearly Averages, 1985-2009 (NODC Accession 0077816)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains a set of monthly and yearly global day-night sea surface temperature averages, derived from the AVHRR Pathfinder Version 5 sea surface...

  5. GHRSST Level 3P North Atlantic Regional Subskin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-19 (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  6. GHRSST Level 3C North Atlantic Regional Subskin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-19 (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  7. Climate Trend Detection using Sea-Surface Temperature Data-sets from the (A)ATSR and AVHRR Space Sensors.

    Science.gov (United States)

    Llewellyn-Jones, D. T.; Corlett, G. K.; Remedios, J. J.; Noyes, E. J.; Good, S. A.

    2007-05-01

    Sea-Surface Temperature (SST) is an important indicator of global change, designated by GCOS as an essential Climate Variable (ECV). The detection of trends in Global SST requires rigorous measurements that are not only global, but also highly accurate and consistent. Space instruments can provide the means to achieve these required attributes in SST data. This paper presents an analysis of 15 years of SST data from two independent data sets, generated from the (A)ATSR and AVHRR series of sensors respectively. The analyses reveal trends of increasing global temperature between 0.13°C to 0.18 °C, per decade, closely matching that expected from some current predictions. A high level of consistency in the results from the two independent observing systems is seen, which gives increased confidence in data from both systems and also enables comparative analyses of the accuracy and stability of both data sets to be carried out. The conclusion is that these satellite SST data-sets provide important means to quantify and explore the processes of climate change. An analysis based upon singular value decomposition, allowing the removal of gross transitory disturbances, notably the El Niño, in order to examine regional areas of change other than the tropical Pacific, is also presented. Interestingly, although El Niño events clearly affect SST globally, they are found to have a non- significant (within error) effect on the calculated trends, which changed by only 0.01 K/decade when the pattern of El Niño and the associated variations was removed from the SST record. Although similar global trends were calculated for these two independent data sets, larger regional differences are noted. Evidence of decreased temperatures after the eruption of Mount Pinatubo in 1991 was also observed. The methodology demonstrated here can be applied to other data-sets, which cover long time-series observations of geophysical observations in order to characterise long-term change.

  8. Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk

    Directory of Open Access Journals (Sweden)

    Chybicki Andrzej

    2017-09-01

    Full Text Available Satellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth’s environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land surface temperature (LST derived from low resolution imagery acquired by the Advanced Very High Resolution Radiometer (AVHRR, using the inverse technique. The effective emissivity derived from another data source is used as a quantity describing thermal properties of the terrain in higher resolution, and allows the downsampling of low spatial resolution LST images. The authors propose an optimized downscaling method formulated as the inverse problem and show that the proposed approach yields better results than the use of other downsampling methods. The proposed method aims to find estimation of high spatial resolution LST data by minimizing the global error of the downscaling. In particular, for the investigated region of the Gulf of Gdansk, the RMSE between the AVHRR image downscaled by the proposed method and the Landsat 8 LST reference image was 2.255°C with correlation coefficient R equal to 0.828 and Bias = 0.557°C. For comparison, using the PBIM method, it was obtained RMSE = 2.832°C, R = 0.775 and Bias = 0.997°C for the same satellite scene. It also has been shown that the obtained results are also good in local scale and can be used for areas much smaller than the entire satellite imagery scene, depicting diverse biophysical conditions. Specifically, for the analyzed set of small sub-datasets of the whole scene, the obtained RSME between the downscaled and reference image was smaller, by approx. 0.53°C on average, in the case of applying the proposed method than in the case of using the PBIM method.

  9. Interet de l'indice de vegetation des satellites NOAA-AVHRR pour le suivi des cultures (resultats d'une etude dans la Basse Vallee du Rhone)

    OpenAIRE

    Lagouarde, Jean-Pierre; SEGUIN, Bernard; Clinet, S.; Gandia, S.; Kerr, Y.

    1986-01-01

    Par rapport aux satellites d’observation de la Terre (Landsat, SPOT) à forte résolution spatiale, mais faible répétitivité temporelle, les satellites météorologiques NOAA-AVHRR ont l’avantage de permettre, grâce à 4 passages par jour, un suivi des cultures au cours de la saison de végétation. L’inconvénient majeur est la résolution spatiale limitée à 1 km2. Une étude a été effectuée sur les années 1983 et 1984 pour évaluer l’intérêt des indices de végétation dérivés des données NOAA, para...

  10. Validation of Satellite-Derived Sea Surface Temperatures for Waters around Taiwan

    Directory of Open Access Journals (Sweden)

    Ming-An Lee

    2005-01-01

    Full Text Available In order to validate the Advanced Very High Resolution Radiometer (AVHRR-derived sea surface temperatures (SST of the waters around Taiwan, we generated a match-up data set of 961 pairs, which included in situ SSTs and concurrent AVHRR measurements for the period of 1998 to 2002. Availability of cloud-free images, i.e., images with more than 85% of cloud-free area in their coverage, was about 2.23% of all AVHRR images during the study period. The range of in situ SSTs was from _ to _ The satellite derived-SSTs through MCSST and NLSST algorithms were linearly related to the in situ SSTs with correlation coefficients of 0.985 and 0.98, respectively. The MCSSTs and NLSSTs had small biases of 0.009 _ and 0.256 _ with root mean square deviations of 0.64 _ and 0.801 _ respectively, therefore the AVHRR-based MCSSTs and NLSSTs had high accuracy in the seas around Taiwan.

  11. Geostatistics and remote sensing using NOAA-AVHRR satellite imagery as predictive tools in tick distribution and habitat suitability estimations for Boophilus microplus (Acari: Ixodidae) in South America. National Oceanographic and Atmosphere Administration-Advanced Very High Resolution Radiometer.

    Science.gov (United States)

    Estrada-Peña, A

    1999-02-01

    Remote sensing based on NOAA (National Oceanographic and Atmosphere Administration) satellite imagery was used, together with geostatistics (cokriging) to model the correlation between the temperature and vegetation variables and the distribution of the cattle tick, Boophilus microplus (Canestrini), in the Neotropical region. The results were used to map the B. microplus habitat suitability on a continental scale. A database of B. microplus capture localities was used, which was tabulated with the AVHRR (Advanced Very High Resolution Radiometer) images from the NOAA satellite series. They were obtained at 10 days intervals between 1983 and 1994, with an 8 km resolution. A cokriging system was generated to extrapolate the results. The data for habitat suitability obtained through two vegetation and four temperature variables were strongly correlated with the known distribution of B. microplus (sensitivity 0.91; specificity 0.88) and provide a good estimation of the tick habitat suitability. This model could be used as a guide to the correct interpretation of the distribution limits of B. microplus. It can be also used to prepare eradication campaigns or to make predictions about the effects of global change on the distribution of the parasite.

  12. 4 km NODC/RSMAS AVHRR Pathfinder v5 Seasonal and Annual Day-Night Sea Surface Temperature Climatologies for 1982-2009 for the Gulf of Mexico (NODC Accession 0072888)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This accession contains a set of sea surface temperature climatologies for the Gulf of Mexico (GOM), derived from the AVHRR Pathfinder Version 5 sea surface...

  13. Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale

    Directory of Open Access Journals (Sweden)

    Christiane Schmullius

    2013-05-01

    Full Text Available Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS, Advanced Very High Resolution Radiometer (AVHRR and (Advanced Along Track Scanning Radiometer ((AATSR are providing long-term time series information. Assessing the quality of remote sensing-based temperature measurements provides feedback to the climate modeling community and other users by identifying agreements and discrepancies when compared to temperature records from meteorological stations. This paper presents a comparison of state-of-the-art remote sensing-based land surface temperature data with air temperature measurements from meteorological stations on a pan-arctic scale (north of 60° latitude. Within this study, we compared land surface temperature products from (AATSR, MODIS and AVHRR with an in situ air temperature (Tair database provided by the National Climate Data Center (NCDC. Despite analyzing the whole acquisition time period of each land surface temperature product, we focused on the inter-annual variability comparing land surface temperature (LST and air temperature for the overlapping time period of the remote sensing data (2000–2005. In addition, land cover information was included in the evaluation approach by using GLC2000. MODIS has been identified as having the highest agreement in comparison to air temperature records. The time series of (AATSR is highly variable, whereas inconsistencies in land surface temperature data from AVHRR have been found.

  14. GHRSST Level 4 AVHRR_AMSR_OI Global Blended Sea Surface Temperature Analysis (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) global Level 4 sea surface temperature analysis produced daily on a 0.25 degree grid at the NOAA...

  15. Mapping of desertification parameters using NOAA-AVHRR data

    Science.gov (United States)

    Roozekrans, Hans

    1995-01-01

    In June 1992 the ASMODE-project was started on the assessment of remote sensing techniques for the monitoring of the extent and progression of desertification in the Mediterranean area. Data of several satellite-sensors (NOAA-AVHRR, METEOSAT and LANDSAT) are researched on their usefulness for the monitoring of desertification. Two approaches to monitor desertification are followed in the ASMODE-project: (1) The energy and water balance approach to monitor vegetation activity. Satellite measured land surface temperatures and albedo's are used to estimate aridity parameters like net radiation, actual evapotranspiration, and rainfall. (2) The direct monitoring of the vegetation cover using the vegetation index. The project consists of a one-year monitoring experiment generating satellite derived datasets of Spain to be analyzed in connection with field survey data and existing datasets in a GIS. KNMI was responsible for the `NOAA-AVHRR' part of the project. In this paper the methodology used by KNMI and final NOAA-AVHRR results are presented.

  16. AVHRR GAC SST Reanalysis Version 1 (RAN1

    Directory of Open Access Journals (Sweden)

    Alexander Ignatov

    2016-04-01

    Full Text Available In response to its users’ needs, the National Oceanic and Atmospheric Administration (NOAA initiated reanalysis (RAN of the Advanced Very High Resolution Radiometer (AVHRR Global Area Coverage (GAC; 4 km sea surface temperature (SST data employing its Advanced Clear Sky Processor for Oceans (ACSPO retrieval system. Initially, AVHRR/3 data from five NOAA and two Metop satellites from 2002 to 2015 have been reprocessed. The derived SSTs have been matched up with two reference SSTs—the quality controlled in situ SSTs from the NOAA in situ Quality Monitor (iQuam and the Canadian Meteorological Centre (CMC L4 SST analysis—and analyzed in the NOAA SST Quality Monitor (SQUAM online system. The corresponding clear-sky ocean brightness temperatures (BT in AVHRR bands 3b, 4 and 5 (centered at 3.7, 11, and 12 µm, respectively have been compared with the Community Radiative Transfer Model simulations in another NOAA online system, Monitoring of Infrared Clear-sky Radiances over Ocean for SST (MICROS. For some AVHRRs, the time series of “AVHRR minus reference” SSTs and “observed minus model” BTs are unstable and inconsistent, with artifacts in the SSTs and BTs strongly correlated. In the official “Reanalysis version 1” (RAN1, data from only five platforms—two midmorning (NOAA-17 and Metop-A and three afternoon (NOAA-16, -18 and -19—were included during the most stable periods of their operations. The stability of the SST time series was further improved using variable regression SST coefficients, similarly to how it was done in the NOAA/NASA Pathfinder version 5.2 (PFV5.2 dataset. For data assimilation applications, especially those blending satellite and in situ SSTs, we recommend bias-correcting the RAN1 SSTs using the newly developed sensor-specific error statistics (SSES, which are reported in the product files. Relative performance of RAN1 and PFV5.2 SSTs is discussed. Work is underway to improve the calibration of AVHRR/3s and

  17. NOAA AVHRR Clear-Sky Products over Oceans (ACSPO): Sea Surface Temperature, Clear Sky Radiances, and Aerosol Optical Depth for the Global Ocean, 2011 - present (NCEI Accession 0072979)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The AVHRR Clear-Sky Processor over Oceans, jointly developed between NESDIS STAR and OSDPD, produces AVHRR clear-sky products over oceans. ACSPO generates output...

  18. Operational generation of AVHRR-based cloud products for Europe and the Arctic at EUMETSAT's Satellite Application Facility on Climate Monitoring (CM-SAF

    Directory of Open Access Journals (Sweden)

    F. Kaspar

    2009-04-01

    Full Text Available The Satelite Application Facility on Climate Monitoring has implemented a new processing environment for AVHRR-based climate monitoring products. AVHRR measurements from NOAA-17, NOAA-18 and MetOp-A are utilized to generate daily and monthly means of several cloud parameters for Europe and the Inner Arctic: Cloud fraction, cloud types, cloud phase, cloud top height, cloud optical thickness and cloud liquid water path.

  19. Analysis of 3-dimensional Hydro-dynamical Model Simulation in the Gulf of Kutch, India and Its Comparison with Satellite Data

    Digital Repository Service at National Institute of Oceanography (India)

    Osawa, T.; Zhao, C.; Kunte, P.D.; Ae, L.S.; Hara, M.; Moriyama, T.

    . The similar trend was also found in NOAA/AVHRR data. However the detail structure of sea surface temperature differs as satellites measures the skin temperature of water body whereas the model considers entire first layer. The sea surface temperature... is considered in the model simulation. The similar trend was also found in NOAA/AVHRR data. However the detail structure of sea surface temperature differs as satellites measures the skin temperature of water body whereas the model considers entire first...

  20. Ice surface temperatures: seasonal cycle and daily variability from in-situ and satellite observations

    Science.gov (United States)

    Madsen, Kristine S.; Dybkjær, Gorm; Høyer, Jacob L.; Nielsen-Englyst, Pia; Rasmussen, Till A. S.; Tonboe, Rasmus T.

    2016-04-01

    Surface temperature is an important parameter for understanding the climate system, including the Polar Regions. Yet, in-situ temperature measurements over ice- and snow covered regions are sparse and unevenly distributed, and atmospheric circulation models estimating surface temperature may have large biases. To change this picture, we will analyse the seasonal cycle and daily variability of in-situ and satellite observations, and give an example of how to utilize the data in a sea ice model. We have compiled a data set of in-situ surface and 2 m air temperature observations over land ice, snow, sea ice, and from the marginal ice zone. 2523 time series of varying length from 14 data providers, with a total of more than 13 million observations, have been quality controlled and gathered in a uniform format. An overview of this data set will be presented. In addition, IST satellite observations have been processed from the Metop/AVHRR sensor and a merged analysis product has been constructed based upon the Metop/AVHRR, IASI and Modis IST observations. The satellite and in-situ observations of IST are analysed in parallel, to characterize the IST variability on diurnal and seasonal scales and its spatial patterns. The in-situ data are used to estimate sampling effects within the satellite observations and the good coverage of the satellite observations are used to complete the geographical variability. As an example of the application of satellite IST data, results will be shown from a coupled HYCOM-CICE ocean and sea ice model run, where the IST products have been ingested. The impact of using IST in models will be assessed. This work is a part of the EUSTACE project under Horizon 2020, where the ice surface temperatures form an important piece of the puzzle of creating an observationally based record of surface temperatures for all corners of the Earth, and of the ESA GlobTemperature project which aims at applying surface temperatures in models in order to

  1. A study of temperature's spatial distribution in Neuquen River valley through satellite imaging

    Directory of Open Access Journals (Sweden)

    Marisa Gloria Cogliati

    2010-01-01

    Full Text Available This paper looks into the spatial distribution of brightness and surface temperature through the use of LAND SAT7 ETM+ and NO AA-AVHRR satellite imagery in the cultivated valley of the Neuquén river. Studying the spatial distribution of temperatures in an area with a somewhat complex terrain requires the use of a great density of meteorological measurements. It is often impossible to obtain the right density of the argometeorological network due to the high installation and maintenance costs. Remote sensors provide a large flow of information in various resolutions, at considerably lower costs. Determining the valley's warm and cold zones would allow for more efficient irrigation and frost-protection methods, and it would provide tools to improve the area's productive planning.

  2. Generating a Long-Term Land Data Record from the AVHRR and MODIS Instruments

    Science.gov (United States)

    Pedelty, Jeffrey; Devadiga, Sadashiva; Masuoka, Edward; Brown, Molly; Pinzon, Jorge; Tucker, Compton; Vermote, Eric; Prince, Stephen; Nagol, Jyotheshwar; Justice, Christopher; Roy, David; Ju, Junchang; Schaaf, Crystal; Liu, Jicheng; Privette, Jeffrey; Pincheiro, Ana

    2007-01-01

    The goal of NASA's Land Long Term Iiata Record (LTDR) project is to produce a consistent long term data set from the AVHRR and MODIS instruments for land climate studies. The project will create daily surface reflectance and normalized difference vegetation index (NDVI) products at a resolution of 0.05 deg., which is identical to the Climate Modeling Grid (CMG) used for MODIS products from EOS Terra and Aqua. Higher order products such as burned area, land surface temperature, albedo, bidirectional reflectance distribution function (BRDF) correction, leaf area index (LAI), and fraction of photosyntheticalIy active radiation absorbed by vegetation (fPAR), will be created. The LTDR project will reprocess Global Area Coverage (GAC) data from AVHRR sensors onboard NOAA satellites by applying the preprocessing improvements identified in the AVHRR Pathfinder Il project and atmospheric and BRDF corrections used in MODIS processing. The preprocessing improvements include radiometric in-flight vicarious calibration for the visible and near infrared channels and inverse navigation to relate an Earth location to each sensor instantaneous field of view (IFOV). Atmospheric corrections for Rayleigh scattering, ozone, and water vapor are undertaken, with aerosol correction being implemented. The LTDR also produces a surface reflectance product for channel 3 (3.75 micrometers). Quality assessment (QA) is an integral part of the LTDR production system, which is monitoring temporal trands in the AVHRR products using time-series approaches developed for MODIS land product quality assessment. The land surface reflectance products have been evaluated at AERONET sites. The AVHRR data record from LTDR is also being compared to products from the PAL (Pathfinder AVHRR Land) and GIMMS (Global Inventory Modeling and Mapping Studies) systems to assess the relative merits of this reprocessing vis-a-vis these existing data products. The LTDR products and associated information can be found at

  3. Comparison of multi-temporal NOAA-AVHRR and SPOT-XS satellite data for mapping land-cover dynamics in the West African Sahel

    Science.gov (United States)

    Marsh, S. E.; Walsh, J. L.; Lee, C. T.; Beck, L. R.; Hutchinson, C. F.

    1992-01-01

    Multi-resolution and multi-temporal remote sensing data (SPOT-XS and AVHRR) were evaluated for mapping local land-cover dynamics in the Sahel of West Africa. The aim of this research was to evaluate the agricultural information that could be derived from both high and low spatial resolution data in areas where there is very often limited ground information. A combination of raster-based image processing and vector-based geographical information system mapping was found to be effective for understanding both spatial and spectral land-cover dynamics. The SPOT data proved useful for mapping local land-cover classes in a dominantly recessive agricultural region. The AVHRR-LAC data could be used to map the dynamics of riparian vegetation, but not the changes associated with recession agriculture. In areas where there was a complex mixture of recession and irrigated agriculture, as well as riparian vegetation, the AVHRR data did not provide an accurate temporal assessment of vegetation dynamics.

  4. LWP retrieval with AMSU and AVHRR

    Science.gov (United States)

    Hauschildt, H.; Macke, A.

    2003-04-01

    Satellite based remote sensing of the vertically integrated cloud liquid water (LWP) provides the experimental basis for studying the water cycle over large areas and for validating cloud products from atmospheric circulation models. As a contribution to the European Cloud Liquid Water Network project CLIWA-NET, LWP has been obtained from co-located visible, infrared and microwave radiances from AVHRR and AMSU onboard the operational NOAA-satellites. Especially for homogeneous non-precipitating water clouds over ocean areas the emitted microwave radiation is strongly correlated with LWP. In this study a neural network (NN) based algorithm for the retrieval of LWP from Advanced Microwave Sounding Unit (AMSU) measurements has been developed. A large set of vertically inhomogeneous water clouds based on radiosonde profiles has been applied to the microwave transfer code MWMOD. The NN algoritm uses the radiances at four frequencies, 23.4 Ghz, 31.4 Ghz, 50.3 Ghz and 89.0 Ghz. The algorithm is compared to AVHRR LWP retrieval from KLAROS (KNMI Local Implementaion of APOLLO Retrieval in an Operational System) scheme. The AVHRR LWP is validated with groundbased measurements and here compared to the AMSU retrieval. From the high resolution measurements it is possible to quantify the error due to in field inhomogeneity to the AMSU retrieval. Differences in AMSU versus AVHRR based LWP are discussed in terms of uncertainties in cloud microphysical properties, ice contamination and radiometric uncertainties.

  5. Global clear-sky surface skin temperature from multiple satellites using a single-channel algorithm with angular anisotropy corrections

    Science.gov (United States)

    Scarino, Benjamin R.; Minnis, Patrick; Chee, Thad; Bedka, Kristopher M.; Yost, Christopher R.; Palikonda, Rabindra

    2017-01-01

    Surface skin temperature (Ts) is an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared (TIR) method to retrieve Ts over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellite imagers. GEO satellites can provide somewhat continuous estimates of Ts over the diurnal cycle in non-polar regions, while polar Ts retrievals from LEO imagers, such as the Advanced Very High Resolution Radiometer (AVHRR), can complement the GEO measurements. The combined global coverage of remotely sensed Ts, along with accompanying cloud and surface radiation parameters, produced in near-realtime and from historical satellite data, should be beneficial for both weather and climate applications. For example, near-realtime hourly Ts observations can be assimilated in high-temporal-resolution numerical weather prediction models and historical observations can be used for validation or assimilation of climate models. Key drawbacks to the utility of TIR-derived Ts data include the limitation to clear-sky conditions, the reliance on a particular set of analyses/reanalyses necessary for atmospheric corrections, and the dependence on viewing and illumination angles. Therefore, Ts validation with established references is essential, as is proper evaluation of Ts sensitivity to atmospheric correction source.This article presents improvements on the NASA Langley GEO satellite and AVHRR TIR-based Ts product that is derived using a single-channel technique. The resulting clear-sky skin temperature values are validated with surface references and independent satellite products. Furthermore, an empirically adjusted theoretical model of satellite land surface temperature (LST) angular anisotropy is tested to improve satellite LST retrievals. Application of the anisotropic correction

  6. Global Clear-Sky Surface Skin Temperature from Multiple Satellites Using a Single-Channel Algorithm with Angular Anisotropy Corrections

    Science.gov (United States)

    Scarino, Benjamin R.; Minnis, Patrick; Chee, Thad; Bedka, Kristopher M.; Yost, Christopher R.; Palikonda, Rabindra

    2017-01-01

    Surface skin temperature (T(sub s)) is an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared (TIR) method to retrieve T(sub s) over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellite imagers. GEO satellites can provide somewhat continuous estimates of T(sub s) over the diurnal cycle in non-polar regions, while polar T(sub s) retrievals from LEO imagers, such as the Advanced Very High Resolution Radiometer (AVHRR), can complement the GEO measurements. The combined global coverage of remotely sensed T(sub s), along with accompanying cloud and surface radiation parameters, produced in near-realtime and from historical satellite data, should be beneficial for both weather and climate applications. For example, near-realtime hourly T(sub s) observations can be assimilated in high-temporal-resolution numerical weather prediction models and historical observations can be used for validation or assimilation of climate models. Key drawbacks to the utility of TIR-derived T(sub s) data include the limitation to clear-sky conditions, the reliance on a particular set of analyses/reanalyses necessary for atmospheric corrections, and the dependence on viewing and illumination angles. Therefore, T(sub s) validation with established references is essential, as is proper evaluation of T(sub s) sensitivity to atmospheric correction source. This article presents improvements on the NASA Langley GEO satellite and AVHRR TIR-based T(sub s) product that is derived using a single-channel technique. The resulting clear-sky skin temperature values are validated with surface references and independent satellite products. Furthermore, an empirically adjusted theoretical model of satellite land surface temperature (LST) angular anisotropy is tested to improve

  7. Relationship Between Sea Surface Temperature Variation Obtained from AVHRR Imagery and Lobster Catching (Panulirus argus in Cuban Waters (1997-2004

    Directory of Open Access Journals (Sweden)

    Milton Kampel

    2007-06-01

    Full Text Available The spatial and temporal variability of sea surface temperature (SST for the Cuban shelf waters was obtained, and the relationship of these with lobster catches in the period from January/1997-December/2004 was analyzed. The data from this environmental variable sensor were obtained from Advanced Very High Resolution Radiometer (AVHRR. The periodicity of the images and data capture by fishing was monthly. Ocean waters and shelf have a seasonal pattern to the SST, reaching the highest in August (29.5 ° C and the lowest in February (26 ° C. The extreme values recorded were recorded in August 1998 with anomalies of 1.9 ° C and -0.9 ° C in February 2001. During the winter period (Nov-Mar it was possible to find a general pattern of water circulation in the area by observing the images; during the summer (May-October this is not observed. Low correlation between SST anomalies and the catch of lobsters by fishing was observed. The best correlation coefficients (0.48 were found to the west of the island, with four years of time lag.

  8. Comparison of TOMS and AVHRR volcanic ssh retrievals from the August 1992 eruption of Mt. Spurr

    Science.gov (United States)

    Krotkov, N.A.; Torres, O.; Seftor, C.; Krueger, A.J.; Kostinski, A.; Rose, William I.; Bluth, G.J.S.; Schneider, D.; Schaefer, S.J.

    1999-01-01

    On August 19, 1992, the Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA-12 and NASA's Total Ozone Mapping Spectrometer (TOMS) onboard the Nimbus-7 satellite simultaneously detected and mapped the ash cloud from the eruption of Mt. Spurr, Alaska. The spatial extent and geometry of the cloud derived from the two datasets are in good agreement and both AVHRR split window IR (11-12??m brightness temperature difference) and the TOMS UV Aerosol Index (0.34-0.38??m ultraviolet backscattering and absorption) methods give the same range of total cloud ash mass. Redundant methods for determination of ash masses in drifting volcanic clouds offer many advantages for potential application to the mitigation of aircraft hazards.

  9. Comparison of satellite and airborne sensor data on sea surface temperature and suspended solid distribution

    Science.gov (United States)

    Nishimura, Y.; Saito, K.; Hayakawa, S.; Narigasawa, K.

    1992-07-01

    Sea surface temperature and suspended solid were observed simultaneously by LANDSAT TM, NOAA AVHRR and airborne MSS. The authors compared the following items through the data, i.e., 1) Sea surface temperature, 2) Suspended solid in the sea water, 3) Monitoring ability on ocean environment. It was found that distribution patterns of sea surface temperature and suspended solid in the Ariake Sea obtained from LANDSAT TM are similar with those from airborne MSS in a scale of 1:300,000. Sea surface temperature estimated from NOAA AVHRR data indicates a fact of an ocean environment of the Ariake Sea and the around sea area. It is concluded that the TM data can be used for the monitoring of sea environment. The NOAA AVHRR data is useful for the estimation of sea surface temperature with the airborne MSS data.

  10. The sea surface temperature field in the Eastern Mediterranean from advanced very high resolution radiometer (AVHRR) data. Part I. Seasonal variability

    Science.gov (United States)

    Marullo, S.; Santoleri, R.; Malanotte-Rizzoli, P.; Bergamasco, A.

    1999-04-01

    A ten-year dataset of Advanced Very High Resolution Radiometer-Sea Surface Temperature (AVHRR-SST) with 18-km space resolution and weekly frequency is used to study the seasonal variability of the Eastern Mediterranean Sea surface field. Three main objectives are addressed in this study. The first is to define the time and space scales of the surface temperature distributions. The second objective is to relate the SST features to the upper thermocline circulation and the third is to compare these features with the observational evidence of the Physical Oceanography of the Eastern Mediterranean (POEM) Programme. The time analysis reveals the presence of a strong seasonal signal characterized by two main seasonal extremes, winter and summer. The transition between the overall zonal distribution of the isotherms (winter) and the mostly meridional pattern of the fronts (summer) occurs very rapidly in May and October. The space analysis shows that the dominant scale is the sub-basin scale and the sub-basin gyres are very well resolved allowing the identification of permanent and semipermanent structures. The results for the two further objectives can be summarized together. The seasonal and monthly SST distributions are strongly correlated with the dynamical structure of the basin upper thermocline circulation. A direct comparison of the September 1987 SST pattern with the corresponding surface temperature map of the POEM-87 survey proves this correlation quantitatively. Furthermore, comparison of the SST monthly climatologies with the POEM circulation scheme shows that all the major currents and the sub-basin gyres are also found consistently in our patterns, with the only exception of the anticyclonic Mersa-Matruh Gyre.

  11. The AVHRR component of a long-term global active fire data record

    Science.gov (United States)

    Csiszar, I. A.; Giglio, L.; Schroeder, W.; Justice, C. O.

    2010-12-01

    capabilities strongly depend on the observing system, establishing a continuity is also needed among AVHRR and other major observing systems, such as the (Advanced) Along-Track Scanning Radiometer ((A)ATSR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the upcoming Visible Infrared Imager Radiometer Suite (VIIRS) and Sea and Land Surface Temperature Radiometer (SLSTR). Such continuity can be established by improved understanding of detection capabilities through product validation and simulations and by using geostationary fire observations as a reference to account for differences in satellite overpass times and the consequent different sampling of the diurnal cycle of fire activity from polar orbiters.

  12. Long-Term Record of Arctic and Antarctic Sea and Ice Surface Temperatures from Thermal Infrared Satellite Sensors

    Science.gov (United States)

    Luis, Cristina; Dybkjær, Gorm; Eastwood, Steinar; Tonboe, Rasmus; Høyer, Jacob

    2015-04-01

    Surface temperature is among the most important variables in the surface energy balance equation and it significantly affects the atmospheric boundary layer structure, the turbulent heat exchange and, over ice, the ice growth rate. Here we measure the surface temperature using thermal infrared sensors from 10-12 µm wavelength, a method whose primary limitation over sea ice is the detection of clouds. However, in the Arctic and around Antarctica there are very few conventional observations of surface temperature from buoys, and it is sometimes difficult to determine if the temperature is measured at the surface or within the snowpack, the latter of which often results in a warm bias. To reduce this bias, much interest is being paid to alternative remote sensing methods for monitoring high latitude surface temperature. We used Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) data to produce a high latitude sea surface temperature (SST), ice surface temperature (IST) and ice cap skin temperature dataset spanning 27 years (1982-2009). This long-term climate record is the first of its kind for IST. In this project we used brightness temperatures from the infrared channels of AVHRR sensors aboard NOAA and Metop polar-orbiting satellites. Surface temperatures were calculated using separate split window algorithms for day SST, night SST, and IST. The snow surface emissivity across all angles of the swath were simulated specifically for all sensors using an emission model. Additionally, all algorithms were tuned to the Arctic using simulated brightness temperatures from a radiative transfer model with atmospheric profiles and skin temperatures from European Centre for Medium-Range Forecasts (ECMWF) re-analysis data (ERA-Interim). Here we present the results of product quality as compared to in situ measurements from buoys and infrared radiometers, as well as a preliminary analysis of climate trends revealed by the record.

  13. A Non-Stationary 1981-2012 AVHRR NDVI(sub 3g) Time Series

    Science.gov (United States)

    Pinzon, Jorge E.; Tucker, Compton J.

    2014-01-01

    The NDVI(sub 3g) time series is an improved 8-km normalized difference vegetation index (NDVI) data set produced from Advanced Very High Resolution Radiometer (AVHRR) instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA) and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of plus or minus 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.

  14. A Non-Stationary 1981–2012 AVHRR NDVI3g Time Series

    Directory of Open Access Journals (Sweden)

    Jorge E. Pinzon

    2014-07-01

    Full Text Available The NDVI3g time series is an improved 8-km normalized difference vegetation index (NDVI data set produced from Advanced Very High Resolution Radiometer (AVHRR instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of ± 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.

  15. Satellite Sensed Skin Sea Surface Temperature

    Science.gov (United States)

    Donlon, Craig

    1997-01-01

    Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to

  16. A stable, unbiased, long-term satellite based data record of sea surface temperature from ESA's Climate Change Initiative

    Science.gov (United States)

    Rayner, Nick; Good, Simon; Merchant, Chris

    2013-04-01

    The study of climate change demands long-term, stable observational records of climate variables such as sea surface temperature (SST). ESA's Climate Change Initiative was set up to unlock the potential of satellite data records for this purpose. As part of this initiative, 13 projects were established to develop the data records for different essential climate variables - aerosol, cloud, fire, greenhouse gases, glaciers, ice sheets, land cover, ocean colour, ozone, sea ice, sea level, soil moisture and SST. In this presentation we describe the development work that has taken place in the SST project and present new prototype data products that are available now for users to trial. The SST project began in 2010 and has now produced two prototype products. The first is a long-term product (covering mid-1991 - 2010 currently, but with a view to update this in the future), which prioritises length of data record and stability over other considerations. It is based on data from the Along-Track Scanning Radiometer (ATSR) and Advanced Very-High Resolution Radiometer (AVHRR) series of satellite instruments. The product aims to combine the favourable stability and bias characteristics of ATSR data with the geographical coverage achieved with the AVHRR series. Following an algorithm selection process, an optimal estimation approach to retrieving SST from the satellite measurements from both sensors was adopted. The retrievals do not depend on in situ data and so this data record represents an independent assessment of SST change. In situ data are, however, being used to validate the resulting data. The second data product demonstrates the coverage that can be achieved using the modern satellite observing system including, for example, geostationary satellite data. Six months worth of data have been processed for this demonstration product. The prototype SST products will be released in April to users to trial in their work. The long term product will be available as

  17. Identification of land surface temperature and albedo trends in AVHRR Pathfinder data from 1982 to 2005 for northern Siberia

    NARCIS (Netherlands)

    Urban, M.; Forkel, M.; Schmullius, C.; Hese, S.; Hüttich, C.; Herold, M.

    2013-01-01

    The arctic regions are highly vulnerable to climate change. Climate models predict an increase in global mean temperatures for the upcoming century. The arctic environment is subject to significant changes of the land surface. Especially the changes of vegetation pattern and the phenological cycle i

  18. Analysis of teleconnections between AVHRR-based sea surface temperature and vegetation productivity in the semi-arid Sahel

    DEFF Research Database (Denmark)

    Huber Gharib, Silvia; Fensholt, Rasmus

    2011-01-01

    Vegetation productivity across the Sahel is known to be affected by a variety of global sea surface temperature (SST) patterns. Often climate indices are used to relate Sahelian vegetation variability to large-scale ocean–atmosphere phenomena. However, previous research findings reporting...... on the Sahelian vegetation response to climate indices have been inconsistent and contradictory, which could partly be caused by the variations in spatial extent/definitions of climate indices and size of the region studied. The aim of this study was to analyze the linkage between climate indices, pixel...... Sahelian vegetation productivity....

  19. AVHRR CoastWatch Regional Data, November 2003 - present (NODC Accession 0099041)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The mapped data derived from AVHRR (Advanced High Resolution Radiometer) onboard NOAA and Metop satellites is divided into files for CoastWatch regions of interest....

  20. Generation of high resolution sea surface temperature using multi-satellite data for operational oceanography

    Institute of Scientific and Technical Information of China (English)

    YANG Chan-Su; KIM Sun-Hwa; OUCHI Kazuo; BACK Ji-Hun

    2015-01-01

    In the present article, we introduce a high resolution sea surface temperature (SST) product generated daily by Korea Institute of Ocean Science and Technology (KIOST). The SST product is comprised of four sets of data including eight-hour and daily average SST data of 1 km resolution, and is based on the four infrared (IR) satellite SST data acquired by advanced very high resolution radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), Multifunctional Transport Satellites-2 (MTSAT-2) Imager and Meteorological Imager (MI), two microwave radiometer SSTs acquired by Advanced Microwave Scanning Radiometer 2 (AMSR2), and WindSAT within-situ temperature data. These input satellite andin-situ SST data are merged by using the optimal interpolation (OI) algorithm. The root-mean-square-errors (RMSEs) of satellite andin-situ data are used as a weighting value in the OI algorithm. As a pilot product, four SST data sets were generated daily from January to December 2013. In the comparison between the SSTs measured by moored buoys and the daily mean KIOST SSTs, the estimated RMSE was 0.71°C and the bias value was –0.08°C. The largest RMSE and bias were 0.86 and –0.26°C respectively, observed at a buoy site in the boundary region of warm and cold waters with increased physical variability in the Sea of Japan/East Sea. Other site near the coasts shows a lower RMSE value of 0.60°C than those at the open waters. To investigate the spatial distributions of SST, the Group for High Resolution Sea Surface Temperature (GHRSST) product was used in the comparison of temperature gradients, and it was shown that the KIOST SST product represents well the water mass structures around the Korean Peninsula. The KIOST SST product generated from both satellite and buoy data is expected to make substantial contribution to the Korea Operational Oceanographic System (KOOS) as an input parameter for data assimilation.

  1. Satellite Global and Hemispheric Lower Tropospheric Temperature Annual Temperature Cycle

    Directory of Open Access Journals (Sweden)

    Michael A. Brunke

    2010-11-01

    Full Text Available Previous analyses of the Earth’s annual cycle and its trends have utilized surface temperature data sets. Here we introduce a new analysis of the global and hemispheric annual cycle using a satellite remote sensing derived data set during the period 1979–2009, as determined from the lower tropospheric (LT channel of the MSU satellite. While the surface annual cycle is tied directly to the heating and cooling of the land areas, the tropospheric annual cycle involves additionally the gain or loss of heat between the surface and atmosphere. The peak in the global tropospheric temperature in the 30 year period occurs on 10 July and the minimum on 9 February in response to the larger land mass in the Northern Hemisphere. The actual dates of the hemispheric maxima and minima are a complex function of many variables which can change from year to year thereby altering these dates.Here we examine the time of occurrence of the global and hemispheric maxima and minima lower tropospheric temperatures, the values of the annual maxima and minima, and the slopes and significance of the changes in these metrics.  The statistically significant trends are all relatively small. The values of the global annual maximum and minimum showed a small, but significant trend. Northern and Southern Hemisphere maxima and minima show a slight trend toward occurring later in the year. Most recent analyses of trends in the global annual cycle using observed surface data have indicated a trend toward earlier maxima and minima.

  2. Developing NOAA's Climate Data Records From AVHRR and Other Data

    Science.gov (United States)

    Privette, J. L.; Bates, J. J.; Kearns, E. J.

    2010-12-01

    As part of the provisional NOAA Climate Service, NOAA is providing leadership in the development of authoritative, measurement-based information on climate change and variability. NOAA’s National Climatic Data Center (NCDC) recently initiated a satellite Climate Data Record Program (CDRP) to provide sustained and objective climate information derived from meteorological satellite data that NOAA has collected over the past 30+ years - particularly from its Polar Orbiting Environmental Satellites (POES) program. These are the longest sustained global measurement records in the world and represent billions of dollars of investment. NOAA is now applying advanced analysis methods -- which have improved remarkably over the last decade -- to the POES AVHRR and other instrument data. Data from other satellite programs, including NASA and international research programs and the Defense Meteorological Satellite Program (DMSP), are also being used. This process will unravel the underlying climate trend and variability information and return new value from the records. In parallel, NCDC will extend these records by applying the same methods to present-day and future satellite measurements, including the Joint Polar Satellite System (JPSS) and Jason-3. In this presentation, we will describe the AVHRR-related algorithm development activities that CDRP recently selected and funded through open competitions. We will particularly discuss some of the technical challenges related to adapting and using AVHRR algorithms with the VIIRS data that should become available with the launch of the NPOESS Preparatory Project (NPP) satellite in early 2012. We will also describe IT system development activities that will provide data processing and reprocessing, storage and management. We will also outline the maturing Program framework, including the strategies for coding and development standards, community reviews, independent program oversight, and research-to-operations algorithm

  3. Contrail observations from space using NOAA-AVHRR data

    Energy Technology Data Exchange (ETDEWEB)

    Mannstein, H. [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Oberpfaffenhofen (Germany). Inst. fuer Physik der Atmosphaere

    1997-12-31

    The infrared channels of the Advanced Very High Resolution Radiometer (AVHRR) onboard of the weather satellites of the NOAA series allow the detection of contrails. An automated detection scheme is described and tested against computer aided visual classifications by two experts. The algorithm seems to identify contrails within the satellite data with a skill comparable to the human observers. Clusters of contrails within the satellite images are connected to outline regions where the atmospheric properties are favourable for the existence of observable contrails. Air traffic data shows that, over Middle Europe at least, in the main flight levels most of these regions should be marked by detectable contrails. The mean areal coverage of these regions is estimated to be in the range of 10% to 20%, the cloud coverage by detected contrails was 0.9% in 60 AVHRR scenes covering Central Europe. (author) 3 refs.

  4. Detection of Water Bodies from AVHRR Data—A TIMELINE Thematic Processor

    Directory of Open Access Journals (Sweden)

    Andreas J. Dietz

    2017-01-01

    Full Text Available The assessment of water body dynamics is not only in itself a topic of strong demand, but the presence of water bodies is important information when it comes to the derivation of products such as land surface temperature, leaf area index, or snow/ice cover mapping from satellite data. For the TIMELINE project, which aims to derive such products for a long time series of Advanced Very High Resolution Radiometer (AVHRR data for Europe, precise water masks are therefore not only an important stand-alone product themselves, they are also an essential interstage information layer, which has to be produced automatically after preprocessing of the raw satellite data. The respective orbit segments from AVHRR are usually more than 2000 km wide and several thousand km long, thus leading to fundamentally different observation geometries, including varying sea surface temperatures, wave patterns, and sediment and algae loads. The water detection algorithm has to be able to manage these conditions based on a limited amount of spectral channels and bandwidths. After reviewing and testing already available methods for water body detection, we concluded that they cannot fully overcome the existing challenges and limitations. Therefore an extended approach was implemented, which takes into account the variations of the reflectance properties of water surfaces on a local to regional scale; the dynamic local threshold determination will train itself automatically by extracting a coarse-scale classification threshold, which is refined successively while analyzing subsets of the orbit segment. The threshold is then interpolated by fitting a minimum curvature surface before additional steps also relying on the brightness temperature are included to reduce possible misclassifications. The classification results have been validated using Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS data and proven an overall accuracy of 93.4%, with the majority of

  5. Nearshore Thermal Habitat and General Circulation Mapping in Arctic Alaskan Coasts Using Archived AVHRR Images

    Science.gov (United States)

    Prakash, A.; Engle, K.; Panda, S.; Margraf, J. F.; Underwood, T.

    2008-12-01

    At the University of Alaska Fairbanks a continuous archive of images from the Advanced Very High Resolution Radiometer (AVHRR) onboard the series of NOAA satellites is now available starting from 1993 through 2008 for large parts of the circum Arctic north. The largest temporal coverage available is for the Alaskan Arctic coasts and includes over 40000 images for the summer months. The broader objective of our study is to use this wealth of available data for mapping general sea surface temperatures and monitoring trends in changes in the sea surface temperatures in the last 15 years in the Alaskan Arctic Coastal regions. A second objective of our study is to look at near shore circulation patterns, and investigate how changes in the landcover of the adjacent lands affect the nearshore circulation patterns. This information is fundamentally important to understand and predict the dynamics of the shallow coastal habitats that in turn influence the distribution and condition of the fish populations. From the AVHRR archive we extracted all images from the months of July, August and September that covered at least 60 percent of the Arctic Alaskan coastal areas. The images that were in sensor projection were converted to map projection using the coastal boundary vector layer as a guideline for manually selecting tie points to correct for the geometry. Starting from the oldest images in our archive from 1993 we processed over 2000 AVHRR scenes which were then used to generate sea surface temperature images and NDVI images and a time series animation of changing patterns of NDVI. The prototype animation generated to demonstrate the landcover and coastal region dynamics will be further extended to cover the entire time span from 1993 through 2008.

  6. Primeros ensayos de zonificacion de las heladas en el Altiplano boliviano con el uso de infrarrojo termico del satelite NOAA-AVHRR = Premiers essais de zonage des gelées sur l'Altiplano bolivien, à l'aide de l'infrarouge thermique du satellite NOAA-AVHRR

    OpenAIRE

    Allirol, Geneviève; Bosseno, Roland; Vacher, Jean

    1992-01-01

    Las heladas en el Altiplano boliviano tienen una influencia muy severa sobre la produccion agricola. Este estudio trata de desarrollar una metodologia para efectuar una zonificacion de las heladas utilizando el infrarrojo de NOAA-AVHRR. Esta metodologia consiste en correlacionar temperaturas minimas del aire de las estaciones meteorologicas y temperaturas de superficie nocturna de NOAA a las 2:00 a.m. Se obtienen buenos resultados con esta correlacion, sin embargo, es necesario afinarla intro...

  7. Processing techniques for global land 1-km AVHRR data

    Science.gov (United States)

    Eidenshink, Jeffery C.; Steinwand, Daniel R.; Wivell, Charles E.; Hollaren, Douglas M.; Meyer, David

    1993-01-01

    The U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in cooperation with several international science organizations has developed techniques for processing daily Advanced Very High Resolution Radiometer (AVHRR) 1-km data of the entire global land surface. These techniques include orbital stitching, geometric rectification, radiometric calibration, and atmospheric correction. An orbital stitching algorithm was developed to combine consecutive observations acquired along an orbit by ground receiving stations into contiguous half-orbital segments. The geometric rectification process uses an AVHRR satellite model that contains modules for forward mapping, forward terrain correction, and inverse mapping with terrain correction. The correction is accomplished by using the hydrologic features coastlines and lakes from the Digital Chart of the World. These features are rasterized into the satellite projection and are matched to the AVHRR imagery using binary edge correlation techniques. The resulting coefficients are related to six attitude correction parameters: roll, roll rate, pitch, pitch rate, yaw, and altitude. The image can then be precision corrected to a variety of map projections and user-selected image frames. Because the AVHRR lacks onboard calibration for the optical wavelengths, a series of time-variant calibration coefficients derived from vicarious calibration methods and are used to model the degradation profile of the instruments. Reducing atmospheric effects on AVHRR data is important. A method has been develop that will remove the effects of molecular scattering and absorption from clear sky observations, using climatological measurements of ozone. Other methods to remove the effects of water vapor and aerosols are being investigated.

  8. Towards a protocol for validating satellite-based Land Surface Temperature: Theoretical considerations

    Science.gov (United States)

    Schneider, Philipp; Ghent, Darren J.; Corlett, Gary C.; Prata, Fred; Remedios, John J.

    2013-04-01

    Land Surface Temperature (LST) and emissivity are important parameters for environmental monitoring and earth system modelling. LST has been observed from space for several decades using a wide variety of satellite instruments with different characteristics, including both platforms in low-earth orbit and in geostationary orbit. This includes for example the series of Advanced Very High Resolution Radiometers (AVHRR) delivering a continuous thermal infrared (TIR) data stream since the early 1980s, the series of Along-Track Scanning Radiometers (ATSR) providing TIR data since 1991, and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard NASA's Terra and Aqua platforms, providing data since the year 2000. In addition, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard of the geostationary Meteosat satellites is now providing LST at unprecedented sub-hour frequency. The data record provided by such instruments is extremely valuable for a wide variety of applications, including climate change, land/atmosphere feedbacks, fire monitoring, modelling, land cover change, geology, crop- and water management. All of these applications, however, require a rigorous validation of the data in order to assess the product quality and the associated uncertainty. Here we report on recent work towards developing a protocol for validation of satellite-based Land Surface Temperature products. Four main validation categories are distinguished within the protocol: A) Comparison with in situ observations, B) Radiance-based validation, C) Inter-comparison with similar LST products, and D) Time-series analysis. Each category is further subdivided into several quality classes, which approximately reflect the validation accuracy that can be achieved by the different approaches, as well as the complexity involved with each method. Advice on best practices is given for methodology common to all categories. For each validation category, recommendations

  9. Retrieval of aerosol optical depth over land surfaces from AVHRR data

    Directory of Open Access Journals (Sweden)

    L. Mei

    2013-02-01

    Full Text Available The Advanced Very High Resolution Radiometer (AVHRR radiance data provide a global, long-term, consistent time series having high spectral and spatial resolution and thus being valuable for the retrieval of surface spectral reflectance, albedo and surface temperature. Long term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. These data have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land and land surface albedo are challenging because of the information content of the measurement is limited and the inversion of these data products being ill defined. Solving the radiative transfer equations requires additional information and knowledge to reduce the number of unknowns. In this contribution we utilise an empirical linear relationship between the surface reflectances in the AVHRR channels at wavelengths of 3.75 μm and 2.1 μm, which has been identified in Moderate Resolution Imaging Spectroradiometer (MODIS data. Next, following the MODIS dark target approach, the surface reflectance at 0.64 μm was obtained. The comparison of the estimated surface reflectance at 0.64 μm with MODIS reflectance products (MOD09 shows a strong correlation (R = 0.7835. Once this was established, the MODIS "dark-target" aerosol retrieval method was adapted to Advanced Very High Resolution Radiometer (AVHRR data. A simplified Look-Up Table (LUT method, adopted from Bremen AErosol Retrieval (BAER algorithm, was used in the retrieval. The Aerosol Optical Depth (AOD values retrieved from AVHRR with this method compare favourably with ground-based measurements, with a correlation coefficient R = 0.861 and Root Mean Square Error (RMSE = 0.17. This method can be easily applied to other satellite instruments which do not have a 2.1 μm channel, such as those currently planned to

  10. NODC Standard Product: World Ocean Circulation Program (WOCE) Global Data, Version 2: Satellite sea surface temperature data on CD-ROM (NODC Accession 0000317)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Sea surface temperature and sea level data were collected from the AVHRR and Topex/Poseidon altimeter in a world-wide distribution from January 1, 1990 to December...

  11. Cloudmask, CLAVR-1, NOAA POES AVHRR, 0.0125 degrees, West US, Daytime

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The CLAVR-1 cloudmask (Stowe, 1999) is used to cloudmask AVHRR high resolution sea surface temperature products. The cloudmask runs a series of tests on each surface...

  12. Cloudmask, CLAVR-1, NOAA POES AVHRR, 0.0125 degrees, West US, Nighttime

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The CLAVR-1 cloudmask (Stowe, 1999) is used to cloudmask AVHRR high resolution sea surface temperature products. The cloudmask runs a series of tests on each surface...

  13. Cloudmask, CLAVR-1, NOAA POES AVHRR, 0.0125 degrees, Alaska, Daytime

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The CLAVR-1 cloudmask (Stowe, 1999) is used to cloudmask AVHRR high resolution sea surface temperature products. The cloudmask runs a series of tests on each surface...

  14. NOAA Climate Data Record (CDR) of AVHRR Surface Reflectance, Version 4

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains gridded daily surface reflectance and brightness temperatures derived from the Advanced Very High Resolution Radiometer (AVHRR) sensors onboard...

  15. Low latitude electron temperature observed by the CHAMP satellite

    DEFF Research Database (Denmark)

    Stolle, Claudia; Truhlik, V.; Richards, P.;

    2012-01-01

    km, although this was not predicted by earlier models. The temperature peaks coincides with the density peaks and are increased during high solar flux. Even more extended possibilities in investigating the ionosphere/thermosphere system are expected from the ESA Swarm satellite constellation mission...

  16. A modified Becker's split window approach for retrieving land surface temperature from the AVHRR and VIRR data%基于AVHRR和VIRR数据的改进型Becker“分裂窗”地表温度反演算法

    Institute of Scientific and Technical Information of China (English)

    权维俊; 韩秀珍; 陈洪滨

    2012-01-01

    为了将基于NOAA-9/AVHRR数据提出的Becker和Li的“分裂窗”地表温度算法成功地应用于长序列NOAA/AVHRR和FY 3A/VIRR数据的地表温度反演,为气候变化研究提供长序列、高精度、高分辨率的地表温度数据集,从辐射传输方程出发,首先利用MODTRA 4.1模式模拟了多种地表和大气状态下的光谱辐亮度数据,并结合AVHRR和VIRR通道4、5的光谱响应函数建立了温度数据集(TS,T4,T5);然后,基于该数据集采用最小二乘法重新计算了Becker和Li算法中的各参数,提出了一个适用于NOAA/AVHRR和FY-3A/VIRR数据的改进型Becker和Li分裂窗地表温度反演算法;并利用改进型算法对2008年4月27日03时12分(世界时)观测的一景覆盖北京地区的NOAA-17/AVHRR数据进行了地表温度的反演,将反演结果与日本东京大学提供的同地区、同时相的MODIS地表温度产品进行了对比分析.结果表明,两种地表温度产品的相关系数为0.88,均方根偏差(RMSD)为2.1K;在两种地表温度差值图像的频率直方图上有69.6%的像元的值在±2K之内,37%的像元的值在±1K之内.%In order to successfully apply the Becker and Li's split window approach, which was proposed based on the NOAA-9 AVHRR data, to estimate the Land Surface Temperature (LST) from the different AVHRRs and VIRR data and further to provide a high-precision, long-time, and high-resolution LST dataset for climate change research, a modified Becker and Li's split widow approach is developed based on the radiative transfer equation in this paper. To begin with, the MODTRAN 4. 1 is used to generate the spectral radiance data under a variety of surface and atmosphere conditions. Then, the temperature dataset (TS,T4,T5) is built by convolving the spectral radiance data with the spectral response functions of channels 4 and 5 of the AVHRRs and VIRR. The parameters of the Becker and Li's split window approach are subsequently recalculated based on

  17. Use of satellite land surface temperatures in the EUSTACE global surface air temperature analysis

    Science.gov (United States)

    Ghent, D.; Good, E.; Rayner, N. A.

    2015-12-01

    EUSTACE (EU Surface Temperatures for All Corners of Earth) is a Horizon2020 project that will produce a spatially complete, near-surface air temperature (NSAT) analysis for the globe for every day since 1850. The analysis will be based on both satellite and in situ surface temperature observations over land, sea, ice and lakes, which will be combined using state-of-the-art statistical methods. The use of satellite data will enable the EUSTACE analysis to offer improved estimates of NSAT in regions that are poorly observed in situ, compared with existing in-situ based analyses. This presentation illustrates how satellite land surface temperature (LST) data - sourced from the European Space Agency (ESA) Data User Element (DUE) GlobTemperature project - will be used in EUSTACE. Satellite LSTs represent the temperature of the Earth's skin, which can differ from the corresponding NSAT by several degrees or more, particularly during the hottest part of the day. Therefore the first challenge is to develop an approach to estimate global NSAT from satellite observations. Two methods will be trialled in EUSTACE, both of which are summarised here: an established empirical regression-based approach for predicting NSAT from satellite data, and a new method whereby NSAT is calculated from LST and other parameters using a physics-based model. The second challenge is in estimating the uncertainties for the satellite NSAT estimates, which will determine how these data are used in the final blended satellite-in situ analysis. This is also important as a key component of EUSTACE is in delivering accurate uncertainty information to users. An overview of the methods to estimate the satellite NSATs is also included in this presentation.

  18. Electron temperature and density probe for small aeronomy satellites

    Energy Technology Data Exchange (ETDEWEB)

    Oyama, K.-I. [Plasma and Space Science Center, National Cheng Kung University, Tainan, Taiwan (China); Institute of Space and Plasma Sciences, National Cheng Kung University, Tainan, Taiwan (China); International Center for Space Weather Study and education, Kyushu University, Fukuoka (Japan); Hsu, Y. W.; Jiang, G. S.; Chen, W. H.; Liu, W. T. [Plasma and Space Science Center, National Cheng Kung University, Tainan, Taiwan (China); Cheng, C. Z.; Fang, H. K. [Plasma and Space Science Center, National Cheng Kung University, Tainan, Taiwan (China); Institute of Space and Plasma Sciences, National Cheng Kung University, Tainan, Taiwan (China)

    2015-08-15

    A compact and low power consumption instrument for measuring the electron density and temperature in the ionosphere has been developed by modifying the previously developed Electron Temperature Probe (ETP). A circuit block which controls frequency of the sinusoidal signal is added to the ETP so that the instrument can measure both T{sub e} in low frequency mode and N{sub e} in high frequency mode from the floating potential shift of the electrode. The floating potential shift shows a minimum at the upper hybrid resonance frequency (f{sub UHR}). The instrument which is named “TeNeP” can be used for tiny satellites which do not have enough conductive surface area for conventional DC Langmuir probe measurements. The instrument also eliminates the serious problems associated with the contamination of satellite surface as well as the sensor electrode.

  19. Electron temperature and density probe for small aeronomy satellites

    Science.gov (United States)

    Oyama, K.-I.; Hsu, Y. W.; Jiang, G. S.; Chen, W. H.; Cheng, C. Z.; Fang, H. K.; Liu, W. T.

    2015-08-01

    A compact and low power consumption instrument for measuring the electron density and temperature in the ionosphere has been developed by modifying the previously developed Electron Temperature Probe (ETP). A circuit block which controls frequency of the sinusoidal signal is added to the ETP so that the instrument can measure both Te in low frequency mode and Ne in high frequency mode from the floating potential shift of the electrode. The floating potential shift shows a minimum at the upper hybrid resonance frequency (fUHR). The instrument which is named "TeNeP" can be used for tiny satellites which do not have enough conductive surface area for conventional DC Langmuir probe measurements. The instrument also eliminates the serious problems associated with the contamination of satellite surface as well as the sensor electrode.

  20. GHRSST Level 4 AVHRR_OI Global Blended Sea Surface Temperature Analysis (GDS version 2) from NCEI (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) global Level 4 sea surface temperature analysis produced daily on a 0.25 degree grid at the NOAA...

  1. APOLLO_NG – a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

    Directory of Open Access Journals (Sweden)

    L. Klüser

    2015-04-01

    Full Text Available The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer heritage instruments. The APOLLO_NG (APOLLO_NextGeneration cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.

  2. Spacecraft design project: High temperature superconducting infrared imaging satellite

    Science.gov (United States)

    1991-01-01

    The High Temperature Superconductor Infrared Imaging Satellite (HTSCIRIS) is designed to perform the space based infrared imaging and surveillance mission. The design of the satellite follows the black box approach. The payload is a stand alone unit, with the spacecraft bus designed to meet the requirements of the payload as listed in the statement of work. Specifications influencing the design of the spacecraft bus were originated by the Naval Research Lab. A description of the following systems is included: spacecraft configuration, orbital dynamics, radio frequency communication subsystem, electrical power system, propulsion, attitude control system, thermal control, and structural design. The issues of testing and cost analysis are also addressed. This design project was part of the course Advanced Spacecraft Design taught at the Naval Postgraduate School.

  3. Quality Assurance statistics for AVHRR Pathfinder Version 5.2 L3-Collated (L3C) sea surface temperature in global and selected regions (NODC Accession 0111871)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These quality monitoring data for Pathfinder Version 5.2 (PFV5.2) Sea Surface Temperature (SST) are based on the concept of a Rich Inventory developed by the...

  4. GHRSST Level 3C North Atlantic Regional (NAR) subskin Sea Surface Temperature from Metop/AVHRR (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) derived from the Advanced Very High Resolution Radiometer...

  5. Geostationary Operational Environmental Satellite (GOES) Gyro Temperature Model

    Science.gov (United States)

    Rowe, J. N.; Noonan, C. H.; Garrick, J.

    1996-01-01

    The geostationary Operational Environmental Satellite (GOES) 1/M series of spacecraft are geostationary weather satellites that use the latest in weather imaging technology. The inertial reference unit package onboard consists of three gyroscopes measuring angular velocity along each of the spacecraft's body axes. This digital integrating rate assembly (DIRA) is calibrated and used to maintain spacecraft attitude during orbital delta-V maneuvers. During the early orbit support of GOES-8 (April 1994), the gyro drift rate biases exhibited a large dependency on gyro temperature. This complicated the calibration and introduced errors into the attitude during delta-V maneuvers. Following GOES-8, a model of the DIRA temperature and drift rate bias variation was developed for GOES-9 (May 1995). This model was used to project a value of the DIRA bias to use during the orbital delta-V maneuvers based on the bias change observed as the DIRA warmed up during the calibration. The model also optimizes the yaw reorientation necessary to achieve the correct delta-V pointing attitude. As a result, a higher accuracy was achieved on GOES-9 leading to more efficient delta-V maneuvers and a propellant savings. This paper summarizes the: Data observed on GOES-8 and the complications it caused in calibration; DIRA temperature/drift rate model; Application and results of the model on GOES-9 support.

  6. MEaSUREs Land Surface Temperature from GOES Satellites

    Science.gov (United States)

    Pinker, Rachel T.; Chen, Wen; Ma, Yingtao; Islam, Tanvir; Borbas, Eva; Hain, Chris; Hulley, Glynn; Hook, Simon

    2017-04-01

    Information on Land Surface Temperature (LST) can be generated from observations made from satellites in low Earth orbit (LEO) such as MODIS and ASTER and by sensors in geostationary Earth orbit (GEO) such as GOES. Under a project titled: "A Unified and Coherent Land Surface Temperature and Emissivity Earth System Data Record for Earth Science" led by Jet Propulsion Laboratory, an effort is underway to develop long term consistent information from both such systems. In this presentation we will describe an effort to derive LST information from GOES satellites. Results will be presented from two approaches: 1) based on regression developed from a wide range of simulations using MODTRAN, SeeBor Version 5.0 global atmospheric profiles and the CAMEL (Combined ASTER and MODIS Emissivity for Land) product based on the standard University of Wisconsin 5 km emissivity values (UWIREMIS) and the ASTER Global Emissivity Database (GED) product; 2) RTTOV radiative transfer model driven with MERRA-2 reanalysis fields. We will present results of evaluation of these two methods against various products, such as MOD11, and ground observations for the five year period of (2004-2008).

  7. Agreement evaluation of AVHRR and MODIS 16-day composite NDVI data sets

    Science.gov (United States)

    Ji, L.; Gallo, K.; Eidenshink, J.C.; Dwyer, J.

    2008-01-01

    Satellite-derived normalized difference vegetation index (NDVI) data have been used extensively to detect and monitor vegetation conditions at regional and global levels. A combination of NDVI data sets derived from AVHRR and MODIS can be used to construct a long NDVI time series that may also be extended to VIIRS. Comparative analysis of NDVI data derived from AVHRR and MODIS is critical to understanding the data continuity through the time series. In this study, the AVHRR and MODIS 16-day composite NDVI products were compared using regression and agreement analysis methods. The analysis shows a high agreement between the AVHRR-NDVI and MODIS-NDVI observed from 2002 and 2003 for the conterminous United States, but the difference between the two data sets is appreciable. Twenty per cent of the total difference between the two data sets is due to systematic difference, with the remainder due to unsystematic difference. The systematic difference can be eliminated with a linear regression-based transformation between two data sets, and the unsystematic difference can be reduced partially by applying spatial filters to the data. We conclude that the continuity of NDVI time series from AVHRR to MODIS is satisfactory, but a linear transformation between the two sets is recommended.

  8. Estimating the Retrievability of Temperature Profiles from Satellite Infrared Measurements

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generalized linear inverse theory and empirical orthogonal function analysis. Utilizing the NCEP global temperature reanalysis data in January and July from 1999 to 2003, the retrievabilities obtained with the Atmospheric Infrared Sounder (AIRS) and the High Resolution Infrared Radiation Sounder/3 (HIRS/3)sounding channel data are derived respectively for each standard pressure level on a global scale. As an incidental result of this study, the optimum truncation number in the method of generalized linear inverse is deduced too. The results show that the retrievabilities of temperature obtained with the two datasets are similar in spatial distribution and seasonal change characteristics. As for the vertical distribution, the retrievabilities are low in the upper and lower atmosphere, and high between 400 hPa and 850 hPa. For the geographical distribution, the retrievabilities are low in the low-latitude oceanic regions and in some regions in Antarctica, and relatively high in mid-high latitudes and continental regions. Compared with the HIRS/3 data, the retrievability obtained with the AIRS data can be improved by an amount between 0.15 and 0.40.

  9. Potential for early warning of maalria in India using NOAA-AVHRR based vegetation health indices

    Science.gov (United States)

    Dhiman, R. C.; Kogan, Felix; Singh, Neeru; Singh, R. P.; Dash, A. P.

    Malaria is still a major public health problem in India with about 1 82 million cases annually and 1000 deaths As per World Health Organization WHO estimates about 1 3 million Disability Adjusted Life Years DALYs are lost annually due to malaria in India Central peninsular region of India is prone to malaria outbreaks Meteorological parameters changes in ecological conditions development of resistance in mosquito vectors development of resistance in Plasmodium falciparum parasite and lack of surveillance are the likely reasons of outbreaks Based on satellite data and climatic factors efforts have been made to develop Early Warning System EWS in Africa but there is no headway in this regard in India In order to find out the potential of NOAA satellite AVHRR derived Vegetation Condition Index VCI Temperature Condition Index TCI and a cumulative indicator Vegetation Health Index VHI were attempted to find out their potential for development of EWS Studies were initiated by analysing epidemiological data of malaria vis-a-vis VCI TCI and VHI from Bikaner and Jaisalmer districts of Rajasthan and Tumkur and Raichur districts of Karnataka Correlation coefficients between VCI and monthly malaria cases for epidemic years were computed Positive correlation 0 67 has been found with one-month lag between VCI and malaria incidence in respect of Tumkur while a negative correlation with TCI -0 45 is observed In Bikaner VCI is found to be negatively related -0 71 with malaria cases in epidemic year of 1994 Weekly

  10. UAH Version 6 global satellite temperature products: Methodology and results

    Science.gov (United States)

    Spencer, Roy W.; Christy, John R.; Braswell, William D.

    2017-02-01

    Version 6 of the UAH MSU/AMSU global satellite temperature dataset represents an extensive revision of the procedures employed in previous versions of the UAH datasets. The two most significant results from an end-user perspective are (1) a decrease in the global-average lower tropospheric temperature (LT) trend from +0.14°C decade-1 to +0.11°C decade-1 (Jan. 1979 through Dec. 2015); and (2) the geographic distribution of the LT trends, including higher spatial resolution, owing to a new method for computing LT. We describe the major changes in processing strategy, including a new method for monthly gridpoint averaging which uses all of the footprint data yet eliminates the need for limb correction; a new multi-channel (rather than multi-angle) method for computing the lower tropospheric (LT) temperature product which requires an additional tropopause (TP) channel to be used; and a new empirical method for diurnal drift correction. We show results for LT, the midtroposphere (MT, from MSU2/AMSU5), and lower stratosphere (LS, from MSU4/AMSU9). A 0.03°C decade-1 reduction in the global LT trend from the Version 5.6 product is partly due to lesser sensitivity of the new LT to land surface skin temperature (est. 0.01°C decade-1), with the remainder of the reduction (0.02°C decade-1) due to the new diurnal drift adjustment, the more robust method of LT calculation, and other changes in processing procedures.

  11. Bridging the Gap Between AATSR and SLTR Observations Using AVHRR and IASI

    Science.gov (United States)

    Tsamalis, Christoforos; Saunders, Roger

    2015-12-01

    There is a need to find a candidate instrument that can bridge the gap between AATSR and SLSTR climate quality IR observations. Due to restrictions relating to the orbit of ENVISAT and Sentinel-3 only MODIS on TERRA and AVHRR on MetOp-A could potentially provide observations for a period that will overlap significantly with SLSTR. Here, the use of AVHRR is explored due to its collocation on the same platform with IASI, which is the reference instrument for calibration studies in the infrared spectrum. Previous studies have examined the calibration accuracy of the two longwave AVHRR channels using IASI, and so this study focuses mainly on the possible temporal trends, including the SWIR channel at 3.7?. There is a spatial correlation of the IASI-AVHRR differences with the water vapour geographical distribution, while the high noise of the shortwave IASI channels makes the comparison at low temperatures (i.e. at high latitudes) problematic. Temporal trends are found in the differences between IASI and AVHRR channels being less or equal to 10 mK/yr.

  12. Satellite air temperature estimation for monitoring the canopy layer heat island of Milan

    DEFF Research Database (Denmark)

    Pichierri, Manuele; Bonafoni, Stefania; Biondi, Riccardo

    2012-01-01

    2007 and 2010 were processed. Analysis of the canopy layer heat island (CLHI) maps during summer months reveals an average heat island effect of 3–4K during nighttime (with some peaks around 5K) and a weak CLHI intensity during daytime. In addition, the satellite maps reveal a well defined island shape......In this work, satellite maps of the urban heat island of Milan are produced using satellite-based infrared sensor data. For this aim, we developed suitable algorithms employing satellite brightness temperatures for the direct air temperature estimation 2 m above the surface (canopy layer), showing...

  13. Sensitivity of Satellite-Based Skin Temperature to Different Surface Emissivity and NWP Reanalysis Sources Demonstrated Using a Single-Channel, Viewing-Angle-Corrected Retrieval Algorithm

    Science.gov (United States)

    Scarino, B. R.; Minnis, P.; Yost, C. R.; Chee, T.; Palikonda, R.

    2015-12-01

    Single-channel algorithms for satellite thermal-infrared- (TIR-) derived land and sea surface skin temperature (LST and SST) are advantageous in that they can be easily applied to a variety of satellite sensors. They can also accommodate decade-spanning instrument series, particularly for periods when split-window capabilities are not available. However, the benefit of one unified retrieval methodology for all sensors comes at the cost of critical sensitivity to surface emissivity (ɛs) and atmospheric transmittance estimation. It has been demonstrated that as little as 0.01 variance in ɛs can amount to more than a 0.5-K adjustment in retrieved LST values. Atmospheric transmittance requires calculations that employ vertical profiles of temperature and humidity from numerical weather prediction (NWP) models. Selection of a given NWP model can significantly affect LST and SST agreement relative to their respective validation sources. Thus, it is necessary to understand the accuracies of the retrievals for various NWP models to ensure the best LST/SST retrievals. The sensitivities of the single-channel retrievals to surface emittance and NWP profiles are investigated using NASA Langley historic land and ocean clear-sky skin temperature (Ts) values derived from high-resolution 11-μm TIR brightness temperature measured from geostationary satellites (GEOSat) and Advanced Very High Resolution Radiometers (AVHRR). It is shown that mean GEOSat-derived, anisotropy-corrected LST can vary by up to ±0.8 K depending on whether CERES or MODIS ɛs sources are used. Furthermore, the use of either NOAA Global Forecast System (GFS) or NASA Goddard Modern-Era Retrospective Analysis for Research and Applications (MERRA) for the radiative transfer model initial atmospheric state can account for more than 0.5-K variation in mean Ts. The results are compared to measurements from the Surface Radiation Budget Network (SURFRAD), an Atmospheric Radiation Measurement (ARM) Program ground

  14. ASTER/AVHRR Data Hybridization to determine Pyroclastic Flow cooling curves

    Science.gov (United States)

    Reath, K. A.; Wright, R.; Ramsey, M. S.

    2014-12-01

    Shiveluch Volcano (Kamchatka, Russia) has been in a consistent state of eruption for the past 15 years. During this period different eruption styles have been documented including: sub-plinian events, dome growth and collapse, and subsequent debris flow deposits. For example, on June 25-26, 2009 a pyroclastic debris flow was emplaced and the eruption onset that produced it was recorded by a series of seismic events spanning several hours. However, due to cloud cover, visual confirmation of the exact emplacement time was obscured. Orbital remote sensing was able to image the deposit repeatedly over the subsequent months. ASTER is a high spatial resolution (90m), low temporal resolution (2 - 4 days at the poles, 16 days at the equator) thermal infrared (TIR) sensor on the NASA Terra satellite. AVHRR is a high temporal resolution (minutes to several hours), low spatial resolution (1km) spaceborne TIR sensor on a series of NOAA satellites. Combined, these sensors provide a unique opportunity to fuse high-spatial and high-temporal resolution data to better observe changes on the surface of the deposit over time. For example, ASTER data were used to determine the flow area and to provide several data points for average temperature while AVHRR data were used to increase the amount of data points. Through this method an accurate average cooling rate over a three month period was determined. This cooling curve was then examined to derive several features about the deposit that were previously unknown. The time of emplacement and period of time needed for negligible thermal output were first determined by extrapolating the cooling curve in time. The total amount of heat output and total flow volume of the deposit were also calculated. This volume was then compared to the volume of the dome to calculate the percentage of collapse. This method can be repeated for other flow deposits to determine if there is a consistent correlation between the dome growth rate, the average

  15. Changes in greening in the high Arctic: insights from a 30 year AVHRR max NDVI dataset for Svalbard

    Science.gov (United States)

    Vickers, Hannah; Arild Høgda, Kjell; Solbø, Stian; Rune Karlsen, Stein; Tømmervik, Hans; Aanes, Ronny; Hansen, Brage B.

    2016-10-01

    Satellite-aided studies of vegetation cover, biomass and productivity are becoming increasingly important for monitoring the effects of a changing climate on the biosphere. With their large spatial coverage and good temporal resolution, space-borne instruments are ideal to observe remote areas over extended time periods. However, long time series datasets with global coverage have in many cases too low spatial resolution for sparsely vegetated high latitude areas. This study has made use of a newly developed 30 year 1 km spatial resolution dataset from 1986 to 2015, provided by the NOAA AVHRR series of satellites, in order to calculate the annual maximum NDVI over parts of Svalbard (78°N). This parameter is indicative of vegetation productivity and has therefore enabled us to study long-term changes in greening within the Inner Fjord Zone on Svalbard. In addition, local meteorological data are available to link maximum NDVI values to the temporal behavior of the mean growing season (summer) temperature for the study area. Over the 30 year period, we find positive trends in both maximum NDVI (average increase of 29%) and mean summer temperature (59%), which were significantly positively correlated with each other. This suggests a temporal greening trend mediated by summer warming. However, as also recently reported for lower latitudes, the strength of the year-to-year correlation between maximum NDVI and mean summer temperature decreased, suggesting that the response of vegetation to summer warming has not remained the same over the entire study period.

  16. A long-term record of blended satellite and in situ sea-surface temperature for climate monitoring, modeling and environmental studies

    Science.gov (United States)

    Banzon, Viva; Smith, Thomas M.; Chin, Toshio Mike; Liu, Chunying; Hankins, William

    2016-04-01

    This paper describes a blended sea-surface temperature (SST) data set that is part of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) program product suite. Using optimum interpolation (OI), in situ and satellite observations are combined on a daily and 0.25° spatial grid to form an SST analysis, i.e., a spatially complete field. A large-scale bias adjustment of the input infrared SSTs is made using buoy and ship observations as a reference. This is particularly important for the time periods when volcanic aerosols from the El Chichón and Mt. Pinatubo eruptions are widespread globally. The main source of SSTs is the Advanced Very High Resolution Radiometer (AVHRR), available from late 1981 to the present, which is also the temporal span of this CDR. The input and processing choices made to ensure a consistent data set that meets the CDR requirements are summarized. A brief history and an explanation of the forward production schedule for the preliminary and science-quality final product are also provided. The data set is produced and archived at the newly formed National Centers for Environmental Information (NCEI) in Network Common Data Form (netCDF) at doi:10.7289/V5SQ8XB5.

  17. A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits. Part 2 ; Validation

    Science.gov (United States)

    Doelling, David R.; Bhatt, Rajendra; Scarino, Benjamin R.; Gopalan, Arun; Haney, Conor O.; Minnis, Patrick; Bedka, Kristopher M.

    2016-01-01

    Consistent cross-sensor Advanced Very High Resolution Radiometer (AVHRR) calibration coefficients are determined using desert, polar ice, and deep convective cloud (DCC) invariant Earth targets. The greatest AVHRR calibration challenge is the slow orbit degradation of the host satellite, which precesses toward a terminator orbit. This issue is solved by characterizing the invariant targets with NOAA-16 AVHRR observed radiances that have been referenced to the Aqua Moderate Resolution Imaging Spectrometer (MODIS) calibration using simultaneous nadir overpass (SNO) observations. Another benefit of the NOAA-16 invariant target-modeled reflectance method is that, because of the similarities among the AVHRR spectral response functions, a smaller spectral band adjustment factor is required than when establishing calibrations relative to a non-AVHRR reference instrument. The sensor- and band-specific calibration uncertainties, with respect to the calibration reference, are, on average, 2 percent and 3 percent for channels 1 and 2, respectively. The uncertainties are smaller for sensors that are in afternoon orbits, have longer records, and spend less time in terminator conditions. The multiple invariant targets referenced to Aqua MODIS (MITRAM) AVHRR calibration coefficients are evaluated for individual target consistency, compared against Aqua MODIS/AVHRR SNOs, and selected published calibration gains. The MITRAM and SNO relative calibration biases mostly agree to within 1 percent for channels 1 and 2, respectively. The individual invariant target and MITRAM sensor relative calibration biases are mostly consistent to within 1 percent and 2 percent for channels 1 and 2, respectively. The differences between the MITRAM and other published calibrations are mostly attributed to the reference instrument calibration differences.

  18. Comparison of North and South American biomes from AVHRR observations

    Science.gov (United States)

    Goward, Samuel N.; Dye, Dennis; Kerber, Arlene; Kalb, Virginia

    1987-01-01

    Previous analysis of the North American continent with AVHRR-derived vegetation index measurements showed a strong relation between known patterns of vegetation seasonality, productivity and the spectral vegetation index measurements. This study extends that analysis to South America to evaluate the degree to which these findings extend to tropical regions. The results show that the spectral vegetation index measurements provide a general indicator of vegetation activity across the major biomes of the Western Hemisphere of the earth, including tropical regions. The satellite-observed patterns are strongly related to the known climatology of the continents and may offer a means to improve understanding of global bioclimatology. For example, South America is shown to have a longer growing season with much earlier spring green-up than North America. The time integral of the measurements, computed from 12 composited monthly values, produces a value that is related to published net primary productivity data. However, limited net primary production data does not allow complete evaluation of satellite-observed contrasts between North and South American biomes. These results suggest that satellite-derived spectral vegetation index measurements are of great potential value in improving knowledge of the earth's biosphere.

  19. Temperature effect on proliferation and differentiation of satellite cells from turkeys with different growth rates.

    Science.gov (United States)

    Clark, D L; Coy, C S; Strasburg, G M; Reed, K M; Velleman, S G

    2016-04-01

    Poultry selected for growth have an inefficient thermoregulatory system and are more sensitive to temperature extremes. Satellite cells are precursors to skeletal muscle and mediate all posthatch muscle growth. Their physiological functions are affected by temperature. The objective of the current study was to determine how temperature affects satellite cells isolated from the pectoralis major (p. major) muscle (breast muscle) of turkeys selected for increased 16 wk body weight (F line) in comparison to a randombred control line (RBC2) from which the F line originated. Pectoralis major muscle satellite cells were thermally challenged by culturing between 33°C and 43°C to analyze the effects of cold and heat on proliferation and differentiation as compared to control temperature of 38°C. Expression levels of myogenic regulatory factors: myogenic differentiation factor 1 (MYOD1) and myogenin (MYOG) were quantified by quantitative polymerase chain reaction (qPCR). At all sampling times, proliferation increased at a linear rate across temperature in both the RBC2 and F lines. Differentiation also increased at a linear rate across temperature from 33 to 41°C at all sampling times in both the F and RBC2 lines. Satellite cells isolated from F line turkeys were more sensitive to both hot and cold temperatures as proliferation and differentiation increased to a greater extent across temperature (33 to 43°C) when compared with the RBC2 line. Expression of MYOD1 and MYOG increased as temperatures increased from 33 to 41°C at all sampling times in both the F and RBC2 lines. These results demonstrate that satellite cell function is sensitive to both cold and hot temperatures and p. major muscle satellite cells from F line turkeys are more sensitive to temperature extremes than RBC2 satellite cells.

  20. 4 km NODC/RSMAS AVHRR Pathfinder Version 5.0 and 5.1 Daily Harmonic Climatologies (1982-2008) (NODC Accession 0071181)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This accession contains a global, 4km daily sea surface temperature climatology derived from harmonic analysis of the AVHRR Pathfinder Version 5.0 and 5.1 sea...

  1. 4 km NODC/RSMAS AVHRR Pathfinder Version 5.0 and 5.1 Monthly Harmonic Climatologies (1982-2008) (NODC Accession 0075098)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This accession contains a global, 4km monthly sea surface temperature climatology derived from harmonic analysis of the AVHRR Pathfinder Version 5.0 and 5.1 sea...

  2. 4 km NODC/RSMAS AVHRR Pathfinder Version 5.0 and 5.1 5-day Harmonic Climatologies (1982-2008) (NODC Accession 0071182)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This accession contains a global, 4km 5-day sea surface temperature climatology derived from harmonic analysis of the AVHRR Pathfinder Version 5.0 and 5.1 sea...

  3. Improving the Accuracy of Satellite Sea Surface Temperature Measurements by Explicitly Accounting for the Bulk-Skin Temperature Difference

    Science.gov (United States)

    Castro, Sandra L.; Emery, William J.

    2002-01-01

    The focus of this research was to determine whether the accuracy of satellite measurements of sea surface temperature (SST) could be improved by explicitly accounting for the complex temperature gradients at the surface of the ocean associated with the cool skin and diurnal warm layers. To achieve this goal, work centered on the development and deployment of low-cost infrared radiometers to enable the direct validation of satellite measurements of skin temperature. During this one year grant, design and construction of an improved infrared radiometer was completed and testing was initiated. In addition, development of an improved parametric model for the bulk-skin temperature difference was completed using data from the previous version of the radiometer. This model will comprise a key component of an improved procedure for estimating the bulk SST from satellites. The results comprised a significant portion of the Ph.D. thesis completed by one graduate student and they are currently being converted into a journal publication.

  4. Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

    Science.gov (United States)

    Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan; Hong, Gang; Bhatt, Rajendra

    2015-01-01

    Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from Aqua and Terra MODIS data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to MODIS data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the MODIS and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.

  5. 2002 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  6. 2003 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  7. 1996 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  8. 2000 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  9. Assessment of CCRS Cloud Detection Algorithm CLEAR Using AVHRR and MODIS Observations

    Science.gov (United States)

    Khlopenkov, K.; Trishchenko, A.

    2005-12-01

    The cloud/clear-sky detection algorithm CLEAR (CLoud Estimation using Aggregated Rating index) has been developed at the Canada Centre for Remote Sensing (CCRS) for the processing of the historical Advanced Very High Resolution Radiometer (AVHRR) observations made from the National Oceanic Atmospheric Administration satellites NOAA-6 to NOAA-17. The algorithm employs observations from 5 AVHRR channels and temperature fields from the North America Regional Reanalysis (NARR). The unique feature of the scene identification algorithm is the incorporation of several tests to produce an aggregated effective cloudiness index. This aggregated index has better reliability than a simple sequence of separate tests and allows for a distinction between the different levels of cloudiness. Other features of the algorithm are the dynamic correction for the sun glint for water pixels, the generation of snow/ice maps for cloud-free and thin-cloud pixels, and the calculation of a cloud shadow mask. The algorithm is implemented to operate for daytime and nighttime scenes during snow-free and snow seasons, over water and land areas. An assessment of the algorithm performance was conducted using supervised cloud/snow classification employing the Maximum Likelihood Classifier (MLC) routine available as a part of the multispectral analysis package of the Geomatica system (PCI Geomatics 2003). Comparison has been done for 12 scenes that covered Canada and US mid-latitude and polar regions and represented various seasons. Comparison showed very good consistency between automated processing using CLEAR scheme and the results of supervised classification. The agreement in the cloud detection was in the range of 89 percent to 91 percent for the summer scenes and around 84 percent to 88 percent for the winter. The consistency in the snow identification varied from 86 percent in winter to 94 percent during the warm season. The CLEAR algorithm has been also tuned to MODIS channels and applied for

  10. Monitoring start of season in Alaska with GLOBE, AVHRR, and MODIS data

    Science.gov (United States)

    Robin, Jessica; Dubayah, Ralph; Sparrow, Elena; Levine, Elissa

    2008-03-01

    This work evaluates whether continuity between Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) is achievable for monitoring phenological changes in Alaska. This work also evaluates whether NDVI can detect changes in start of the growing season (SOS) in this region. Six quadratic regression models with NDVI as a function of accumulated growing degree days (AGDD) were developed from 2001 through 2004 AVHRR and MODIS NDVI data sets for urban, mixed, and forested land covers. Model parameters determined NDVI values for start of the observational period as well as peak and length of the growing season. NDVI values for start of the growing season were determined from the model equations and field observations of SOS made by GLOBE students and researchers at University of Alaska Fairbanks. AGDD was computed from daily air temperature. AVHRR and MODIS models were significantly different from one another with differences in the start of the observational season as well as start, peak, and length of the growing season. Furthermore, AGDD for SOS was significantly lower during the 1990s than the 1980s. NDVI values at SOS did not detect this change. There are limitations with using NDVI to monitor phenological changes in these regions because of snow, the large extent of conifers, and clouds, which restrict the composite period. In addition, differing processing and spectral characteristics restrict continuity between AVHRR and MODIS NDVI data sets.

  11. Assessment of the quality of OSIRIS mesospheric temperatures using satellite and ground-based measurements

    Directory of Open Access Journals (Sweden)

    P. E. Sheese

    2012-12-01

    Full Text Available The Optical Spectrograph and InfraRed Imaging System (OSIRIS on the Odin satellite is currently in its 12th year of observing the Earth's limb. For the first time, continuous temperature profiles extending from the stratopause to the upper mesosphere have been derived from OSIRIS measurements of Rayleigh-scattered sunlight. Through most of the mesosphere, OSIRIS temperatures are in good agreement with coincident temperature profiles derived from other satellite and ground-based measurements. In the altitude region of 55–80 km, OSIRIS temperatures are typically within 4–5 K of those from the SABER, ACE-FTS, and SOFIE instruments on the TIMED, SciSat-I, and AIM satellites, respectively. The mean differences between individual OSIRIS profiles and those of the other satellite instruments are typically within the combined uncertainties and previously reported biases. OSIRIS temperatures are typically within 2 K of those from the University of Western Ontario's Purple Crow Lidar in the altitude region of 52–79 km, where the mean differences are within combined uncertainties. Near 84 km, OSIRIS temperatures exhibit a cold bias of 10–15 K, which is due to a cold bias in OSIRIS O2 A-band temperatures at 85 km, the upper boundary of the Rayleigh-scatter derived temperatures; and near 48 km OSIRIS temperatures exhibit a cold bias of 5–15 K, which is likely due to multiple-scatter effects that are not taken into account in the retrieval.

  12. Nonlinear analysis of a simple model of temperature evolution in a satellite

    CERN Document Server

    Gaite, Jose; Pérez-Grande, Isabel

    2007-01-01

    We analyse a simple model of the heat transfer to and from a small satellite orbiting round a solar system planet. Our approach considers the satellite isothermal, with external heat input from the environment and from internal energy dissipation, and output to the environment as black-body radiation. The resulting nonlinear ordinary differential equation for the satellite's temperature is analysed by qualitative, perturbation and numerical methods, which show that the temperature approaches a periodic pattern (attracting limit cycle). This approach can occur in two ways, according to the values of the parameters: (i) a slow decay towards the limit cycle over a time longer than the period, or (ii) a fast decay towards the limit cycle over a time shorter than the period. In the first case, an exactly soluble average equation is valid. We discuss the consequences of our model for the thermal stability of satellites.

  13. Monitoring natural vegetation in Southern Greenland using NOAA AVHRR and field measurements

    DEFF Research Database (Denmark)

    Hansen, Birger Ulf

    1991-01-01

    vegetation, sheep farming, biomass production, Remote Sensing, NOAA AVHRR, Southern Greenland, NDVI......vegetation, sheep farming, biomass production, Remote Sensing, NOAA AVHRR, Southern Greenland, NDVI...

  14. Historical Snow Cover Variability Data Reconstructed from AVHRR and MODIS over High Asia

    Science.gov (United States)

    Zhou, H.; Aizen, E.; Aizen, V. B.

    2010-12-01

    Seasonal snow cover (SSC) contributes up to 60% of river runoff in Central Asia (CA) river basins. Decrease in SSC area is one of the major consequences of CA low lands desertification. The dynamics of seasonal snow that covered huge territory of CA has strong teleconnection with global and regional atmospheric processes. Accurate, high resolution SSC data over CA, from Mongolia (113°E) to Caspian Sea (51°E) and from Western Siberia (56°N) to Tibetan Plateau (32°N) for the last 25 years reconstructed from AVHRR and MODIS data may have very large scope of applications in developing different scale hydrological models and climate study. In our research we present a 24 years (1986-2009) SSC area product computed from AVHRR and MODIS that demonstrate the variability of SSC areas over CA. Daily and 8-day cloud free snow cover product in 500m spatial resolution have been generated from existing MODIS snow cover products since March 2000. Level 1 AVHRR swath data has been used to generate snow cover with 1km spatial resolution since 1986. The georeferencing accuracy of snow cover product derived from AVHRR is better than 1/3 of one pixel, which is achieved by using the new GCP image correction method and automated image matching technique. A new aggregated rating snow detection scheme has been designed to work over CA for each AVHRR image. It makes use of the spectral properties of AVHRR, as well as the surface skin temperature from the NCEP reanalysis dataset. Maximum snow cover composite strategy has been used to generate the 8-day composite product. Validation against MODIS snow cover product suggests the performance of AVHRR 8-day composite snow cover product is similar to MODIS 8-day snow cover. This product is a valuable asset for our further climate and hydrological simulations in CA. Using newly developed product the following information has been calculated: SSC area, SSC days and SSC index, maximum SSC area and day of maximum SSC areas, snow cover onset

  15. A statistical method to get surface level air-temperature from satellite observations of precipitable water

    Digital Repository Service at National Institute of Oceanography (India)

    Pankajakshan, T.; Shikauchi, A.; Sugimori, Y.; Kubota, M.

    Vol. 49, pp. 551 to 558. 1993 A Statistical Method to Get Surface Level Air-Temperature from Satellite Observations of Precipitable Water PANKAJAKSHAN THADATHIL*, AKIRA SHIKAUCHI, YASUHIRO SUGIMORI and MASAHISA KUBOTA School of Marine Science... observations for getting the estimates of heat flux across the air-sea boundary (Miller, 1981; Liu, 1988). Bulk method has widely been used for this purpose and the parameters required are: sea surface temperature, and wind speed, air-temperature and specific...

  16. Climate applications for NOAA 1/4° Daily Optimum Interpolation Sea Surface Temperature

    Science.gov (United States)

    Boyer, T.; Banzon, P. V. F.; Liu, G.; Saha, K.; Wilson, C.; Stachniewicz, J. S.

    2015-12-01

    Few sea surface temperature (SST) datasets from satellites have the long temporal span needed for climate studies. The NOAA Daily Optimum Interpolation Sea Surface Temperature (DOISST) on a 1/4° grid, produced at National Centers for Environmental Information, is based primarily on SSTs from the Advanced Very High Resolution Radiometer (AVHRR), available from 1981 to the present. AVHRR data can contain biases, particularly when aerosols are present. Over the three decade span, the largest departure of AVHRR SSTs from buoy temperatures occurred during the Mt Pinatubo and El Chichon eruptions. Therefore, in DOISST, AVHRR SSTs are bias-adjusted to match in situ SSTs prior to interpolation. This produces a consistent time series of complete SST fields that is suitable for modelling and investigating local climate phenomena like El Nino or the Pacific warm blob in a long term context. Because many biological processes and animal distributions are temperature dependent, there are also many ecological uses of DOISST (e.g., coral bleaching thermal stress, fish and marine mammal distributions), thereby providing insights into resource management in a changing ocean. The advantages and limitations of using DOISST for different applications will be discussed.

  17. Identification and recovery of discontinuous synoptic features in satellite-retrieved brightness temperatures using a radiative transfer model

    Science.gov (United States)

    White, G. A., III; Mcguirk, J. P.; Thompson, A. H.

    1988-01-01

    An attempt is made to recover and identify discontinuous synoptic features from satellite-retrieved brightness temperatures, with attention to near-discontinuities in temperature and moisture that are typically found in fronts and inversions. Efforts are made to ascertain whether the vectors of satellite channel brightness temperatures can be classified according to synoptic source, and whether those sources are amenable to quantification.

  18. Simulation of land surface temperatures: comparison of two climate models and satellite retrievals

    Directory of Open Access Journals (Sweden)

    J. M. Edwards

    2009-03-01

    Full Text Available Recently there has been significant progress in the retrieval of land surface temperature from satellite observations. Satellite retrievals of surface temperature offer several advantages, including broad spatial coverage, and such data are potentially of great value in assessing general circulation models of the atmosphere. Here, retrievals of the land surface temperature over the contiguous United States are compared with simulations from two climate models. The models generally simulate the diurnal range realistically, but show significant warm biases during the summer. The models' diurnal cycle of surface temperature is related to their surface flux budgets. Differences in the diurnal cycle of the surface flux budget between the models are found to be more pronounced than those in the diurnal cycle of surface temperature.

  19. Satellite observations of the northeast monsoon coastal current

    Digital Repository Service at National Institute of Oceanography (India)

    Shenoi, S.S.C.; Gouveia, A.D.; Shetye, S.R.; Rao, L.V.G.

    Satellite Infrared observations, from Advanced Very High Resolution Radiometer (AVHRR), during November 1987-February 1988 and hydrographic data from the eastern Arabian Sea are used to describe the poleward flowing coastal current in the eastern...

  20. A pathway to generating Climate Data Records of sea-surface temperature from satellite measurements

    Science.gov (United States)

    Minnett, Peter J.; Corlett, Gary K.

    2012-11-01

    In addition to having known uncertainty characteristics, Climate Data Records (CDRs) of geophysical variables derived from satellite measurements must be of sufficient length to resolve signals that might reveal the signatures of climate change against a background of larger, unrelated variability. The length of the record requires using satellite measurements from many instruments over several decades, and the uncertainty requirement implies that a consistent approach be used to establish the errors in the satellite retrievals over the entire period. Retrieving sea-surface temperature (SST) from satellite is a relatively mature topic, and the uncertainties of satellite retrievals are determined by comparison with collocated independent measurements. To avoid the complicating effects of near-surface temperature gradients in the upper ocean, the best validating measurements are from ship-board radiometers that measure, at source, the surface emission that is measured in space, after modification by its propagation through the atmosphere. To attain sufficient accuracy, such ship-based radiometers must use internal blackbody calibration targets, but to determine the uncertainties in these radiometric measurements, i.e. to confirm that the internal calibration is effective, it is necessary to conduct verification of the field calibration using independent blackbodies with accurately known emissivity and at very accurately measured temperatures. This is a well-justifiable approach to providing the necessary underpinning of a Climate Data Record of SST.

  1. Numerical methods for computing the temperature distribution in satellite systems

    OpenAIRE

    Gómez-Valadés Maturano, Francisco José

    2012-01-01

    [ANGLÈS] The present thesis has been done at ASTRIUM company to find new methods to obtain temperature distributions. Current software packages such as ESATAN or ESARAD provide not only excellent thermal analysis solutions, at a high price as they are very time consuming though, but also radiative simulations in orbit scenarios. Since licenses of this product are usually limited for the use of many engineers, it is important to provide new tools to do these calculations. In consequence, a dif...

  2. Numerical methods for computing the temperature distribution in satellite systems

    OpenAIRE

    Gómez-Valadés Maturano, Francisco José

    2012-01-01

    [ANGLÈS] The present thesis has been done at ASTRIUM company to find new methods to obtain temperature distributions. Current software packages such as ESATAN or ESARAD provide not only excellent thermal analysis solutions, at a high price as they are very time consuming though, but also radiative simulations in orbit scenarios. Since licenses of this product are usually limited for the use of many engineers, it is important to provide new tools to do these calculations. In consequence, a dif...

  3. Seasonal dynamics of surface chlorophyll concentration and sea surface temperature, as indicator of hydrological structure of the ocean (by satellite data)

    Science.gov (United States)

    Shevyrnogov, Anatoly; Vysotskaya, Galina

    Continuous monitoring of phytopigment concentrations and sea surface temperature in the ocean by space-borne methods makes possible to estimate ecological condition of biocenoses in critical areas. Unlike land vegetation, hydrological processes largely determine phytoplank-ton dynamics, which may be either recurrent or random. The types of chlorophyll concentration dynamics and sea surface temperature can manifest as zones quasistationary by seasonal dynamics, quasistationary areas (QSA). In the papers of the authors (A. Shevyrnogov, G. Vysotskaya, E. Shevyrnogov, A study of the stationary and the anomalous in the ocean surface chlorophyll distribution by satellite data. International Journal of Remote Sensing, Vol. 25, №7-8, pp. 1383-1387, April 2004 & A. P. Shevyrnogov, G. S. Vysotskaya, J. I. Gitelson, Quasistationary areas of chlorophyll concentra-tion in the world ocean as observed satellite data Advances in Space Research, Volume 18, Issue 7, Pages 129-132, 1996) existence of zones, which are quasi-stationary with similar seasonal dynamics of chlorophyll concentration at surface layer of ocean, was shown. Results were obtained on the base of processing of time series of satellite images SeaWiFS. It was shown that fronts and frontal zones coincide with dividing lines between quasi-stationary are-as, especially in areas of large oceanic streams. To study the dynamics of the ocean for the period from 1985 through 2012 we used data on the temperature of the surface layer of the ocean and chlorophyll concentration (AVHRR, SeaWiFS and MODIS). Biota of surface oceanic layer is more stable in comparison with quickly changing surface tem-perature. It gives a possibility to circumvent influence of high-frequency component (for exam-ple, a diurnal cycle) in investigation of dynamics of spatial distribution of surface streams. In addition, an analyses of nonstable ocean productivity phenomena, stood out time series of satellite images, showed existence of areas with

  4. Contrail and Cirrus Observations over Europe from 6 Years of NOAA-AVHRR Data

    OpenAIRE

    R. Meyer; Mannstein, H.; Meerkötter, R.; Wendling, P.

    2002-01-01

    Thin ice clouds – cirrus and contrails – are analysed in a long-term 1 km data set from the Advanced Very High Resolution Radiometer (AVHRR). Here twice daily data received at DLR Oberpfaffenhofen covering most of Europe over the full lifetime of the NOAA-14 satellite from January 1995 until October 2001 is taken into account to derive high resolution contrail and cirrus cloud maps. The data presented here is part of the ongoing European Cloud Climatology (ECC). For the detection of thin cirr...

  5. Daytime Low Stratiform Cloud Detection on AVHRR Imagery

    Directory of Open Access Journals (Sweden)

    Jan Pawel Musial

    2014-06-01

    Full Text Available The near-real time retrieval of low stratiform cloud (LSC coverage is of vital interest for such disciplines as meteorology, transport safety, economy and air quality. Within this scope, a novel methodology is proposed which provides the LSC occurrence probability estimates for a satellite scene. The algorithm is suited for the 1 × 1 km Advanced Very High Resolution Radiometer (AVHRR data and was trained and validated against collocated SYNOP observations. Utilisation of these two combined data sources requires a formulation of constraints in order to discriminate cases where the LSC is overlaid by higher clouds. The LSC classification process is based on six features which are first converted to the integer form by step functions and combined by means of bitwise operations. Consequently, a set of values reflecting a unique combination of those features is derived which is further employed to extract the LSC occurrence probability estimates from the precomputed look-up vectors (LUV. Although the validation analyses confirmed good performance of the algorithm, some inevitable misclassification with other optically thick clouds were reported. Moreover, the comparison against Polar Platform System (PPS cloud-type product revealed superior classification accuracy. From the temporal perspective, the acquired results reported a presence of diurnal and annual LSC probability cycles over Europe.

  6. Study of High-Temperature Superconductor Diplexers for Satellite Communications

    Institute of Scientific and Technical Information of China (English)

    LIU Juan-xiu; YANG Kai; LUO Zheng-xiang; BU Shi-rong; NING Jun-song; ZHANG Tian-liang

    2005-01-01

    The high-temperature superconductor (HTSC) resonator and diplexer are simulated by full-wave tools.A newly developed miniature HTSC diplexer is designed and fabricated on double sided YBa2Cu3O7 (YBCO) film (YBCO/LaAlO3/YBCO), the thickness of which is 400 nm for YBCO and 0.5 mm for the LaAlO3. The measured results show a good agreement with the simulation. The volume and mass of the diplexers are greatly reduced by miniaturized configuration.

  7. A Climate-Data Record (CDR) of the "Clear Sky" Surface Temperature of the Greenland Ice Sheet

    Science.gov (United States)

    Hall, Dorothy K.; Comiso, J. C.; DiGirolamo, N. E.; Shuman, C. A.

    2011-01-01

    To quantify the ice-surface temperature (IST) we are developing a climate-data record (CDR) of monthly IST of the Greenland ice sheet, from 1982 to the present using Advanced Very High Resolution Radiometer (AVHRR) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data at 5-km resolution. "Clear-sky" surface temperature increases have been measured from the early 1980s to the early 2000s in the Arctic using AVHRR data, showing increases ranging from 0.57-0.02 (Wang and Key, 2005) to 0.72 0.10 deg C per decade (Comiso, 2006). Arctic warming has implications for ice-sheet mass balance because much of the periphery of the ice sheet is near 0 deg C in the melt season and is thus vulnerable to more extensive melting (Hanna et al., 2008). The algorithm used for this work has a long history of measuring IST in the Arctic with AVHRR (Key and Haefliger, 1992). The data are currently available from 1981 to 2004 in the AVHRR Polar Pathfinder (APP) dataset (Fowler et al., 2000). J. Key1NOAA modified the AVHRR algorithm for use with MODIS (Hall et al., 2004). The MODIS algorithm is now being processed over Greenland. Issues being addressed in the production of the CDR are: time-series bias caused by cloud cover, and cross-calibration between AVHRR and MODIS instruments. Because of uncertainties, time series of satellite ISTs do not necessarily correspond with actual surface temperatures. The CDR will be validated by comparing results with in-situ (see Koenig and Hall, in press) and automatic-weather station data (e.g., Shuman et al., 2001).

  8. Comparative Analysis on Applicability of Satellite and Meteorological Data for Prediction of Malaria in Endemic Area in Bangladesh

    Directory of Open Access Journals (Sweden)

    Atiqur Rahman

    2010-01-01

    Full Text Available Relationships between yearly malaria incidence and (1 climate data from weather station and (2 satellite-based vegetation health (VH indices were investigated for prediction of malaria vector activities in Bangladesh. Correlation analysis of percent of malaria cases with Advanced Very High Resolution Radiometer- (AVHRR- based VH indices represented by the vegetation condition index (VCI—moisture condition and the temperature condition index (TCI—estimates thermal condition and with rainfall, relative humidity, and temperature from ground-based meteorological stations. Results show that climate data from weather stations are poorly correlated and are not applicable to estimate prevalence in Bangladesh. The study also has shown that AVHRR-based vegetation health (VH indices are highly applicable for malaria trend assessment and also for the estimation of the total number of malaria cases in Bangladesh for the period of 1992–2001.

  9. The effect of temperature on proliferation and differentiation of chicken skeletal muscle satellite cells isolated from different muscle types.

    Science.gov (United States)

    Harding, Rachel L; Halevy, Orna; Yahav, Shlomo; Velleman, Sandra G

    2016-04-01

    Skeletal muscle satellite cells are a muscle stem cell population that mediate posthatch muscle growth and repair. Satellite cells respond differentially to environmental stimuli based upon their fiber-type of origin. The objective of this study was to determine how temperatures below and above the in vitro control of 38°C affected the proliferation and differentiation of satellite cells isolated from the chicken anaerobic pectoralis major (p. major) or mixed fiber biceps femoris (b.femoris) muscles. The satellite cells isolated from the p. major muscle were more sensitive to both cold and hot temperatures compared to the b.femoris satellite cells during both proliferation and differentiation. The expressions of myogenic regulatory transcription factors were also different between satellite cells from different fiber types. MyoD expression, which partially regulates proliferation, was generally expressed at higher levels in p. major satellite cells compared to the b.femoris satellite cells from 33 to 43°C during proliferation and differentiation. Similarly, myogenin expression, which is required for differentiation, was also expressed at higher levels in p. major satellite cells in response to both cold and hot temperatures during proliferation and differentiation than b. femoris satellite cells. These data demonstrate that satellite cells from the anaerobic p. major muscle are more sensitive than satellite cells from the aerobic b. femoris muscle to both hot and cold thermal stress during myogenic proliferation and differentiation.

  10. Analysis of some methods for obtaining sea surface temperature from satellite observations

    Science.gov (United States)

    Price, J. C.

    1973-01-01

    Satellite measurements of sea surface temperature must be corrected for atmospheric moisture, cloud contamination, reflected solar radiation and other sources of error. Procedures for reducing errors are discussed. It appears that routine accuracies of 1 C are possible, given low noise spectral measurements in the infrared.

  11. Offshore Wind Energy: Wind and Sea Surface Temperature from Satellite Observations

    DEFF Research Database (Denmark)

    Karagali, Ioanna

    as the entire atmosphere above. Under conditions of light winds and strong solar insolation, warming of the upper oceanic layer may occur. In this PhD study, remote sensing from satellites is used to obtain information for the near-surface ocean wind and the sea surface temperature over the North Sea...

  12. Fractional calculus approach to study temperature distribution within a spinning satellite

    Directory of Open Access Journals (Sweden)

    Jyotindra C. Prajapati

    2016-09-01

    Full Text Available This paper deals with the temperature distribution within spinning satellites and problem is formulated in terms of fractional differential equation. Applying fractional calculus approach, solution of this equation is obtained in terms of Wright generalized hypergeometric function, a generalization of exponential function.

  13. The Relativistic Effect of the Deviation between the CMB Temperatures Obtained by the COBE Satellite

    Directory of Open Access Journals (Sweden)

    Rabounski D.

    2007-01-01

    Full Text Available The Far-Infrared Absolute Spectrophotometer (FIRAS on the COBE satellite, gives different temperatures of the Cosmic Microwave Background. This deviation has a theoretical explanation in the Doppler effect on the dipole (weak component of the radiation, the true microwave background of the Universe that moves at 365 km/sec, if the monopole (strong component of the radiation is due to the Earth. Owing to the Doppler effect, the dipole radiation temperature (determined by the 1st derivative of the monopole is lower than the monopole radiation temperature, with a value equal to the observed deviation. By this theory, the WMAP and PLANCK satellites, targeting the L2 point in the Sun-Earth-Moon system, should be insensitive to the monopole radiation. In contrast to the launched WMAP satellite, the PLANCK satellite will have on board absolute instruments which will not be able to detect the measured temperature of the Cosmic Microwave Background. That the monopole (strong component of the observed Cosmic Microwave Background is generated by the Earth is given a complete theoretical proof herein.

  14. Satellite-based detection of global urban heat-island temperature influence

    Science.gov (United States)

    Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

    2002-01-01

    This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

  15. Can interannual land surface signal be discerned in composite AVHRR data?

    Science.gov (United States)

    Cihlar, J.; Chen, J. M.; Li, Z.; Huang, F.; Latifovic, R.; Dixon, R.

    1998-09-01

    The ability to make repeated measurements of the changing Earth's surface is the principal advantage of satellite remote sensing. To realize its potential, it is necessary that true surface changes be isolated in the satellite signal from other effects which also influence the signal. In this study, we explore the magnitude of such effects in composite NOAA advanced very high resolution radiometer (AVHRR) images with a pixel spacing of 1 km. A compositing procedure is frequently used in the preparation of data sets for land biosphere studies to minimize the effect of clouds. However, the composite images contain residual artifacts which make it difficult to compare measurements at various times. We have employed a 4-year (1993-1996) AVHRR data set from NOAA 11 and 14 covering the Canadian landmass and corrected these data for the influence of the remaining clouds (full pixel or subpixel), atmospheric attenuation, and bidirectional reflectance. We have found that such corrections are essential for studies of interannual variations. The magnitude of the interannual signal varied with the AVHRR channel, land cover type, and satellite sensor but it was reduced by a factor of 2 to 8 between top of the atmosphere and the normalized surface reflectance. The remaining variations consisted of true interannual signal and the residual noise in the data (including sensor calibration) which was not removed by the correction process. Assuming that barren or sparsely vegetated land in northern Canada has not changed over the 4-year period, the mean residual uncertainty in surface reflectance of the selected sites was 0.012 for AVHRR channel 1, 0.042 for channel 2, and 0.068 for the normalized difference vegetation index (NDVI). These values decreased to 0.011, 0.024 and 0.038, respectively, when excluding 1994 data because their atmospheric and bidirectional corrections were hampered by high solar zenith angles (mean values above 55° in all 1994 composite periods). The errors

  16. Saturn's icy satellites investigated by Cassini - VIMS. IV. Daytime temperature maps

    CERN Document Server

    Filacchione, Gianrico; Capaccioni, Fabrizio; Clark, Roger N; Cruikshank, Dale P; Ciarniello, Mauro; Cerroni, Priscilla; Bellucci, Giancarlo; Brown, Robert H; Buratti, Bonnie J; Nicholson, Phillip D; Jaumann, Ralf; McCord, Thomas B; Sotin, Christophe; Stephan, Katrin; Ore, Cristina M Dalle

    2016-01-01

    The spectral position of the 3.6 micron continuum peak measured on Cassini-VIMS I/F spectra is used as a marker to infer the temperature of the regolith particles covering the surfaces of Saturn's icy satellites. This feature is characterizing the crystalline water ice spectrum which is the dominant compositional endmember of the satellites' surfaces. Laboratory measurements indicate that the position of the 3.6 micron peak of pure water ice is temperature-dependent, shifting towards shorter wavelengths when the sample is cooled, from about 3.65 micron at T=123 K to about 3.55 micron at T=88 K. A similar method was already applied to VIMS Saturn's rings mosaics to retrieve ring particles temperature (Filacchione et al., 2014). We report here about the daytime temperature variations observed on the icy satellites as derived from three different VIMS observation types. Temperature maps are built by mining the complete VIMS dataset collected in years 2004-2009 (pre-equinox) and in 2009-2012 (post equinox) by sel...

  17. Transfer and distortion of atmospheric information in the satellite temperature retrieval problem

    Science.gov (United States)

    Thompson, O. E.

    1981-01-01

    A systematic approach to investigating the transfer of basic ambient temperature information and its distortion by satellite systems and subsequent analysis algorithms is discussed. The retrieval analysis cycle is derived, the variance spectrum of information is examined as it takes different forms in that process, and the quality and quantity of information existing at each stop is compared with the initial ambient temperature information. Temperature retrieval algorithms can smooth, add, or further distort information, depending on how stable the algorithm is, and how heavily influenced by a priori data.

  18. Contribution of satellite lines to temperature diagnostics with He-like triplet lines in photoionized plasma

    Science.gov (United States)

    Wang, Feilu; Han, Bo; Salzmann, David; Zhao, Gang

    2017-04-01

    In the present paper, the He α triplet line ratios (resonance, intercombination, and forbidden lines) are computed for photoionized plasmas, when the contributions of nearby satellite lines are taken into account. The computations have been carried out with our radiative-collisional code, RCF, which is based on the flexible atomic code. The calculations of these line ratios have been done for three materials, namely, silicon, magnesium, and neon. Our calculations are used to derive the plasma temperatures for several astronomical objects, where the spectra are emitted from photoionizing plasmas. It is shown that the incorporation of the satellite lines from doubly excited Li-like ions into the He α triplet lines is necessary to obtain reliable temperature diagnostics for these astrophysical objects.

  19. COMPARISON OF THE GROUND AND SATELLITE TEMPERATURE DATA, CASE OF WRANGELL ISLAND

    Directory of Open Access Journals (Sweden)

    M. Y. Grishchenko

    2016-01-01

    Full Text Available In modern times, in the country many remote areas are characterized by low density of weather stations, which reduces the accuracy of synoptic forecasts for territories remoted from the weather stations. In this regard, the use of thermal infrared satellite images for simulation of some climatic parameters is considered by the authors as a promising area of science. The article presents the results of comparing the land surface temperature values calculated from Landsat satellites images and ground-measured air temperature values. For the considered seasons the indicators are characterized by a pronounced linear relationship with a high correlation coefficient.

  20. Influence of aerosol vertical profile variability on retrievals of aerosol optical thickness from NOAA AVHRR measurements in the Baltic region

    Directory of Open Access Journals (Sweden)

    Anna Rozwadowska

    2007-06-01

    Full Text Available The expected influence of variability in atmospheric aerosolprofiles on retrievals of aerosol optical thickness (AOTfrom NOAA AVHRR measurements is analysed. In particular, thebias in the AOT retrieval due to the assumption of a climatologicalaerosol profile in the retrieval algorithm is studied. The biasis defined as the difference between AOT retrieved with analgorithm using a climatological aerosol profile, and the actual AOTemployed in the calculations of radiances at the top of the atmosphere(TOA. The TOA radiances are simulated by means of the MODTRANcode for different aerosol profiles. Atmospheric conditions andsolar and satellite angles used in the bias simulations are typicalof the Baltic region. In the simulations, the maximum absolutevalue of the bias amounts to nearly 40% in channel 2 and 14%in channel 1 of AVHRR.

  1. High-Temperature Superconductive Cabling Investigated for Space Solar Power Satellites

    Science.gov (United States)

    Tew, Roy C.; Juhasz, Albert J.

    2000-01-01

    NASA has been directed by Congress to take a fresh look at the Space Solar Power (SSP) concept that was studied by the Department of Energy and NASA about 20 years ago. To summarize, the concept involves (1) collecting solar energy and converting it to electrical energy via photovoltaic arrays on satellites in Earth orbit, (2) conducting the electricity to the microwave transmitting portion of the satellite, and (3) transmitting the power via microwave transmitters (or possibly via lasers) to ground power station antennas located on the surface of the Earth. One Sun Tower SSP satellite concept is illustrated here. This figure shows many photovoltaic arrays attached to a "backbone" that conducts electricity down to a wireless transmitter, which is pointed toward the Earth. Other variations on this concept use multiple backbones to reduce the overall length of the satellite structure. In addition, non-Sun-Tower concepts are being considered. The objective of the work reported here was to determine the benefits to the SSP concept of using high-temperature superconductors (HTS) to conduct the electricity from the photovoltaic arrays to the wireless power transmitters. Possible benefits are, for example, reduced mass, improved efficiency, and improved reliability. Dr. James Powell of Plus Ultra Technologies, Inc., of Stony Brook, New York, is conducting the study, and it is being managed by the NASA Glenn Research Center at Lewis Field via a task-order contract through Scientific Applications International Corp. (SAIC).

  2. Ice Sheet Temperature Records - Satellite and In Situ Data from Antarctica and Greenland

    Science.gov (United States)

    Shuman, C. A.; Comiso, J. C.

    2001-12-01

    Recently completed decadal-length surface temperature records from Antarctica and Greenland are providing insights into the challenge of detecting climate change. Ice and snow cover at high latitudes influence the global climate system by reflecting much of the incoming solar energy back to space. An expected consequence of global warming is a decrease in area covered by snow and ice and an increase in Earth's absorption of solar radiation. Models have predicted that the effects of climate warming may be amplified at high latitudes; thinning of the Greenland ice sheet margins and the breakup of Antarctic Peninsula ice shelves suggest this process may have begun. Satellite data provide an excellent means of observing climate parameters across both long temporal and remote spatial domains but calibration and validation of their data remains a challenge. Infrared sensors can provide excellent temperature information but cloud cover and calibration remain as problems. Passive-microwave sensors can obtain data during the long polar night and through clouds but have calibration issues and a much lower spatial resolution. Automatic weather stations are generally spatially- and temporally-restricted and may have long gaps due to equipment failure. Stable isotopes of oxygen and hydrogen from ice sheet locations provide another means of determining temperature variations with time but are challenging to calibrate to observed temperatures and also represent restricted areas. This presentation will discuss these issues and elaborate on the development and limitations of composite satellite, automatic weather station, and proxy temperature data from selected sites in Antarctica and Greenland.

  3. PERSPECTIVE Working towards a community-wide understanding of satellite skin temperature observations

    Science.gov (United States)

    Shreve, Cheney

    2010-12-01

    With more than sixty free and publicly available high-quality datasets, including ecosystem variables, radiation budget variables, and land cover products, the MODIS instrument and the MODIS scientific team have contributed significantly to scientific investigations of ecosystems across the globe. The MODIS instrument, launched in December 1999, has 36 spectral bands, a viewing swath of 2330 km, and acquires data at 250 m, 500 m, and 1000 m spatial resolution every one to two days. Radiation budget variables include surface reflectance, skin temperature, emissivity, and albedo, to list a few. Ecosystem variables include several vegetation indices and productivity measures. Land cover characteristics encompass land cover classifications as well as model parameters and vegetation classifications. Many of these products are instrumental in constraining global climate models and climate change studies, as well as monitoring events such as the recent flooding in Pakistan, the unprecedented oil spill in the Gulf of Mexico, or phytoplankton bloom in the Barents Sea. While product validation efforts by the MODIS scientific team are both vigorous and continually improving, validation is unquestionably one of the most difficult tasks when dealing with remotely derived datasets, especially at the global scale. The quality and availability of MODIS data have led to widespread usage in the scientific community that has further contributed to validation and development of the MODIS products. In their recent paper entitled 'Land surface skin temperature climatology: benefitting from the strengths of satellite observations', Jin and Dickinson review the scientific theory behind, and demonstrate application of, a MODIS temperature product: surface skin temperature. Utilizing datasets from the Global Historical Climatological Network (GHCN), daily skin and air temperature from the Atmospheric Radiation Measurement (ARM) program, and MODIS products (skin temperature, albedo, land

  4. GHRSST Level 3C North Atlantic Regional (NAR) subskin Sea Surface Temperature from SNPP/VIIRS and Metop-A/AVHRR (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) derived from the Advanced Very High Resolution Radiometer...

  5. Evaluation of Land Surface Temperature Operationally Retrieved from Korean Geostationary Satellite (COMS Data

    Directory of Open Access Journals (Sweden)

    A-Ra Cho

    2013-08-01

    Full Text Available We evaluated the precision of land surface temperature (LST operationally retrieved from the Korean multipurpose geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS. The split-window (SW-type retrieval algorithm was developed through radiative transfer model simulations under various atmospheric profiles, satellite zenith angles, surface emissivity values and surface lapse rate conditions using Moderate Resolution Atmospheric Transmission version 4 (MODTRAN4. The estimation capabilities of the COMS SW (CSW LST algorithm were evaluated for various impacting factors, and the retrieval accuracy of COMS LST data was evaluated with collocated Moderate Resolution Imaging Spectroradiometer (MODIS LST data. The surface emissivity values for two SW channels were generated using a vegetation cover method. The CSW algorithm estimated the LST distribution reasonably well (averaged bias = 0.00 K, Root Mean Square Error (RMSE = 1.41 K, correlation coefficient = 0.99; however, the estimation capabilities of the CSW algorithm were significantly impacted by large brightness temperature differences and surface lapse rates. The CSW algorithm reproduced spatiotemporal variations of LST comparing well to MODIS LST data, irrespective of what month or time of day the data were collected from. The one-year evaluation results with MODIS LST data showed that the annual mean bias, RMSE and correlation coefficient for the CSW algorithm were −1.009 K, 2.613 K and 0.988, respectively.

  6. Impact of sea surface temperature on satellite retrieval of sea surface salinity

    Science.gov (United States)

    Jin, Xuchen; Zhu, Qiankun; He, Xianqiang; Chen, Peng; Wang, Difeng; Hao, Zengzhou; Huang, Haiqing

    2016-10-01

    Currently, global sea surface salinity (SSS) can be retrieved by the satellite microwave radiometer onboard the satellite, such as the Soil Moisture and Ocean Salinity(SMOS) and the Aqurius. SMOS is an Earth Explorer Opportunity Mission from the European Space Agency(ESA). It was launched at a sun-synchronous orbit in 2009 and one of the payloads is called MIRAS(Microwave Imaging Radiometer using Aperture Synthesis), which is the first interferometric microwave radiometer designed for observing SSS at L-band(1.41 GHz).The foundation of the salinity retrieval by microwave radiometer is that the sea surface radiance at L-band has the most suitable sensitivity with the variation of the salinity. It is well known that the sensitivity of brightness temperatures(TB) to SSS depends on the sea surface temperature (SST), but the quantitative impact of the SST on the satellite retrieval of the SSS is still poorly known. In this study, we investigate the impact of the SST on the accuracy of salinity retrieval from the SMOS. First of all, The dielectric constant model proposed by Klein and Swift has been used to estimate the vertically and horizontally polarized brightness temperatures(TV and TH) of a smooth sea water surface at L-band and derive the derivatives of TV and TH as a function of SSS to show the relative sensitivity at 45° incident angle. Then, we use the GAM(generalized additive model) method to evaluate the association between the satellite-measured brightness temperature and in-situ SSS at different SST. Moreover, the satellite-derived SSS from the SMOS is validated using the ARGO data to assess the RMSE(root mean squared error). We compare the SMOS SSS and ARGO SSS over two regions of Pacific ocean far from land and ice under different SST. The RMSE of retrieved SSS at different SST have been estimated. Our results showed that SST is one of the most significant factors affecting the accuracy of SSS retrieval. The satellite-measured brightness temperature has a

  7. Long term sea surface temperature trends in US Affiliated Pacific Islands from satellite data, 1982-2003

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Monthly average NOAA satellite-derived Sea Surface Temperature (SST) values from 1982-2003 and their long-term trends are presented for sixteen US affiliated Pacific...

  8. Application of remote sensing to thermal pollution analysis. [satellite sea surface temperature measurement assessment

    Science.gov (United States)

    Hiser, H. W.; Lee, S. S.; Veziroglu, T. N.; Sengupta, S.

    1975-01-01

    A comprehensive numerical model development program for near-field thermal plume discharge and far field general circulation in coastal regions is being carried on at the University of Miami Clean Energy Research Institute. The objective of the program is to develop a generalized, three-dimensional, predictive model for thermal pollution studies. Two regions of specific application of the model are the power plants sites at the Biscayne Bay and Hutchinson Island area along the Florida coastline. Remote sensing from aircraft as well as satellites are used in parallel with in situ measurements to provide information needed for the development and verification of the mathematical model. This paper describes the efforts that have been made to identify problems and limitations of the presently available satellite data and to develop methods for enhancing and enlarging thermal infrared displays for mesoscale sea surface temperature measurements.

  9. Calibration of the Distributed Hydrological Model mHM using Satellite derived Land Surface Temperature

    Science.gov (United States)

    Zink, M.; Samaniego, L. E.; Cuntz, M.

    2012-12-01

    A combined investigation of the water and energy balance in hydrologic models can lead to a more accurate estimation of hydrological fluxes and state variables, such as evapotranspiration and soil moisture. Hydrologic models are usually calibrated against discharge measurements, and thus are only trained on information of few points within a catchment. This procedure does not take into account any spatio-temporal variability of fluxes or state variables. Satellite data are a useful source of information to account for this spatial distributions. The objective of this study is to calibrate the distributed hydrological model mHM with satellite derived Land Surface Temperature (LST) fields provided by the Land Surface Analysis - Satellite Application Facility (LSA-SAF). LST is preferred to other satellite products such as soil moisture or evapotranspiration due to its higher precision. LST is obtained by solving the energy balance by assuming that the soil heat flux and the storage term are negligible on a daily time step. The evapotranspiration is determined by closing the water balance in mHM. The net radiation is calculated by using the incoming short- and longwave radiation, albedo and emissivity data provided by LSA-SAF. The Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010) is used to determine the aerodynamic resistance among other parameters. The optimization is performed within the time period 2008-2010 using three objective functions that consider 1) only discharge, 2) only LST, and 3) a combination of both. The proposed method is applied to seven major German river basins: Danube, Ems, Main, Mulde, Neckar, Saale, and Weser. The annual coefficient of correlation between LSA-SAF incoming shortwave radiation and 28 meteorological stations operated by the German Weather Service (DWD) is 0.94 (RMSE = 29 W m-2) in 2009. LSA-SAF incoming longwave radiation could be further evaluated at two eddy covariance stations with a very similar

  10. An improved RST approach for timely alert and Near Real Time monitoring of oil spill disasters by using AVHRR data

    Directory of Open Access Journals (Sweden)

    C. S. L. Grimaldi

    2011-05-01

    Full Text Available Information acquired and provided in Near Real Time is fundamental in contributing to reduce the impact of different sea pollution sources on the maritime environment. Optical data acquired by sensors aboard meteorological satellites, thanks to their high temporal resolution as well as to their delivery policy, can be profitably used for a Near Real Time sea monitoring, provided that accurate and reliable methodologies for analysis and investigation are designed, implemented and fully assessed.

    In this paper, the results achieved by the application of an improved version of RST (Robust Satellite Technique to oil spill detection and monitoring will be shown. In particular, thermal infrared data acquired by the NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer have been analyzed and a new RST-based change detection index applied to the case of the oil spills that occurred off the Kuwait and Saudi Arabian coasts in January 1991 and during the Lebanon War in July 2006.

    The results obtained, even in comparison with those achieved by other AVHRR-based techniques, confirm the unique performance of the proposed approach in automatically detecting the presence of oil spill with a high level of reliability and sensitivity. Moreover, the potential of the extension of the proposed technique to sensors onboard geostationary satellites will be discussed within the context of oil spill monitoring systems, integrating products generated by high temporal (optical and high spatial (radar resolution satellite systems.

  11. Intercomparison of planetary-scale diagnostics derived from separate satellite and radiosonde time-mean temperature fields

    Science.gov (United States)

    Miles, T.; Chapman, W. A.

    1984-01-01

    The planetary-scale components of the extratropical Northern Hemisphere troposphere-stratosphere 1973-74 winter circulation are diagnosed using separate time-mean temperature fields based on radiosonde and satellite observations. Meridional cross-sections of zonal wind together with, for zonal wavenumbers 1, 2 and 3, the streamfunction amplitude, phase and Eliassen-Palm flux are displayed, with the relative accuracy of the satellite-derived diagnostics assessed through comparison with the 'ground-truth' radiosonde information. The satellite and radiosonde diagnostics compare most favourably in terms of zonal wind speed and shear, direction of wave propagation and meridional wave structure - all of which are closely related to the differential properties of the atmospheric temperature field. The intensity of the satellite-derived patterns of tropospheric wave propagation is underestimated due to the effects of spatial smoothing and residual cloud contamination present in the satellite radiance measurements.

  12. NOAA Climate Data Record (CDR) of AVHRR Polar Pathfinder (APP) Cryosphere

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This NOAA Climate Data Record (CDR) contains the AVHRR Polar Pathfinder (APP) product. APP is a fundamental CDR comprised of calibrated and navigated AVHRR channel...

  13. AVHRR Orbital Segment = NOAA's Advanced Very High Resolution Radiometer Files: 1992 - 2000

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Advanced Very High Resolution Radiometer (AVHRR) data set is comprised of data collected by the AVHRR sensor and held in the archives of the USGS Earth Resources...

  14. AVHRR Orbital Segment = NOAA's Advanced Very High Resolution Radiometer Files: 1992 - 2000

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Advanced Very High Resolution Radiometer (AVHRR) data set is comprised of data collected by the AVHRR sensor and held in the archives of the USGS Earth...

  15. AVHRR Orbital Segment = NOAA's Advanced Very High Resolution Radiometer Files: 1992 - 2000

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Advanced Very High Resolution Radiometer (AVHRR) data set is comprised of data collected by the AVHRR sensor and held in the archives of the USGS Earth Resources...

  16. Validation of Satellite-Derived Land Surface Temperature Products - Methods and Good Practice

    Science.gov (United States)

    Guillevic, P. C.; Hulley, G. C.; Hook, S. J.; Biard, J.; Ghent, D.

    2014-12-01

    Land Surface Temperature (LST) is a key variable for surface water and energy budget calculations that can be obtained globally and operationally from satellite observations. LST is used for many applications, including weather forecasting, short-term climate prediction, extreme weather monitoring, and irrigation and water resource management. In order to maximize the usefulness of LST for research and studies it is necessary to know the uncertainty in the LST measurement. Multiple validation methods and activities are necessary to assess LST compliance with the quality specifications of operational users. This work presents four different validation methods that have been widely used to determine the uncertainties in LST products derived from satellite measurements. 1) The temperature based validation method involves comparisons with ground-based measurements of LST. The method is strongly limited by the number and quality of available field stations. 2) Scene-based comparisons involve comparing a new satellite LST product with a heritage LST product. This method is not an absolute validation and satellite LST inter-comparisons alone do not provide an independent validation measurement. 3) The radiance-based validation method does not require ground-based measurements and is usually used for large scale validation effort or for LST products with coarser spatial resolution (> 1km). 4) Time series comparisons are used to detect problems that can occur during the instrument's life, e.g. calibration drift, or unrealistic outliers due to cloud coverage. This study enumerates the sources of errors associated with each method. The four different approaches are complementary and provide different levels of information about the quality of the retrieved LST. The challenges in retrieving the LST from satellite measurements are discussed using results obtained for MODIS and VIIRS. This work contributes to the objective of the Land Product Validation (LPV) sub-group of the

  17. Monitoring changes in biodiversity over Canada during the past three decades using a dynamic habitat index derived from a long-term AVHRR record

    Science.gov (United States)

    Fontana, F. M.; Coops, N. C.; Khlopenkov, K. V.; Trishchenko, A. P.; Wulder, M. A.

    2010-12-01

    Understanding the drivers of biodiversity and establishing methods for biodiversity monitoring and conservation has gained increasing importance over the past decade, with particular focus in 2010, proclaimed by the United Nations to be the International Year of Biodiversity. In this context, satellite remote sensing can provide broad-scale information on a range of geophysical variables such as fraction of photosynthetically active radiation (fPAR) absorbed by a vegetated canopy, or land cover, both of which have been shown to be useful indirect indicators of biodiversity through a connection to species abundance and richness. One satellite-derived indirect indicator of species diversity is the Dynamic Habitat Index (DHI), which combines the cumulative annual fPAR, providing an indication of overall site greenness, the minimum annual apparent fPAR, indicating the base level of vegetation cover observed at a location, and the variation of fPAR (seasonality), estimated as the coefficient of variation. To date the application of the DHI has been restricted to data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors from 2000 onwards. To obtain a longer term time series and earlier baseline of DHI conditions across Canada utilization of the archive of historical satellite data from the Advanced Very High Resolution Radiometer (AVHRR) sensor is proposed. In this paper we will discuss the reprocessing of the 1 km spatial resolution AVHRR archive (1981-2007) using a recently developed processing system, Canadian AVHRR Processing System (CAPS). The CAPS produces multi-date composites that satisfy the geolocation requirements defined by the Global Climate Observing System (GCOS). For the compositing process, a cloud contamination index as well as information on the view zenith angle and cloud shadows is incorporated, and observations are constrained to either the forward or backward scattering hemisphere to reduce Bidirectional Reflectance Distribution

  18. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    This PhD-thesis investigates the directional effects in land surface temperature (LST) estimates from the SEVIRI sensor onboard the Meteosat Second Generation (MSG) satellites. The directional effects are caused by the land surface structure (i.e. tree size and shape) interacting with the changing...... sun-target-sensor geometry. The directional effects occur because the different surface components, e.g. tree canopies and bare soil surfaces, will in many cases have significantly different temperatures. Depending on the viewing angle, different fractions of each of the components will be viewed......; shaded and sunlit canopy and background, respectively. Given data on vegetation structure and density, the model estimates the fractions of the four components as well as the directional composite temperature in the view of a sensor, given the illumination and viewing geometry. The modeling results show...

  19. Development of a Climate-Data Record (CDR) of the Surface Temperature of the Greenland Ice Sheet

    Science.gov (United States)

    Hall, Dorthy K.; Comiso, Josefino C.; Shuman, Christopher A.; DiGirolamo, Nicolo E.; Stock, Larry V.

    2010-01-01

    Regional "clear sky" surface temperature increases since the early 1980s in the Arctic, measured using Advanced Very High Resolution Radiometer (AVHRR) infrared data, range from 0.57+/-0.02 deg C to 72+/-0.10 deg C per decade. Arctic warming has important implications for ice-sheet mass balance because much of the periphery of the Greenland Ice Sheet is already near 0 deg C during the melt season, and is thus vulnerable to rapid melting if temperatures continue to increase. An increase in melting of the ice sheet would accelerate sea-level rise, an issue affecting potentially billions of people worldwide. To quantify the ice-surface temperature (IST) of the Greenland Ice Sheet, and to provide an IST dataset of Greenland for modelers that provides uncertainties, we are developing a climate-data record (CDR) of daily "clear-sky" IST of the Greenland Ice Sheet, from 1982 to the present using AVHRR (1982 - present) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data (2000 - present) at a resolution of approximately 5 km. Known issues being addressed in the production of the CDR are: time-series bias caused by cloud cover (surface temperatures can be different under clouds vs. clear areas) and cross-calibration in the overlap period between AVHRR instruments, and between AVHRR and MODIS instruments. Because of uncertainties, mainly due to clouds, time-series of satellite IST do not necessarily correspond with actual surface temperatures. The CDR will be validated by comparing results with automatic-weather station data and with satellite-derived surface-temperature products and biases will be calculated.

  20. A Three-Dimensional Satellite Retrieval Method for Atmospheric Temperature and Moisture Profiles

    Institute of Scientific and Technical Information of China (English)

    ZHANG Lei; QIU Chongjian; HUANG Jianping

    2008-01-01

    A three-dimensional variational method iS proposed to simultaneously retrieve the 3-D atmospheric temperature and moisture profiles from satellite radiance measurements.To include both vertical structure and the horizontal patterns of the atmospheric temperature and moisture.an EOF technique iS used to decompose the temperature and moisture field in a 3-D space.A number of numerical simulations are conducted and they demonstrate that the 3-D method iS less sensitive to the observation errors compared to the 1-D method.When the observation error iS more than 2.0 K.to get the best results.the truncation number for the EOF'S expansion have to be restricted to 2 in the 1-D method.while it can be set as large as 40 in a 3-D method.This results in the truncation error being reduced and the retrieval accuracy being improved in the 3-D method.Compared to the 1-D method.the rlTLS errors of the 3-D method are reduced by 48%and 36%for the temperature and moisture retrievals,respectively.Using the real satellite measured brightness temperatures at 0557 UTC 31 July 2002,the temperature and moisture profiles are retrieved over a region(20°-45°N,100°-125°E)and compared with 37 collocated radiosonde observations.The results show that the retrieval accuracy with a 3-D method iS significantly higher than those with the 1-D method.

  1. Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

    Science.gov (United States)

    Fang, Li

    The Geostationary Operational Environmental Satellites (GOES) have been continuously monitoring the earth surface since 1970, providing valuable and intensive data from a very broad range of wavelengths, day and night. The National Oceanic and Atmospheric Administration's (NOAA's) National Environmental Satellite, Data, and Information Service (NESDIS) is currently operating GOES-15 and GOES-13. The design of the GOES series is now heading to the 4 th generation. GOES-R, as a representative of the new generation of the GOES series, is scheduled to be launched in 2015 with higher spatial and temporal resolution images and full-time soundings. These frequent observations provided by GOES Image make them attractive for deriving information on the diurnal land surface temperature (LST) cycle and diurnal temperature range (DTR). These parameters are of great value for research on the Earth's diurnal variability and climate change. Accurate derivation of satellite-based LSTs from thermal infrared data has long been an interesting and challenging research area. To better support the research on climate change, the generation of consistent GOES LST products for both GOES-East and GOES-West from operational dataset as well as historical archive is in great demand. The derivation of GOES LST products and the evaluation of proposed retrieval methods are two major objectives of this study. Literature relevant to satellite-based LST retrieval techniques was reviewed. Specifically, the evolution of two LST algorithm families and LST retrieval methods for geostationary satellites were summarized in this dissertation. Literature relevant to the evaluation of satellite-based LSTs was also reviewed. All the existing methods are a valuable reference to develop the GOES LST product. The primary objective of this dissertation is the development of models for deriving consistent GOES LSTs with high spatial and high temporal coverage. Proper LST retrieval algorithms were studied

  2. Satellite observations of surface temperature during the March 2015 total solar eclipse.

    Science.gov (United States)

    Good, Elizabeth

    2016-09-28

    The behaviour of remotely sensed land surface temperatures (LSTs) from the spinning-enhanced visible and infrared imager (SEVIRI) during the total solar eclipse of 20 March 2015 is analysed over Europe. LST is found to drop by up to several degrees Celcius during the eclipse, with the minimum LST occurring just after the eclipse mid-point (median=+1.5 min). The drop in LST is typically larger than the drop in near-surface air temperatures reported elsewhere, and correlates with solar obscuration (r=-0.47; larger obscuration = larger LST drop), eclipse duration (r=-0.62; longer duration = larger LST drop) and time (r=+0.37; earlier eclipse = larger LST drop). Locally, the LST drop is also correlated with vegetation (up to r=+0.6), with smaller LST drops occurring over more vegetated surfaces. The LSTs at locations near the coast and at higher elevation are also less affected by the eclipse. This study covers the largest area and uses the most observations of eclipse-induced surface temperature drops to date, and is the first full characterization of satellite LST during an eclipse (known to the author). The methods described could be applied to Geostationary Operational Environmental Satellite (GOES) LST data over North America during the August 2017 total solar eclipse.This article is part of the themed issue 'Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse'.

  3. Stratospheric aerosol perturbing effect on remote sensing of vegetation: Operational method for the correction of AVHRR composite NDVI

    Energy Technology Data Exchange (ETDEWEB)

    Vermote, E.; El Saleous, N. [Univ. of Maryland, College Park, MD (United States). Dept. of Geography

    1995-12-31

    In this paper the authors present an operational stratospheric aerosol correction scheme adopted by the Laboratory for Terrestrial Physics, NASA/GSFC. The stratospheric aerosol distribution is assumed to be only variable with latitude. Each 9 days the latitudinal distribution of the optical thickness is computed by inverting radiances observed in AVHRR channel 1 (0.63 microns) and channel 2 (0.83 microns) over the Pacific Ocean. This radiance data set is used to check the validity of model used for inversion by checking consistency of the optical thickness deduced from each channel as well as optical thickness deduced from different scattering angles. The deduced optical thickness and spectral dependence are compared to Mauna Loa observation from 1991 to end of 1992 for validation. Using the optical thickness profile previously computed and radiative transfer code assuming lambertian boundary condition, each pixel of channel 1 and 2 are corrected prior to computation of NDVI. Comparison between corrected, non-corrected, and years prior to Pinatubo eruption (1989, 1990) NDVI composite, shows the necessity and the accuracy of the operational correction scheme. The same technique is applied to the afternoon satellite AVHRR archive (NOAA 7, 9, 11) from 1981 to 1993. The stratospheric profile derived over ocean shows that the El Chichon eruption was of less importance than Pinatubo. The stratospheric aerosol optical depth distribution computed from AVHRR data during the El Chichon period compared well to latitudinal monthly profile based on SAGE observations.

  4. Cirrus cloud-temperature interactions over a tropical station, Gadanki from lidar and satellite observations

    Energy Technology Data Exchange (ETDEWEB)

    S, Motty G, E-mail: mottygs@gmail.com; Satyanarayana, M., E-mail: mottygs@gmail.com; Krishnakumar, V., E-mail: mottygs@gmail.com; Dhaman, Reji k., E-mail: mottygs@gmail.com [Department of Optoelectronics, University of Kerala, Kariavattom, Trivandrum-695 581, Kerala (India)

    2014-10-15

    The cirrus clouds play an important role in the radiation budget of the earth's atmospheric system and are important to characterize their vertical structure and optical properties. LIDAR measurements are obtained from the tropical station Gadanki (13.5{sup 0} N, 79.2{sup 0} E), India, and meteorological indicators derived from Radiosonde data. Most of the cirrus clouds are observed near to the tropopause, which substantiates the strength of the tropical convective processes. The height and temperature dependencies of cloud height, optical depth, and depolarization ratio were investigated. Cirrus observations made using CALIPSO satellite are compared with lidar data for systematic statistical study of cirrus climatology.

  5. The annual cycle of satellite-derived sea surface temperature in the southwestern Atlantic Ocean

    Science.gov (United States)

    Podesta, Guillermo P.; Brown, Otis B.; Evans, Robert H.

    1991-01-01

    The annual cycle of sea surface temperature (SST) in the southwestern Atlantic Ocean was estimated using four years (July 1984-July 1988) of NOAA Advanced Very High Resolution Radiometer observations. High resolution satellite observations at 1-km space and daily time resolution were grided at 100-km space and 5-day time intervals to develop an analysis dataset for determination of low frequency SST variability. The integral time scale, a measure of serial correlation, was found to vary from 40 to 60 days in the domain of interest. The existence of superannual trends in the SST data was investigated, but conclusive results could not be obtained. The annual cycle (and, in particular, the annual harmonic) explains a large proportion of the SST variability. The estimated amplitude of the cycle ranges between 5 deg and 13 deg C throughout the study area, with minima in August-September and maxima in February. The resultant climatology is compared with an arbitrary 5-day satellite SST field, and with the COADS/ICE SST climatology. It was found that the higher resolution satellite-based SST climatology resolves boundary current structure and has significantly better structural agreement with the observed field.

  6. Atmospheric correction for sea surface temperature retrieval from single thermal channel radiometer data onboard Kalpana satellite

    Science.gov (United States)

    Shahi, Naveen R.; Agarwal, Neeraj; Mathur, Aloke K.; Sarkar, Abhijit

    2011-06-01

    An atmospheric correction method has been applied on sea surface temperature (SST) retrieval algorithm using Very High Resolution Radiometer (VHRR) single window channel radiance data onboard Kalpana satellite (K-SAT). The technique makes use of concurrent water vapour fields available from Microwave Imager onboard Tropical Rainfall Measuring Mission (TRMM/TMI) satellite. Total water vapour content and satellite zenith angle dependent SST retrieval algorithm has been developed using Radiative Transfer Model [MODTRAN ver3.0] simulations for Kalpana 10.5-12.5 μm thermal window channel. Retrieval of Kalpana SST (K-SST) has been carried out for every half-hourly acquisition of Kalpana data for the year 2008 to cover whole annual cycle of SST over Indian Ocean (IO). Validation of the retrieved corrected SST has been carried out using near-simultaneous observations of ship and buoys datasets covering Arabian Sea, Bay of Bengal and IO regions. A significant improvement in Root Mean Square Deviation (RMSD) of K-SST with respect to buoy (1.50-1.02 K) and to ship datasets (1.41-1.19 K) is seen with the use of near real-time water vapour fields of TMI. Furthermore, comparison of the retrieved SST has also been carried out using near simultaneous observations of TRMM/TMI SST over IO regions. The analysis shows that K-SST has overall cold bias of 1.17 K and an RMSD of 1.09 K after bias correction.

  7. Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data

    Directory of Open Access Journals (Sweden)

    Ugur Avdan

    2016-01-01

    Full Text Available Land surface temperature is an important factor in many areas, such as global climate change, hydrological, geo-/biophysical, and urban land use/land cover. As the latest launched satellite from the LANDSAT family, LANDSAT 8 has opened new possibilities for understanding the events on the Earth with remote sensing. This study presents an algorithm for the automatic mapping of land surface temperature from LANDSAT 8 data. The tool was developed using the LANDSAT 8 thermal infrared sensor Band 10 data. Different methods and formulas were used in the algorithm that successfully retrieves the land surface temperature to help us study the thermal environment of the ground surface. To verify the algorithm, the land surface temperature and the near-air temperature were compared. The results showed that, for the first case, the standard deviation was 2.4°C, and for the second case, it was 2.7°C. For future studies, the tool should be refined with in situ measurements of land surface temperature.

  8. Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

    Science.gov (United States)

    Hall, Dorothy K.; Box, Jason E.; Casey, Kimberly A.; Hook, Simon J.; Shuman, Christopher A.; Steffen, Konrad

    2008-01-01

    The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

  9. Effects of Slope and Aspect Variations on Satellite Surface Temperature Retrievals and Mesoscale Analysis in Mountainous Terrain.

    Science.gov (United States)

    Lipton, Alan E.

    1992-03-01

    Surface temperature retrieval in mountainous areas is complicated by the high variability of temperatures that can occur within a single satellite field of view. Temperatures depend in part on slope orientation relative to the sun, which can vary radically over very short distances. The surface temperature detected by a satellite is biased toward the temperatures of the sub-field-of-view terrain elements that most directly face the satellite. Numerical simulations were conducted to estimate the effects of satellite viewing geometry on surface temperature retrievals for a section of central Colorado. Surface temperatures were computed using a mesoscale model with a parameterization of subgrid variations in slope and aspect angles.The simulations indicate that the slope-aspect effect can lead to local surface temperature variations up to 30°C for autumn conditions in the Colorado mountains. For realistic satellite viewing conditions, these variations can give rise to biases in retrieved surface temperatures of about 3°C. Relative biases between retrievals from two satellites with different viewing angles can be over 6°C, which could lead to confusion when merging datasets. The bias computations were limited by the resolution of the available terrain height data (90 m). The results suggest that the biases would be significantly larger if the data resolution was fine enough to represent every detail of the real Colorado terrain or if retrievals were made in mountain areas that have a larger proportion of steep slopes than the Colorado Rockies. The computed bias gradients across the Colorado domain were not large enough to significantly alter the forcing of the diurnal upslope-downslope circulations, according to simulations in which surface temperature retrievals with view-dependent biases were assimilated into time-continuous analyses. View-dependent retrieval biases may be relevant to climatological analysts that rely on remotely sensed data, given that bias

  10. Study of land surface temperature and spectral emissivity using multi-sensor satellite data

    Indian Academy of Sciences (India)

    P K Srivastava; T J Majumdar; Amit K Bhattacharya

    2010-02-01

    In this study, an attempt has been made to estimate land surface temperatures (LST) and spectral emissivities over a hard rock terrain using multi-sensor satellite data. The study area, of about 6000 km2, is a part of Singhbhum–Orissa craton situated in the eastern part of India. TIR data from ASTER, MODIS and Landsat ETM+ have been used in the present study. Telatemp Model AG-42D Portable Infrared Thermometer was used for ground measurements to validate the results derived from satellite (MODIS/ASTER) data. LSTs derived using Landsat ETM+ data of two different dates have been compared with the satellite data (ASTER and MODIS) of those two dates. Various techniques, viz., temperature and emissivity separation (TES) algorithm, gray body adjustment approach in TES algorithm, Split-Window algorithms and Single Channel algorithm along with NDVI based emissivity approach have been used. LSTs derived from bands 31 and 32 of MODIS data using Split-Window algorithms with higher viewing angle (50°) (LST1 and LST2) are found to have closer agreement with ground temperature measurements (ground LST) over waterbody, Dalma forest and Simlipal forest, than that derived from ASTER data (TES with AST 13). However, over agriculture land, there is some uncertainty and difference between the measured and the estimated LSTs for both validation dates for all the derived LSTs. LST obtained using Single Channel algorithm with NDVI based emissivity method in channel 13 of ASTER data has yielded closer agreement with ground measurements recorded over vegetation and mixed lands of low spectral contrast. LST results obtained with TIR band 6 of Landsat ETM+ using Single Channel algorithm show close agreement over Dalma forest, Simlipal forest and waterbody with LSTs obtained using MODIS and ASTER data for a different date. Comparison of LSTs shows good agreement with ground measurements in thermally homogeneous area. However, results in agriculture area with less homogeneity show

  11. Barium Strontium Titanate Thin Film Growth with rotational speed variation as a satellite temperature sensor prototype

    Science.gov (United States)

    Mulyadi; Rika, W.; Sulidah; Irzaman; Hardhienata, Hendradi

    2017-01-01

    Barium Strontium Titanate(BST) is a promising material for sensor devices such as temperature and infrared sensor. BaxSr1-xTiO3 thin films with affordable Si substrate were prepared by chemical solution deposition method and spin coating technique for 30 seconds with variation in rotation speed (3000 rpm, 5500 rpm and 8000 rpm). A high baking temperature at 8500C has been used for 15 hours during the annealing process. The thickness of BST film was calculated via gravimetric calculation. USB 2000 VIS-NIR was used to characterize the optical properties of BST thin film. The obtained reflectance curve showed that the most reflected wavelengths were in the range of 408-452 nm respectively. The result of the optical film characterization is very important for further development as a sensor in satellite technology.

  12. Towards a protocol for validating satellite-based Land Surface Temperature: Application to AATSR data

    Science.gov (United States)

    Ghent, Darren; Schneider, Philipp; Remedios, John

    2013-04-01

    Land surface temperature (LST) retrieval accuracy can be challenging as a result of emissivity variability and atmospheric effects. Surface emissivities can be highly variable owing to the heterogeneity of the land; a problem which is amplified in regions of high topographic variance or for larger viewing angles. Atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. Combined, atmospheric effects and emissivity variability can result in retrieval errors of several degrees. If though these are appropriately handled satellite-derived LST products can be used to improve our ability to monitor and to understand land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. Here we present validation of an improved LST data record from the Advanced Along-Track Scanning Radiometer (AATSR) and illustrate the improvements in accuracy and precision compared with the standard ESA LST product. Validation is a critical part of developing any satellite product, although over the land heterogeneity ensures this is a challenging undertaking. A substantial amount of previous effort has gone into the area of structuring and standardizing calibration and validation approaches within the field of Earth Observation. However, no unified approach for accomplishing this for LST has yet to be practised by the LST community. Recent work has attempted to address this situation with the development of a protocol for validating LST (Schneider et al., 2012) under the auspices of ESA and the support of the wider LST community. We report here on a first application of this protocol to satellite LST data. The approach can briefly be summarised thus: in situ validation is performed where ground-based observations are available - being predominantly homogeneous sites; heterogeneous pixels are validated by way of established radiometric-based techniques (Wan and Li

  13. Probabilistic approach to cloud and snow detection on AVHRR imagery

    Science.gov (United States)

    Musial, J. P.; Hüsler, F.; Sütterlin, M.; Neuhaus, C.; Wunderle, S.

    2013-09-01

    The derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. The information about a confidence level of provided physical quantities is required to construct an error budget of higher level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data the common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher level products and may alter their usability. Within this scope a novel Probabilistic Cloud Mask (PCM) algorithm suited for the 1×1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on a decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve the probability estimates from the pre-computed Look Up Tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of thresholds. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the Invariant Coordinate System (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the PPSv2012 and MOD35 collection 6 cloud masks, SYNOP weather

  14. Probabilistic approach to cloud and snow detection on AVHRR imagery

    Directory of Open Access Journals (Sweden)

    J. P. Musial

    2013-09-01

    Full Text Available The derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. The information about a confidence level of provided physical quantities is required to construct an error budget of higher level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data the common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher level products and may alter their usability. Within this scope a novel Probabilistic Cloud Mask (PCM algorithm suited for the 1×1 km Advanced Very High Resolution Radiometer (AVHRR data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on a decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve the probability estimates from the pre-computed Look Up Tables (LUTs. Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of thresholds. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the Invariant Coordinate System (ICS transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the PPSv2012 and MOD35 collection 6 cloud masks

  15. Multi-Sensor Calibration Studies of AVHRR-Heritage Channel Radiances Using the Simultaneous Nadir Observation Approach

    Directory of Open Access Journals (Sweden)

    Karl-Göran Karlsson

    2014-02-01

    Full Text Available The European Space Agency project for studies of cloud properties in the Climate Change Initiative programme (ESA-CLOUD-CCI aims at compiling the longest possible time series of cloud products from one single multispectral sensor—The five-channel Advanced Very High Resolution Radiometer (AVHRR instrument. A particular aspect here is to include corresponding products based on other existing (Moderate Resolution Imaging Spectroradiometer (MODIS, Advanced Along-Track Scanning Radiometer (AATSR, MEdium Resolution Imaging Spectrometer (MERIS, Visible and Infrared Radiometer Suite (VIIRS and future Sea and Land Surface Temperature Radiometer (SLSTR sensors measuring in similar (AVHRR-heritage spectral channels. Initial inter-comparisons of the involved AVHRR-heritage channel radiances over a short demonstration period (2007–2009 were performed. Using Aqua-MODIS as reference, AVHRR (NOAA-18, AATSR, and MERIS channel radiances were evaluated using the simultaneous nadir (SNO approach. Results show generally agreeing radiances within approximately 3% for channels at 0.6 µm and 0.8 µm. Larger deviations (+5% were found for the corresponding AATSR channel at 0.6 µm. Excessive deviations but with opposite sign were also indicated for AATSR 1.6 µm and MERIS 0.8 µm radiances. Observed differences may largely be attributed to residual temporal and spatial matching differences while excessive AATSR and MERIS deviations are likely partly attributed to incomplete compensation for spectrally varying surface and atmospheric conditions. However, very good agreement was found for all infrared channels among all the studied sensors. Here, deviations were generally less than 0.2% for the measured brightness temperatures with the exception of some remaining non-linear deviations at extreme low and high temperatures.

  16. High resolution 3-D temperature and salinity fields derived from in situ and satellite observations

    Directory of Open Access Journals (Sweden)

    S. Guinehut

    2012-10-01

    Full Text Available This paper describes an observation-based approach that efficiently combines the main components of the global ocean observing system using statistical methods. Accurate but sparse in situ temperature and salinity profiles (mainly from Argo for the last 10 yr are merged with the lower accuracy but high-resolution synthetic data derived from satellite altimeter and sea surface temperature observations to provide global 3-D temperature and salinity fields at high temporal and spatial resolution. The first step of the method consists in deriving synthetic temperature fields from altimeter and sea surface temperature observations, and salinity fields from altimeter observations, through multiple/simple linear regression methods. The second step of the method consists in combining the synthetic fields with in situ temperature and salinity profiles using an optimal interpolation method. Results show the revolutionary nature of the Argo observing system. Argo observations now allow a global description of the statistical relationships that exist between surface and subsurface fields needed for step 1 of the method, and can constrain the large-scale temperature and mainly salinity fields during step 2 of the method. Compared to the use of climatological estimates, results indicate that up to 50% of the variance of the temperature fields can be reconstructed from altimeter and sea surface temperature observations and a statistical method. For salinity, only about 20 to 30% of the signal can be reconstructed from altimeter observations, making the in situ observing system essential for salinity estimates. The in situ observations (step 2 of the method further reduce the differences between the gridded products and the observations by up to 20% for the temperature field in the mixed layer, and the main contribution is for salinity and the near surface layer with an improvement up to 30%. Compared to estimates derived using in situ observations only, the

  17. High Resolution 3-D temperature and salinity fields derived from in situ and satellite observations

    Directory of Open Access Journals (Sweden)

    S. Guinehut

    2012-03-01

    Full Text Available This paper describes an observation-based approach that combines efficiently the main components of the global ocean observing system using statistical methods. Accurate but sparse in situ temperature and salinity profiles (mainly from Argo for the last 10 years are merged with the lower accuracy but high-resolution synthetic data derived from altimeter and sea surface temperature satellite observations to provide global 3-D temperature and salinity fields at high temporal and spatial resolution. The first step of the method consists in deriving synthetic temperature fields from altimeter and sea surface temperature observations and salinity fields from altimeter observations through multiple/simple linear regression methods. The second step of the method consists in combining the synthetic fields with in situ temperature and salinity profiles using an optimal interpolation method. Results show the revolution of the Argo observing system. Argo observations now allow a global description of the statistical relationships that exist between surface and subsurface fields needed for step 1 of the method and can constrain the large-scale temperature and mainly salinity fields during step 2 of the method. Compared to the use of climatological estimates, results indicate that up to 50 % of the variance of the temperature fields can be reconstructed from altimeter and sea surface temperature observations and a statistical method. For salinity, only about 20 to 30 % of the signal can be reconstructed from altimeter observations, making the in situ observing system mandatory for salinity estimates. The in situ observations (step 2 of the method reduce additionally the error by up to 20 % for the temperature field in the mixed layer and the main contribution is for salinity and the near surface layer with an improvement up to 30 %. Compared to estimates derived using in situ observations only, the merged fields provide a better reconstruction of the high

  18. Retrieving Clear-Sky Surface Skin Temperature for Numerical Weather Prediction Applications from Geostationary Satellite Data

    Directory of Open Access Journals (Sweden)

    Baojuan Shan

    2013-01-01

    Full Text Available Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Remote sensing of the Earth’s energy budget, particularly with instruments flown on geostationary satellites, allows for near-real-time evaluation of cloud and surface radiation properties. The persistence and coverage of geostationary remote sensing instruments grant the frequent retrieval of near-instantaneous quasi-global skin temperature. Among other cloud and clear-sky retrieval parameters, NASA Langley provides a non-polar, high-resolution land and ocean skin temperature dataset for atmospheric modelers by applying an inverted correlated k-distribution method to clear-pixel values of top-of-atmosphere infrared temperature. The present paper shows that this method yields clear-sky skin temperature values that are, for the most part, within 2 K of measurements from ground-site instruments, like the Southern Great Plains Atmospheric Radiation Measurement (ARM Infrared Thermometer and the National Climatic Data Center Apogee Precision Infrared Thermocouple Sensor. The level of accuracy relative to the ARM site is comparable to that of the Moderate-resolution Imaging Spectroradiometer (MODIS with the benefit of an increased number of daily measurements without added bias or increased error. Additionally, matched comparisons of the high-resolution skin temperature product with MODIS land surface temperature reveal a level of accuracy well within 1 K for both day and night. This confidence will help in characterizing the diurnal and seasonal biases and root-mean-square differences between the retrievals and modeled values from the NASA Goddard Earth Observing System Version 5 (GEOS-5 in preparation for assimilation of the retrievals into GEOS-5. Modelers should find the immediate availability and broad coverage of these skin temperature

  19. Application of satellite microwave remote sensed brightness temperature in the regional soil moisture simulation

    Directory of Open Access Journals (Sweden)

    X. K. Shi

    2009-02-01

    Full Text Available As the satellite microwave remote sensed brightness temperature is sensitive to land surface soil moisture (SM and SM is a basic output variable in model simulation, it is of great significance to use the brightness temperature data to improve SM numerical simulation. In this paper, the theory developed by Yan et al. (2004 about the relationship between satellite microwave remote sensing polarization index and SM was used to estimate the land surface SM from AMSR-E (Advanced Microwave Scanning Radiometer – Earth Observing System brightness temperature data. With consideration of land surface soil texture, surface roughness, vegetation optical thickness, and the AMSR-E monthly SM products, the regional daily land surface SM was estimated over the eastern part of the Qinghai-Tibet Plateau. The results show that the estimated SM is lower than the ground measurements and the NCEP (American National Centers for Environmental Prediction reanalysis data at the Maqu Station (33.85° N, 102.57° E and the Tanglha Station (33.07° N, 91.94° E, but its regional distribution is reasonable and somewhat better than that from the daily AMSR-E SM product, and its temporal variation shows a quick response to the ground daily precipitations. Furthermore, in order to improve the simulating ability of the WRF (Weather Research and Forecasting model to land surface SM, the estimated SM was assimilated into the Noah land surface model by the Newtonian relaxation (NR method. The results indicate that, by fine tuning of the quality factor in NR method, the simulated SM values are improved most in desert area, followed by grassland, shrub and grass mixed zone. At temporal scale, Root Mean Square Error (RMSE values between simulated and observed SM are decreased 0.03 and 0.07 m3/m3 by using the NR method in the Maqu Station and the Tanglha Station, respectively.

  20. Preliminary study on direct assimilation of cloud-affected satellite microwave brightness temperatures

    Science.gov (United States)

    Zhang, Sibo; Guan, Li

    2017-02-01

    Direct assimilation of cloud-affected microwave brightness temperatures from AMSU-A into the GSI three-dimensional variational (3D-Var) assimilation system is preliminarily studied in this paper. A combination of cloud microphysics parameters retrieved by the 1D-Var algorithm (including vertical profiles of cloud liquid water content, ice water content, and rain water content) and atmospheric state parameters from objective analysis fields of an NWP model are used as background fields. Three cloud microphysics parameters (cloud liquid water content, ice water content, and rain water content) are applied to the control variable. Typhoon Halong (2014) is selected as an example. The results show that direct assimilation of cloud-affected AMSU-A observations can effectively adjust the structure of large-scale temperature, humidity and wind analysis fields due to the assimilation of more AMSU-A observations in typhoon cloudy areas, especially typhoon spiral cloud belts. These adjustments, with temperatures increasing and humidities decreasing in the movement direction of the typhoon, bring the forecasted typhoon moving direction closer to its real path. The assimilation of cloud-affected satellite microwave brightness temperatures can provide better analysis fields that are more similar to the actual situation. Furthermore, typhoon prediction accuracy is improved using these assimilation analysis fields as the initial forecast fields in NWP models.

  1. Sea Temperature Fiducial Reference Measurements for the Validation and Data Gap Bridging of Satellite SST Data Products

    Science.gov (United States)

    Wimmer, Werenfrid

    2016-08-01

    The Infrared Sea surface temperature Autonomous Radiometer (ISAR) was developed to provide reference data for the validation of satellite Sea Surface Temperature at the Skin interface (SSTskin) temperature data products, particularly the Advanced Along Track Scanning Radiometer (AATSR). Since March 2004 ISAR instruments have been deployed nearly continuously on ferries crossing the English Channel and the Bay of Biscay, between Portsmouth (UK) and Bilbao/Santander (Spain). The resulting twelve years of ISAR data, including an individual uncertainty estimate for each SST record, are calibrated with traceability to national standards (National Institute of Standards and Technology, USA (NIST) and National Physical Laboratory, Teddigton, UK (NPL), Fiducial Reference Measurements for satellite derived surface temperature product validation (FRM4STS)). They provide a unique independent in situ reference dataset against which to validate satellite derived products. We present results of the AATSR validation, and show the use of ISAR fiducial reference measurements as a common traceable validation data source for both AATSR and Sea and Land Surface Temperature Radiometer (SLSTR). ISAR data were also used to review performance of the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Sea Surface Temperature (SST) analysis before and after the demise of ESA Environmental Satellite (Envisat) when AATSR inputs ceased This demonstrates use of the ISAR reference data set for validating the SST climatologies that will bridge the data gap between AATSR and SLSTR.

  2. The influence of snow depth and surface air temperature on satellite-derived microwave brightness temperature. [central Russian steppes, and high plains of Montana, North Dakota, and Canada

    Science.gov (United States)

    Foster, J. L.; Hall, D. K.; Chang, A. T. C.; Rango, A.; Allison, L. J.; Diesen, B. C., III

    1980-01-01

    Areas of the steppes of central Russia, the high plains of Montana and North Dakota, and the high plains of Canada were studied in an effort to determine the relationship between passive microwave satellite brightness temperature, surface air temperature, and snow depth. Significant regression relationships were developed in each of these homogeneous areas. Results show that sq R values obtained for air temperature versus snow depth and the ratio of microwave brightness temperature and air temperature versus snow depth were not as the sq R values obtained by simply plotting microwave brightness temperature versus snow depth. Multiple regression analysis provided only marginal improvement over the results obtained by using simple linear regression.

  3. Atmospheric correction for sea surface temperature retrieval from single thermal channel radiometer data onboard Kalpana satellite

    Indian Academy of Sciences (India)

    Naveen R Shahi; Neeraj Agarwal; Aloke K Mathur; Abhijit Sarkar

    2011-06-01

    An atmospheric correction method has been applied on sea surface temperature (SST) retrieval algorithm using Very High Resolution Radiometer (VHRR) single window channel radiance data onboard Kalpana satellite (K-SAT). The technique makes use of concurrent water vapour fields available from Microwave Imager onboard Tropical Rainfall Measuring Mission (TRMM/TMI) satellite. Total water vapour content and satellite zenith angle dependent SST retrieval algorithm has been developed using Radiative Transfer Model [MODTRAN ver3.0] simulations for Kalpana 10.5–12.5 m thermal window channel. Retrieval of Kalpana SST (K-SST) has been carried out for every half-hourly acquisition of Kalpana data for the year 2008 to cover whole annual cycle of SST over Indian Ocean (IO). Validation of the retrieved corrected SST has been carried out using near-simultaneous observations of ship and buoys datasets covering Arabian Sea, Bay of Bengal and IO regions. A significant improvement in Root Mean Square Deviation (RMSD) of K-SST with respect to buoy (1.50–1.02 K) and to ship datasets (1.41–1.19 K) is seen with the use of near real-time water vapour fields of TMI. Furthermore, comparison of the retrieved SST has also been carried out using near simultaneous observations of TRMM/TMI SST over IO regions. The analysis shows that K-SST has overall cold bias of 1.17 K and an RMSD of 1.09 K after bias correction.

  4. Global Assessment of Land Surface Temperature From Geostationary Satellites and Model Estimates

    Science.gov (United States)

    Reichle, Rolf H.; Liu, Q.; Minnis, P.; daSilva, A. M., Jr.; Palikonda, R.; Yost, C. R.

    2012-01-01

    Land surface (or 'skin') temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research we compare two global and independent data sets: (i) LST retrievals from five geostationary satellites generated at the NASA Langley Research Center (LaRC) and (ii) LST estimates from the quasi-operational NASA GEOS-5 global modeling and assimilation system. The objective is to thoroughly understand both data sets and their systematic differences in preparation for the assimilation of the LaRC LST retrievals into GEOS-5. As expected, mean differences (MD) and root-mean-square differences (RMSD) between modeled and retrieved LST vary tremendously by region and time of day. Typical (absolute) MD values range from 1-3 K in Northern Hemisphere mid-latitude regions to near 10 K in regions where modeled clouds are unrealistic, for example in north-eastern Argentina, Uruguay, Paraguay, and southern Brazil. Typically, model estimates of LST are higher than satellite retrievals during the night and lower during the day. RMSD values range from 1-3 K during the night to 2-5 K during the day, but are larger over the 50-120 W longitude band where the LST retrievals are derived from the FY2E platform

  5. Satellite Observations of Wind Farm Impacts on Nocturnal Land Surface Temperature in Iowa

    Directory of Open Access Journals (Sweden)

    Ronald A. Harris

    2014-12-01

    Full Text Available Wind farms (WFs are believed to have an impact on lower boundary layer meteorology. A recent study examined satellite-measured land surface temperature data (LST and found a local nighttime warming effect attributable to a group of four large WFs in Texas. This study furthers their work by investigating the impacts of five individual WFs in Iowa, where the land surface properties and climate conditions are different from those in Texas. Two methods are used to assess WF impacts: first, compare the spatial coupling between the LST changes (after turbine construction versus before and the geographic layouts of the WFs; second, quantify the LST difference between the WFs and their immediate surroundings (non-WF areas. Each WF shows an irrefutable nighttime warming signal relative to the surrounding areas after their turbines were installed, and these warming signals are generally coupled with the geographic layouts of the wind turbines, especially in summer. This study provides further observational evidence that WFs can cause surface warming at nighttime, and that such a signal can be detected by satellite-based sensors.

  6. Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

    2017-04-01

    The model of water and heat exchange between vegetation covered territory and atmosphere (LSM, Land Surface Model) for vegetation season has been developed to calculate soil water content, evapotranspiration, infiltration of water into the soil, vertical latent and sensible heat fluxes and other water and heat balances components as well as soil surface and vegetation cover temperatures and depth distributions of moisture and temperature. The LSM is suited for utilizing satellite-derived estimates of precipitation, land surface temperature and vegetation characteristics and soil surface humidity for each pixel. Vegetation and meteorological characteristics being the model parameters and input variables, correspondingly, have been estimated by ground observations and thematic processing measurement data of scanning radiometers AVHRR/NOAA, SEVIRI/Meteosat-9, -10 (MSG-2, -3) and MSU-MR/Meteor-M № 2. Values of soil surface humidity has been calculated from remote sensing data of scatterometers ASCAT/MetOp-A, -B. The case study has been carried out for the territory of part of the agricultural Central Black Earth Region of European Russia with area of 227300 km2 located in the forest-steppe zone for years 2012-2015 vegetation seasons. The main objectives of the study have been: - to built estimates of precipitation, land surface temperatures (LST) and vegetation characteristics from MSU-MR measurement data using the refined technologies (including algorithms and programs) of thematic processing satellite information matured on AVHRR and SEVIRI data. All technologies have been adapted to the area of interest; - to investigate the possibility of utilizing satellite-derived estimates of values above in the LSM including verification of obtained estimates and development of procedure of their inputting into the model. From the AVHRR data there have been built the estimates of precipitation, three types of LST: land skin temperature Tsg, air temperature at a level of

  7. Normalization and calibration of geostationary satellite radiances for the International Satellite Cloud Climatology Project

    Science.gov (United States)

    Desormeaux, Yves; Rossow, William B.; Brest, Christopher L.; Campbell, G. G.

    1993-01-01

    Procedures are described for normalizing the radiometric calibration of image radiances obtained from geostationary weather satellites that contributed data to the International Satellite Cloud Climatology Project. The key step is comparison of coincident and collocated measurements made by each satellite and the concurrent AVHRR on the 'afternoon' NOAA polar-orbiting weather satellite at the same viewing geometry. The results of this comparison allow transfer of the AVHRR absolute calibration, which has been established over the whole series, to the radiometers on the geostationary satellites. Results are given for Meteosat-2, 3, and 4, for GOES-5, 6, and 7, for GMS-2, 3, and 4 and for Insat-1B. The relative stability of the calibrations of these radiance data is estimated to be within +/- 3 percent; the uncertainty of the absolute calibrations is estimated to be less than 10 percent. The remaining uncertainties are at least two times smaller than for the original radiance data.

  8. In-flight measurements of space count in the AVHRR solar reflectance bands

    Science.gov (United States)

    Ignatov, Alexander; Cao, Changyong; Sullivan, Jerry T.; Levin, Robert H.; Wu, Xiangqian; Galvin, Roy P.

    2005-01-01

    The solar reflectance bands (SRB) of the Advanced Very High Resolution Radiometers (AVHRR) flown onboard NOAA satellites are often referred to as non-calibrated in-flight. In contrast, the Earth emission bands (EEB) are calibrated using two reference points, deep space and the internal calibration target. In the SRBs, measurements of space count (SC) are also available, however, historically they are not used to specify the calibration offset ("zero count", ZC), which does not even appear in the calibration equation. A regression calibration formulation is used instead, equivalent to setting the ZC to a constant, whose value is specified from pre-launch measurements. Our analyses supported by a review of the instrument design and a wealth of historical SC information show that the SC varies in-flight and it differs from its pre-launch value. We therefore suggest that (1) the AVHRR calibration equation in the SRBs be re-formulated to explicitly use the ZC, consistently with the EEBs, and (2) the value of ZC be specified from the onboard measurements of SC. This study emphasizes the importance of clear discrimination between the SC (which is a measured quantity and therefore takes on a range of values, characterized by the empirical probability density function, PDF), from the ZC (which is a parameter in the calibration equation, i.e. a number whose value needs to be estimated from the measured SC as a mean, median or other statistic of the measured PDF). The ZC-formulation of the calibration equation is physically solid, and it minimizes human-induced calibration errors resulting from the use of a regression formulation with an un-constrained intercept. Specifying the calibration offset improves radiances, most notably at the low end of radiometric scale, and subsequently provides for more accurate vicarious determinations of the calibration slope (inverse gain). These calibration improvements are important for the products derived from the AVHRR low-radiances, such

  9. Comparison of TOMS and AVHRR imagery of volcanic clouds

    Science.gov (United States)

    Rose, William I.

    1994-01-01

    This project consisted of merging volcanic cloud data from initial studies from TOMS and AVHRR sensors. Because of the different data acquisition platforms and processing algorithms and formats, the combination of the two data required special consideration. Once the registration technique was perfected, several eruptions with data from both sensors were studied. The conclusion showed that, from the initial work, the positions of the volcanic clouds as detected by the two sensors are very similar. Because the AVHRR algorithm is now capable of retrieving masses of ash and sulfate aerosol, the capability of comparing data from the two sensors now allows changes in SO2, H2SO4, and silicated ash in drifting clouds to be described. The results of this study culminated in several presentations, and a master's thesis, which in turn was converted into a paper submitted to the Journal of Geophysical Research. Abstracts of two presentations are attached.

  10. Mapping Fire Scars in the Brazilian Cerrado Using AVHRR Imagery

    Science.gov (United States)

    Hlavka, C. A.; Ambrosia, V. G.; Brass, J. A.; Rezendez, A.; Alexander, S.; Guild, L. S.; Peterson, David L. (Technical Monitor)

    1995-01-01

    The Brazilian cerrado, or savanna, spans an area of 1,800,000 square kilometers on the great plateau of Central Brazil. Large fires covering hundreds of square kilometers, frequently occur in wildland areas of the cerrado, dominated by grasslands or grasslands mixed with shrubs and small trees, and also within area in the cerrado used for agricultural purposes, particularly for grazing. Smaller fires, typically extending over arm of a few square kilometers or less, are associated with the clewing of crops, such as dry land rice. A method for mapping fire scars and differentiating them from extensive areas of bare sod with AVHRR bands 1 (.55 -.68 micrometer) and 3 (3.5 - 3.9 micrometers) and measures of performance based on comparison with maps of fires with Landsat imagery will be presented. Methods of estimating total area burned from the AVHRR fire scar map will be discussed and related to land use and scar size.

  11. Land Surface Temperature- Comparing Data from Polar Orbiting and Geostationary Satellites

    Science.gov (United States)

    Comyn-Platt, E.; Remedios, J. J.; Good, E. J.; Ghent, D.; Saunders, R.

    2012-04-01

    Land Surface Temperature (LST) is a vital parameter in Earth climate science, driving long-wave radiation exchanges that control the surface energy budget and carbon fluxes, which are important factors in Numerical Weather Prediction (NWP) and the monitoring of climate change. Satellites offer a convenient way to observe LST consistently and regularly over large areas. A comparison between LST retrieved from a Geostationary Instrument, the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), and a Polar Orbiting Instrument, the Advanced Along Track Scanning Radiometer (AATSR) is presented. Both sensors offer differing benefits. AATSR offers superior precision and spatial resolution with global coverage but given its sun-synchronous platform only observes at two local times, ~10am and ~10pm. SEVIRI provides the high-temporal resolution (every 15 minutes) required for observing diurnal variability of surface temperatures but given its geostationary platform has a poorer resolution, 3km at nadir, which declines at higher latitudes. A number of retrieval methods are applied to the raw satellite data: First order coefficient based algorithms provided on an operational basis by the LandSAF (for SEVIRI) and the University of Leicester (for AATSR); Second order coefficient based algorithms put forward by the University of Valencia; and an optimal estimation method using the 1DVar software provided by the NWP SAF. Optimal estimation is an iterative technique based upon inverse theory, thus is very useful for expanding into data assimilation systems. The retrievals are assessed and compared on both a fine scale using in-situ data from recognised validation sites and on a broad scale using two 100x100 regions such that biases can be better understood. Overall, the importance of LST lies in monitoring daily temperature extremes, e.g. for estimating permafrost thawing depth or risk of crop damage due to frost, hence the ideal dataset would use a combination of observations

  12. Retrieving Marine Inherent Optical Properties from Satellites Using Temperature and Salinity-dependent Backscattering by Seawater

    Science.gov (United States)

    Werdell, Paul J.; Franz, Bryan Alden; Lefler, Jason Travis; Robinson, Wayne D.; Boss, Emmanuel

    2013-01-01

    Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.

  13. Can satellite land surface temperature data be used similarly to ground discharge measurements for distributed hydrological model calibration?

    NARCIS (Netherlands)

    Corbari, C.; Mancini, M.; Li, J.; Su, Zhongbo

    2015-01-01

    This study proposes a new methodology for the calibration of distributed hydrological models at basin scale by constraining an internal model variable using satellite data of land surface temperature. The model algorithm solves the system of energy and mass balances in terms of a representative equi

  14. Maximizing the Use of Satellite Thermal Infrared Data for Advancing Land Surface Temperature Analysis

    Science.gov (United States)

    Weng, Q.; Fu, P.; Gao, F.

    2014-12-01

    Land surface temperature (LST) is a crucial parameter in investigating environmental, ecological processes and climate change at various scales, and is also valuable in the studies of evapotranspiration, soil moisture conditions, surface energy balance, and urban heat islands. These studies require thermal infrared (TIR) images at both high temporal and spatial resolution to retrieve LST. However, currently, no single satellite sensors can deliver TIR data at both high temporal and spatial resolution. Thus, various algorithms/models have been developed to enhance the spatial or the temporal resolution of TIR data, but rare of those can enhance both spatial and temporal details. This paper presents a new data fusion algorithm for producing Landsat-like LST data by blending daily MODIS and periodic Landsat TM datasets. The original Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was improved and modified for predicting thermal radiance and LST data by considering annual temperature cycle (ATC) and urban thermal landscape heterogeneity. The technique of linear spectral mixture analysis was employed to relate the Landsat radiance with the MODIS one, so that the temporal changes in radiance can be incorporated in the fusion model. This paper details the theoretical basis and the implementation procedures of the proposed data fusion algorithm, Spatio-temporal Adaptive Data Fusion Algorithm for Temperature mapping (SADFAT). A case study was conducted that predicted LSTs of five dates in 2005 from July to October in Los Angeles County, California. The results indicate that the prediction accuracy for the whole study area ranged from 1.3 K to 2 K. Like existing spatio-temporal data fusion models, the SADFAT method has a limitation in predicting LST changes that were not recorded in the MODIS and/or Landsat pixels due to the model assumption.

  15. Examination of elevation dependency in observed and projected temperature change in the Upper Indus Basin and Western Himalaya

    Science.gov (United States)

    Fowler, H. J.; Forsythe, N. D.; Blenkinsop, S.; Archer, D.; Hardy, A.; Janes, T.; Jones, R. G.; Holderness, T.

    2013-12-01

    We present results of two distinct, complementary analyses to assess evidence of elevation dependency in temperature change in the UIB (Karakoram, Eastern Hindu Kush) and wider WH. The first analysis component examines historical remotely-sensed land surface temperature (LST) from the second and third generation of the Advanced Very High Resolution Radiometer (AVHRR/2, AVHRR/3) instrument flown on NOAA satellite platforms since the mid-1980s through present day. The high spatial resolution (AVHRR instrument enables precise consideration of the relationship between estimated LST and surface topography. The LST data product was developed as part of initiative to produce continuous time-series for key remotely sensed spatial products (LST, snow covered area, cloud cover, NDVI) extending as far back into the historical record as feasible. Context for the AVHRR LST data product is provided by results of bias assessment and validation procedures against both available local observations, both manned and automatic weather stations. Local observations provide meaningful validation and bias assessment of the vertical gradients found in the AVHRR LST as the elevation range from the lowest manned meteorological station (at 1460m asl) to the highest automatic weather station (4733m asl) covers much of the key range yielding runoff from seasonal snowmelt. Furthermore the common available record period of these stations (1995 to 2007) enables assessment not only of the AVHRR LST but also performance comparisons with the more recent MODIS LST data product. A range of spatial aggregations (from minor tributary catchments to primary basin headwaters) is performed to assess regional homogeneity and identify potential latitudinal or longitudinal gradients in elevation dependency. The second analysis component investigates elevation dependency, including its uncertainty, in projected temperature change trajectories in the downscaling of a seventeen member Global Climate Model (GCM

  16. IDENTIFICATION OF OCEANOGRAPHIC PARAMETERS FOR DETERMINING PELAGIC TUNA FISHING GROUND IN THE NORTH PAPUA WATERS USING MULTI-SENSOR SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    VlNCENTIUS SlREGAR

    2006-01-01

    Full Text Available The North Papua waters as one of the important fi shing grounds in the world contribute approximately 75% of world production of pelagic tunas. These fishing grounds are still determined by hunting method. This method is time consuming and costly. However, in many areas determination of fishing ground using satellited data lias been applied by detecting the important oceanographic parameter of the presence of fish schooling such as, sea surface temperature and chlorophyl. Mostly these parameters are used integrat edly. The aim of this study is to assess the important oceanographic parameters detected from mu lti-sensor satellites (NO AA/AVHRR, Seawifs and Topex Poisedon for determining fishing ground of pelagic tunas in the North Papua waters at east season. The parameters include Sea Surface Temperature (STT, chlorophyl-a and currents. The ava ilability of data from optic sensor (Seawifs: chl-a and AVHRR: Thermal is limited by the presence of cloud cover. In that case, Topex Poseidon satellite data can be used to provide the currents data. The integration of data from multi-sensors increases the availability of the oceanographic parameters for prediction of the potential fishing zones in the study area.

  17. Mapping landscape phenology preference of yellow-billed cuckoo with AVHRR data

    Science.gov (United States)

    Wallace, Cynthia S.A.; Villarreal, Miguel; Van Riper, Charles

    2013-01-01

    We mapped habitat for threatened Yellow-billed Cuckoo (Coccycus americanus occidentalis) in the State of Arizona using the temporal greenness dynamics of the landscape, or the landscape phenology. Landscape phenometrics were derived from Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data for 1998 and 1999 by using Fourier harmonic analysis to analyze the waveform of the annual NDVI profile at each pixel. We modeled the spatial distribution of Yellow-billed Cuckoo habitat by coupling the field data of Cuckoo presence or absence and point-based samples of riparian and cottonwood-willow vegetation types with satellite phenometrics for 1998. Models were validated using field and satellite data collected in 1999. The results indicate that Yellow-billed Cuckoo occupy locations within their preferred habitat that exhibit peak greenness after the start of the summer monsoon and are greener and more dynamic than “average” habitat. Identification of preferred phenotypes within recognized habitat areas can be used to refine habitat models, inform predictions of habitat response to climate change, and suggest adaptation strategies.

  18. Land Surface Albedo From EPS/AVHRR : Method For Retrieval and Validation

    Science.gov (United States)

    Jacob, G.

    2015-12-01

    The scope of Land Surface Analysis Satellite Applications Facility (LSA-SAF) is to increase benefit from EUMETSAT Satellites (MSG and EPS) data by providing added value products for the meteorological and environmental science communities with main applications in the fields of climate modelling, environmental management, natural hazards management, and climate change detection. The MSG/SEVIRI daily albedo product is disseminated operationally by the LSA-SAF processing centre based in Portugal since 2009. This product so-called MDAL covers Europe and Africa includes in the visible, near infrared and shortwave bands at a resolution of 3km at the equator. Recently, an albedo product at 1km so-called ETAL has been built from EPS/AVHRR observations in order to primarily MDAL product outside the MSG disk, while ensuring a global coverage. The methodology is common to MSG and EPS data and relies on the inversion of the BRDF (Bidirectional Reflectance Distribution Function) model of Roujean et al. On a given target, ETAL products exploits the variability of viewing angles whereas MDAL looks at the variations of solar illumination. The comparison of ETAL albedo product against MODIS and MSG/SEVIRI products over the year 2015 is instructive in many ways and shows in general a good agreement between them. The dispersion may be accounted by different factors that will be explained The additional information provided by EPS appears to be particularly beneficial for high latitudes during winter and for snow albedo.

  19. Spatial and Temporal Variability of Satellite-Derived Cloud and Surface Characteristics During FIRE-ACE

    Science.gov (United States)

    Maslanik, J. A.; Key, J.; Fowler, C. W.; Nguyen, T.; Wang, X.a

    2000-01-01

    Advanced very high resolution radiometer (AVHRR) products calculated for the western Arctic for April-July 1998 are used to investigate spatial, temporal, and regional patterns and variability in energy budget parameters associated with ocean- ice-atmosphere interactions over the Arctic Ocean during the Surface Heat Budget of the Arctic Ocean (SHEBA) project and the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment - Arctic Cloud Experiment (FIRE-ACE). The AVHRR-derived parameters include cloud fraction, clear-sky and all-sky skin temperature and broadband albedo, upwelling and downwelling shortwave and longwave radiation, cloud top pressure and temperature, and cloud optical depth. The remotely sensed products generally agree well with field observations at the SHEBA site, which in turn is shown to be representative of a surrounding region comparable in size to a climate-model grid cell. Time series of products for other locations in the western Arctic illustrate the magnitude of spatial variability during the study period and provide spatial and temporal detail useful for studying regional processes. The data illustrate the progression of reduction in cloud cover, albedo decrease, and the considerable heating of the open ocean associated with the anomalous decrease in sea ice cover in the eastern Beaufort Sea that began in late spring. Above-freezing temperatures are also recorded within the ice pack, suggesting warming of the open water areas within the ice cover.

  20. Mutual influence between climate and vegetation cover through satellite data in Egypt

    Science.gov (United States)

    El-Shirbeny, Mohammed A.; Aboelghar, Mohamed A.; Arafat, Sayed M.; El-Gindy, Abdel-Ghany M.

    2011-11-01

    The effect of vegetation cover on climatic change has not yet observed in Egypt. In the current study, Ismailia Governorate was selected as a case study to assess the impact of the vegetation cover expansion on both land surface and air temperature during twenty-eight years from 1983 to 2010. This observation site was carefully selected as a clear example for the highly rate of reclamation and vegetation expansion process in Egypt. Land Surface Temperature (LST) that were extracted from NOAA/AVHRR satellite data and air temperature (Tair) data that were collected from ground stations, were correlated with the expansion of vegetation cover that was delineated using Landsat TM and Landsat ETM+ data. The result showed that (LST) decreased by about 2.3°C while (Tair) decreased by about 1.6°C with the expansion of the cultivated land during twenty-eight years.

  1. Recent Inland Water Temperature Trends

    Science.gov (United States)

    Hook, Simon; Healey, Nathan; Lenters, John; O'Reilly, Catherine

    2016-04-01

    We are using thermal infrared satellite data in conjunction with in situ measurements to produce water temperatures for all the large inland water bodies in North America and the rest of the world for potential use as climate indicator. Recent studies have revealed significant warming of inland waters throughout the world. The observed rate of warming is - in many cases - greater than that of the ambient air temperature. These rapid, unprecedented changes in inland water temperatures have profound implications for lake hydrodynamics, productivity, and biotic communities. Scientists are just beginning to understand the global extent, regional patterns, physical mechanisms, and ecological consequences of lake warming. As part of our work we have collected thermal infrared satellite data from those satellite sensors that provide long-term and frequent spaceborne thermal infrared measurements of inland waters including ATSR, AVHRR, and MODIS and used these to examine trends in water surface temperature for approximately 169 of the largest inland water bodies in the world. We are now extending this work to generate temperature time-series of all North American inland water bodies that are sufficiently large to be studied using 1km resolution satellite data for the last 3 decades, approximately 268 lakes. These data are then being related to changes in the surface air temperature and compared with regional trends in water surface temperature derived from CMIP5/IPCC model simulations/projections to better predict future temperature changes. We will discuss the available datasets and processing methodologies together with the patterns they reveal based on recent changes in the global warming, with a particular focus on the inland waters of the southwestern USA.

  2. The multifractal structure of satellite sea surface temperature maps can be used to obtain global maps of streamlines

    Directory of Open Access Journals (Sweden)

    A. Turiel

    2009-01-01

    Full Text Available Nowadays Earth observation satellites provide information about many relevant variables of the ocean-climate system, such as temperature, moisture, aerosols, etc. However, to retrieve the velocity field, which is the most relevant dynamical variable, is still a technological challenge, specially in the case of oceans. New processing techniques, emerged from the theory of turbulent flows, have come to assist us in this task. In this paper, we show that multifractal techniques applied to new Sea Surface Temperature satellite products opens the way to build maps of ocean currents with unprecedented accuracy. With the application of singularity analysis, we show that global ocean circulation patterns can be retrieved in a daily basis. We compare these results with high-quality altimetry-derived geostrophic velocities, finding a quite good correspondence of the observed patterns both qualitatively and quantitatively. The implications of this findings from the perspective both of theory and of operational applications are discussed.

  3. Assessing regional crop water demand using a satellite-based combination equation with a land surface temperature componen

    DEFF Research Database (Denmark)

    Moyano, Carmen; Garcia, Monica; Tornos, Lucia

    2015-01-01

    consumption trends in the area. The results showed that the thermal-PT-JPL model is a suitable and simple tool requiring only air temperature and incoming solar radiation apart from standard satellites-products freely available. Our results show that in comparison with the hydrological model conceptual...... to estimate soil surface conductance based on an apparent thermal inertia index. A process-based model was applied to estimate surface energy fluxes including daily ET based on a modified version of the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model at 1km pixel resolution during a chrono......-sequence spanning for more than a decade (2002-2013). The thermal-PT-JPL model was forced with vegetation, albedo, reflectance and temperature products from the Moderate-resolution Imaging Spectroradiometer (MODIS) from both Aqua and Terra satellites. The study region, B-XII Irrigation District of the Lower...

  4. Monitoring of wildfires in boreal forests using large area AVHRR NDVI composite image data

    Energy Technology Data Exchange (ETDEWEB)

    Kasischke, E.S.; French, N.H.F. (Environmental Research Inst. of Michigan, Ann Arbor (United States)); Harrell, P.; Christensen, N.L. Jr. (Duke Univ., Durham, NC (United States)); Ustin, S.L. (Univ. of California, Davis (United States)); Barry, D. (U.S. Bureau of Land Management, Fairbanks, AK (United States))

    1993-06-01

    Normalized difference vegetation index (NDVI) composite image data, produced from AVHRR data collected in 1990, were evaluated for locating and mapping the areal extent of wildfires in the boreal forests of Alaska during that year. A technique was developed to map forest fire boundaries by subtracting a late-summer AVHRR NDVI image from an early summer scene. The locations and boundaries of wildfires within the interior region of Alaska were obtained from the Alaska Fire Service, and compared to the AVHRR-derived fire-boundary map. It was found that AVHRR detected 89.5% of all fires with sizes greater than 2,000ha with no false alarms and that, for most cases, the general shape of the fire boundary detected by AVHRR matched those mapped by field observers. However, the total area contained within the fire boundaries mapped by AVHRR were only 61% of those mapped by the field observers. However, the AVHRR data used in this study did not span the entire time period during which fires occurred, and it is believed the areal estimates could be improved significantly if an expanded AVHRR data set were used.

  5. Detección de incendios en México utilizando imágenes AVHRR (temporada 1998

    Directory of Open Access Journals (Sweden)

    José Luis Palacio-Prieto

    1999-01-01

    Full Text Available The 1998 "burning" season in Mexico was outstanding. Hurricanes, low temperatures and unexpected snowfall contributed to the disposal of large quantities of fuelgrass, shrub and wood. Based on the processing of channel 3. 120 AVHRR images from January to June 1998, an evaluation of burned areas is presented. Up to 8 147 pixels assuming the presence of fire were recorded. In order to check accuracy of band 3 derived data, 3 312 sites corresponding to fires were crossed to fires estimated from imagery. About 94% of accuracy was assessed for the map presented here.

  6. Modelling Angular Dependencies in Land Surface Temperatures From the SEVIRI Instrument onboard the Geostationary Meteosat Second Generation Satellites

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander; Pinheiro, AC; Proud, Simon Richard

    2010-01-01

    Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence on vegetat......Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence...... on vegetation structure and viewing and illumination geometry. Despite this, these effects are not considered in current operational LST products from neither polar-orbiting nor geostationary satellites. In this paper, we simulate the angular dependence that can be expected when estimating LST with the viewing...... by different land covers. The results show that the sun-target-sensor geometry plays a significant role in the estimated temperature, with variations strictly due to the angular configuration of more than ±3°C in some cases. On the continental scale, the average error is small except in hot-spot conditions...

  7. An automated processing chains for surface temperature monitoring on Earth's most active volcanoes by optical data from multiple satellites

    Science.gov (United States)

    Silvestri, Malvina; Musacchio, Massimo; Fabrizia Buongiorno, Maria

    2017-04-01

    The Geohazards Exploitation Platform, or GEP is one of six Thematic Exploitation Platforms developed by ESA to serve data user communities. As a new element of the ground segment delivering satellite results to users, these cloud-based platforms provide an online environment to access information, processing tools, computing resources for community collaboration. The aim is to enable the easy extraction of valuable knowledge from vast quantities of satellite-sensed data now being produced by Europe's Copernicus programme and other Earth observation satellites. In this context, the estimation of surface temperature on active volcanoes around the world is considered. E2E processing chains have been developed for different satellite data (ASTER, Landsat8 and Sentinel 3 missions) using thermal infrared (TIR) channels by applying specific algorithms. These chains have been implemented on the GEP platform enabling the use of EO missions and the generation of added value product such as surface temperature map, from not skilled users. This solution will enhance the use of satellite data and improve the dissemination of the results saving valuable time (no manual browsing, downloading or processing is needed) and producing time series data that can be speedily extracted from a single co-registered pixel, to highlight gradual trends within a narrow area. Moreover, thanks to the high-resolution optical imagery of Sentinel 2 (MSI), the detection of lava maps during an eruption can be automatically obtained. The proposed lava detection method is based on a contextual algorithm applied to Sentinel-2 NIR (band 8 - 0.8 micron) and SWIR (band 12 - 2.25 micron) data. Examples derived by last eruptions on active volcanoes are showed.

  8. Determining the Pixel-to-Pixel Uncertainty in Satellite-Derived SST Fields

    Directory of Open Access Journals (Sweden)

    Fan Wu

    2017-08-01

    Full Text Available The primary measure of the quality of sea surface temperature (SST fields obtained from satellite-borne infrared sensors has been the bias and variance of matchups with co-located in-situ values. Because such matchups tend to be widely separated, these bias and variance estimates are not necessarily a good measure of small scale (several pixels gradients in these fields because one of the primary contributors to the uncertainty in satellite retrievals is atmospheric contamination, which tends to have large spatial scales compared with the pixel separation of infrared sensors. Hence, there is not a good measure to use in selecting SST fields appropriate for the study of submesoscale processes and, in particular, of processes associated with near-surface fronts, both of which have recently seen a rapid increase in interest. In this study, two methods are examined to address this problem, one based on spectra of the SST data and the other on their variograms. To evaluate the methods, instrument noise was estimated in Level-2 Visible-Infrared Imager-Radiometer Suite (VIIRS and Advanced Very High Resolution Radiometer (AVHRR SST fields of the Sargasso Sea. The two methods provided very nearly identical results for AVHRR: along-scan values of approximately 0.18 K for both day and night and along-track values of 0.21 K for day and night. By contrast, the instrument noise estimated for VIIRS varied by method, scan geometry and day-night. Specifically, daytime, along-scan (along-track, spectral estimates were found to be approximately 0.05 K (0.08 K and the corresponding nighttime values of 0.02 K (0.03 K. Daytime estimates based on the variogram were found to be 0.08 K (0.10 K with the corresponding nighttime values of 0.04 K (0.06 K. Taken together, AVHRR instrument noise is significantly larger than VIIRS instrument noise, along-track noise is larger than along-scan noise and daytime levels are higher than nighttime levels. Given the similarity of

  9. Initial Validation of NDVI time seriesfrom AVHRR, VEGETATION, and MODIS

    Science.gov (United States)

    Morisette, Jeffrey T.; Pinzon, Jorge E.; Brown, Molly E.; Tucker, Jim; Justice, Christopher O.

    2004-01-01

    The paper will address Theme 7: Multi-sensor opportunities for VEGETATION. We present analysis of a long-term vegetation record derived from three moderate resolution sensors: AVHRR, VEGETATION, and MODIS. While empirically based manipulation can ensure agreement between the three data sets, there is a need to validate the series. This paper uses atmospherically corrected ETM+ data available over the EOS Land Validation Core Sites as an independent data set with which to compare the time series. We use ETM+ data from 15 globally distributed sites, 7 of which contain repeat coverage in time. These high-resolution data are compared to the values of each sensor by spatially aggregating the ETM+ to each specific sensors' spatial coverage. The aggregated ETM+ value provides a point estimate for a specific site on a specific date. The standard deviation of that point estimate is used to construct a confidence interval for that point estimate. The values from each moderate resolution sensor are then evaluated with respect to that confident interval. Result show that AVHRR, VEGETATION, and MODIS data can be combined to assess temporal uncertainties and address data continuity issues and that the atmospherically corrected ETM+ data provide an independent source with which to compare that record. The final product is a consistent time series climate record that links historical observations to current and future measurements.

  10. Analyzing the Effects of Climate Change on Sea Surface Temperature in Monitoring Coral Reef Health in the Florida Keys Using Sea Surface Temperature Data

    Science.gov (United States)

    Jones, Jason; Burbank, Renane; Billiot, Amanda; Schultz, Logan

    2011-01-01

    This presentation discusses use of 4 kilometer satellite-based sea surface temperature (SST) data to monitor and assess coral reef areas of the Florida Keys. There are growing concerns about the impacts of climate change on coral reef systems throughout the world. Satellite remote sensing technology is being used for monitoring coral reef areas with the goal of understanding the climatic and oceanic changes that can lead to coral bleaching events. Elevated SST is a well-documented cause of coral bleaching events. Some coral monitoring studies have used 50 km data from the Advanced Very High Resolution Radiometer (AVHRR) to study the relationships of sea surface temperature anomalies to bleaching events. In partnership with NOAA's Office of National Marine Sanctuaries and the University of South Florida's Institute for Marine Remote Sensing, this project utilized higher resolution SST data from the Terra's Moderate Resolution Imaging Spectroradiometer (MODIS) and AVHRR. SST data for 2000-2010 was employed to compute sea surface temperature anomalies within the study area. The 4 km SST anomaly products enabled visualization of SST levels for known coral bleaching events from 2000-2010.

  11. Rayleigh Lidar observed atmospheric temperature characteristics over a western Indian location: intercomparison with satellite observations and models

    Science.gov (United States)

    Sharma, Som; Vaishnav, Rajesh; Shukla, Krishna K.; Lal, Shyam; Chandra, Harish; Acharya, Yashwant B.

    2017-07-01

    General characteristics of sub-tropical middle atmospheric temperature structure over a high altitude station, Mt. Abu (24.5°N, 72.7°E, altitude 1670 m, above mean sea level (amsl)) are presented using about 150 nights observational datasets of Rayleigh Lidar. The monthly mean temperature contour plot shows two distinct maxima in the stratopause region ( 45-55 km), occurring during February-March and September-October, a seasonal dependence similar to that reported for mid- and high-latitudes respectively. Semi-Annual Oscillation (SAO) are stronger at an altitude 60 km in the mesospheric temperature in comparison to stratospheric region. A comparison with the satellite (Halogen Occultation Experiment, (HALOE)) data shows qualitative agreement, but quantitatively a significant difference is found between the observation and satellite. The derived temperatures from Lidar observations are warmer 2-3 K in the stratospheric region and 5-10 K in the mesospheric region than temperatures observed from the satellite. A comparison with the models, COSPAR International Reference Atmosphere (CIRA)-86 and Mass Spectrometer Incoherent Scatter Extended (MSISE)-90, showed differences of 3 K in the stratosphere and 5-10 K in the mesosphere, with deviations somewhat larger for CIRA-86. In most of the months and in all altitude regions model temperatures were lower than the Lidar observed temperature except in the altitude range of 40-50 km. MSISE-90 Model temperature overestimates as compared to Lidar temperature during December-February in the altitude region of 50-60 km. In the altitude region of 55-70 km both models deviate significantly, with differences exceeding 10-12 K, particularly during equinoctial periods. An average heating rate of 2.5 K/month during equinoxes and cooling rate of 4 K/month during November-December are found in altitude region of 50-70 km, relatively less heating and cooling rates are found in the altitude range of 30-50 km. The stratospheric

  12. Use of SSU/MSU Satellite Observations to Validate Upper Atmospheric Temperature Trends in CMIP5 Simulations

    Directory of Open Access Journals (Sweden)

    Lilong Zhao

    2015-12-01

    Full Text Available The tropospheric and stratospheric temperature trends and uncertainties in the fifth Coupled Model Intercomparison Project (CMIP5 model simulations in the period of 1979–2005 have been compared with satellite observations. The satellite data include those from the Stratospheric Sounding Units (SSU, Microwave Sounding Units (MSU, and the Advanced Microwave Sounding Unit-A (AMSU. The results show that the CMIP5 model simulations reproduced the common stratospheric cooling (−0.46–−0.95 K/decade and tropospheric warming (0.05–0.19 K/decade features although a significant discrepancy was found among the individual models being selected. The changes of global mean temperature in CMIP5 simulations are highly consistent with the SSU measurements in the stratosphere, and the temporal correlation coefficients between observation and model simulations vary from 0.6–0.99 at the 99% confidence level. At the same time, the spread of temperature mean in CMIP5 simulations increased from stratosphere to troposphere. Multiple linear regression analysis indicates that the temperature variability in the stratosphere is dominated by radioactive gases, volcanic events and solar forcing. Generally, the high-top models show better agreement with observations than the low-top model, especially in the lower stratosphere. The CMIP5 simulations underestimated the stratospheric cooling in the tropics and overestimated the cooling over the Antarctic compared to the satellite observations. The largest spread of temperature trends in CMIP5 simulations is seen in both the Arctic and Antarctic areas, especially in the stratospheric Antarctic.

  13. Comparison of Snow Albedo from MISR, MODIS and AVHRR with ground-based observations on the Greenland Ice Sheet

    Science.gov (United States)

    Stroeve, J. C.; Nolin, A.

    2001-12-01

    The surface albedo is an important climate parameter, as it controls the amount of solar radiation absorbed by the surface. For snow-covered surfaces, the albedo may be greater than 0.80, thereby allowing very little solar energy to be absorbed by the snowpack. As the snow ages and/or begins to melt, the albedo is reduced considerably, leading to enhanced absorption of solar radiation. Consequently, snow melt, comprises an unstable, positive feedback component of the climate system, which amplifies small pertubations to that system. Satellite remote sensing offers a means for measuring and monitoring the surface albedo of snow-covered areas. This study evaluates snow surface albedo retrievals from MISR, MODIS and AVHRR through comparisons with surface albedo measurements obtained in Greenland. Data from automatic weather stations, in addition to other in situ data collected during 2000 provide the ground-based measurements with which to compare coincident clear-sky satellite albedo retrievals. In general, agreements are good with the satellite data. However, satellite calibration and difficulties accurately representing the angular signature of the snow surface make it difficult to reach an albedo accuracy within 0.05.

  14. Combining MSS and AVHRR imagery to assess vegetation biomass and dynamics in an arid pastoral ecosystem, Turkana District, Kenya

    Energy Technology Data Exchange (ETDEWEB)

    Ellis, J.E.; Swift, D.M.; Hart, T.C.; Dick, O.B.

    1987-07-01

    Landsat multi-spectral scanner (MSS) imagery was used to develop a vegetation type-biomass map of the 84,000 Km/sup 2/ Turkana District, Kenya. NOAA satellite advanced very high resolution radiometry (AVHRR) imagery was overlaid on the MSS map to trace the seasonal and annual dynamics of vegetation communities used by Turkana pastoral nomads, 1981-1984. Four regions (sub-sectional territories) were compared with respect to peak herbaceous biomass, woody canopy cover, and seasonal fluxes in total green biomass. Results demonstrated major variations among regions and between wet and dry season ranges within regions. Pastoral land use patterns appear to minimize effects of seasonal vegetation fluxes on livestock herds.

  15. Coastal Geostationary Sea Surface Temperature (SST) Products from NOAA GOES and Japanese MTSAT-1R satellites, coastal United States, 2000 - present (NCEI Accession 0108128)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA's Office of Satellite and Data Distribution (OSDPD) generates geostationary sea surface temperature (SST) products. These products are derived from NOAA's...

  16. Enhancement in electron and ion temperatures due to solar flares as measured by SROSS-C2 satellite

    Directory of Open Access Journals (Sweden)

    D. K. Sharma

    2004-06-01

    Full Text Available The observations on the ionospheric electron and ion temperatures (Te and Ti measured by the RPA payload aboard the SROSS-C2 satellite have been used to study the effect of solar flares on ionospheric heating. The data on solar flare has been obtained from the National Geophysical Data Center (NGDC Boulder, Colorado (USA. It has been found that the electron and ion temperatures have a consistent enhancement during the solar flares on the dayside Earth's ionosphere. The estimated enhancement for the average electron temperature is from 1.3 to 1.9 times whereas for ion temperature it is from 1.2 to 1.4 times to the normal days average temperature. The enhancement of ionospheric temperatures due to solar flares is correlated with the diurnal variation of normal days' ionospheric temperatures. The solar flare does not have any significant effect on the nightside ionosphere. A comparison with the temperature obtained from the IRI-95 model also shows a similar enhancement.

  17. BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

    Science.gov (United States)

    Steyaert, Lou; Hall, Forrest G.; Newcomer, Jeffrey A. (Editor); Knapp, David E. (Editor); Loveland, Thomas R.; Smith, David E. (Technical Monitor)

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape

  18. Air-sea Fluxes Derived From Satellite Data: Achievements and Perspectives

    Science.gov (United States)

    Schulz, J.; Andersson, A.; Bakan, S.; Fennig, K.; Klepp, C. P.; Klocke, D.

    2007-05-01

    Time series of satellite data, suitable for retrieval of water cycle components over the ocean, approach lengths that make them attractive to be used for the analysis of inter-annual variability and trends. Additionally, they can serve as an evaluation tool for model based atmospheric reanalyses and climate models. Based on the example of the satellite-derived Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data set (HOAPS-3) the presentation will contain some comparisons to ERA40 and control runs of the ECHAM5 climate model to elucidate the current status of similarities and differences between models and observations. The HOAPS-3 data set utilized the NOAA pathfinder sea surface temperature data set and several retrieval schemes for basic variables as near-surface humidity and wind speed applicable to the series of SSM/I instruments. The data set covers a time span from 1987-2005. Satellite based data sets are constructed from a series of instruments flying on successive platforms, e.g. SSM/I on the DMSP series and AVHRR on the NOAA series. To use those data for establishing time series suitable for trend detection a very careful correction of individual instrument and satellite platform errors has to be performed. Examples for those errors are orbit decay of the satellite that changes zenith angles over time and diurnal drift of the satellite platform aliasing in the diurnal cycle. Despite the high quality of some of those corrections a inter- sensor homogenization to a reference platform is unavoidable. The presentation will give a short review on used techniques and their advantages and disadvantages. Finally, the presentation will discuss the idea to use infrared sounding data from the IASI instrument on the MetOp satellite to improve current near-surface humidity and temperature retrievals and ways to include error information to the data sets.

  19. Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites.

    Science.gov (United States)

    Yan, Wai Yeung; Mahendrarajah, Prathees; Shaker, Ahmed; Faisal, Kamil; Luong, Robin; Al-Ahmad, Mohamed

    2014-12-01

    This studypresents a remote sensing application of using time series Landsat satellite images for monitoring the Trail Road and Nepean municipal solid waste (MSW) disposal sites in Ottawa, Ontario, Canada. Currently, the Trail Road landfill is in operation; however, during the 1960s and 1980s, the city relied heavily on the Nepean landfill. More than 400 Landsat satellite images were acquired from the US Geological Survey (USGS) data archive between 1984 and 2011. Atmospheric correction was conducted on the Landsat images in order to derive the landfill sites' land surface temperature (LST). The findings unveil that the average LST of the landfill was always higher than the immediate surrounding vegetation and air temperature by 4 to 10 °C and 5 to 11.5 °C, respectively. During the summer, higher differences of LST between the landfill and its immediate surrounding vegetation were apparent, while minima were mostly found in fall. Furthermore, there was no significant temperature difference between the Nepean landfill (closed) and the Trail Road landfill (active) from 1984 to 2007. Nevertheless, the LST of the Trail Road landfill was much higher than the Nepean by 15 to 20 °C after 2007. This is mainly due to the construction and dumping activities (which were found to be active within the past few years) associated with the expansion of the Trail Road landfill. The study demonstrates that the use of the Landsat data archive can provide additional and viable information for the aid of MSW disposal site monitoring.

  20. Evaluation of HCMM satellite data for estuarine tidal circulation patterns and thermal inertia soil moisture measurements. [Delaware Bay, Cooper River, and the Potomac River estuaries; Luverne, Minnesota, soil moisture, and water temperature of Lake Anna, Virginia

    Science.gov (United States)

    Wiesnet, D. R.; Mcginnis, D. F., Jr. (Principal Investigator); Matson, M.; Pritchard, J. A.

    1981-01-01

    Digital thermal maps of the Cooper River (SC) and the Potomac River estuaries were prepared from heat capacity mapping radiometer (HCMR) tapes. Tidal phases were correctly interpreted and verified. Synoptic surface circulation patterns were charted by location thermal fronts and water mass boundaries within the estuaries. Thermal anomalies were detected adjacent of a conventional power plant on the Potomac. Under optimum conditions, estuaries as small as the Cooper River can be monitored for generalized thermal/tidal circulation patterns by the HCMM-type IR sensors. The HCMM thermal inertia approach to estimating soil moisture at the Luverne (MN) test site was found to be unsatisfactory as a NESS operational satellite technique because of cloud cover interference. Thermal-IR data show similar structure of the Baltimore and Washington heat islands when compared to NOAA AVHRR thermal-IR data. Thermal anomalies from the warm water discharge water of a nuclear power plant were mapped in Lake Anna, Virginia.

  1. SST, NOAA POES AVHRR, GAC, 0.1 degrees, Global, Day and Night

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides sea surface temperature (SST) products derived from NOAA's Polar Operational Environmental Satellites (POES). This data provides global area...

  2. SST, NOAA POES AVHRR, GAC, 0.1 degrees, Global, Day and Night

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides sea surface temperature (SST) products derived from NOAA's Polar Operational Environmental Satellites (POES). This data provides global...

  3. SST, NOAA POES AVHRR, GAC, 0.1 degrees, Global, Day and Night

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides sea surface temperature (SST) products derived from NOAA's Polar Operational Environmental Satellites (POES). This data provides global area...

  4. SST, NOAA POES AVHRR, LAC, 0.0125 degrees, West US, Daytime

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides sea surface temperature (SST) products derived from NOAA's Polar Operational Environmental Satellites (POES). This data is provided at high...

  5. SST, NOAA POES AVHRR, LAC, 0.0125 degrees, West US, Nighttime

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides sea surface temperature (SST) products derived from NOAA's Polar Operational Environmental Satellites (POES). This data is provided at high...

  6. SST, NOAA POES AVHRR, LAC, 0.0125 degrees, Alaska, Daytime

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides sea surface temperature (SST) products derived from NOAA's Polar Operational Environmental Satellites (POES). This data is provided at high...

  7. SST, NOAA POES AVHRR, LAC, 0.0125 degrees, West US, Day and Night

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides sea surface temperature (SST) products derived from NOAA's Polar Operational Environmental Satellites (POES). This data is provided at high...

  8. SST, NOAA POES AVHRR, LAC, 0.0125 degrees, Alaska, Day and Night

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides sea surface temperature (SST) products derived from NOAA's Polar Operational Environmental Satellites (POES). This data is provided at high...

  9. SST, NOAA POES AVHRR, LAC, 0.0125 degrees, West US, Day and Night

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides sea surface temperature (SST) products derived from NOAA's Polar Operational Environmental Satellites (POES). This data is provided at high...

  10. AVHRR CoastWatch Alaska Regional Node Data, April 1991-March 2004 (NODC Accession 0121315)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The sea surface temperature (SST) products were derived from NOAA's Polar-orbiting Operational Environmental Satellites (POES) for the coastal United States and...

  11. AVHRR CoastWatch Caribbean Regional Node Data, May 1991-March 2004 (NODC Accession 0121316)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The sea surface temperature (SST) products were derived from NOAA's Polar-orbiting Operational Environmental Satellites (POES) for the coastal United States and...

  12. AVHRR CoastWatch East Coast Regional Node Data, May 1991-March 2004 (NODC Accession 0121320)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The sea surface temperature (SST) products were derived from NOAA's Polar-orbiting Operational Environmental Satellites (POES) for the coastal United States and...

  13. AVHRR CoastWatch West Coast Regional Node Data, November 1991-March 2004 (NODC Accession 0121322)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The sea surface temperature (SST) products were derived from NOAA's Polar-orbiting Operational Environmental Satellites (POES) for the coastal United States and...

  14. AVHRR CoastWatch Great Lakes Regional Node Data, May 1991-March 2004 (NODC Accession 0121318)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The sea surface temperature (SST) products were derived from NOAA's Polar-orbiting Operational Environmental Satellites (POES) for the coastal United States and...

  15. AVHRR CoastWatch Southeast Regional Node Data, February 1989-March 2004 (NODC Accession 0121321)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The sea surface temperature (SST) products were derived from NOAA's Polar-orbiting Operational Environmental Satellites (POES) for the coastal United States and...

  16. Spatial variability of the Black Sea surface temperature from high resolution modeling and satellite measurements

    Science.gov (United States)

    Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady

    2016-04-01

    Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)

  17. Effect of temperature on the pathogenesis, accumulation of viral and satellite RNAs and on plant proteome in peanut stunt virus and satellite RNA-infected plants

    Directory of Open Access Journals (Sweden)

    Aleksandra eObrępalska-Stęplowska

    2015-10-01

    Full Text Available Temperature is an important environmental factor influencing plant development in natural and diseased conditions. The growth rate of plants grown at 27°C is more rapid than for plants grown at 21°C. Thus, temperature affects the rate of pathogenesis progression in individual plants. We have analyzed the effect of temperature conditions (either 21°C or 27°C during the day on the accumulation rate of the virus and satellite RNA (satRNA in Nicotiana benthamiana plants infected by peanut stunt virus (PSV with and without its satRNA, at four time points. In addition, we extracted proteins from PSV and PSV+satRNA-infected plants harvested at 21 dpi, when disease symptoms began to appear on plants grown at 21°C and were well developed on those grown at 27°C, to assess the proteome profile in infected plants compared to mock-inoculated plants grown at these two temperatures, using 2D-gel electrophoresis and mass spectrometry approaches. The accumulation rate of the viral RNAs and satRNA was more rapid at 27°C at the beginning of the infection and then rapidly decreased in PSV-infected plants. At 21 dpi, PSV and satRNA accumulation was higher at 21°C and had a tendency to increase further. In all studied plants grown at 27°C, we observed a significant drop in the identified proteins participating in photosynthesis and carbohydrate metabolism at the proteome level, in comparison to plants maintained at 21°C. On the other hand, the proteins involved in protein metabolic processes were all more abundant in plants grown at 27°C. This was especially evident when PSV-infected plants were analyzed, where increase in abundance of proteins involved in protein synthesis, degradation, and folding was revealed. In mock-inoculated and PSV-infected plants we found an increase in abundance of the majority of stress-related differently-regulated proteins and those associated with protein metabolism. In contrast, in PSV+satRNA-infected plants the shift in the

  18. Analysis of trends in fused AVHRR and MODIS NDVI data for 1982-2006: Indication for a CO2 fertilization effect in global vegetation

    Science.gov (United States)

    Los, S. O.

    2013-04-01

    Recent studies report an increase in vegetation greenness in mid-to-high northern latitudes. This increase is observed in leaf-out data in Europe and North America since the 1950s and in satellite data since the 1980s. Increased vegetation greenness is potentially a factor contributing to a land CO2 sink. Various causes for increased vegetation greenness are suggested, but their relative importance is uncertain. In the present study, the effect of climate and CO2 fertilization on increased vegetation greenness and the land CO2 sink are investigated. The study is organized as follows: (1) A model is used to simulate monthly global normalized difference vegetation index (NDVI) fields for 1901-2006. The model is derived from NDVI, precipitation, and temperature data for 1982-1999. The modeled fields, referred to as reconstructed vegetation index (RVI), are tested back in time on phenological data (1950s-1990s) and forward in time on Moderate Resolution Imaging Spectrometer (MODIS) data (2001-2006). The RVI represents the response of NDVI to variations in climate. (2) Residuals between RVI and NDVI are analyzed for associations with variations in downwelling solar radiation, nitrogen deposition, satellite-related artifacts, and CO2 fertilization. CO2 fertilization was the only factor that improved RVI modeling. (3) The effect of climate variations and CO2 fertilization on the land CO2 sink, as manifested in the RVI, is explored with the Carnegie Ames Stanford Assimilation (CASA) model. Climate (temperature and precipitation) and CO2 fertilization each explain approximately 40% of the observed global trend in NDVI for 1982-2006. For 1901-2006, estimated trends in NDVI related to CO2 fertilization are four to five times larger than climate-related trends. CASA simulations indicate that the CO2 fertilization effect on vegetation greenness contributes about 0.7 Pg C per year to the recent land CO2 sink. This is a conservative estimate and is likely larger. This effect of

  19. SST Anomaly, NOAA POES AVHRR, Casey and Cornillon Climatology, 0.1 degrees, Global

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch distributes SST anomaly data using a combination of the POES AVHRR Global Area Coverage data, and data from a climatological database by Casey and...

  20. AVHRR Global 1K = Advanced Very High Resolution Radiometer Mosaics 1995 - 1996

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The global land 1-km data set project represents an international effort to acquire, archive, process, and distribute 1-km AVHRR data of the entire global land...

  1. AVHRR Composites = Advanced Very High Resolution Radiometer U.S. Alaska: 1989 - Present

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Normalized Difference Vegetation Index (NDVI) Composites are produced from multiple Advanced Very High Resolution Radiometer (AVHRR) daily observations that have...

  2. AVHRR Global 1K = Advanced Very High Resolution Radiometer Mosaics 1995 - 1996

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The global land 1-km data set project represents an international effort to acquire, archive, process, and distribute 1-km AVHRR data of the entire global land...

  3. NOAA Climate Data Record (CDR) of AVHRR Polar Pathfinder Extended (APP-X) Cryosphere

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Climate Data Record (CDR) of the extended AVHRR Polar Pathfinder (APP-x) cryosphere contains 19 geophysical variables over the Arctic and Antarctic for the...

  4. Advective surface velocity in the north west Pacific derived from NOAA AVHRR images

    Digital Repository Service at National Institute of Oceanography (India)

    Pankajakshan, T.; Akiyama, M.; Okada, Y.; Sugimori, Y.

    Using sequential AVHRR images in November 1983, nearsurface advective velocities are derived in the region Kuroshio south of Japan. For deriving the velocities two methods are used. One is the Method of Cross Correlation (MCC), using image pair...

  5. SST Anomaly, NOAA POES AVHRR, Casey and Cornillon Climatology, 0.1 degrees, Global

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch distributes SST anomaly data using a combination of the POES AVHRR Global Area Coverage data, and data from a climatological database by Casey and...

  6. GHRSST Level 2P Eastern Pacific Regional Skin Sea Surface Temperature from the Geostationary Operational Environmental Satellites (GOES) Imager on the GOES-11 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Geostationary Operational Environmental Satellites (GOES) operated by the United States National Oceanic and Atmospheric Administration (NOAA) support weather...

  7. GHRSST Level 2P West Atlantic Regional Skin Sea Surface Temperature from the Geostationary Operational Environmental Satellites (GOES) Imager on the GOES-12 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Geostationary Operational Environmental Satellites (GOES) operated by the United States National Oceanic and Atmospheric Administration (NOAA) support weather...

  8. Validation of JAXA/MODIS Sea Surface Temperature in Water around Taiwan Using the Terra and Aqua Satellites

    Directory of Open Access Journals (Sweden)

    Ming-An Lee

    2010-01-01

    Full Text Available The research vessel-based Conductivity Temperature Depth profiler (CTD provides underwater measurements of the bulk sea surface temperature (SST at the depths of shallower than 5 m. The CTD observations of the seas around Taiwan provide useful data for comparison with SST of MODIS (Moderate Resolution Imaging Spectroradiometers aboard Aqua and Terra satellites archived by JAXA (Japan Aerospace Exploration Agency. We produce a high-resolution (1 km MODIS SST by using Multi-Channel SST (MCSST algorithm. There were 1516 cloud-free match-up data pairs of MODIS SST and in situ measurements during the period from 2003 - 2005. The difference of the root mean square error (RMSE of satellite observations from each platform during the day and at night was: _ in Aqua daytime, _ in Aqua nighttime, _ in Terra daytime, and _ in Terra nighttime. The total analysis of MODIS-derived SST shows good agreement with a bias of _ and RMSE of _ The analyses indicate that the bias of Aqua daytime was always positive throughout the year and the large RMSE should be attributed to the large positive bias _ under diurnal warming. It was also found that the bias of Terra daytime was usually negative with a mean bias of _ its large RMSE should be treated with care because of low solar radiation in the morning.

  9. The multifractal structure of satellite sea surface temperature maps can be used to obtain global maps of streamlines

    Directory of Open Access Journals (Sweden)

    A. Turiel

    2009-10-01

    Full Text Available Nowadays Earth observation satellites provide information about many relevant variables of the ocean-climate system, such as temperature, moisture, aerosols, etc. However, to retrieve the velocity field, which is the most relevant dynamical variable, is still a technological challenge, specially in the case of oceans. New processing techniques, emerged from the theory of turbulent flows, have come to assist us in this task. In this paper, we show that multifractal techniques applied to new Sea Surface Temperature satellite products opens the way to build maps of ocean currents with unprecedented accuracy. With the application of singularity analysis, we show that global ocean circulation patterns can be retrieved in a daily basis. We compare these results with high-quality altimetry-derived geostrophic velocities, finding a quite good correspondence of the observed patterns both qualitatively and quantitatively; and this is done for the first time on a global basis, even for less active areas. The implications of this findings from the perspective both of theory and of operational applications are discussed.

  10. Estimation of net photosynthetically available radiation over oceans from satellite data - Application to a dynamical model of a plankton bloom in the Atlantic Ocean

    Energy Technology Data Exchange (ETDEWEB)

    Bauer, P.; Gaito, S.; Mcglade, J.M.; Winter, D. (Marine Spill Response Corp., Washington, DC (United States) Michigan Environmental Research Inst., Ann Arbor (United States))

    1993-03-01

    A radiative transport model has been developed for the simulation of photosynthetically available radiation (PAR) flux density transfer in clear and cloudy atmospheres. Vertical profiles of temperature, pressure, and atmospheric constituents by globally distributed radiosonde measurements with multiple cloud layers of different types and fractional coverages are used to represent the natural variability of clear and cloudy atmospheres. The resulting retrievals show standard errors less than 35 W/sq m for cloudy scenes and 5 W/sq m for clear skies. The regression algorithms were applied to NOAA AVHRR satellite measurements and compared to simultaneously recorded shipborne data logs during a cruise of the UK research vessel Charles Darwin in May 1990 in the north Atlantic. The impact of the satellite net PAR maps on two-dimensional dynamical phytoplankton modeling is described. 19 refs.

  11. Modelling dengue fever risk in the State of Yucatan, Mexico using regional-scale satellite-derived sea surface temperature.

    Science.gov (United States)

    Laureano-Rosario, Abdiel E; Garcia-Rejon, Julian E; Gomez-Carro, Salvador; Farfan-Ale, Jose A; Muller-Karger, Frank E

    2017-08-01

    Accurately predicting vector-borne diseases, such as dengue fever, is essential for communities worldwide. Changes in environmental parameters such as precipitation, air temperature, and humidity are known to influence dengue fever dynamics. Furthermore, previous studies have shown how oceanographic variables, such as El Niño Southern Oscillation (ENSO)-related sea surface temperature from the Pacific Ocean, influences dengue fever in the Americas. However, literature is lacking on the use of regional-scale satellite-derived sea surface temperature (SST) to assess its relationship with dengue fever in coastal areas. Data on confirmed dengue cases, demographics, precipitation, and air temperature were collected. Incidence of weekly dengue cases was examined. Stepwise multiple regression analyses (AIC model selection) were used to assess which environmental variables best explained increased dengue incidence rates. SST, minimum air temperature, precipitation, and humidity substantially explained 42% of the observed variation (r(2)=0.42). Infectious diseases are characterized by the influence of past cases on current cases and results show that previous dengue cases alone explained 89% of the variation. Ordinary least-squares analyses showed a positive trend of 0.20±0.03°C in SST from 2006 to 2015. An important element of this study is to help develop strategic recommendations for public health officials in Mexico by providing a simple early warning capability for dengue incidence. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Comparative Analysis of Sea Surface Temperature Pattern in the Eastern and Western Gulfs of Arabian Sea and the Red Sea in Recent Past Using Satellite Data

    Directory of Open Access Journals (Sweden)

    Neha Nandkeolyar

    2013-01-01

    Full Text Available With unprecedented rate of development in the countries surrounding the gulfs of the Arabian Sea, there has been a rapid warming of these gulfs. In this regard, using Advanced Very High Resolution Radiometer (AVHRR data from 1985 to 2009, a climatological study of Sea Surface Temperature (SST and its inter annual variability in the Persian Gulf (PG, Gulf of Oman (GO, Gulf of Aden (GA, Gulf of Kutch (KTCH, Gulf of Khambhat (KMBT, and Red Sea (RS was carried out using the normalized SST anomaly index. KTCH, KMBT, and GA pursued the typical Arabian Sea basin bimodal SST pattern, whereas PG, GO, and RS followed unimodal SST curve. In the western gulfs and RS, from 1985 to 1991-1992, cooling was observed followed by rapid warming phase from 1993 onwards, whereas in the eastern gulfs, the phase of sharp rise of SST was observed from 1995 onwards. Strong influence of the El Niño and La Niña and the Indian Ocean Dipole on interannual variability of SST of gulfs was observed. Annual and seasonal increase of SST was lower in the eastern gulfs than the western gulfs. RS showed the highest annual increase of normalized SST anomaly (+0.64/decade followed by PG (+0.4/decade.

  13. Multi-Temporal Evaluation of Soil Moisture and Land Surface Temperature Dynamics Using in Situ and Satellite Observations

    Directory of Open Access Journals (Sweden)

    Miriam Pablos

    2016-07-01

    Full Text Available Soil moisture (SM is an important component of the Earth’s surface water balance and by extension the energy balance, regulating the land surface temperature (LST and evapotranspiration (ET. Nowadays, there are two missions dedicated to monitoring the Earth’s surface SM using L-band radiometers: ESA’s Soil Moisture and Ocean Salinity (SMOS and NASA’s Soil Moisture Active Passive (SMAP. LST is remotely sensed using thermal infrared (TIR sensors on-board satellites, such as NASA’s Terra/Aqua MODIS or ESA & EUMETSAT’s MSG SEVIRI. This study provides an assessment of SM and LST dynamics at daily and seasonal scales, using 4 years (2011–2014 of in situ and satellite observations over the central part of the river Duero basin in Spain. Specifically, the agreement of instantaneous SM with a variety of LST-derived parameters is analyzed to better understand the fundamental link of the SM–LST relationship through ET and thermal inertia. Ground-based SM and LST measurements from the REMEDHUS network are compared to SMOS SM and MODIS LST spaceborne observations. ET is obtained from the HidroMORE regional hydrological model. At the daily scale, a strong anticorrelation is observed between in situ SM and maximum LST (R ≈ − 0.6 to −0.8, and between SMOS SM and MODIS LST Terra/Aqua day (R ≈ − 0.7. At the seasonal scale, results show a stronger anticorrelation in autumn, spring and summer (in situ R ≈ − 0.5 to −0.7; satellite R ≈ − 0.4 to −0.7 indicating SM–LST coupling, than in winter (in situ R ≈ +0.3; satellite R ≈ − 0.3 indicating SM–LST decoupling. These different behaviors evidence changes from water-limited to energy-limited moisture flux across seasons, which are confirmed by the observed ET evolution. In water-limited periods, SM is extracted from the soil through ET until critical SM is reached. A method to estimate the soil critical SM is proposed. For REMEDHUS, the critical SM is estimated to be ∼0

  14. Retrieval of sea surface air temperature from satellite data over Indian Ocean: An empirical approach

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.; Muraleedharan, P.M.

    the surface air temperature and surface humidity is analysed by fitting a polynomial between the two for different regions of the Indian Ocean in different seasons. Taking into account the variation in surface air temperatures, the Indian Ocean is split in 14...

  15. Chronic effects of temperature on mortality in the Southeastern USA using satellite-based exposure metrics

    Science.gov (United States)

    Shi, Liuhua; Liu, Pengfei; Wang, Yan; Zanobetti, Antonella; Kosheleva, Anna; Koutrakis, Petros; Schwartz, Joel

    2016-07-01

    Climate change may affect human health, particularly for elderly individuals who are vulnerable to temperature changes. While many studies have investigated the acute effects of heat, only a few have dealt with the chronic ones. We have examined the effects of seasonal temperatures on survival of the elderly in the Southeastern USA, where a large fraction of subpopulation resides. We found that both seasonal mean temperature and its standard deviation (SD) affected long-term survival among the 13 million Medicare beneficiaries (aged 65+) in this region during 2000-2013. A 1 °C increase in summer mean temperature corresponded to an increase of 2.5% in death rate. Whereas, 1 °C increase in winter mean temperature was associated with a decrease of 1.5%. Increases in seasonal temperature SD also influence mortality. We decomposed seasonal mean temperature and its temperature SD into long-term geographic contrasts between ZIP codes and annual anomalies within ZIP code. Effect modifications by different subgroups were also examined to find out whether certain individuals are more vulnerable. Our findings will be critical to future efforts assessing health risks related to the future climate change.

  16. A study on the Abruzzo 6 April 2009 earthquake by applying the RST approach to 15 years of AVHRR TIR observations

    Directory of Open Access Journals (Sweden)

    M. Lisi

    2010-02-01

    Full Text Available A self adaptive approach (RST, Robust Satellite Technique has been proposed as a suitable tool for satellite TIR surveys in seismically active regions devoted to detect and monitor thermal anomalies possibly related to earthquake occurrence. In this work, RST approach has been applied to 15 years of AVHRR (Advanced Very High Resolution Radiometer thermal infrared observations in order to study the 6 April 2009 Abruzzo earthquake. Preliminary results show clear differences in TIR anomalies occurrence during the periods used for validation (15 March–15 April 2009 and the one (15 March–15 April 2008 without earthquakes with ML≥4.5, used for confutation purposes. Quite clear TIR anomalies appears also to mark main tectonic lineaments during the preparatory phases of others, low magnitude(3.9<ML<4.6 earthquakes, occurred in the area in the same period.

  17. Utilization of satellite-derived estimates of meteorological and land surface characteristics in the Land Surface Model for vast agricultural region territory

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena

    2015-04-01

    The method has been elaborated to evaluate the water and heat regime characteristics of the territory on a regional scale for the vegetation season based on a physical-mathematical model of water and heat exchange between vegetation covered land surface and atmosphere (LSM, Land Surface Model) appropriate for using satellite information on land surface and meteorological conditions. The developed model is intended for calculating soil water content, evapotranspiration (evaporation from bare soil and transpiration by vegetation), vertical water and heat fluxes as well as land surface and vegetation cover temperatures and vertical distributions of temperature and moisture in the active soil layer. Parameters of the model are soil and vegetation characteristics and input variables are meteorological characteristics. Their values have been obtained from ground-based observations at agricultural meteorological stations and satellite-based measurements by scanning radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua and SEVIRI (geostationary satellites Meteosat-9, -10). The AVHRR data have been used to build the estimates of three types of land surface temperature (LST): land skin temperature Tsg, air temperature at a level of vegetation cover Ta and efficient radiation temperature Tseff, emissivity E, normalized vegetation index NDVI, vegetation cover fraction B, leaf area index LAI, and precipitation. The set of estimates derived from MODIS data has comprised values of LST Tls, E, NDVI and LAI. The SEVIRI-based retrievals have included Tls, Ta, Е at daylight and nighttime, LAI (daily) and precipitation. The case study has been carried out for agricultural Central Black Earth region of the European Russia of 227,300 sq.km containing 7 regions of the Russian Federation for years 2009-2013 vegetation seasons. Estimates of described characteristics have been built with the help of the developed original and improved pre-existing methods and technologies of thematic processing

  18. Geo-spatial distribution of cloud cover and influence of cloud induced attenuation and noise temperature on satellite signal propagation over Nigeria

    Science.gov (United States)

    Ojo, Joseph Sunday

    2017-05-01

    The study of the influence of cloud cover on satellite propagation links is becoming more demanding due to the requirement of larger bandwidth for different satellite applications. Cloud attenuation is one of the major factors to consider for optimum performance of Ka/V and other higher frequency bands. In this paper, the geo-spatial distribution of cloud coverage over some chosen stations in Nigeria has been considered. The substantial scale spatial dispersion of cloud cover based on synoptic meteorological data and the possible impact on satellite communication links at higher frequency bands was also investigated. The investigation was based on 5 years (2008-2012) achieved cloud cover data collected by the Nigerian Meteorological Agency (NIMET) Federal Ministry of Aviation, Oshodi Lagos over four synoptic hours of the day covering day and night. The performances of satellite signals as they traverse through the cloud and cloud noise temperature at different seasons and over different hours of days at Ku/W-bands frequency are also examined. The overall result shows that the additional total atmospheric noise temperature due to the clear air effect and the noise temperature from the cloud reduces the signal-to-noise ratio of the satellite receiver systems, leading to more signal loss and if not adequately taken care of may lead to significant outage. The present results will be useful for Earth-space link budgeting, especially for the proposed multi-sensors communication satellite systems in Nigeria.

  19. Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate

    Science.gov (United States)

    Wang, Lei; Sun, Litao; Shrestha, Maheswor; Li, Xiuping; Liu, Wenbin; Zhou, Jing; Yang, Kun; Lu, Hui; Chen, Deliang

    2016-10-01

    In distributed hydrological modeling, surface air temperature (Tair) is of great importance in simulating cold region processes, while the near-surface-air-temperature lapse rate (NLR) is crucial to prepare Tair (when interpolating Tair from site observations to model grids). In this study, a distributed biosphere hydrological model with improved snow physics (WEB-DHM-S) was rigorously evaluated in a typical cold, large river basin (e.g., the upper Yellow River basin), given a mean monthly NLRs. Based on the validated model, we have examined the influence of the NLR on the simulated snow processes and streamflows. We found that the NLR has a large effect on the simulated streamflows, with a maximum difference of greater than 24% among the various scenarios for NLRs considered. To supplement the insufficient number of monitoring sites for near-surface-air-temperature at developing/undeveloped mountain regions, the nighttime Moderate Resolution Imaging Spectroradiometer land surface temperature is used as an alternative to derive the approximate NLR at a finer spatial scale (e.g., at different elevation bands, different land covers, different aspects, and different snow conditions). Using satellite-based estimation of NLR, the modeling of snow processes has been greatly refined. Results show that both the determination of rainfall/snowfall and the snowpack process were significantly improved, contributing to a reduced summer evapotranspiration and thus an improved streamflow simulation.

  20. Impact of temperature on childhood pneumonia estimated from satellite remote sensing.

    Science.gov (United States)

    Xu, Zhiwei; Liu, Yang; Ma, Zongwei; Li, Shenghui; Hu, Wenbiao; Tong, Shilu

    2014-07-01

    The effect of temperature on childhood pneumonia in subtropical regions is largely unknown so far. This study examined the impact of temperature on childhood pneumonia in Brisbane, Australia. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model was used to quantify the main effect of temperature on emergency department visits (EDVs) for childhood pneumonia in Brisbane from 2001 to 2010. The model residuals were checked to identify added effects due to heat waves or cold spells. Both high and low temperatures were associated with an increase in EDVs for childhood pneumonia. Children aged 2-5 years, and female children were particularly vulnerable to the impacts of heat and cold, and Indigenous children were sensitive to heat. Heat waves and cold spells had significant added effects on childhood pneumonia, and the magnitude of these effects increased with intensity and duration. There were changes over time in both the main and added effects of temperature on childhood pneumonia. Children, especially those female and Indigenous, should be particularly protected from extreme temperatures. Future development of early warning systems should take the change over time in the impact of temperature on children's health into account.

  1. Retrieval of humidity and temperature profiles over the oceans from INSAT 3D satellite radiances

    Indian Academy of Sciences (India)

    C Krishnamoorthy; Deo Kumar; C Balaji

    2016-03-01

    In this study, retrieval of temperature and humidity profiles of atmosphere from INSAT 3D-observed radiances has been accomplished. As the first step, a fast forward radiative transfer model using an Artificial neural network has been developed and it was proven to be highly effective, giving a correlationcoefficient of 0.97. In order to develop this, a diverse set of physics-based clear sky profiles of pressure (P), temperature (T) and specific humidity (q) has been developed. The developed database was further used for geophysical retrieval experiments in two different frameworks, namely, an ANN and Bayesianestimation. The neural network retrievals were performed for three different cases, viz., temperature only retrieval, humidity only retrieval and combined retrieval. The temperature/humidity only ANN retrievals were found superior to combined retrieval using an ANN. Furthermore, Bayesian estimation showed superior results when compared with the combined ANN retrievals.

  2. Low temperature testing and neutron irradiation of a swept charge device on board the HXMT satellite

    Institute of Scientific and Technical Information of China (English)

    WANG Yu-Sa; CHEN Tian-Xiang; LI Cheng-Kui; HUO Jia; LI Zheng-Wei; LI Wei; HU Wei; ZHANG Yi; LU Bo; ZHU Yue; LIU Yan; CHEN Yong; WU Di; SUN Qing-Rong; ZHANG Zi-Liang; XU Yu-Peng; YANG Yan-Ji; CUI Wei-Wei; LI Mao-Shun; LIU Xiao-Yan; WANG Juan; HAN Da-Wei

    2012-01-01

    We present the low temperature testing of an SCD detector,investigating its performance such as readout noise,energy resolution at 5.9 keV and dark current.The SCD's performance is closely related to temperature,and the temperature range of -80 ℃ to -50 ℃ is the best choice,where the FWHM at 5.9 keV is about 130 eV.The influence of the neutron irradiation from an electrostatic accelerator with fluence up to 1 × 109 cm-2 has been examined.We find the SCD is not vulnerable to neutron irradiation.The detailed operations of the SCD and the test results of low temperature are reported,and the results of neutron irradiation are discussed.

  3. Comparison of stratospheric temperature profiles from a ground-based microwave radiometer with lidar, radiosonde and satellite data

    Science.gov (United States)

    Navas-Guzmán, Francisco; Kämpfer, Niklaus; Haefele, Alexander; Keckhut, Philippe; Hauchecorne, Alain

    2015-04-01

    The importance of the knowledge of the temperature structure in the atmosphere has been widely recognized. Temperature is a key parameter for dynamical, chemical and radiative processes in the atmosphere. The cooling of the stratosphere is an indicator for climate change as it provides evidence of natural and anthropogenic climate forcing just like surface warming ( [1] and references therein). However, our understanding of the observed stratospheric temperature trend and our ability to test simulations of the stratospheric response to emissions of greenhouse gases and ozone depleting substances remains limited. Stratospheric long-term datasets are sparse and obtained trends differ from one another [1]. Therefore it is important that in the future such datasets are generated. Different techniques allow to measure stratospheric temperature profiles as radiosonde, lidar or satellite. The main advantage of microwave radiometers against these other instruments is a high temporal resolution with a reasonable good spatial resolution. Moreover, the measurement at a fixed location allows to observe local atmospheric dynamics over a long time period, which is crucial for climate research. TEMPERA (TEMPERature RAdiometer) is a newly developed ground-based microwave radiometer designed, built and operated at the University of Bern. The instrument and the retrieval of temperature profiles has been described in detail in [2]. TEMPERA is measuring a pressure broadened oxygen line at 53.1 GHz in order to determine stratospheric temperature profiles. The retrieved profiles of TEMPERA cover an altitude range of approximately 20 to 45 km with a vertical resolution in the order of 15 km. The lower limit is given by the instrumental baseline and the bandwidth of the measured spectrum. The upper limit is given by the fact that above 50 km the oxygen lines are splitted by the Zeeman effect in the terrestrial magnetic field. In this study we present a comparison of stratospheric

  4. Analysing the Effects of Different Land Cover Types on Land Surface Temperature Using Satellite Data

    Science.gov (United States)

    Şekertekin, A.; Kutoglu, Ş. H.; Kaya, S.; Marangoz, A. M.

    2015-12-01

    Monitoring Land Surface Temperature (LST) via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES) Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

  5. ANALYSING THE EFFECTS OF DIFFERENT LAND COVER TYPES ON LAND SURFACE TEMPERATURE USING SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    A. Şekertekin

    2015-12-01

    Full Text Available Monitoring Land Surface Temperature (LST via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

  6. Wind-driven changes of surface current, temperature, and chlorophyll observed by satellites north of New Guinea

    Science.gov (United States)

    Radenac, Marie-Hélène; Léger, Fabien; Messié, Monique; Dutrieux, Pierre; Menkes, Christophe; Eldin, Gérard

    2016-04-01

    Satellite observations of wind, sea level and derived currents, sea surface temperature (SST), and chlorophyll are used to expand our understanding of the physical and biological variability of the ocean surface north of New Guinea. Based on scarce cruise and mooring data, previous studies differentiated a trade wind situation (austral winter) when the New Guinea Coastal Current (NGCC) flows northwestward and a northwest monsoon situation (austral summer) when a coastal upwelling develops and the NGCC reverses. This circulation pattern is confirmed by satellite observations, except in Vitiaz Strait where the surface northwestward flow persists. We find that intraseasonal and seasonal time scale variations explain most of the variance north of New Guinea. SST and chlorophyll variabilities are mainly driven by two processes: penetration of Solomon Sea waters and coastal upwelling. In the trade wind situation, the NGCC transports cold Solomon Sea waters through Vitiaz Strait in a narrow vein hugging the coast. Coastal upwelling is generated in westerly wind situations (westerly wind event, northwest monsoon). Highly productive coastal waters are advected toward the equator and, during some westerly wind events, toward the eastern part of the warm pool. During El Niño, coastal upwelling events and northward penetration of Solomon Sea waters combine to influence SST and chlorophyll anomalies.

  7. Modeling Agricultural Crop Production in China using AVHRR-based Vegetation Health Indices

    Science.gov (United States)

    Yang, B.; Kogan, F.; Guo, W.; Zhiyuan, P.; Xianfeng, J.

    Weather related crop losses have always been a concern for farmers On a wider scale it has always influenced decision of Governments traders and other policy makers for the purpose of balanced food supplies trade and distribution of aid to the nations in need Therefore national policy and decision makers are giving increasing importance to early assessment of crop losses in response to weather fluctuations This presentation emphasizes utility of AVHRR-based Vegetation health index VHI for early warning of drought-related losses of agricultural production in China The VHI is a three-channel index characterizing greenness vigor and temperature of land surface which can be used as proxy for estimation of how healthy and potentially productive could be vegetation China is the largest in the world producer of grain including wheat and rice and cotton In the major agricultural areas China s crop production is very dependent on weather The VHI being a proxy indicator of weather impact on vegetation showed some correlation with productivity of agricultural crops during the critical period of their development The periods of the strongest correlation were investigated and used to build regression models where crop yield deviation from technological trend was accepted as a dependent and VHI as independent variables The models were developed for several major crops including wheat corn and soybeans

  8. The neutral atmosphere temperature experiment. [for thermospheric nitrogen measurement on AEROS satellite

    Science.gov (United States)

    Spencer, N. W.; Pelz, D. T.; Niemann, H. B.; Carignan, G. R.; Caldwell, J. R.

    1974-01-01

    The AEROS Neutral Atmosphere Temperature Experiment (NATE) is designed to measure the kinetic temperature of molecular nitrogen in the thermosphere. A quadrupole mass spectrometer tuned to N2 measures the N2 density variation in a small spherical antechamber having a knife-edged orifice which is exposed to the atmosphere at the outer surface of the spacecraft. The changing density of N2 due to the spinning motion of the spacecraft permits determination of the velocity distribution of the N2 from which the temperature is calculated. An alternate mode of operation of the instrument allows measurement of the other gases in the atmosphere as well as N2 permitting determination of the neutral particle composition of the atmosphere.

  9. Effects of Satellite Spectral Resolution and Atmospheric Water Vapor on Retrieval of Near-Ground Temperatures

    Science.gov (United States)

    1993-04-28

    alternate low-level water vapor profile was considered. This " dry " water vapor profile (dashed in Fig. I) was specified to be equal to the "basic...the dry water vapor profile for the night situation. As expected, the unresolvable perturbations of surface temperature were smaller for the dry

  10. Contribution of Modis Satellite Image to Estimate the Daily Air Temperature in the Casablanca City, Morocco

    Science.gov (United States)

    Bahi, Hicham; Rhinane, Hassan; Bensalmia, Ahmed

    2016-10-01

    Air temperature is considered to be an essential variable for the study and analysis of meteorological regimes and chronics. However, the implementation of a daily monitoring of this variable is very difficult to achieve. It requires sufficient of measurements stations density, meteorological parks and favourable logistics. The present work aims to establish relationship between day and night land surface temperatures from MODIS data and the daily measurements of air temperature acquired between [2011-20112] and provided by the Department of National Meteorology [DMN] of Casablanca, Morocco. The results of the statistical analysis show significant interdependence during night observations with correlation coefficient of R2=0.921 and Root Mean Square Error RMSE=1.503 for Tmin while the physical magnitude estimated from daytime MODIS observation shows a relatively coarse error with R2=0.775 and RMSE=2.037 for Tmax. A method based on Gaussian process regression was applied to compute the spatial distribution of air temperature from MODIS throughout the city of Casablanca.

  11. CONTRIBUTION OF MODIS SATELLITE IMAGE TO ESTIMATE THE DAILY AIR TEMPERATURE IN THE CASABLANCA CITY, MOROCCO

    Directory of Open Access Journals (Sweden)

    H. Bahi

    2016-10-01

    Full Text Available Air temperature is considered to be an essential variable for the study and analysis of meteorological regimes and chronics. However, the implementation of a daily monitoring of this variable is very difficult to achieve. It requires sufficient of measurements stations density, meteorological parks and favourable logistics. The present work aims to establish relationship between day and night land surface temperatures from MODIS data and the daily measurements of air temperature acquired between [2011-20112] and provided by the Department of National Meteorology [DMN] of Casablanca, Morocco. The results of the statistical analysis show significant interdependence during night observations with correlation coefficient of R2=0.921 and Root Mean Square Error RMSE=1.503 for Tmin while the physical magnitude estimated from daytime MODIS observation shows a relatively coarse error with R2=0.775 and RMSE=2.037 for Tmax. A method based on Gaussian process regression was applied to compute the spatial distribution of air temperature from MODIS throughout the city of Casablanca.

  12. Monitoring sea level and sea surface temperature trends from ERS satellites

    DEFF Research Database (Denmark)

    Andersen, Ole Baltazar; Knudsen, Per; Beckley, B.

    2002-01-01

    over this period. In the Indian Ocean and particularly the Pacific Ocean the trends in both sea level and temperature are still dominated by the large changes associated with the El Nino Southern Oscillation. In terms of contribution to the total global sea level change, the contribution of the central...

  13. Offshore Wind Energy: Wind and Sea Surface Temperature from Satellite Observations

    DEFF Research Database (Denmark)

    Karagali, Ioanna

    and the Baltic Sea. The aim is to evaluate their potential use and demonstrate their applicability within the context of offshore wind energy; for the quantication of the wind resources and for the identication of diurnal warming of the sea surface temperature. Space-borne observations of wind are obtained from...

  14. Modelling snowpack surface temperature in the Canadian Prairies using simplified heat flow models

    Science.gov (United States)

    Singh, Purushottam Raj; Yew Gan, Thian

    2005-11-01

    Three practical schemes for computing the snow surface temperature Ts, i.e. the force-restore method (FRM), the surface conductance method (SCM), and the Kondo and Yamazaki method (KYM), were assessed with respect to Ts retrieved from cloud-free, NOAA-AVHRR satellite data for three land-cover types of the Paddle River basin of central Alberta. In terms of R2, the mean Ts, the t-test and F-test, the FRM generally simulated more accurate Ts than the SCM and KYM. The bias in simulated Ts is usually within several degrees Celsius of the NOAA-AVHRR Ts for both the calibration and validation periods, but larger errors are encountered occasionally, especially when Ts is substantially above 0 °C. Results show that the simulated Ts of the FRM is more consistent than that of the SCM, which in turn was more consistent than that of the KYM. This is partly because the FRM considers two aspects of heat conduction into snow, a stationary-mean diurnal (sinusoidal) temperature variation at the surface coupled to a near steady-state ground heat flux, whereas the SCM assumes a near steady-state, simple heat conduction, and other simplifying assumptions, and the KYM does not balance the snowpack heat fluxes by assuming the snowpack having a vertical temperature profile that is linear. Copyright

  15. Mapping Landscape Phenology Preference of Yellow-billed Cuckoo with AVHRR data

    Science.gov (United States)

    Wallace, C.; Villarreal, M. L.; Van Riper, C., III

    2011-12-01

    The yellow-billed cuckoo (Coccycus americanus occidentalis) is a neo-tropical migrant bird that travels north from South America into the southwestern United States during the summer to nest. In Arizona, favored riparian forest and woodland nesting habitat has declined in recent decades, due primarily to human activities and the prolonged drought conditions. As a result, western yellow-billed cuckoos have been petitioned for possible listing under the Endangered Species Act. In this study, we map yellow-billed cuckoo habitat in the state of Arizona using the temporal greenness dynamics of the landscape, or the landscape phenology. Landscape phenometrics were derived from Advanced Very High Resolution Radiometer (AVHRR) satellite Normalized Difference Vegetation Index (NDVI) composite data using Fourier harmonic analysis. Applying Fourier analysis to the waveform composed of the 26 annual composite NDVI values produces phenometrics related to the overall vegetation amount, variability and timing. Field data on Cuckoo presence were obtained from 1998 surveys conducted by Northern Arizona University (NAU), the Arizona Game and Fish Department (AGFD) and the U.S. Geological Survey (USGS). To focus the research within probable landscapes, an AGFD vegetation map (derived from the Arizona GAP program) was used to extract polygons of riparian vegetation and cottonwood-willow riparian vegetation. To create the models, we coupled the satellite phenometrics with field data of cuckoo presence or absence and with points sampling the entirety of mapped riparian and cottonwood-willow vegetation types. Statistical tests reveal that locations with cuckoos present are landscapes with greenness that is significantly more variable and that peaks significantly later than locations in average riparian vegetation, average cottonwood-willow vegetation, or with cuckoos absent. Interestingly, the mean peak greenness date of July 3 for survey locations with cuckoos present coincides with the

  16. Probabilistic approach to cloud and snow detection on Advanced Very High Resolution Radiometer (AVHRR) imagery

    Science.gov (United States)

    Musial, J. P.; Hüsler, F.; Sütterlin, M.; Neuhaus, C.; Wunderle, S.

    2014-03-01

    Derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. Information about a confidence level of provided physical quantities is required to construct an error budget of higher-level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data a common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher-level products and may alter their usability. Within this scope a novel probabilistic cloud mask (PCM) algorithm suited for the 1 km × 1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on the decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve probability estimates from the precomputed look-up tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of intervals. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the invariant coordinate system (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the Polar Platform System (PPS) version 2012 and Moderate Resolution Imaging

  17. Agriculture pest and disease risk maps considering MSG satellite data and land surface temperature

    Science.gov (United States)

    Marques da Silva, J. R.; Damásio, C. V.; Sousa, A. M. O.; Bugalho, L.; Pessanha, L.; Quaresma, P.

    2015-06-01

    Pest risk maps for agricultural use are usually constructed from data obtained from in-situ meteorological weather stations, which are relatively sparsely distributed and are often quite expensive to install and difficult to maintain. This leads to the creation of maps with relatively low spatial resolution, which are very much dependent on interpolation methodologies. Considering that agricultural applications typically require a more detailed scale analysis than has traditionally been available, remote sensing technology can offer better monitoring at increasing spatial and temporal resolutions, thereby, improving pest management results and reducing costs. This article uses ground temperature, or land surface temperature (LST), data distributed by EUMETSAT/LSASAF (with a spatial resolution of 3 × 3 km (nadir resolution) and a revisiting time of 15 min) to generate one of the most commonly used parameters in pest modeling and monitoring: "thermal integral over air temperature (accumulated degree-days)". The results show a clear association between the accumulated LST values over a threshold and the accumulated values computed from meteorological stations over the same threshold (specific to a particular tomato pest). The results are very promising and enable the production of risk maps for agricultural pests with a degree of spatial and temporal detail that is difficult to achieve using in-situ meteorological stations.

  18. Linking Satellite Derived Land Surface Temperature with Cholera: A Case Study for South Sudan

    Science.gov (United States)

    Aldaach, H. S. V.; Jutla, A.; Akanda, A. S.; Colwell, R. R.

    2014-12-01

    A sudden onset of cholera in South Sudan, in April 2014 in Northern Bari in Juba town resulted in more than 400 cholera cases after four weeks of initial outbreak with a case of fatality rate of CFR 5.4%. The total number of reported cholera cases for the period of April to July, 2014 were 5,141 including 114 deaths. With the limited efficacy of cholera vaccines, it is necessary to develop mechanisms to predict cholera occurrence and thereafter devise intervention strategies for mitigating impacts of the disease. Hydroclimatic processes, primarily precipitation and air temperature are related to epidemic and episodic outbreak of cholera. However, due to coarse resolution of both datasets, it is not possible to precisely locate the geographical location of disease. Here, using Land Surface Temperature (LST) from MODIS sensors, we have developed an algorithm to identify regions susceptible for cholera. Conditions for occurrence of cholera were detectable at least one month in advance in South Sudan and were statistically sensitive to hydroclimatic anomalies of land surface and air temperature, and precipitation. Our results indicate significant spatial and temporal averaging required to infer usable information from LST over South Sudan. Preliminary results that geographically location of cholera outbreak was identifiable within 1km resolution of the LST data.

  19. Comparison between MODIS and AIRS/AMSU satellite-derived surface skin temperatures

    Directory of Open Access Journals (Sweden)

    Y.-R. Lee

    2012-10-01

    Full Text Available Surface skin temperatures of the Version 5 Level 3 products of MODIS and AIRS/AMSU have been compared in terms of monthly anomaly trends and climatology over the globe during the period from September 2002 to August 2011. The MODIS temperatures in the 50° N–50° S region tend to systematically be ~1.7 K colder over land and ~0.5 K warmer over ocean than the AIRS/AMSU temperatures. Over high latitude ocean the MODIS values are ~5.5 K warmer than the AIRS/AMSU. The discrepancies between the annual averages of the two sensors are as much as ~12 K in the sea ice regions. Both MODIS and AIRS/AMSU show cooling trends from −0.05 ± 0.06 to −0.14 ± 0.07 K (9 yr−1 over the globe, but warming trends (0.02 ± 0.12–0.15 ± 0.19 K (9 yr−1 in the high latitude regions. The disagreement between the two sensors results mainly from the differences in ice/snow emissivity between MODIS infrared and AMSU microwave, and also in their observational local times.

  20. Spatial heterogeneity of satellite derived land surface parameters and energy flux densities for LITFASS-area

    Directory of Open Access Journals (Sweden)

    A. Tittebrand

    2009-03-01

    Full Text Available Based on satellite data in different temporal and spatial resolution, the current use of frequency distribution functions (PDF for surface parameters and energy fluxes is one of the most promising ways to describe subgrid heterogeneity of a landscape. Objective of this study is to find typical distribution patterns of parameters (albedo, NDVI for the determination of the actual latent heat flux (L.E determined from highly resolved satellite data within pixel on coarser scale.

    Landsat ETM+, Terra MODIS and NOAA-AVHRR surface temperature and spectral reflectance were used to infer further surface parameters and radiant- and energy flux densities for LITFASS-area, a 20×20 km2 heterogeneous area in Eastern Germany, mainly characterised by the land use types forest, crop, grass and water. Based on the Penman-Monteith-approach L.E, as key quantity of the hydrological cycle, is determined for each sensor in the accordant spatial resolution with an improved parametrisation. However, using three sensors, significant discrepancies between the inferred parameters can cause flux distinctions resultant from differences of the sensor filter response functions or atmospheric correction methods. The approximation of MODIS- and AVHRR- derived surface parameters to the reference parameters of ETM (via regression lines and histogram stretching, respectively, further the use of accurate land use classifications (CORINE and a new Landsat-classification, and a consistent parametrisation for the three sensors were realized to obtain a uniform base for investigations of the spatial variability.

    The analyses for 4 scenes in 2002 and 2003 showed that for forest clear distribution-patterns for NDVI and albedo are found. Grass and crop distributions show higher variability and differ significantly to each other in NDVI but only marginal in albedo. Regarding NDVI-distribution functions NDVI was found to be the key variable for L.E-determination.

  1. Temperature dependence of the Kondo resonance and its satellites in CeCu_2Si_2

    OpenAIRE

    Reinert, F.; Ehm, D.; Schmidt, S; Nicolay, G.; H"ufner, S.; Kroha, J.; Trovarelli, O.; Geibel, C.

    2001-01-01

    We present high-resolution photoemission spectroscopy studies on the Kondo resonance of the strongly-correlated Ce system CeCu$_2$Si$_2$. Exploiting the thermal broadening of the Fermi edge we analyze position, spectral weight, and temperature dependence of the low-energy 4f spectral features, whose major weight lies above the Fermi level $E_F$. We also present theoretical predictions based on the single-impurity Anderson model using an extended non-crossing approximation (NCA), including all...

  2. Long-Term Variability of Satellite Lake Surface Water Temperatures in the Great Lakes

    Science.gov (United States)

    Gierach, M. M.; Matsumoto, K.; Holt, B.; McKinney, P. J.; Tokos, K.

    2014-12-01

    The Great Lakes are the largest group of freshwater lakes on Earth that approximately 37 million people depend upon for fresh drinking water, food, flood and drought mitigation, and natural resources that support industry, jobs, shipping and tourism. Recent reports have stated (e.g., the National Climate Assessment) that climate change can impact and exacerbate a range of risks to the Great Lakes, including changes in the range and distribution of certain fish species, increased invasive species and harmful algal blooms, declining beach health, and lengthened commercial navigation season. In this study, we will examine the impact of climate change on the Laurentian Great Lakes through investigation of long-term lake surface water temperatures (LSWT). We will use the ATSR Reprocessing for Climate: Lake Surface Water Temperature & Ice Cover (ARC-Lake) product over the period 1995-2012 to investigate individual and interlake variability. Specifically, we will quantify the seasonal amplitude of LSWTs, the first and last appearances of the 4°C isotherm (i.e., an important identifier of the seasonal evolution of the lakes denoting winter and summer stratification), and interpret these quantities in the context of global interannual climate variability such as ENSO.

  3. A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE for Satellite-Based Actual Evapotranspiration Estimation

    Directory of Open Access Journals (Sweden)

    Hua Zhang

    2016-09-01

    Full Text Available The estimation of spatially-variable actual evapotranspiration (AET is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE, to generate daily AET estimates based on satellite-derived land surface temperature and the vegetation index NDVI. The TAVE captures heterogeneity in AET across elevation zones and permits variability in determining local values of wet and dry end-member classes (known as edges. Compared to traditional triangle methods, TAVE introduces three unique features: (i the discretization of the domain as overlapping elevation zones; (ii a variable wet edge that is a function of elevation zone; and (iii variable values of a combined-effect parameter (that accounts for aerodynamic and surface resistance, vapor pressure gradient, and soil moisture availability along both wet and dry edges. With these features, TAVE effectively addresses the combined influence of terrain and water stress on semi-arid environment AET estimates. We demonstrate the effectiveness of this method in one of the driest countries in the world—Jordan, and compare it to a traditional triangle method (TA and a global AET product (MOD16 over different land use types. In irrigated agricultural lands, TAVE matched the results of the single crop coefficient model (−3%, in contrast to substantial overestimation by TA (+234% and underestimation by MOD16 (−50%. In forested (non-irrigated, water consuming regions, TA and MOD16 produced AET average deviations 15.5 times and −3.5 times of those based on TAVE. As TAVE has a simple structure and low data requirements, it provides an efficient means to satisfy the increasing need for evapotranspiration estimation in data-scarce semi-arid regions. This study constitutes a much needed step towards the satellite-based quantification of agricultural water consumption in Jordan.

  4. EUMETSAT and OSI-SAF Sea Surface Temperature: Recent results and future developments

    Science.gov (United States)

    O'Carroll, Anne; Le Borgne, Pierre

    2014-05-01

    The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) delivers operational weather and climate-related satellite data, images and products throughout all day and year. EUMETSAT also has commitments to operational oceanography and atmospheric composition monitoring. Activities over the next twenty years include the continuation of the Mandatory Programmes (MSG, EPS) and future (MTG, EPS-SG), which all include ocean observations of Sea Surface Temperature. The EUMETSAT Ocean and Sea-ice (OSI) Satellite Application Facility (SAF) is lead by Meteo-France with a consortium of institutes from EUMETSAT member states, and provides reliable and timely operational services related to meteorology, oceanography and the marine environment. The OSI-SAF delivers level-2 Sea Surface Temperature products in GHRSST format from a range of EUMETSAT data including Metop AVHRR, IASI; and SEVIRI. EUMETSAT is participating in Copernicus Sentinel-3 in partnership with ESA, where EUMETSAT will operate the satellite and will serve the marine user community. The operational Sea Surface Temperature product delivered by EUMETSAT for Sentinel-3 SLSTR will be in GHRSST L2P format. On-going work towards access to relevant data from third-parties with the preparation of agreements with ISRO, SOA and JAXA, will give EUMETSAT access to an enhanced ocean products catalogue. The presentation will give an overview of activities relating to Sea Surface Temperature at EUMETSAT and the OSI-SAF, and their support to GHRSST, focusing on recent results and future developments.

  5. Patrones fenologico de la provincia de Mendoza, Argentina: Mediante serie temporal de imágenes NOAA - AVHRR NDI GAC

    NARCIS (Netherlands)

    González Loyarte, M.M.; Menenti, M.; Roig, F.A.

    2010-01-01

    Phenological patterns of the province of Mendoza, Argentina, through a temporal series of NOAA-AVHRR NDVI GAC images. The temporal dynamics of vegetation in Mendoza is described through analysis of regional foliar phenology using a series of 108 monthly NOAA-AVHRR NDVI GAC images. A Fast Fourier

  6. Patrones fenologico de la provincia de Mendoza, Argentina: Mediante serie temporal de imágenes NOAA - AVHRR NDI GAC

    NARCIS (Netherlands)

    González Loyarte, M.M.; Menenti, M.; Roig, F.A.

    2010-01-01

    Phenological patterns of the province of Mendoza, Argentina, through a temporal series of NOAA-AVHRR NDVI GAC images. The temporal dynamics of vegetation in Mendoza is described through analysis of regional foliar phenology using a series of 108 monthly NOAA-AVHRR NDVI GAC images. A Fast Fourier Tra

  7. Homogenised daily lake surface water temperature data generated from multiple satellite sensors: A long-term case study of a large sub-Alpine lake

    Science.gov (United States)

    Pareeth, Sajid; Salmaso, Nico; Adrian, Rita; Neteler, Markus

    2016-08-01

    Availability of remotely sensed multi-spectral images since the 1980’s, which cover three decades of voluminous data could help researchers to study the changing dynamics of bio-physical characteristics of land and water. In this study, we introduce a new methodology to develop homogenised Lake Surface Water Temperature (LSWT) from multiple polar orbiting satellites. Precisely, we developed homogenised 1 km daily LSWT maps covering the last 30 years (1986 to 2015) combining data from 13 satellites. We used a split-window technique to derive LSWT from brightness temperatures and a modified diurnal temperature cycle model to homogenise data which were acquired between 8:00 to 17:00 UTC. Gaps in the temporal LSWT data due to the presence of clouds were filled by applying Harmonic ANalysis of Time Series (HANTS). The satellite derived LSWT maps were validated based on long-term monthly in-situ bulk temperature measurements in Lake Garda, the largest lake in Italy. We found the satellite derived homogenised LSWT being significantly correlated to in-situ data. The new LSWT time series showed a significant annual rate of increase of 0.020 °C yr-1 (*P summer.

  8. 基于AVHRR和MODIS数据的全球植被物候比较分析%Comparative Analysis of Global Vegetation Phenology based on AVHRR and MODIS

    Institute of Scientific and Technical Information of China (English)

    刘玲玲; 刘良云; 胡勇

    2012-01-01

    The AVHRR and MODIS satellites have played a vital role in monitoring vegetation phenology responses to climate change at a global scale. It is important to examine whether the derived phenological parameters from AVHRR are consistent with from MODIS. In this paper,a dynamic threshold method was applied to extract the phenological metrics based on GIMMS AVHRR NDVI and MODIS 13A2 NDVI data- set smoothed with HANTS in 2005 ,such as Start of Season (SOS),End of Season (EOS),and Duration of Season (DOS). Then, the comparative analysis was performed on the phenological metrics between AVHRR and MODIS. The results showed the SOS appeared between 100th and 140th days, the EOS oc- curred between 260th and 300th days,the DOS mainly existed from 130th to 180th days in most regions. The phenological variation along latitude based on AVHRR was consistent with based on MODIS,a trend of later SOS,an earlier EOS and a shorter DOS with increase of latitude were observed. The SOS,EOS and DOS from AVHRR and MODIS data were quite consistent with a correlation coefficient larger than 0.9 for the deciduous forests and grasslands in Eurasia and North America.%AVHRR和MODIS卫星数据在全球和区域尺度植物物候对气候变化响应研究中起着重要的作用,然而两种传感器在全球尺度物候监测的一致性有待验证。首先利用时间序列谐波分析法(HA—NTS)对2005年全球GIMMSAVHRRNDVI和MODIS13A2数据进行滤波处理;然后基于改进的动态阈值方法,提取全球植被的返青期(sOs)、枯黄期(EOs)和生长季长度(DOS);最后分区域比较和评估两种传感器提取物候参数的潜力。研究结果表明:2005年全球大部分地区植被在第100~140d开始生长,到第260-300d逐渐停止生长,生长季长度集中在130~180d,并且和区域研究结果具有一致性;两种传感器提取的植被关键物候期的空间变化趋势是一致的,随着纬度升高,返青期呈现推

  9. Temperature dependence of the Kondo resonance and its satellites in CeCu2Si2.

    Science.gov (United States)

    Reinert, F; Ehm, D; Schmidt, S; Nicolay, G; Hüfner, S; Kroha, J; Trovarelli, O; Geibel, C

    2001-09-03

    We present high-resolution photoemission spectroscopy studies on the Kondo resonance of the strongly correlated Ce system CeCu2Si2. By exploiting the thermal broadening of the Fermi edge we analyze position, spectral weight, and temperature dependence of the low-energy 4f spectral features, whose major weight lies above the Fermi level E(F). We also present theoretical predictions based on the single-impurity Anderson model using an extended noncrossing approximation, including all spin-orbit and crystal field splittings of the 4f states. The excellent agreement between theory and experiment provides strong evidence that the spectral properties of CeCu2Si2 can be described by single-impurity Kondo physics down to T approximately 5 K.

  10. Inland Water Temperature and the recent Global Warming Hiatus

    Science.gov (United States)

    Hook, S. J.; Healey, N.; Lenters, J. D.; O'Reilly, C.

    2015-12-01

    We are using thermal infrared satellite data in conjunction with in situ measurements to produce water temperatures for all the large inland water bodies in North America and the rest of the world for potential use as climate indicator. Recent studies have revealed significant warming of inland waters throughout the world. The observed rate of warming is - in many cases - greater than that of the ambient air temperature. These rapid, unprecedented changes in inland water temperatures have profound implications for lake hydrodynamics, productivity, and biotic communities. Scientists are just beginning to understand the global extent, regional patterns, physical mechanisms, and ecological consequences of lake warming. As part of our earlier studies we have collected thermal infrared satellite data from those satellite sensors that provide long-term and frequent spaceborne thermal infrared measurements of inland waters including ATSR, AVHRR, and MODIS and used these to examine trends in water surface temperature for approximately 169 of the largest inland water bodies in the world. We are now extending this work to generate temperature time-series of all North American inland water bodies that are sufficiently large to be studied using 1km resolution satellite data for the last 3 decades, approximately 268 lakes. These data are then being related to changes in the surface air temperature and compared with regional trends in water surface temperature derived from CMIP5/IPCC model simulations/projections to better predict future temperature changes. We will discuss the available datasets and processing methodologies together with the patterns they reveal based on recent changes in the global warming, with a particular focus on the inland waters of the southwestern USA.

  11. Snowline retrievals using operational satellite data

    Science.gov (United States)

    Becker, R.

    2010-09-01

    Making use of atmosphere and surface parameters derived from satellite remote sensing is of increasing importance to describe appropriately status and changes of weather and climate. Even in regions with poor coverage concerning ground based measurements and/or heterogenous terrain satellite products contribute to fill temporal and spatial gaps. Imaging radiometers provide information on surface snow and ice based on multispectral algorithms with a spatial resolution from 250 m to about 3000 m. Observations by passive imaging spectro-/radiometers like SEVIRI onboard Meteosat second generation, Noaa/MetOp AVHRR and Terra/Aqua MODIS have the potential to provide snow products on a daily basis with spatial resolution comparable or better than grid increment of the hydrological models. For the evaluation of MODIS imagery a dedicated algorithm was set up utilising multispectral thresholding of calibrated radiances to separate clear land and sea from cloudy and snow-covered scenes. The scheme works independently of a-priori atmospheric data like numerical model forecasts. It outputs a combined snow/cloudmask that is finally convoluted with background topography information (GIS), allowing for the calculation of snowlines. The core snow and ice detection is based on a NDSI module (normalised difference snow index, Hall et.al. 2001). A well established algorithm developed within the framework of the Satellite Application Facility for Nowcasting (NWCSAF, Dybbroe et.al. 2005), is used to detect snowy pixels in the AVHRR imagery. MODIS and AVHRR results were compared to each other. It shows a good agreement by means of correlation (.94) but systematic deviations are considered. A verification study was carried out by taking into account all European synoptical and climatological snow measurements with snow depths of at least 1 cm. The scores show a clear seasonal cycle with PODs of .2 in summer (both) and .86 (AVHRR) and .82 (MODIS) in winter months. The evaluation data

  12. Interannual Variation of the Surface Temperature of Tropical Forests from Satellite Observations

    Directory of Open Access Journals (Sweden)

    Huilin Gao

    2016-01-01

    Full Text Available Land surface temperatures (LSTs within tropical forests contribute to climate variations. However, observational data are very limited in such regions. This study used passive microwave remote sensing data from the Special Sensor Microwave/Imager (SSM/I and the Special Sensor Microwave Imager Sounder (SSMIS, providing observations under all weather conditions, to investigate the LST over the Amazon and Congo rainforests. The SSM/I and SSMIS data were collected from 1996 to 2012. The morning and afternoon observations from passive microwave remote sensing facilitate the investigation of the interannual changes of LST anomalies on a diurnal basis. As a result of the variability of cloud cover and the corresponding reduction of solar radiation, the afternoon LST anomalies tend to vary more than the morning LST anomalies. The dominant spatial and temporal patterns for interseasonal variations of the LST anomalies over the tropical rainforest were analyzed. The impacts of droughts and El Niños on this LST were also investigated. Differences between early morning and late afternoon LST anomalies were identified by the remote sensing product, with the morning LST anomalies controlled by humidity (according to comparisons with the National Centers for Environmental Prediction (NCEP reanalysis data.

  13. Evaluating the consistency of the 1982-1999 NDVI trends in the Iberian Peninsula across four time-series derived from the AVHRR sensor: LTDR, GIMMS, FASIR, and PAL-II.

    Science.gov (United States)

    Alcaraz-Segura, Domingo; Liras, Elisa; Tabik, Siham; Paruelo, José; Cabello, Javier

    2010-01-01

    Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR) sensor archive to produce Normalized Difference Vegetation Index (NDVI) datasets (i.e., PAL, FASIR, GIMMS, and LTDR) under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations' carbon budgets in meeting international targets (such as the Kyoto Protocol). This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal) by evaluating whether their 1982-1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann-Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges) showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant), the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia). Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative) and in 32% more pixels than GIMMS) has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast.

  14. Evaluating the Consistency of the 1982–1999 NDVI Trends in the Iberian Peninsula across Four Time-series Derived from the AVHRR Sensor: LTDR, GIMMS, FASIR, and PAL-II

    Directory of Open Access Journals (Sweden)

    José Paruelo

    2010-02-01

    Full Text Available Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR sensor archive to produce Normalized Difference Vegetation Index (NDVI datasets (i.e., PAL, FASIR, GIMMS, and LTDR under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations’ carbon budgets in meeting international targets (such as the Kyoto Protocol. This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal by evaluating whether their 1982–1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann-Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant, the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia. Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative and in 32% more pixels than GIMMS has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast.

  15. Evaluating the Consistency of the 1982–1999 NDVI Trends in the Iberian Peninsula across Four Time-series Derived from the AVHRR Sensor: LTDR, GIMMS, FASIR, and PAL-II

    Science.gov (United States)

    Alcaraz-Segura, Domingo; Liras, Elisa; Tabik, Siham; Paruelo, José; Cabello, Javier

    2010-01-01

    Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR) sensor archive to produce Normalized Difference Vegetation Index (NDVI) datasets (i.e., PAL, FASIR, GIMMS, and LTDR) under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations’ carbon budgets in meeting international targets (such as the Kyoto Protocol). This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal) by evaluating whether their 1982–1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann-Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges) showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant), the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia). Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative) and in 32% more pixels than GIMMS) has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast. PMID:22205868

  16. The retrieval of cloud microphysical properties using satellite measurements and an in situ database

    Directory of Open Access Journals (Sweden)

    Christophe Poix

    Full Text Available By combining AVHRR data from the NOAA satellites with information from a database of in situ measurements, large-scale maps can be generated of the microphysical parameters most immediately significant for the modelling of global circulation and climate. From the satellite data, the clouds can be classified into cumuliform, stratiform and cirrus classes and then into further sub-classes by cloud top temperature. At the same time a database of in situ measurements made by research aircraft is classified into the same sub-classes and a statistical analysis is used to derive relationships between the sub-classes and the cloud microphysical properties. These two analyses are then linked to give estimates of the microphysical properties of the satellite observed clouds. Examples are given of the application of this technique to derive maps of the probability of occurrence of precipitating clouds and of precipitating water content derived from a case study within the International Cirrus Experiment (ICE held in 1989 over the North Sea.

  17. Spatial Downscaling Research of Satellite Land Surface Temperature Based on Spectral Normalization Index

    Directory of Open Access Journals (Sweden)

    LI Xiaojun

    2017-03-01

    Full Text Available Aiming at the problem that the spatial and temporal resolution of land surface temperature (LST have the contradiction with each other, a new downscaling model was put forward, based on the TsHARP(an algorithm for sharpening thermal imagery downscaling method, this research makes improvements by selecting the better correlation of spectral index(normalized difference vegetation index, NDVI; normalized difference build-up index, NDBI; modified normalized difference water index, MNDWI; enhanced bare soil index, EBSI with LST, i.e., replaces the original NDVI with new spectral index according to the different surface land-cover types, to assess the accuracy of each downscaling method based on qualitative and quantitative analysis with synchronous Landsat 8 TIRS LST data. The results show that both models could effectively enhance the spatial resolution while simultaneously preserving the characteristics and spatial distribution of the original 1 km MODIS LST image, and also eliminate the “mosaic” effect in the original 1 km image, both models were proved to be effective and applicable in our study area; global scale analysis shows that the new model (RMSE:1.635℃ is better than the TsHARP method (RMSE:2.736℃ in terms of the spatial variability and accuracy of the results; the different land-cover types of downscaling statistical analysis shows that the TsHARP method has poor downscaling results in the low vegetation coverage area, especially for the bare land and building-up area(|MBE|>3℃, the new model has obvious advantages in the description of the low vegetation coverage area. Seasonal analysis shows that the downscaling results of two models in summer and autumn are superior to those in spring and winter, the new model downscaling results are better than the TsHARP method in the four seasons, in which the spring and winter downscaling improvement is better than summer and autumn.

  18. Soil moisture deficit estimation using satellite multi-angle brightness temperature

    Science.gov (United States)

    Zhuo, Lu; Han, Dawei; Dai, Qiang

    2016-08-01

    Accurate soil moisture information is critically important for hydrological modelling. Although remote sensing soil moisture measurement has become an important data source, it cannot be used directly in hydrological modelling. A novel study based on nonlinear techniques (a local linear regression (LLR) and two feedforward artificial neural networks (ANNs)) is carried out to estimate soil moisture deficit (SMD), using the Soil Moisture and Ocean Salinity (SMOS) multi-angle brightness temperatures (Tbs) with both horizontal (H) and vertical (V) polarisations. The gamma test is used for the first time to determine the optimum number of Tbs required to construct a reliable smooth model for SMD estimation, and the relationship between model input and output is achieved through error variance estimation. The simulated SMD time series in the study area is from the Xinanjiang hydrological model. The results have shown that LLR model is better at capturing the interrelations between SMD and Tbs than ANNs, with outstanding statistical performances obtained during both training (NSE = 0.88, r = 0.94, RMSE = 0.008 m) and testing phases (NSE = 0.85, r = 0.93, RMSE = 0.009 m). Nevertheless, both ANN training algorithms (radial BFGS and conjugate gradient) have performed well in estimating the SMD data and showed excellent performances compared with those derived directly from the SMOS soil moisture products. This study has also demonstrated the informative capability of the gamma test in the input data selection for model development. These results provide interesting perspectives for data-assimilation in flood-forecasting.

  19. A Satellite-Based Estimation of Evapotranspiration Using Vegetation Index-Temperature Trapezoid Concept: A Case Study in Southern Florida, U.S.A.

    Science.gov (United States)

    Yagci, A. L.; Santanello, J. A., Jr.; Jones, J. W.

    2015-12-01

    One of the key surface variables for hydrological applications, monitoring of natural and anthropogenic water consumption, closing energy balance and water budgets and drought identification is evapotranspiration (ET). There is currently a strong need for high temporal and spatial resolution ET products for climate and hydrological modelers. A satellite-based retrieval method based on vegetation index-temperature trapezoid (VITT) concept has been developed. This model has the ability to generate accurate ET estimates at high temporal and spatial resolutions by taking advantage of key remotely sensed parameters such as vegetation indices (VIs) and land surface temperature (LST) acquired by satellites as well as routinely-measured meteorological variables such as air temperature (Ta) and net radiation. For local-scale applications, the model has been successfully implemented in Python programming language and tested using Landsat satellite products at an eddy covariance flux tower in Florida. It is fully functional and automated such that there is no need of user intervention to run the model. The model development for continental-scale applications using VI and LST products from NASA satellites such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) is currently in progress. The results for local-scale application and early results for continental-scale (US) will be presented and discussed.

  20. Distributed land surface modeling with utilization of multi-sensor satellite data: application for the vast agricultural terrain in cold region

    Science.gov (United States)

    Muzylev, E.; Uspensky, A.; Gelfan, A.; Startseva, Z.; Volkova, E.; Kukharsky, A.; Romanov, P.; Alexandrovich, M.

    2012-04-01

    A technique for satellite-data-based modeling water and heat regimes of a large scale area has been developed and applied for the 227,300 km2 agricultural region in the European Russia. The core component of the technique is the physically based distributed Remote Sensing Based Land Surface Model (RSBLSM) intended for simulating transpiration by vegetation and evaporation from bare soil, vertical transfer of water and heat within soil and vegetation covers during a vegetation season as well as hydrothermal processes in soil and snow covers during a cold season, including snow accumulation and melt, dynamics of soil moisture and temperature during soil freezing and thawing, infiltration into frozen soil. Processes in the "atmosphere-snow-frozen soil" system are critical for cold region agriculture, as they control crop development in early spring before the vegetation season beginning. For assigning the model parameters as well as for preliminary calibrating and validating the model, available multi-year data sets of soil moisture/temperature profiles, evaporation, snow and soil freezing depth measured at the meteorological stations located within the study region have been utilized. To provide an appropriate parametrization of the model for the areas where ground-based measurements are unavailable, estimates have been utilized for vegetation, meteorological and snow characteristics derived from the multispectral measurements of AVHRR/NOAA (1999-2010), MODIS/EOS Terra & Aqua (2002-2010), AMSR-E/Aqua (2003-2004; 2008-2010), and SEVIRI/Meteosat-9 (2009-2010). The technologies of thematic processing the listed satellite data have been developed and applied to estimate the land surface and snow cover characteristics for the study area. The developed technologies of AVHRR data processing have been adapted to retrieve land surface temperature (LST) and emissivity (E), surface-air temperature at a level of vegetation cover (TA), normalized vegetation index (NDVI), leaf

  1. Cross-satellite comparison of operational land surface temperature products derived from MODIS and ASTER data over bare soil surfaces

    Science.gov (United States)

    Duan, Si-Bo; Li, Zhao-Liang; Cheng, Jie; Leng, Pei

    2017-04-01

    The collection 6 (C6) MODIS land surface temperature (LST) product is publicly available for the user community. Compared to the collection 5 (C5) MODIS LST product, the C6 MODIS LST product has been refined over bare soil pixels. Assessing the accuracy of the C6 MODIS LST product will help to facilitate the use of the LST product in various applications. In this study, we present a cross-satellite comparison to evaluate the accuracy of the C6 MODIS LST product (MOD11_L2) over bare soil surfaces under various atmospheric and surface conditions using the ASTER LST product as a reference. For comparison, the C5 MODIS LST product was also used in the analysis. The absolute biases (0.2-1.5 K) of the differences between the C6 MODIS LST and ASTER LST over bare soil surfaces are approximately two times less than those (0.6-3.8 K) of the differences between the C5 MODIS LST and ASTER LST. Furthermore, the RMSEs (0.7-2.3 K) over bare soil surfaces for the C6 MODIS LST are significantly smaller than those (0.9-4.2 K) for the C5 MODIS LST. These results indicate that the accuracy of the C6 MODIS LST product is much better than that of the C5 MODIS LST product. We recommend that the user community employs the C6 MODIS LST product in their applications.

  2. Validation of satellite data with IASOA observatories and shipboard measurements in Arctic Ocean

    Science.gov (United States)

    Repina, Irina; Artamonov, Arseniy; Mazilkina, Alexandra; Valiullin, Denis; Stanichny, Sergey

    2016-04-01

    The paper shows the possibility of using surface observation data at high latitudes for the validation of different satellite products. We use data from International Arctic Systems for Observing the Atmosphere (IASOA) observatories and data from Nansen and Amundsen basins observation system (NABOS) project. The NABOS field experiment was carried out in the central part of the Arctic and in the eastern Arctic seas during summer and fall period of 2004-2009, 2013 and 2015. Newly improved satellite products and surface observations provide an opportunity to revisit remote-sensing capabilities for estimating shortwave and longwave radiative fluxes, as well as turbulent fluxes at high latitudes. Estimates of SW fluxes from the MODIS and LW fluxes from the NOAA satellites are evaluated against land observations from IASOA observatories, and unique shipboard measurements. Results show that the satellite products are in better agreement with observations than those from numerical models. Therefore, the large scale satellite based estimates should be useful for model evaluation and for providing information in formulating energy budgets at high latitudes. Visible and near-infrared albedos over snow and ice surfaces are retrieved from AVHRR. Comparison with surface measurements of albedo in arctic observatories and Arctic ocean shows very good agreement. Meteorological and micrometeorological observations were used to validate the surface temperature and surface heat fluxes in the satellite data. Compared data arrays are independent and sufficiently detailed to perform trustworthy evaluations. The spatial and temporal patterns of the resulting flux fields are investigated and compared with those derived from satellite observations such as HOAPS, from blended data such as AOFLUX (in the open water cases). A computation of the sensible heat flux at the surface is formulated on the basis of spatial variations of the surface temperature estimated from satellite data. Based on

  3. Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh

    Science.gov (United States)

    Nizamuddin, Mohammad; Akhand, Kawsar; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch

    2015-06-01

    Rice is a dominant food crop of Bangladesh accounting about 75 percent of agricultural land use for rice cultivation and currently Bangladesh is the world's fourth largest rice producing country. Rice provides about two-third of total calorie supply and about one-half of the agricultural GDP and one-sixth of the national income in Bangladesh. Aus is one of the main rice varieties in Bangladesh. Crop production, especially rice, the main food staple, is the most susceptible to climate change and variability. Any change in climate will, thus, increase uncertainty regarding rice production as climate is major cause year-to-year variability in rice productivity. This paper shows the application of remote sensing data for estimating Aus rice yield in Bangladesh using official statistics of rice yield with real time acquired satellite data from Advanced Very High Resolution Radiometer (AVHRR) sensor and Principal Component Regression (PCR) method was used to construct a model. The simulated result was compared with official agricultural statistics showing that the error of estimation of Aus rice yield was less than 10%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.

  4. A comparison of conventional and geostatistical methods to replace clouded pixels in NOAA-AVHRR images

    NARCIS (Netherlands)

    Addink, E.A.; Stein, A.

    1999-01-01

    The potential of using National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) images for large areas is often limited by cloud cover. It could be increased when small clouds are replaced by estimated reflection and emission values. In this study seven

  5. Neural Networks as a Tool for Constructing Continuous NDVI Time Series from AVHRR and MODIS

    Science.gov (United States)

    Brown, Molly E.; Lary, David J.; Vrieling, Anton; Stathakis, Demetris; Mussa, Hamse

    2008-01-01

    The long term Advanced Very High Resolution Radiometer-Normalized Difference Vegetation Index (AVHRR-NDVI) record provides a critical historical perspective on vegetation dynamics necessary for global change research. Despite the proliferation of new sources of global, moderate resolution vegetation datasets, the remote sensing community is still struggling to create datasets derived from multiple sensors that allow the simultaneous use of spectral vegetation for time series analysis. To overcome the non-stationary aspect of NDVI, we use an artificial neural network (ANN) to map the NDVI indices from AVHRR to those from MODIS using atmospheric, surface type and sensor-specific inputs to account for the differences between the sensors. The NDVI dynamics and range of MODIS NDVI data at one degree is matched and extended through the AVHRR record. Four years of overlap between the two sensors is used to train a neural network to remove atmospheric and sensor specific effects on the AVHRR NDVI. In this paper, we present the resulting continuous dataset, its relationship to MODIS data, and a validation of the product.

  6. Exploring Long Term Spatial Vegetation Trends in Taiwan from AVHRR NDVI3g Dataset Using RDA and HCA Analyses

    Directory of Open Access Journals (Sweden)

    Hui Ping Tsai

    2016-03-01

    Full Text Available Due to 4000 m elevation variation with temperature differences equivalent to 50 degrees of latitudinal gradient, exploring Taiwan’s spatial vegetation trends is valuable in terms of diverse ecosystems and climatic types covering a relatively small island with an area of 36,000 km2. This study analyzed Taiwan’s spatial vegetation trends with controlling environmental variables through redundancy (RDA and hierarchical cluster (HCA analyses over three decades (1982–2012 of monthly normalized difference vegetation index (NDVI derived from the Advanced Very High Resolution Radiometer (AVHRR NDVI3g data for 19 selected weather stations over the island. Results showed two spatially distinct vegetation response groups. Group 1 comprises weather stations which remained relatively natural showing a slight increasing NDVI tendency accompanied with rising temperature, whereas Group 2 comprises stations with high level of human development showing a slight decreasing NDVI tendency associated with increasing temperature-induced moisture stress. Statistically significant controlling variables include climatic factors (temperature and precipitation, orographic factors (mean slope and aspects, and anthropogenic factor (population density. Given the potential trajectories for future warming, variable precipitation, and population pressure, challenges, such as land-cover and water-induced vegetation stress, need to be considered simultaneously for establishing adequate adaptation strategies to combat climate change challenges in Taiwan.

  7. Constructing new satellite-only time series of global mean, sea surface temperature data for climate from ATSR data

    Science.gov (United States)

    Veal, Karen; Remedios, John; Ghent, Darren

    2013-04-01

    The Along Track Scanning Radiometers (ATSRs) have provided a near-continuous record of sea surface temperature (SST) data for climate from the launch of ATSR-1 in 1991 to the loss of the Advanced ATSR (AATSR) in April 2012. The intention was always to provide an SST record, independent of in situ data, to corroborate and improve climate data records in recent times. We show that the ATSR record provides a very suitable data set with which to study the recent climate record, particularly during the ATSR-2 and AATSR periods (1995 to 2012) in three major respects. First, ATSR climate time series achieve anomaly accuracies of better than 0.05 K (and high stability). Second, the overlap between instruments allows for excellent determination and removal of biases; between ATSR-2 and AATSR, these are less than 0.05 K for the highest accuracy SST data. Finally, uncertainties on global monthly mean data are less than 0.02 K and hence comparable to those achieved by in situ analyses such as HadSST3. A particular hallmark of the ATSR instruments was their exceptional design for accuracy incorporating high accuracy radiometric calibration, dual-view of the Earth's surface and the use of three thermal emission channels; additional channels are included for cloud clearing in this context. The use of dual-view and multiple thermnal wavelengths allows a number of combinations for retrievals of SST, the most accurate being the dual-view, three-channel retrieval (D3) at nighttime. This restriction is due to the use of the 3.7 micron channel which is sensitive to solar radiation during the day. Extensive work has resulted in a major advances recently resulting in both an operational V2.0 SST product and a further improved ATSR Re-analysis for Climate (ARC) product, a particular feature of the latter being the development of a depth SST product in addition to the skin SST directly determined from satellite data. We will discuss the characteristics of these data sets in terms of

  8. Mapping the Spatial Distribution of Winter Crops at Sub-Pixel Level Using AVHRR NDVI Time Series and Neural Nets

    Directory of Open Access Journals (Sweden)

    Felix Rembold

    2013-03-01

    Full Text Available For large areas, it is difficult to assess the spatial distribution and inter-annual variation of crop acreages through field surveys. Such information, however, is of great value for governments, land managers, planning authorities, commodity traders and environmental scientists. Time series of coarse resolution imagery offer the advantage of global coverage at low costs, and are therefore suitable for large-scale crop type mapping. Due to their coarse spatial resolution, however, the problem of mixed pixels has to be addressed. Traditional hard classification approaches cannot be applied because of sub-pixel heterogeneity. We evaluate neural networks as a modeling tool for sub-pixel crop acreage estimation. The proposed methodology is based on the assumption that different cover type proportions within coarse pixels prompt changes in time profiles of remotely sensed vegetation indices like the Normalized Difference Vegetation Index (NDVI. Neural networks can learn the relation between temporal NDVI signatures and the sought crop acreage information. This learning step permits a non-linear unmixing of the temporal information provided by coarse resolution satellite sensors. For assessing the feasibility and accuracy of the approach, a study region in central Italy (Tuscany was selected. The task consisted of mapping the spatial distribution of winter crops abundances within 1 km AVHRR pixels between 1988 and 2001. Reference crop acreage information for network training and validation was derived from high resolution Thematic Mapper/Enhanced Thematic Mapper (TM/ETM+ images and official agricultural statistics. Encouraging results were obtained demonstrating the potential of the proposed approach. For example, the spatial distribution of winter crop acreage at sub-pixel level was mapped with a cross-validated coefficient of determination of 0.8 with respect to the reference information from high resolution imagery. For the eight years for which

  9. Modeling water and heat balance components of large territory for vegetation season using information from polar-orbital and geostationary meteorological satellites

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

    2015-04-01

    To date, physical-mathematical modeling processes of land surface-atmosphere interaction is considered to be the most appropriate tool for obtaining reliable estimates of water and heat balance components of large territories. The model of these processes (Land Surface Model, LSM) developed for vegetation period is destined for simulating soil water content W, evapotranspiration Ev, vertical latent LE and heat fluxes from land surface as well as vertically distributed soil temperature and moisture, soil surface Tg and foliage Tf temperatures, and land surface skin temperature (LST) Ts. The model is suitable for utilizing remote sensing data on land surface and meteorological conditions. In the study these data have been obtained from measurements by scanning radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua, SEVIRI/geostationary satellites Meteosat-9, -10 (MSG-2, -3). The heterogeneity of the land surface and meteorological conditions has been taken into account in the model by using soil and vegetation characteristics as parameters and meteorological characteristics as input variables. Values of these characteristics have been determined from ground observations and remote sensing information. So, AVHRR data have been used to build the estimates of effective land surface temperature (LST) Ts.eff and emissivity E, vegetation-air temperature (temperature at the vegetation level) Ta, normalized vegetation index NDVI, vegetation cover fraction B, the leaf area index LAI, and precipitation. From MODIS data the values of LST Tls, Å, NDVI, LAI have been derived. From SEVIRI data there have been retrieved Tls, E, Ta, NDVI, LAI and precipitation. All named retrievals covered the vast territory of the part of the agricultural Central Black Earth Region located in the steppe-forest zone of European Russia. This territory with coordinates 49°30'-54°N, 31°-43°E and a total area of 227,300 km2 has been chosen for investigation. It has been carried out for years 2009

  10. Assimilation of simulated satellite altimetric data and ARGO temperature data into a double-gyre NEMO ocean model

    Science.gov (United States)

    Yan, Yajing; Barth, Alexander; Laenen, François; Beckers, Jean-Marie

    2013-04-01

    In recent years, data assimilation, adressing the problem of producing useful analyses and forecasts given imperfect dynamical models and observations, has shown increasing interest in the atmosphere and ocean science community. The efficiency of data assimilation in improving the model prediction has been proven by numerous work. However, it is still a challenge to design operational data assimilation schemes which can be operated with realistic ocean models, with reasonable quality and at acceptable cost. In this work, several experiments, assimilating the simulated altimetry and temperature observations into a double-gyre NEMO ocean model, are performed with objective to investigate the impact of different assimilation setups, including changing the observation distribution, the ensemble size and the localisation scale, on the quality of the analysis. The double-gyre NEMO ocean model corresponds to an idealized configuration of the NEMO model: a square and 5000-meter deep flat bottom ocean at mid latitudes (the so called square-box or SQB configuration). The main physical parameters governing the dominant characteristics of the flow are the initial stratification, the wind stress, the bottom friction and the lateral mixing parameterization. The domain extends from 24N to 44N, over 30° in longitude (60W - 30W) with 11 vertical levels between 152 m and 4613 m in depth. The minimum horizontal resolution of the model is 1/4°. The observations are generated from the model simulations (the truth) by adding spatially uncorrelated gaussian noise with given standard deviation. Two types of observation are considered : sea surface height (SSH) and temperature. The observation grid of the SSH is simulated from the ENVISAT and Jason-1 satellite tracks, and that of the temperature is generated in order to mimic the ARGO float profile. The observation localisation is performed in order to avoid spurious correlation at large distance. For this, the observations are weighted

  11. Trend Assessment of Spatio-Temporal Change of Tehran Heat Island Using Satellite Images

    Science.gov (United States)

    Saradjian, M. R.; Sherafati, Sh.

    2015-12-01

    Numerous investigations on Urban Heat Island (UHI) show that land cover change is the main factor of increasing Land Surface Temperature (LST) in urban areas, especially conversion of vegetation and bare soil to concrete, asphalt and other man-made structures. On the other hand, other human activities like those which cause to burning fossil fuels, that increase the amount of carbon dioxide, may raise temperature in global scale in comparison with small scales (urban areas). In this study, multiple satellite images with different spatial and temporal resolutions have been used to determine Land Surface Temperature (LST) variability in Tehran metropolitan area. High temporal resolution of AVHRR images have been used as the main data source when investigating temperature variability in the urban area. The analysis shows that UHI appears more significant at afternoon and night hours. But the urban class temperature is almost equal to its surrounding vegetation and bare soil classes at around noon. It also reveals that there is no specific difference in UHI intense during the days throughout the year. However, it can be concluded that in the process of city expansion in years, UHI has been grown both spatially and in magnitude. In order to locate land-cover types and relate them to LST, Thematic Mapper (TM) images have been exploited. The influence of elevation on the LST has also been studied, using digital elevation model derived from SRTM database.

  12. TREND ASSESSMENT OF SPATIO-TEMPORAL CHANGE OF TEHRAN HEAT ISLAND USING SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. R. Saradjian

    2015-12-01

    Full Text Available Numerous investigations on Urban Heat Island (UHI show that land cover change is the main factor of increasing Land Surface Temperature (LST in urban areas, especially conversion of vegetation and bare soil to concrete, asphalt and other man-made structures. On the other hand, other human activities like those which cause to burning fossil fuels, that increase the amount of carbon dioxide, may raise temperature in global scale in comparison with small scales (urban areas. In this study, multiple satellite images with different spatial and temporal resolutions have been used to determine Land Surface Temperature (LST variability in Tehran metropolitan area. High temporal resolution of AVHRR images have been used as the main data source when investigating temperature variability in the urban area. The analysis shows that UHI appears more significant at afternoon and night hours. But the urban class temperature is almost equal to its surrounding vegetation and bare soil classes at around noon. It also reveals that there is no specific difference in UHI intense during the days throughout the year. However, it can be concluded that in the process of city expansion in years, UHI has been grown both spatially and in magnitude. In order to locate land-cover types and relate them to LST, Thematic Mapper (TM images have been exploited. The influence of elevation on the LST has also been studied, using digital elevation model derived from SRTM database.

  13. Space simulation chambers for complete satellites: High vacuum and extreme temperatures challenges; Camaras de simulacion espacial para satelites completos: los retos de alto vacio y temperaturas extremas

    Energy Technology Data Exchange (ETDEWEB)

    Galan, M.; Cazador, M.

    2010-07-01

    During any satellite development phase, many operational factors can only be experimentally determined by testing under the most extreme environmental conditions that will be encountered in its life. Simulating the different temperatures, thermal loads and vacuum conditions allows analyzing the suitability of new materials, components and systems for these extreme conditions. In a space project, thermal vacuum testing reaches 70% of the total testing costs. They are the most similar conditions to the real ones that will be encountered in the outer space.In this article, the function of both the thermal and vacuum subsystems are explained and analyzed.Thermal control units are the most fundamental part in a space simulation chamber; they must cover the required extreme temperature range with the required heating and cooling speed. The vacuum subsystem must allow reaching the required operating pressure within the specified time, handling significant degassing loads both from the satellite and the large exposed surfaces inside the chamber. (Author) 6 refs.

  14. AVHRR CoastWatch Gulf of Mexico Regional Node Data, May 1991-March 2004 (NODC Accession 0121317)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The sea surface temperature (SST) products were derived from NOAA's Polar-orbiting Operational Environmental Satellites (POES) for the coastal United States and...

  15. Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates

    Science.gov (United States)

    Steffen, Konrad; Key, J.; Maslanik, J.; Schweiger, A.

    1993-01-01

    This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.

  16. NOAA Climate Data Record (CDR) of Visible and Near Infrared Reflectance from GOES and AVHRR, Version 1.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The AVHRR visible gains and offsets convert GAC pixel level counts to radiances and are provided for each visible band encompassing TIROS-N, NOAA-6 through NOAA-19...

  17. NOAA Climate Data Record (CDR) of Cloud Properties from AVHRR Pathfinder Atmospheres - Extended (PATMOS-x), Version 5.3

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This NOAA Climate Data Record (CDR) of cloud products was produced by the University of Wisconsin using the AVHRR Pathfinder Atmospheres - Extended (PATMOS-X)...

  18. Sea Surface Temperature Climate Data Record for the North Sea and Baltic Sea

    DEFF Research Database (Denmark)

    Høyer, Jacob L.; Karagali, Ioanna

    2016-01-01

    A 30-yr climate data record (CDR) of sea surface temperature (SST) has been produced with daily gap-free analysis fields for the North Sea and the Baltic Sea region from 1982 to 2012 by combining the Pathfinder AVHRR satellite data record with the Along-Track Scanning Radiometer (ATSR) Reprocessing...... observations on average. Validation against independent in situ observations shows a very stable performance of the data record, with a mean difference of -0.06 °C compared to moored buoys and a 0.46 °C standard deviation of the differences. The mean annual biases of the SST CDR are small for all years......, with a negligible temporal trend when compared against drifting and moored buoys. Analysis of the SST CDR reveals that the monthly anomalies for the North Sea, the Danish straits, and the central Baltic Sea regions show a high degree of correlation for interannual and decadal time scales, whereas the monthly...

  19. Surface flow structure of the Gulf Stream from composite imagery and satellite-tracked drifters

    Directory of Open Access Journals (Sweden)

    C. P. Mullen

    1994-01-01

    Full Text Available A unique set of coutemporaneous satellite-tracked drifters and five-day composite Advanced Very High Resolution Radionmeter (AVHRR satellite imagery of the North Atlantic has been analyzed to examine the surface flow structure of the Gulf Stream. The study region was divided into two sections, greater than 37° N and less than 37° N, in order to answer the question of geographic variability. Fractal and spectral analyses methods were applied to the data. Fractal analysis of the Lagrangian trajectories showed a fractal dimension of 1.21 + 0.02 with a scaling range of 83 - 343 km. The fractal dimension of the temperature fronts of the composite imagery is similar for the two regions with D = 1.11 + 0.01 over a scaling range of 4 - 44 km. Spectral analysis also reports a fairly consistent value for the spectral slope and its scaling range. Therefore, we conclude there is no geographic variability in the data set. A suitable scaling range for this contemporaneous data set is 80 - 200 km which is consistent with the expected physical conditions in the region. Finally, we address the idea of using five-day composite imagery to infer the surface flow of the Gulf Stream. Close analyses of the composite thermal fronts and the Lagrangian drifter trajectories show that the former is not a good indicator of the latter.

  20. ANALISA PERBANDINGAN CURAH HUJAN BERDASARKAN DATA CITRA NOAA AVHRR DENGAN DATA CURAH HUJAN DI LAPANGAN

    Directory of Open Access Journals (Sweden)

    Muammar Muzayyin Ramadlon

    2015-02-01

    Full Text Available Peraturan Pemerintah No. 26 tahun 2008 menjelaskan bahwa Pulau Jawa merupakan salah satu kawasan strategis nasional (KSN sebagai kawasan pertumbuhan ekonomi yang meliputi Provinsi Jawa Timur, Provinsi Jawa Tengah, Provinsi DI Yogyakarta, Provinsi Jawa Barat, Provinsi DKI Jakarta, dan Provinsi Banten. Bidang pertanian merupakan salah satu sektor andalan kawasan Pulau Jawa. Salah satu visi misi wilayah Pulau Jawa yaitu peningkatan lahan produktif untuk peningkatan produktivitas pertanian. Salah satu faktor penunjang yang dibutuhkan dalam peningkatan produktivitas pertanian adalah pengetahuan tentang distribusi curah hujan. Penelitian ini akan membahas dan menganalisa tentang tingkat curah hujan di Pulau Jawa menggunakan metode penginderaan jauh dari data citra satelit NOAA AVHRR. Hasil pengolahan dari citra NOAA AVHRR tersebut kemudian dianalisa dengan cara membandingkan data tersebut dengan data curah hujan hasil pengukuran in situ yang didapat dari Badan Meteorologi Klimatologi dan Geofisika (BMKG pusat. Algoritma yang digunakan pada penelitian ini menggunakan algoritma suhu kecerahan yang dirumuskan oleh Parwati (2009. Hasil yang diperoleh dari penelitian ini menunjukkan bahwa nilai korelasi (R2 antara data lapangan dengan data curah hujan NOAA AVHRR-19 pada bulan Juli sebebesar 0,430, bulan Agustus sebesar 0,499, bulan November sebesar 0,464, dan bulan Desember sebesar 0,440. Kemudian nilai intensitas curah hujan yang diperoleh dari citra NOAA AVHRR-19 berupa estimasi minimal curah hujan pada bulan November-Desember sebesar 1,806 mm/jam dan estimasi maksimal sebesar 9,304 mm/jam. sedangkan pada pada bulan Juli-Agustus, nilai estimasi minimal curah hujan sebesar 0,0 mm/jam dan estimasi maksimal sebesar 5,047 mm/jam.

  1. Upper ocean currents and sea surface temperatures (SST) from Satellite-tracked drifting buoys (drifters) as part of the Global Drifter Program for Hawaii region 1980/02/01 - 2009/03/31 (NODC Accession 0063296)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Satellite-tracked drifting buoys ("drifters") collect measurements of upper ocean currents and sea surface temperatures (SST) around the world as part of the Global...

  2. Satellite- versus temperature-derived green wave indices for predicting the timing of spring migration of avian herbivores

    NARCIS (Netherlands)

    Shariati Najafabadi, M.; Darvishzadeh, R.; Skidmore, A.K.; Kölzsch, A.; Vrieling, A.; Nolet, B.A.; Exo, K.; Meratnia, N.; Havinga, P.J.M.; Stahl, J.; Toxopeus, A.G.

    2015-01-01

    According to the green wave hypothesis, herbivores follow the flush of spring growth of forage plants during their spring migration to northern breeding grounds. In this study we compared two green wave indices for predicting the timing of the spring migration of avian herbivores: the satellite-deri

  3. Evaluation of NPP VIIRS Vegetation Index EDR performance using MODIS and AVHRR data records

    Science.gov (United States)

    vargas, M.; Shabanov, N.; Miura, T.

    2012-12-01

    Vegetation Index (VI) is one key parameter to specify the boundary condition in global climate models, weather forecasting models and numerous remote sensing applications for monitoring environmental state and its change. The VI Environmental Data Record (EDR), which includes the Top of Atmosphere Normalized Difference Vegetation Index (TOA NDVI) and the Top of Canopy Enhanced Vegetation Index (TOC EVI), is currently operationally generated from data delivered by the Visible Infrared Imaging radiometer Suite (VIIRS) instrument onboard the National Polar-orbiting Partnership (NPP) platform launched in October 2011. The VI EDR was implemented to provide continuity for 30+ years of historical VI records provided by MODIS and AVHRR sensors. This presentation reports on the results of the analysis performed by the JPSS VI group at NOAA-NESDIS-STAR on two major aspects of performance of the VI EDR in the early phase of the NPP mission: (1) assessment of accuracy of the VIIRS VI EDR product with respect to input data including Surface Reflectances, Cloud and Aerosol masks as function of vegetation (biome) types; (2) temporal and spatial consistency of VIIRS VI EDR with respect to heritage MODIS and AVHRR VI products. This analysis is based on data from VIIRS (daily TOA NDVI and TOC EVI, and daily surface reflectances), Terra MODIS (16 days composites of TOC EVI and TOC NDVI, and daily TOA radiances) and NOAA-18 AVHRR (7-days composites of TOA NDVI). MODIS 8-biome landcover mask was used to quantify variations in VI product performance as function of vegetation type. Best overall agreement is achieved between VIIRS and MODIS data (TOC EVI and TOC NDVI) in terms of minimum systematic discrepancy (minimum bias and STD) and highest correlation of spatial patterns (highest r^2). The agreement is highest for biomes with low vegetation cover, but degrades with increased foliage density. VIIRS cloud mask provides a fair screening of daily data over the globe. While performance of

  4. From skin to bulk: An adjustment technique for assimilation of satellite-derived temperature observations in numerical models of small inland water bodies

    Science.gov (United States)

    Javaheri, Amir; Babbar-Sebens, Meghna; Miller, Robert N.

    2016-06-01

    Data Assimilation (DA) has been proposed for multiple water resources studies that require rapid employment of incoming observations to update and improve accuracy of operational prediction models. The usefulness of DA approaches in assimilating water temperature observations from different types of monitoring technologies (e.g., remote sensing and in-situ sensors) into numerical models of in-land water bodies (e.g., lakes and reservoirs) has, however, received limited attention. In contrast to in-situ temperature sensors, remote sensing technologies (e.g., satellites) provide the benefit of collecting measurements with better X-Y spatial coverage. However, assimilating water temperature measurements from satellites can introduce biases in the updated numerical model of water bodies because the physical region represented by these measurements do not directly correspond with the numerical model's representation of the water column. This study proposes a novel approach to address this representation challenge by coupling a skin temperature adjustment technique based on available air and in-situ water temperature observations, with an ensemble Kalman filter based data assimilation technique. Additionally, the proposed approach used in this study for four-dimensional analysis of a reservoir provides reasonably accurate surface layer and water column temperature forecasts, in spite of the use of a fairly small ensemble. Application of the methodology on a test site - Eagle Creek Reservoir - in Central Indiana demonstrated that assimilation of remotely sensed skin temperature data using the proposed approach improved the overall root mean square difference between modeled surface layer temperatures and the adjusted remotely sensed skin temperature observations from 5.6°C to 0.51°C (i.e., 91% improvement). In addition, the overall error in the water column temperature predictions when compared with in-situ observations also decreased from 1.95°C (before assimilation

  5. A closer look at the climatological discontinuities present in the NCEP/NCAR reanalysis temperature due to the introduction of satellite data

    Energy Technology Data Exchange (ETDEWEB)

    Sturaro, G. [Institute of Atmospheric Sciences and Climate, CNR-ISAC, Unita Operativa Clima e Microclima, Corso Stati Uniti, 4 I-35127 Padova (Italy)

    2003-09-01

    Principal component analysis was applied to NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalyses data for monthly temperature at given pressure levels between 1948-2000. The series composed with the time coefficients of the main components were tested for possible discontinuities. The study proved useful in gaining a better understanding of the impact of satellite observations in the reanalyses. The period 1975-1979 proved to be the most affected by inhomogeneities, in particular in August-September 1976 and December 1978-January 1979. The latter time corresponds with the introduction of satellite infrared and microwave retrievals, which gave global coverage to the observing network. Inhomogeneities due to satellite data especially affect patterns in the tropics for levels between 700 and 50 hPa and over the Southern Ocean in the layer 500 to 250 hPa, i.e. the affected regions are larger than previously determined with other methods. Greatest shifts were observed in the tropics at 100 and 150 hPa, where the discontinuity is equal to 1.6-2.0 standard deviations. (orig.)

  6. Satellite Data Product and Data Dissemination Updates for the SPoRT Sea Surface Temperature Composite Product

    Science.gov (United States)

    Zavodsky, Bradley; LaFontaine, Frank; Berndt, Emily; Meyer, Paul; Jedlovec, Gary

    2017-01-01

    The SPoRT SST composite is a reliable and robust high-resolution product generated twice per day in near real time. It incorporates highest quality data satellite data from infrared imagers and global analysis from NESDIS and UKMO. Recent updates to the product include the inclusion of VIIRS data to extend the life of the product beyond the MODIS era. It is used by a number of users in their DSS.

  7. Assimilation of satellite information in a snowpack model to improve characterization of snow cover for runoff simulation and forecasting

    Directory of Open Access Journals (Sweden)

    L. S. Kuchment

    2009-08-01

    Full Text Available A new technique for constructing spatial fields of snow characteristics for runoff simulation and forecasting is presented. The technique incorporates satellite land surface monitoring data and available ground-based hydrometeorological measurements in a physical based snowpack model. The snowpack model provides simulation of temporal changes of the snow depth, density and water equivalent (SWE, accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with a special focus on forest cover effects. The model was first calibrated against available ground-based snow measurements and then was applied to calculate the spatial distribution of snow characteristics using satellite data and interpolated ground-based meteorological data. The remote sensing data used in the model consist of products derived from observations of MODIS and AMSR-E instruments onboard Terra and Aqua satellites. They include daily maps of snow cover, snow water equivalent (SWE, land surface temperature, and weekly maps of surface albedo. Maps of land cover classes and tree cover fraction derived from NOAA AVHRR were used to characterize the vegetation cover. The developed technique was tested over a study area of approximately 200 000 km2 located in the European part of Russia (56° N to 60° N, and 48° E to 54° E. The study area comprises the Vyatka River basin with the catchment area of 124 000 km2. The spatial distributions of SWE, obtained with the coupled model, as well as solely from satellite data were used as the inputs in a physically-based model of runoff generation to simulate runoff hydrographs on the Vyatka river for spring seasons of 2003, 2005. The comparison of simulated hydrographs with the observed ones has shown that suggested procedure gives a higher accuracy of snow cover spatial distribution representation and hydrograph simulations than the direct use of satellite SWE data.

  8. Assimilation of satellite information in a snowpack model to improve characterization of snow cover for runoff simulation and forecasting

    Science.gov (United States)

    Kuchment, L. S.; Romanov, P.; Gelfan, A. N.; Demidov, V. N.

    2009-08-01

    A new technique for constructing spatial fields of snow characteristics for runoff simulation and forecasting is presented. The technique incorporates satellite land surface monitoring data and available ground-based hydrometeorological measurements in a physical based snowpack model. The snowpack model provides simulation of temporal changes of the snow depth, density and water equivalent (SWE), accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with a special focus on forest cover effects. The model was first calibrated against available ground-based snow measurements and then was applied to calculate the spatial distribution of snow characteristics using satellite data and interpolated ground-based meteorological data. The remote sensing data used in the model consist of products derived from observations of MODIS and AMSR-E instruments onboard Terra and Aqua satellites. They include daily maps of snow cover, snow water equivalent (SWE), land surface temperature, and weekly maps of surface albedo. Maps of land cover classes and tree cover fraction derived from NOAA AVHRR were used to characterize the vegetation cover. The developed technique was tested over a study area of approximately 200 000 km2 located in the European part of Russia (56° N to 60° N, and 48° E to 54° E). The study area comprises the Vyatka River basin with the catchment area of 124 000 km2. The spatial distributions of SWE, obtained with the coupled model, as well as solely from satellite data were used as the inputs in a physically-based model of runoff generation to simulate runoff hydrographs on the Vyatka river for spring seasons of 2003, 2005. The comparison of simulated hydrographs with the observed ones has shown that suggested procedure gives a higher accuracy of snow cover spatial distribution representation and hydrograph simulations than the direct use of satellite SWE data.

  9. Satellite Communication.

    Science.gov (United States)

    Technology Teacher, 1985

    1985-01-01

    Presents a discussion of communication satellites: explains the principles of satellite communication, describes examples of how governments and industries are currently applying communication satellites, analyzes issues confronting satellite communication, links mathematics and science to the study of satellite communication, and applies…

  10. Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

    Science.gov (United States)

    Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

    2012-01-01

    The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters

  11. All sky imaging observations in visible and infrared waveband for validation of satellite cloud and aerosol products

    Science.gov (United States)

    Lu, Daren; Huo, Juan; Zhang, W.; Liu, J.

    A series of satellite sensors in visible and infrared wavelengths have been successfully operated on board a number of research satellites, e.g. NOAA/AVHRR, the MODIS onboard Terra and Aqua, etc. A number of cloud and aerosol products are produced and released in recent years. However, the validation of the product quality and accuracy are still a challenge to the atmospheric remote sensing community. In this paper, we suggest a ground based validation scheme for satellite-derived cloud and aerosol products by using combined visible and thermal infrared all sky imaging observations as well as surface meteorological observations. In the scheme, a visible digital camera with a fish-eye lens is used to continuously monitor the all sky with the view angle greater than 180 deg. The digital camera system is calibrated for both its geometry and radiance (broad blue, green, and red band) so as to a retrieval method can be used to detect the clear and cloudy sky spatial distribution and their temporal variations. A calibrated scanning thermal infrared thermometer is used to monitor the all sky brightness temperature distribution. An algorithm is developed to detect the clear and cloudy sky as well as cloud base height by using sky brightness distribution and surface temperature and humidity as input. Based on these composite retrieval of clear and cloudy sky distribution, it can be used to validate the satellite retrievals in the sense of real-simultaneous comparison and statistics, respectively. What will be presented in this talk include the results of the field observations and comparisons completed in Beijing (40 deg N, 116.5 deg E) in year 2003 and 2004. This work is supported by NSFC grant No. 4002700, and MOST grant No 2001CCA02200

  12. A 30+ Year AVHRR Land Surface Reflectance Climate Data Record and Its Application to Wheat Yield Monitoring

    Directory of Open Access Journals (Sweden)

    Belen Franch

    2017-03-01

    Full Text Available The Advanced Very High Resolution Radiometer (AVHRR sensor provides a unique global remote sensing dataset that ranges from the 1980s to the present. Over the years, several efforts have been made on the calibration of the different instruments to establish a consistent land surface reflectance time-series and to augment the AVHRR data record with data from other sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS. In this paper, we present a summary of all the corrections applied to the AVHRR surface reflectance and NDVI Version 4 Product, developed in the framework of the National Oceanic and Atmospheric Administration (NOAA Climate Data Record (CDR program. These corrections result from assessment of the geolocation, improvement of cloud masking, and calibration monitoring. Additionally, we evaluate the performance of the surface reflectance over the AERONET sites by a cross-comparison with MODIS, which is an already validated product, and evaluation of a downstream leaf area index (LAI product. We demonstrate the utility of this long time-series by estimating the winter wheat yield over the USA. The methods developed by Becker-Reshef et al. (2010 and Franch et al. (2015 are applied to both the MODIS and AVHRR data. Comparison of the results from both sensors during the MODIS-era shows the consistency of the dataset with similar errors of 10%. When applying the methods to AVHRR historical data from the 1980s, the results have errors equivalent to those derived from MODIS.

  13. Detection, emission estimation and risk prediction of forest fires in China using satellite sensors and simulation models in the past three decades--an overview.

    Science.gov (United States)

    Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K

    2011-08-01

    Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.

  14. Progress in Understanding the Pre-Earthquake Associated Events by Analyzing IR Satellite Data

    Science.gov (United States)

    Ouzounov, Dimitar; Taylor, Patrick; Bryant, Nevin

    2004-01-01

    We present latest result in understanding the potential relationship between tectonic stress, electro-chemical and thermodynamic processes in the Earths crust and atmosphere with an increase in IR flux as a potential signature of electromagnetic (EM) phenomena that are related to earthquake activity, either pre-, co- or post seismic. Thermal infra-red (TIR) surveys performed by the polar orbiting (NOAA/AVHRR MODIS) and geosynchronous weather satellites (GOES, METEOSAT) gave an indication of the appearance (from days to weeks before the event) of "anomalous" space-time TIR transients that are associated with the location (epicenter and local tectonic structures) and time of a number of major earthquakes with M>5 and focal depths less than 50km. We analyzed broad category of associated pre-earthquake events, which provided evidence for changes in surface temperature, surface latent heat flux, chlorophyll concentrations, soil moisture, brightness temperature, emissivity of surface, water vapour in the atmosphere prior to the earthquakes occurred in Algeria, India, Iran, Italy, Mexico and Japan. The cause of such anomalies has been mainly related to the change of near-surface thermal properties due to complex lithosphere-hydrosphere-atmospheric interactions. As final results we present examples from the most recent (2000-2004) worldwide strong earthquakes and the techniques used to capture the tracks of EM emission mid-IR anomalies and a methodology for practical future use of such phenomena in the early warning systems.

  15. The effect of temperature cycling typical of low earth orbit satellites on thin films of YBa2Cu3O(7-x)

    Science.gov (United States)

    Mogro-Campero, A.; Turner, L. G.; Bogorad, A.; Herschitz, R.

    1990-01-01

    The refrigeration of superconductors in space poses a challenging problem. The problem could be less severe if superconducting materials would not have to be cooled when not in use. Thin films of the YBa2Cu3O(7-x) (YBCO) superconductor were subjected to thermal cycling, which was carried out to simulate a large number of eclipses of a low earth orbit satellite. Electrical measurements were performed to find the effect of the temperature cycling. Thin films of YBCO were formed by coevaporation of Y, BaF2, and Cu and postannealing in wet oxygen at 850 C for 3.5 h. The substrates used were (100) SrTiO3, polycrystalline alumina, and oxidized silicon; the last two have an evaporated zirconia layer. Processing and microstructure studies of these types of films have been published. THe zero resistance transition temperatures of the samples used in this study were 91, 82, and 86 K, respectively. The samples were characterized by four point probe electrical measurements as a function of temperature. The parameters measured were: the zero resistance transition temperature, the 10 to 90 percent transition width, and the room temperature resistance, normalized to that measured before temperature cycling. The results for two samples are presented. Each sample had a cumulative exposure. Cycling in atmospheric pressure nitrogen was performed at a rate of about 60 cycles per day, whereas in vacuum the rate was only about 10 cycles per day. The results indicate only little or no changes in the parameters measured. Degradation of superconducting thin films of YBCO has been reported due to storage in nitrogen. It is believed that the relatively good performance of films after temperature cycling is related to the fact that BaF2 was used as an evaporation source. The latest result on extended temperature cycling indicates significant degradation. Further tests of extended cycling will be carried out to provide additional data and to clarify this preliminary finding.

  16. Food Security Through the Eyes of AVHRR: Changes and Variability of African Food Production

    Science.gov (United States)

    Vrieling, A.; de Beurs, K. M.; Brown, M. E.

    2008-12-01

    Food security is defined by FAO as a situation that exists when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life. Despite globalization and food trade, access to food remains a major problem for an important part of Africa's population. As a contribution to the food security analysis we identify at a coarse scale where trends and high interannual variability of food production occur within Africa. We use the 8-km resolution AVHRR NDVI 15-day composites of the GIMMS group (1981-2006). Two methods were applied to extract phenology indicators from the dataset. The indicators are start of season, length of season, time of maximum NDVI, maximum NDVI, and cumulated NDVI over the season. To focus the analysis on food production we spatially aggregate the annual indicators at sub-national level using a general crop mask. Persistent changes during the 26-year period were assessed using trend analysis on the yearly aggregated indicators. These trends may indicate changes in production, and consequent potential increases of food insecurity. We evaluate then where strong interannual variability of phenology indicators occurs. This relates to regular shortages of food availability. For Africa, field information on phenology or accurate time series of production figures at the sub-national scale are scarce. Validating the outcome of the AVHRR analysis is consequently difficult. We propose to use crop-specific national FAOSTAT yield statistics. For this purpose, we aggregate phenology outputs per country using specific masks for the major staple food crops. Although data quality and scale issues influence results, for several countries and crops significant positive correlations between indicators and crop production exist. We conclude that AVHRR-derived phenology information can provide useful inputs to food security analysis.

  17. Optimized High Temperature PEM Fuel Cell & High Pressure PEM Electrolyser for Regenerative Fuel Cell Systems in GEO Telecommunication Satellites

    Directory of Open Access Journals (Sweden)

    Farnes Jarle

    2017-01-01

    Full Text Available Next generation telecommunication satellites will demand increasingly more power. Power levels up to 50 kW are foreseen for the next decades. Battery technology that can sustain up to 50 kW for eclipse lengths of up to 72 minutes will represent a major impact on the total mass of the satellite, even with new Li-ion battery technologies. Regenerative fuel cell systems (RFCS were identified years ago as a possible alternative to rechargeable batteries. CMR Prototech has investigated this technology in a series of projects initiated by ESA focusing on both the essential fuel cell technology, demonstration of cycle performance of a RFCS, corresponding to 15 years in orbit, as well as the very important reactants storage systems. In the last two years the development has been focused towards optimising the key elements of the RFCS; the HTPEM fuel cell and the High Pressure PEM electrolyser. In these ESA activities the main target has been to optimise the design by reducing the mass and at the same time improve the performance, thus increasing the specific energy. This paper will present the latest development, including the main results, showing that significant steps have been taken to increase TRL on these key components.

  18. Using NOAA-AVHRR estimates of land surface temperature for regional agrometeoro[lo]gical modelling

    NARCIS (Netherlands)

    Wit, de A.J.W.; Boogaard, H.L.; Diepen, van C.A.

    2004-01-01

    This paper presents a case study on the use of features derived from remote sensing data for mapping the highly fragmented semideciduous Atlantic forest in Brazil. Innovative aspects of this research include the evaluation of different feature sets in order to improve land cover mapping. The feature

  19. Characterization of urban heat island effects over Asian megacities with hourly LST maps derived from Japanese geostationary satellite data

    Science.gov (United States)

    Oyoshi, K.; Tamura, M.

    2009-12-01

    Asian countries are expected to continue economic growth with high rate and urban structure can be transformed dramatically. Urbanization and increase in anthropogenic energy consumption cause urban heat island effect. And, Heat island effect increases cooling cost in summer and induces health problem such as heat stroke. Remotely sensed data can be powerful tool to characterize urban area and measure urban thermal conditions, because it is able to capture spatio-temporal variations in urban environments. Japanese geostationary meteorological satellite, MTSAT which covers east Asia and the western Pacific region from 140 degrees East above the equator was launched in February 2005. MTSAT provides hourly visible and thermal infrared image, and hourly Land Surface Temperature (LST) can be retrieved. Therefore, compared to polar orbiting satellites such as MODIS or AVHRR, MTSAT is expected to characterize urban thermal conditions in much detailed temporal scale. In this study, in order to evaluate thermal conditions over Asian megacities with MTSAT data, we investigated methodology for monitoring urban LST with satellite data and characterize thermal conditions by using hourly LST data. Firstly, LST were retrieved from MTSAT thermal infrared data with split-window algorithm, and it was confirmed that MTSAT is able to capture hourly spatio-temporal changes and detect urban heat island effects. Then, we constructed LST database of Asian megacities and the database was open to public on the WWW (http://eiserv.uee.kyoto-u.ac.jp/MTSAT/LST/index_e.php). Finally, by using developed LST database, characteristics of hourly temperature changes of Asian megacities were compared and categorized. And it is found that these characteristics were depend on urban structure of each city. Near-real time land surface temperature (LST) monitoring system on the WWW. Latest LST images of Asian megacities are displayed on the top page.

  20. Data Assimilation of the High-Resolution Sea Surface Temperature Obtained from the Aqua-Terra Satellites (MODIS-SST Using an Ensemble Kalman Filter

    Directory of Open Access Journals (Sweden)

    Takuji Waseda

    2013-06-01

    Full Text Available We develop an assimilation method of high horizontal resolution sea surface temperature data, provided from the Moderate Resolution Imaging Spectroradiometer (MODIS-SST sensors boarded on the Aqua and Terra satellites operated by National Aeronautics and Space Administration (NASA, focusing on the reproducibility of the Kuroshio front variations south of Japan in February 2010. Major concerns associated with the development are (1 negative temperature bias due to the cloud effects, and (2 the representation of error covariance for detection of highly variable phenomena. We treat them by utilizing an advanced data assimilation method allowing use of spatiotemporally varying error covariance: the Local Ensemble Transformation Kalman Filter (LETKF. It is found that the quality control, by comparing the model forecast variable with the MODIS-SST data, is useful to remove the negative temperature bias and results in the mean negative bias within −0.4 °C. The additional assimilation of MODIS-SST enhances spatial variability of analysis SST over 50 km to 25 km scales. The ensemble spread variance is effectively utilized for excluding the erroneous temperature data from the assimilation process.

  1. Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

    Energy Technology Data Exchange (ETDEWEB)

    Gautam, R.S.; Singh, D.; Mittal, A.; Sajin, P. [Indian Institute for Technology, Roorkee (India)

    2008-07-01

    The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots.

  2. Preliminary results on the comparison between satellite derived ground temperature and in-situ measurement of soil CO2 flux and soil temperature at Solfatara of Pozzuoli (Naples, Italy)

    Science.gov (United States)

    Cardellini, Carlo; Silvestri, Malvina; Chiodini, Giovanni; Fabrizia Buongiorno, Maria

    2014-05-01

    In this work we want to analyze the comparison between the ground temperature acquired with in-situ campaigns and the ground temperature obtained by processing remote sensing data with particular attention to ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data. Moreover we have studied the possible correlation between the CO2 measurements and the ground temperature. Test site area has been the Solfatara volcano, situated to the west of Naples, Italy. The Solfatara crater has a persistent volcanic-hydrothermal activity as demonstrate by ground deformation, seismicity and variations of the chemical-physical characteristics of the fluids emitted from fumaroles. Solfatara crater is characterized by a large soil diffuse degassing structure (Solfatara DDS, abot 0.8 km2), from where a CO2 flux in the order of 1000-1500 t/d is released by the soil. Solfatara DDS is also characterized by anomalous soil temperature. The correspondence between high CO2 fluxes and soil temperature has been interpreted as the results of the condensation of CO2-rich steam, rising from the hydrothermal system, in the uppermost part of the soil (Chiodini et al., 2001; 2005). The energy dissipated daily by the degassing at Solfatara DDS is the main source of energy release in the entire Campi Flegrei caldera in the current period (Chiodini et al., 2001; 2005). Concerning the satellite data, to monitor the thermal state of volcanic areas it is necessary to use TIR sensors with high spatial resolution in order to obtain detailed information on the areas where there are significant changes. Thanks to ASTER thermal infrared (TIR, 5 bands, 90 m spatial resolution) regions of the electromagnetic spectrum we have obtained the temperature ground map on the volcano area. For this study we have considered the ASTER's night observations that show well defined episodes of increasing thermal emission of crater thanks to a more uniform background temperature. CO2 fluxes and soil

  3. Storm impact on sea surface temperature and chlorophyll a in the Gulf of Mexico and Sargasso Sea based on daily cloud-free satellite data reconstructions

    Science.gov (United States)

    Shropshire, Taylor; Li, Yizhen; He, Ruoying

    2016-12-01

    Upper ocean responses to tropical storms/hurricanes have been extensively studied using satellite observations. However, resolving concurrent sea surface temperature (SST) and chlorophyll a (chl a) responses along storm tracks remains a major challenge due to extensive cloud coverage in satellite images. Here we produce daily cloud-free SST and chl a reconstructions based on the Data INterpolating Empirical Orthogonal Function method over a 10 year period (2003-2012) for the Gulf of Mexico and Sargasso Sea regions. Daily reconstructions allow us to characterize and contrast previously obscured subweekly SST and chl a responses to storms in the two main storm-impacted regions of the Atlantic Ocean. Statistical analyses of daily SST and chl a responses revealed regional differences in the response time as well as the response sensitivity to maximum sustained wind speed and translation speed. This study demonstrates that SST and chl a responses clearly depend on regional ocean conditions and are not as universal as might have been previously suggested.

  4. Assessing phenological change in China from 1982 to 2006 using AVHRR imagery

    Institute of Scientific and Technical Information of China (English)

    Haiyan WEI; Philip HEILMAN; Jiaguo QI; Mark A. NEARING; Zhihui GU; Yongguang ZHANG

    2012-01-01

    Long-term trends in vegetation phenology indicate ecosystem change due to the combined impacts of human activities and'climate.In this study we used 1982 to 2006 Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (AVHRR NDVI) imagery across China and the TIMESAT program to quantify annual vegetation production and its changing trend.Results showed great spatial variability in vegetation growth and its temporal trend across the country during the 25-year study period.Significant decreases in vegetation production were detected in the grasslands of Inner Mongolia,and in industrializing regions in southern China,including the Pearl River Delta,the Yangtze River Delta,and areas along the Yangtze River.Significant increases in vegetation production were found in Xinjiang,Central China,and North-east China.Validation of the NDVI trends and vegetated area changes were conducted using Landsat imagery and the results were consistent with the analysis from AVHRR data.We also found that although the causes of the vegetation change vary locally,the spatial pattern of the vegetation change and the areas of greatest impact from national policies launched in the 1970s,such as the opening of economic zones and the ‘Three-North Shelter Forest Programme',are similar,which indicates an impact of national policies on ecosystem change and that such impacts can be detected using the method described in this paper.

  5. SNOWCOVER: An approach for continuous daily snow cover Estimation from AVHRR and MODIS Imagery.

    Science.gov (United States)

    Fernandes, R.; Zhao, H.

    2008-12-01

    The Global Climate Observing System calls for historical and ongoing daily snow cover estimates at 1km resolution. Polar orbiting VNIR sensors such as NOAA AVHRR and MODIS provide sufficient historical coverage and spatial resolution to meet these requirements. However, clouds and sub-pixel variability in land surface properties remain obstacles for continuous daily snow cover estimation. We present a new approach, SNOWCOVER, capable of continuous daily estimates of snow cover using top of atmosphere thermal and visible band measurements from sensors such as NOAA AVHRR and MODIS. The approach includes a new temporal filter to identify clear sky pixels, a pixel based normalization of aquisition geometry and a robust approach, based on radiative transfer modelling, for identifying thresholds for snow discrimination. The algorithm is applied to mapping northern hemisphere snow cover and validated over in-situ snow courses in Canada and the former Soviet Union. Results indicate performance similar to Version 005 MODIS snow cover product but with 95 percent retrieval rates.

  6. Satellite sea surface temperatures along the West Coast of the United States during the 2014-2016 northeast Pacific marine heat wave

    Science.gov (United States)

    Gentemann, Chelle L.; Fewings, Melanie R.; García-Reyes, Marisol

    2017-01-01

    From January 2014 to August 2016, sea surface temperatures (SSTs) along the Washington, Oregon, and California coasts were significantly warmer than usual, reaching a maximum SST anomaly of 6.2°C off Southern California. This marine heat wave occurred alongside the Gulf of Alaska marine heat wave and resulted in major disturbances in the California Current ecosystem and massive economic impacts. Here we use satellite and blended reanalysis products to report the magnitude, extent, duration, and evolution of SSTs and wind stress anomalies along the West Coast of the continental United States during this event. Nearshore SST anomalies along the entire coast were persistent during the marine heat wave, and only abated seasonally, during spring upwelling-favorable wind stress. The coastal marine heat wave weakened in July 2016 and disappeared by September 2016.

  7. Application of SeaWIFS- and AVHRR-derived data for mesoscale and regional validation of a 3-D high-resolution physical biological model of the Gulf of St. Lawrence (Canada)

    Science.gov (United States)

    Le Fouest, V.; Zakardjian, B.; Saucier, F. J.; Çizmeli, S. A.

    2006-04-01

    We present here a first attempt to validate a regional three-dimensional (3-D) physical-biological coupled model of the Gulf of St. Lawrence with coincident Advanced Very High Resolution Radiometer (AVHRR)-derived sea surface temperature (SST) and Sea-viewing Wide Field-of-view Sensor (SeaWIFS)-derived Chlorophyll- a (Chl- a) data. The analysis focused on comparisons between remotely sensed data and simulated as well as in situ temperature, salinity, Chl- a, and nitrate. Results show that the simulated and AVHRR-derived fields of SST were qualitatively and quantitatively in agreement with in situ measurements. By contrast, marked differences were found between the simulated and SeaWIFS-derived fields of Chl- a, the latter comparing better with the freshwater-associated turbidity simulated by the model. Simulated temperature, salinity, nitrate, and Chl- a data compared well with coincident in situ measurements, and it is then suggested that freshwater-associated turbidity related to the river discharges largely contributed to the Chl- a retrievals by SeaWIFS in the Gulf's waters when using the standard OC4v.4 algorithm and atmospheric correction. Nevertheless, the striking agreement between SeaWIFS-derived ocean colour data and the simulated freshwater-associated turbidity allowed to validate the regional estuarine circulation and associated mesoscale variability. This result brings support to the model's ability to simulate realistic physical and biogeochemical fields in the Gulf of St. Lawrence.

  8. Assessment of surface dryness due to deforestation using satellite-based temperature-vegetation dryness index (TVDI) in Rondônia, Amazon

    Science.gov (United States)

    Ryu, J. H.; Cho, J.

    2016-12-01

    The Rondônia is the most deforested region in the Amazon due to human activities such as forest lumbering for the several decades. The deforestation affects to water cycle because evapotranspiration was reduced, and then soil moisture and precipitation will be changed. In this study, we assess surface dryness using satellite-based data such as moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST), normalized difference vegetation index (NDVI), albedo, TRMM Multi-sensor Precipitation Analysis (TMPA) precipitation from 2002 to 2014, and Global Ozone Monitoring Experiment-2 (GOME-2) sun-induced fluorescence (SIF) from 2007 to 2014. Temperature-vegetation dryness index (TVDI) was calculated using LST and NDVI to evaluate surface dryness during dry season (June-July). TVDI relatively represents the surface dryness on specific area and period. Forest, deforesting and deforested regions were selected in the Rondônia to assess the relative changes on surface dryness occurred from human activity. The relative TVDI (rTVDI) at deforesting region increased because of deforestation, it means that surface in deforesting region became more dryness. We also found that to assess the impact of deforestation using satellite-based precipitation and vegetation conditions such as NDVI and sun-induced fluorescence (SIF) is possible. The relative NDVI (rNDVI) and SIF decreased when TVDI increased, and two variables (rTVDI-rNDVI, rTVDI-SIF) had linear correlation. Thesis results can be helpful to comprehend impact of deforestation in Amazon, and to validate simulations of deforestation from hydrological models.

  9. TOWARD CALIBRATED MODULAR WIRELESS SYSTEM BASED AD HOC SENSORS FOR IN SITU LAND SURFACE TEMPERATURE MEASUREMENTS AS SUPPORT TO SATELLITE REMOTE SENSING

    Directory of Open Access Journals (Sweden)

    ASAAD CHAHBOUN

    2011-06-01

    Full Text Available This paper presents a new method for in situ Land Surface Temperature (LST measurements' campaigns for satellite algorithms validations. The proposed method based on Wireless Sensor Network (WSN is constituted by modules of node arrays. Each of which is constituted by 25 smart nodes scattered throughout a target field. Every node represents a Thermal Infra Red (TIR radiation sensor and keeps a minimum size while ensuring the functions of communication, sensing, and processing. This Wireless-LST (Wi-LST system is convenient to beinstalled on a field pointing to any type of targets (e.g. bare soil, grass, water, etc.. Ad hoc topology is adopted among the TIR nodes with multi-hop mesh routing protocol for communication, acquisition data are transmitted to the client tier wirelessly. Using these emergent technologies, we propose a practical method for Wi-LSTsystem calibration. TIR sensor (i.e. OSM101 from OMEGA society measures temperature, which is conditioned and amplified by an AD595 within a precision of 0.1 °C. Assessed LST is transmitted over thedeveloped ad hoc WSN modules (i.e. MICA2DOT from CROSSBOW society, and collected at in situ base station (i.e. PANASONIC CF19 laptop using an integrated database. LST is evaluated with a polynomialalgorithm structure as part of developed software. Finally, the comparison of the mean values of LST(Wi-LST in each site with the Moderate Resolution Imaging Spectro-radiometer (MODIS sensor, obtained from the daily LST product (MOD11C1 developed by the MODIS-NASA Science Team, on board TERRA satellite during the campaign period is provided.

  10. Impact of satellite-based lake surface observations on the initial state of HIRLAM. Part II: Analysis of lake surface temperature and ice cover

    Directory of Open Access Journals (Sweden)

    Homa Kheyrollah Pour

    2014-09-01

    Full Text Available This paper presents results from a study on the impact of remote-sensing Lake Surface Water Temperature (LSWT observations in the analysis of lake surface state of a numerical weather prediction (NWP model. Data assimilation experiments were performed with the High Resolution Limited Area Model (HIRLAM, a three-dimensional operational NWP model. Selected thermal remote-sensing LSWT observations provided by the Moderate Resolution Imaging Spectroradiometer (MODIS and Advanced Along-Track Scanning Radiometer (AATSR sensors onboard the Terra/Aqua and ENVISAT satellites, respectively, were included into the assimilation. The domain of our experiments, which focussed on two winters (2010–2011 and 2011–2012, covered northern Europe. Validation of the resulting objective analyses against independent observations demonstrated that the description of the lake surface state can be improved by the introduction of space-borne LSWT observations, compared to the result of pure prognostic parameterisations or assimilation of the available limited number of in-situ lake temperature observations. Further development of the data assimilation methods and solving of several practical issues are necessary in order to fully benefit from the space-borne observations of lake surface state for the improvement of the operational weather forecast. This paper is the second part of a series of two papers aimed at improving the objective analysis of lake temperature and ice conditions in HIRLAM.

  11. Temperature dependent ozone absorption cross section spectra measured with the GOME-2 FM3 spectrometer and first application in satellite retrievals

    Directory of Open Access Journals (Sweden)

    W. Chehade

    2012-10-01

    Full Text Available The Global Ozone Monitoring Experiment (GOME-2 Flight Model (FM absorption cross section spectra of ozone were measured under representative atmospheric conditions in the laboratory setup at temperatures between 203 K and 293 K in the wavelength range of 230–790 nm at a medium spectral resolution of 0.24 to 0.54 nm. Since the exact ozone amounts were unknown in the gas flow system used, the measured ozone cross sections were required to be scaled to absolute cross section units using published literature data. The Hartley, Huggins and Chappuis bands were recorded simultaneously and their temperature dependence is in good agreement with previous studies (strong temperature effect in the Huggins band and weak in the Hartley and Chappuis bands. The overall agreement of the GOME-2 FM cross sections with the literature data is well within 3%. The total ozone column retrieved from the GOME-2/MetOp-A satellite using the new cross section data is within 1% compared to the ozone amounts retrieved routinely from GOME-2.

  12. Comparison of sensible heat flux estimates using AVHRR with scintillometer measurements over semi-arid grassland in northwest Mexico

    NARCIS (Netherlands)

    Watts, C.J.; Chehbouni, A.; Rodriguez, J.C.; Kerr, Y.H.; Hartogensis, O.K.; Bruin, de H.A.R.

    2000-01-01

    The problems associated with the validation of satellite-derived estimates of the surface fluxes are discussed and the possibility of using the large aperture scintillometer is investigated. Simple models are described to derive surface temperature and sensible heat flux from the advanced very high

  13. GHRSST Level 2P Western Atlantic Regional Skin Sea Surface Temperature from the Geostationary Operational Environmental Satellites (GOES) Imager on the GOES-13 satellite (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Geostationary Operational Environmental Satellites (GOES) operated by the United States National Oceanic and Atmospheric Administration (NOAA) support weather...

  14. GHRSST Level 2P Central Pacific Regional Skin Sea Surface Temperature from the Geostationary Operational Environmental Satellites (GOES) Imager on the GOES-15 satellite (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Geostationary Operational Environmental Satellites (GOES) operated by the United States National Oceanic and Atmospheric Administration (NOAA) support weather...

  15. Satellite sea surface temperature: a powerful tool for interpreting in situ pCO{sub 2} measurements in the equatorial Pacific Ocean

    Energy Technology Data Exchange (ETDEWEB)

    Boutin, J.; Etcheto, J.; Dandonneau, Y.; Bakker, D.C.E. [CNRS/ORSTOM/UPMC, Paris (France). Lab. d`Oceanographie Dynamique et de Climatologie; Feely, R.A. [National Oceanic and Atmospheric Administration, Seattle, WA (United States). Pacific Marine Environmental Lab.; Inoue, H.Y.; Ishii, M. [Meteorological Research Inst., Tsukuba (Japan). Geochemical Lab.; Ling, R.D.; Nightingale, P.D. [Plymouth Marine Lab. (United Kingdom); Metzl, N. [LPCM, URA CNRS/UPMC, Paris (France); Wanninkhof, R. [National Oceanic and Atmospheric Administration, Miami, FL (United States). Atlantic Oceanographic and Meteorological Labs.

    1999-04-01

    In order to determine the seasonal and interannual variability of the CO{sub 2} released to the atmosphere from the equatorial Pacific, we have developed pCO{sub 2}-temperature relationships based upon shipboard oceanic CO{sub 2} partial pressure measurements, pCO{sub 2}, and satellite sea surface temperature, SST, measurements. We interpret the spatial variability in pCO{sub 2} with the help of the SST imagery. In the eastern equatorial Pacific, at 5 deg S, pCO{sub 2} variations of up to 100 {mu}atm are caused by undulations in the southern boundary of the equatorial upwelled waters. These undulations appear to be periodic with a phase and a wavelength comparable to tropical instability waves, TIW, observed at the northern boundary of the equatorial upwelling. Once the pCO{sub 2} signature of the TIW is removed from the Alize II cruise measurements in January 1991, the equatorial pCO{sub 2} data exhibit a diel cycle of about 10 {mu}atm with maximum values occurring at night. In the western equatorial Pacific, the variability in pCO{sub 2} is primarily governed by the displacement of the boundary between warm pool waters, where air-sea CO{sub 2} fluxes are weak, and equatorial upwelled waters which release high CO{sub 2} fluxes to the atmosphere. We detect this boundary using satellite SST maps. East of the warm pool, {Delta}P is related to SST and SST anomalies. The 1985-1997 CO{sub 2} flux is computed in a 5 deg wide latitudinal band as a combination of {Delta}P and CO{sub 2} exchange coefficient, K, deduced from satellite wind speeds, U. It exhibits up to a factor 2 seasonal variation caused by K-seasonal variation and a large interannual variability, a factor 5 variation between 1987 and 1988. The interannual variability is primarily driven by displacements of the warm pool that makes the surface area of the outgassing region variable. The contribution of {Delta}P to the flux variability is about half the contribution of K. The mean CO{sub 2} flux computed

  16. A Sample-Based Forest Monitoring Strategy Using Landsat, AVHRR and MODIS Data to Estimate Gross Forest Cover Loss in Malaysia between 1990 and 2005

    Directory of Open Access Journals (Sweden)

    Peter Potapov

    2013-04-01

    Full Text Available Insular Southeast Asia is a hotspot of humid tropical forest cover loss. A sample-based monitoring approach quantifying forest cover loss from Landsat imagery was implemented to estimate gross forest cover loss for two eras, 1990–2000 and 2000–2005. For each time interval, a probability sample of 18.5 km × 18.5 km blocks was selected, and pairs of Landsat images acquired per sample block were interpreted to quantify forest cover area and gross forest cover loss. Stratified random sampling was implemented for 2000–2005 with MODIS-derived forest cover loss used to define the strata. A probability proportional to x (πpx design was implemented for 1990–2000 with AVHRR-derived forest cover loss used as the x variable to increase the likelihood of including forest loss area in the sample. The estimated annual gross forest cover loss for Malaysia was 0.43 Mha/yr (SE = 0.04 during 1990–2000 and 0.64 Mha/yr (SE = 0.055 during 2000–2005. Our use of the πpx sampling design represents a first practical trial of this design for sampling satellite imagery. Although the design performed adequately in this study, a thorough comparative investigation of the πpx design relative to other sampling strategies is needed before general design recommendations can be put forth.

  17. Robust satellite techniques for oil spill detection and monitoring

    Science.gov (United States)

    Casciello, D.; Pergola, N.; Tramutoli, V.

    Discharge of oil into the sea is one of the most dangerous, among technological hazards, for the maritime environment. In the last years maritime transport and exploitation of marine resources continued to increase; as a result, tanker accidents are nowadays increasingly frequent, continuously menacing the maritime security and safety. Satellite remote sensing could contribute in multiple ways, in particular for what concerns early warning and real-time (or near real-time) monitoring. Several satellite techniques exist, mainly based on the use of SAR (Synthetic Aperture Radar) technology, which are able to recognise, with sufficient accuracy, oil spills discharged into the sea. Unfortunately, such methods cannot be profitably used for real-time detection, because of the low observational frequency assured by present satellite platforms carrying SAR sensors (the mean repetition rate is something like 30 days). On the other hand, potential of optical sensors aboard meteorological satellites, was not yet fully exploited and no reliable techniques have been developed until now for this purpose. Main limit of proposed techniques can be found in the ``fixed threshold'' approach which makes such techniques difficult to implement without operator supervision and, generally, without an independent information on the oil spill presence that could drive the choice of the best threshold. A different methodological approach (RAT, Robust AVHRR Techniques) proposed by Tramutoli (1998) and already successfully applied to several natural and environmental emergencies related to volcanic eruptions, forest fires and seismic activity. In this paper its extension to near real-time detection and monitoring of oil spills by means of NOAA-AVHRR (Advanced Very High Resolution Radiometer) records will be described. Briefly, RAT approach is an automatic change-detection scheme that considers a satellite image as a space-time process, described at each place (x,y) and time t, by the value of

  18. NOAA Climate Data Record (CDR) of Gridded Satellite Data from ISCCP B1 (GridSat-B1) Infrared Channel Brightness Temperature, Version 2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Gridded Satellite (GridSat-B1) data provides a uniform set of quality controlled geostationary satellite observations for the visible, infrared window and...

  19. GHRSST Level 2P Western Pacific Regional Skin Sea Surface Temperature from the Multifunctional Transport Satellite 1R (MTSAT-1R) (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Multi-functional Transport Satellites (MTSAT) are a series of geostationary weather satellites operated by the Japan Meteorological Agency (JMA). MTSAT carries an...

  20. GHRSST Level 2P Western Pacific Regional Skin Sea Surface Temperature from the Multifunctional Transport Satellite 2 (MTSAT-2) (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Multi-functional Transport Satellites (MTSAT) are a series of geostationary weather satellites operated by the Japan Meteorological Agency (JMA). MTSAT carries an...

  1. Consistent forest change maps 1981 – 2000 from the AVHRR time series. Case studies for South America and Indonesia

    NARCIS (Netherlands)

    Eberenz, J.; Herold, M.; Verbesselt, J.; Wijaya, A.; Lindquist, E.; Defourny, P.; Gibbs, H.K.; Arino, O.; Achard, F.

    2015-01-01

    This study predicts global forest cover change for the 1980s and 1990s from AVHRR time series metrics in order to show how the series of consistent land cover maps for climate modeling produced by the ESA climate change initiative land cover project can be extended back in time. A Random Forest mode

  2. Assessing the consistency between AVHRR and MODIS NDVI datasets for estimating terrestrial net primary productivity over India

    Indian Academy of Sciences (India)

    R K Nayak; N Mishra; V K Dadhwal; N R Patel; M Salim; K H Rao; C B S Dutt

    2016-08-01

    This study examines the consistency between the AVHRR and MODIS normalized difference vegetation index (NDVI) datasets in estimating net primary productivity (NPP) and net ecosystem productivity (NEP) over India during 2001–2006 in a terrestrial ecosystem model. Harmonic analysis is employed to estimate seasonal components of the time series. The stationary components (representing long-termmean) of the respective NDVI time series are highly coherent and exhibit inherent natural vegetation characteristics with high values over the forest, moderate over the cropland, and small over the grassland. Both data exhibit strong semi-annual oscillations over the cropland dominated Indo-Gangetic plains while annual oscillations are strong over most parts of the country. MODIS has larger annual amplitude than that of the AVHRR. The similar variability exists on the estimates of NPP and NEP across India. In an annual scale, MODIS-based NPP budget is 1.78 PgC, which is 27% higher than the AVHRR-based estimate. It revealed that the Indian terrestrial ecosystem remained the sink of atmospheric CO$_2$during the study period with 42 TgC y$^{−1}$ NEP budget associated with MODIS-based estimate against 18 TgC y$^{−1}$ for the AVHRR-based estimate.

  3. NOAA Climate Data Record (CDR) of AVHRR Daily and Monthly Aerosol Optical Thickness over Global Oceans, Version 2.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This NOAA Climate Data Record (CDR) of Aerosol Optical Thickness (AOT) is derived from data taken over global oceans from the PATMOS-x AVHRR level-2b channel 1 (0.63...

  4. Global Cloud Detection and Distribution with Night Time using Satellite Infrared Data

    Science.gov (United States)

    Kadosaki, G.; Yamanouchi, T.; Hirasawa, N.

    2007-12-01

    Knowledge of the current climate system is necessary to clearly estimate large-scale global warming and abnormal weather in the future. Net radiation is one of the main factors that influence a climate system. The earth, which is covered by cloud of dozens of surface giving it a high albedo, reflects a large part of solar radiation. In addition, during nights, when the earth's radiation increases, the earth acts as a radiator. There is no doubt that clouds are closely related to the radiation balance. Satellite data analysis is the most useful method to understand cloud climatology. The targets are to establish an algorithm to detect clouds for night term of the earth, and to get to know more about global cloud distribution with night term. Brightness temperature difference of split window channels is used in this method. We decided three thresholds which have some slopes are used in the case of over land, open sea, and snow or ice surface including sea ice, respectively. We examined on some sensors which has difference response function in itself plat home, GLI/ADEOS2, AVHRR/NOAA, MODIS/Terra and Aqua.

  5. Using remote sensing satellite data and artificial neural network for prediction of potato yield in Bangladesh

    Science.gov (United States)

    Akhand, Kawsar; Nizamuddin, Mohammad; Roytman, Leonid; Kogan, Felix

    2016-09-01

    Potato is one of the staple foods and cash crops in Bangladesh. It is widely cultivated in all of the districts and ranks second after rice in production. Bangladesh is the fourth largest potato producer in Asia and is among the world's top 15 potato producing countries. The weather condition for potato cultivation is favorable during the sowing, growing and harvesting period. It is a winter crop and is cultivated during the period of November to March. Bangladesh is mainly an agricultural based country with respect to agriculture's contribution to GDP, employment and consumption. Potato is a prominent crop in consideration of production, its internal demand and economic value. Bangladesh has a big economic activities related to potato cultivation and marketing, especially the economic relations among farmers, traders, stockers and cold storage owners. Potato yield prediction before harvest is an important issue for the Government and the stakeholders in managing and controlling the potato market. Advanced very high resolution radiometer (AVHRR) based satellite data product vegetation health indices VCI (vegetation condition index) and TCI (temperature condition index) are used as predictors for early prediction. Artificial neural network (ANN) is used to develop a prediction model. The simulated result from this model is encouraging and the error of prediction is less than 10%.

  6. Comparison and Evaluation of Annual NDVI Time Series in China Derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 Products.

    Science.gov (United States)

    Guo, Xiaoyi; Zhang, Hongyan; Wu, Zhengfang; Zhao, Jianjun; Zhang, Zhengxiang

    2017-06-06

    Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets (MOD13C1) are compared and evaluated for the period from 2001 to 2014 in China. The spatial patterns of the NDVI generally match between the LTDR V4 and MOD13C1 datasets. The transitional zone between high and low NDVI values generally matches the boundary of semi-arid and sub-humid regions. A significant and high coefficient of determination is found between the two datasets according to a pixel-based correlation analysis. The spatially averaged NDVI of LTDR V4 is characterized by a much weaker positive regression slope relative to that of the spatially averaged NDVI of the MOD13C1 dataset because of changes in NOAA AVHRR sensors between 2005 and 2006. The measured NDVI values of LTDR V4 were always higher than that of MOD13C1 in western China due to the relatively lower atmospheric water vapor content in western China, and opposite observation appeared in eastern China. In total, 18.54% of the LTDR V4 NDVI pixels exhibit significant trends, whereas 35.79% of the MOD13C1 NDVI pixels show significant trends. Good agreement is observed between the significant trends of the two datasets in the Northeast Plain, Bohai Economic Rim, Loess Plateau, and Yangtze River Delta. By contrast, the datasets contrasted in northwestern desert regions and southern China. A trend analysis of the regression slope values according to the vegetation type shows good agreement between the LTDR V4 and MOD13C1 datasets. This study demonstrates the spatial and temporal consistencies and discrepancies between the AVHRR LTDR and MODIS MOD13C1 NDVI

  7. A Model For The Use Of Satellite Remote Sensing For The Measurement Of Primary Production In The Ocean

    Science.gov (United States)

    Collins, Donald J.; Kiefer, Dale A.; SooHoo, Janice B.; Stallings, Casson; Yang, Wei-Liang

    1986-08-01

    The estimation of oceanic primary production on a global scale is the focus of efforts in remote sensing using the Coastal Zone Color Scanner (CZCS). The goal of this research is to provide a measure of the primary production using only satellite data for the estimate. This estimate requires the measurement of surface pigments (chlorophyll a + phaeophytin a) using the CZCS, an estimate of the sea-surface temperature using the AVHRR and determination of the incident solar irradiance using GOES imagery. In this paper, we describe a model of primary production based upon the responses of phytoplankton to differing light and nutrient fields. This model includes the effects on production of variations in surface pigment concentration, the mixed layer depth and the dependence on the incident solar irradiance. The model has been tested using in situ data provided by the Southern California Bight Studies (Eppley, et al., 1979), California Cooperative Fisheries Investigations (CalCOFI), Organization of Persistent Upwelling Structures (J.B. Soolloo in OPUS Data Report) and other data sets. A synoptic measure of the distribution of surface pigments is derived from the West Coast Chlorophyll and Temperature Time Series (West Coast Time Series Advisory Group, 1985). The features and behavior of the model will be presented together with the results of the model verification.

  8. Urban Surface Temperature Time Series Estimation at the Local Scale by Spatial-Spectral Unmixing of Satellite Observations

    Directory of Open Access Journals (Sweden)

    Zina Mitraka

    2015-04-01

    Full Text Available The study of urban climate requires frequent and accurate monitoring of land surface temperature (LST, at the local scale. Since currently, no space-borne sensor provides frequent thermal infrared imagery at high spatial resolution, the scientific community has focused on synergistic methods for retrieving LST that can be suitable for urban studies. Synergistic methods that combine the spatial structure of visible and near-infrared observations with the more frequent, but low-resolution surface temperature patterns derived by thermal infrared imagery provide excellent means for obtaining frequent LST estimates at the local scale in cities. In this study, a new approach based on spatial-spectral unmixing techniques was developed for improving the spatial resolution of thermal infrared observations and the subsequent LST estimation. The method was applied to an urban area in Crete, Greece, for the time period of one year. The results were evaluated against independent high-resolution LST datasets and found to be very promising, with RMSE less than 2 K in all cases. The developed approach has therefore a high potential to be operationally used in the near future, exploiting the Copernicus Sentinel (2 and 3 observations, to provide high spatio-temporal resolution LST estimates in cities.

  9. Estimation of glacier mass balance: An approach based on satellite-derived transient snowlines and a temperature index driven by meteorological observations

    Science.gov (United States)

    Tawde, S. A.; Kulkarni, A. V.; Bala, G.

    2015-12-01

    In the Himalaya, large area is comprised of glaciers and seasonal snow, mainly due to its high elevated mountain ranges. Long term and continuous assessment of glaciers in this region is important for climatological and hydrological applications. However, rugged terrains and severe weather conditions in the Himalaya lead to paucity in field observations. Therefore, in recent decades, glacier dynamics are extensively monitored using remote sensing in inaccessible terrain like Himalaya. Estimation of glacier mass balance using empirical relationship between mass balance and area accumulation ratio (AAR) requires an accurate estimate of equilibrium-line altitude (ELA). ELA is defined as the snowline at the end of the hydrological year. However, identification of ELA, using remote sensing is difficult because of temporal gaps, cloud cover and intermediate snowfall on glaciers. This leads to large uncertainty in glacier mass-balance estimates by the conventional AAR method that uses satellite-derived highest snowline in ablation season as an ELA. The present study suggests a new approach to improve estimates of ELA location. First, positions of modelled snowlines are optimized using satellite-derived snowlines in the early melt season. Secondly, ELA at the end of the glaciological year is estimated by the melt and accumulation models driven using in situ temperature and precipitation records. From the modelled ELA, mass balance is estimated using the empirical relationship between AAR and mass balance. The modelled mass balance is validated using field measurements on Chhota Shigri and Hamtah glaciers, Himachal Pradesh, India. The new approach shows a substantial improvement in glacier mass-balance estimation, reducing bias by 46% and 108% for Chhota Shigiri and Hamtah glaciers respectively. The cumulative mass loss reconstructed from our approach is 0.85 Gt for nine glaciers in the Chandra basin from 2001 to 2009. The result of the present study is in agreement with

  10. Temporal-space characterization of satellite sea surface temperature in tourist destinations: Partido de la Costa, Pinamar and Villa Gesell, Buenos Aires, Argentina

    Directory of Open Access Journals (Sweden)

    E. Verón

    2017-06-01

    Full Text Available The coastal spaces are fragile and complex areas that receive strong pressure because of the many uses and activities that are developed in them. The tourism of sun and beaches is one of the main economic practices present in these spaces that value the physical-natural conditions and their environmental variables. Of all of them, the sea surface temperature (SST has been the least studied variable, especially associated to tourist destinations. The coastal zone of the province of Buenos Aires, Argentina, concentrates numerous tourist centers like the Partido de la Costa, Pinamar and Villa Gesell that attract in the summer time, a great flow of population. The objective of the present paper was to perform a descriptive and comparative analysis of SST in these parties through the use of monthly satellite images obtained by the Aqua-MODIS satellite-sensor during the period 2003-2013. The results showed a spatial and seasonal behavior of the SST differentiated for the entire study area. The SST for the warm period (January-March ranged between 21.5 - 24.5°C and for the cold (July-September between 9.4 - 11.5°C. This difference was lower in the cold period, allowing distinguishing 3 thermal zones with variations smaller than 0.5°C between them: Costa Norte, Costa Centro- Costa Sur, and Pinamar-Villa Gesell. The warm period presented more intense spatial thermal variations between the studied tourist destinations. Four thermal zones with 0.5°C differences were identified: Costa Norte, Costa Centro, Costa Sur, and Pinamar-Villa Gesell.

  11. Some practical aspects of lossless and nearly-lossless compression of AVHRR imagery

    Science.gov (United States)

    Hogan, David B.; Miller, Chris X.; Christensen, Than Lee; Moorti, Raj

    1994-01-01

    Compression of Advanced Very high Resolution Radiometers (AVHRR) imagery operating in a lossless or nearly-lossless mode is evaluated. Several practical issues are analyzed including: variability of compression over time and among channels, rate-smoothing buffer size, multi-spectral preprocessing of data, day/night handling, and impact on key operational data applications. This analysis is based on a DPCM algorithm employing the Universal Noiseless Coder, which is a candidate for inclusion in many future remote sensing systems. It is shown that compression rates of about 2:1 (daytime) can be achieved with modest buffer sizes (less than or equal to 2.5 Mbytes) and a relatively simple multi-spectral preprocessing step.

  12. Vegetation coupling to global climate: Trajectories of vegetation change and phenology modeling from satellite observations

    Science.gov (United States)

    Fisher, Jeremy Isaac

    Important systematic shifts in ecosystem function are often masked by natural variability. The rich legacy of over two decades of continuous satellite observations provides an important database for distinguishing climatological and anthropogenic ecosystem changes. Examples from semi-arid Sudanian West Africa and New England (USA) illustrate the response of vegetation to climate and land-use. In Burkina Faso, West Africa, pastoral and agricultural practices compete for land area, while degradation may follow intensification. The Nouhao Valley is a natural experiment in which pastoral and agricultural land uses were allocated separate, coherent reserves. Trajectories of annual net primary productivity were derived from 18 years of coarse-grain (AVHRR) satellite data. Trends suggested that pastoral lands had responded rigorously to increasing rainfall after the 1980's droughts. A detailed analysis at Landsat resolution (30m) indicated that the increased vegetative cover was concentrated in the river basins of the pastoral region, implying a riparian wood expansion. In comparison, riparian cover was reduced in agricultural regions. We suggest that broad-scale patterns of increasing semi-arid West African greenness may be indicative of climate variability, whereas local losses may be anthropogenic in nature. The contiguous deciduous forests, ocean proximity, topography, and dense urban developments of New England provide an ideal landscape to examine influences of climate variability and the impact of urban development vegetation response. Spatial and temporal patterns of interannual climate variability were examined via green leaf phenology. Phenology, or seasonal growth and senescence, is driven by deficits of light, temperature, and water. In temperate environments, phenology variability is driven by interannual temperature and precipitation shifts. Average and interannual phenology analyses across southern New England were conducted at resolutions of 30m (Landsat

  13. The CACAO Method for Smoothing, Gap Filling, and Characterizing Seasonal Anomalies in Satellite Time Series

    Science.gov (United States)

    Verger, Aleixandre; Baret, F.; Weiss, M.; Kandasamy, S.; Vermote, E.

    2013-01-01

    Consistent, continuous, and long time series of global biophysical variables derived from satellite data are required for global change research. A novel climatology fitting approach called CACAO (Consistent Adjustment of the Climatology to Actual Observations) is proposed to reduce noise and fill gaps in time series by scaling and shifting the seasonal climatological patterns to the actual observations. The shift and scale CACAO parameters adjusted for each season allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. CACAO was assessed first over simulated daily Leaf Area Index (LAI) time series with varying fractions of missing data and noise. Then, performances were analyzed over actual satellite LAI products derived from AVHRR Long-Term Data Record for the 1981-2000 period over the BELMANIP2 globally representative sample of sites. Comparison with two widely used temporal filtering methods-the asymmetric Gaussian (AG) model and the Savitzky-Golay (SG) filter as implemented in TIMESAT-revealed that CACAO achieved better performances for smoothing AVHRR time series characterized by high level of noise and frequent missing observations. The resulting smoothed time series captures well the vegetation dynamics and shows no gaps as compared to the 50-60% of still missing data after AG or SG reconstructions. Results of simulation experiments as well as confrontation with actual AVHRR time series indicate that the proposed CACAO method is more robust to noise and missing data than AG and SG methods for phenology extraction.

  14. Rayleigh LIDAR and satellite (HALOE, SABER, CHAMP and COSMIC) measurements of stratosphere-mesosphere temperature over a southern sub-tropical site, Reunion (20.8° S; 55.5° E): climatology and comparison study

    CSIR Research Space (South Africa)

    Sivakumar, V

    2011-01-01

    Full Text Available For the first time, climatology of the middle atmosphere thermal structure is presented, based on 14 years of LIDAR and satellite (HALOE, SABER, CHAMP and COSMIC) temperature measurements. The data is collected over a southern sub-tropical site...

  15. Temperature Dependence of the Kondo Resonance and Its Satellites in CeCu{sub 2}Si{sub 2}

    Energy Technology Data Exchange (ETDEWEB)

    Reinert, F.; Ehm, D.; Schmidt, S.; Nicolay, G.; Huefner, S.; Kroha, J.; Trovarelli, O.; Geibel, C.

    2001-09-03

    We present high-resolution photoemission spectroscopy studies on the Kondo resonance of the strongly correlated Ce system CeCu{sub 2}Si {sub 2} . By exploiting the thermal broadening of the Fermi edge we analyze position, spectral weight, and temperature dependence of the low-energy 4f spectral features, whose major weight lies above the Fermi level E{sub F} . We also present theoretical predictions based on the single-impurity Anderson model using an extended noncrossing approximation, including all spin-orbit and crystal field splittings of the 4f states. The excellent agreement between theory and experiment provides strong evidence that the spectral properties of CeCu{sub 2}Si {sub 2} can be described by single-impurity Kondo physics down to T{approx}5 K .

  16. Analysis of Satellite sea surface temperature time series in the Brazil-Malvinas Current confluence region: Dominance of the annual and semiannual periods

    Science.gov (United States)

    Provost, Christine; Garcia, Omar; GarçOn, VéRonique

    1992-11-01

    We study the dominant periodic variations of sea surface temperature (SST) in the Brazil-Malvinas Confluence region from a satellite-derived data set compiled by Olson et al. (1988). This data set is composed of 202 sea surface temperature images with a 4 × 4 km resolution and extends over 3 years (from July 1984 to July 1987). Each image is a 5-day composite. The dominant signal, as already observed by Podesta et al. (1991), has a 1-year period. We first fit a single-frequency sinusoidal model of the annual cycle in order to estimate mean temperature, amplitude, and phase at 159 points uniformly distributed over the region. The residuals are generally small (less than 2°C). The largest departures from this cycle are located either in the Brazil-Malvinas frontal region or in the southeastern part of the region. Other periods in SST variations are identified by means of periodograms of the 159 residual time series in which the annual cycle has been substracted. The periodograms show that a semiannual frequency signal is present at almost every location. The ratio of the semiannual amplitude to the annual amplitude increases southward from 0% at 30°S to reach up to 45% at 50°S. In the south the semiannual signal creates an asymmetry, and the resulting (total) annual cycle has a cold period (winter) longer than the warm one (summer). In the frontal region the annual and semiannual signals have an important interannual variation. This semiannual frequency is associated with the semiannual wave present in the atmospheric forcing of the southern hemisphere. Differential heating over the mid-latitude oceans and the high-latitude ice-covered Antarctic Continent has been suggested as the cause of this semiannual wave (Van Loon, 1967).

  17. The spectral reflectance of water-mineral mixtures at low temperatures. [observed on natural satellites and other solar system objects

    Science.gov (United States)

    Clark, R. N.

    1981-01-01

    Laboratory reflectance spectra in the 0.325-2.5 micron region of bound water, water-mineral mixtures, mineral grains on frost, and frost on minerals are presented. The materials used in this study are montmorillonite, kaolinite, beryl, Mauna Kea red cinder, and black charcoal. It is found that the wavelengths of bound water and bound OH absorptions do not shift appreciably with temperature and can be detected when large amounts of free water ice are present. The decrease in the visible reflectance seen in many planetary reflectance spectra containing strong water ice absorptions can be explained by water-mineral mixtures, mineral grains on frost, or frost on mineral grains. Mineral grains on frost are detectable in very small quantities (fractional areal coverage less than approximately 0.005) depending on the mineral reflectance features, while it takes a thick layer of frost (greater than approximately 1 mm) to mask a mineral below 1.4 microns, again depending on the mineral reflectance. Frost on a very dark surface (albedo about 6%) is easily seen; however, a dark mineral mixed with water could completely mask the water absorptions (shortward of 2.5 microns).

  18. Development of coastal upwelling edge detection algorithms associated with harmful algal blooms off the Washington coast using sea surface temperature imagery.

    Energy Technology Data Exchange (ETDEWEB)

    Evans, Nathan R.; Woodruff, Dana L.; Trainer, Vera L.

    2005-01-01

    Satellite remote sensing imagery is being used to identify and characterize upwelling conditions on the coast of Washington State, with an emphasis on detecting ocean features associated with harmful algal bloom events. Blooms of phytoplankton, including the domoic acid-producing diatom Pseudo-nitzschia, appear to be associated with a semi-permanent eddy bordering Washington and British Columbia that is observed in satellite imagery during extended upwelling events. Strong upwelling conditions may act as a barrier to movement of these blooms onshore. Using NOAA AVHRR temperature imagery, edge detection algorithms are being developed to define the strength, location and extent of the surface temperature expression of upwelling along the coast of Washington. The edge detection technique uses a simple kernel-based gradient method that compares temperatures of pixels at a user-specified distance. This allows identification of larger features with subtle edges. The resulting maximum-gradient map is then converted to a binary format with a user-specified temperature threshold. Skeletonization and edge-linking algorithms are then employed to develop final map products. The upwelling edge detection maps are being examined in relation to harmful algal bloom events that have occurred along the coast.

  19. Development of coastal upwelling edge detection algorithms associated with harmful algal blooms off the Washington coast using sea surface temperature imagery

    Science.gov (United States)

    Evans, Nathan R.; Woodruff, Dana L.; Trainer, Vera L.

    2005-08-01

    Satellite remote sensing imagery is being used to identify and characterize upwelling conditions on the coast of Washington State, with an emphasis on detecting ocean features associated with harmful algal bloom events. Blooms of phytoplankton, including the domoic acid-producing diatom Pseudo-nitzschia, appear to be associated with a semi-permanent eddy bordering Washington and British Columbia that is observed in satellite imagery during extended upwelling events. Strong upwelling conditions may act as a barrier to movement of these blooms onshore. Using NOAA AVHRR temperature imagery, edge detection algorithms are being developed to define the strength, location and extent of the surface temperature expression of upwelling along the coast of Washington. The edge detection technique uses a simple kernel-based gradient method that compares temperatures of pixels at a user-specified distance. This allows identification of larger features with subtle edges. The resulting maximum-gradient map is then converted to a binary format with a user-specified temperature threshold. Skeletonization and edge-linking algorithms are then employed to develop final map products. The upwelling edge detection maps are being examined in relation to harmful algal bloom events that have occurred along the coast.

  20. SAT-MAP-CLIMATE project results[SATellite base bio-geophysical parameter MAPping and aggregation modelling for CLIMATE models

    Energy Technology Data Exchange (ETDEWEB)

    Bay Hasager, C.; Woetmann Nielsen, N.; Soegaard, H.; Boegh, E.; Hesselbjerg Christensen, J.; Jensen, N.O.; Schultz Rasmussen, M.; Astrup, P.; Dellwik, E.

    2002-08-01

    Earth Observation (EO) data from imaging satellites are analysed with respect to albedo, land and sea surface temperatures, land cover types and vegetation parameters such as the Normalized Difference Vegetation Index (NDVI) and the leaf area index (LAI). The observed parameters are used in the DMI-HIRLAM-D05 weather prediction model in order to improve the forecasting. The effect of introducing actual sea surface temperatures from NOAA AVHHR compared to climatological mean values, shows a more pronounced land-sea breeze effect which is also observable in field observations. The albedo maps from NOAA AVHRR are rather similar to the climatological mean values so for the HIRLAM model this is insignicant, yet most likely of some importance in the HIRHAM regional climate model. Land cover type maps are assigned local roughness values determined from meteorological field observations. Only maps with a spatial resolution around 25 m can adequately map the roughness variations of the typical patch size distribution in Denmark. A roughness map covering Denmark is aggregated (ie area-average non-linearly) by a microscale aggregation model that takes the non-linear turbulent responses of each roughness step change between patches in an arbitrary pattern into account. The effective roughnesses are calculated into a 15 km by 15 km grid for the HIRLAM model. The effect of hedgerows is included as an added roughness effect as a function of hedge density mapped from a digital vector map. Introducing the new effective roughness maps into the HIRLAM model appears to remedy on the seasonal wind speed bias over land and sea in spring. A new parameterisation on the effective roughness for scalar surface fluxes is developed and tested on synthetic data. Further is a method for the estimation the evapotranspiration from albedo, surface temperatures and NDVI succesfully compared to field observations. The HIRLAM predictions of water vapour at 12 GMT are used for atmospheric correction of

  1. Satellite monitoring the rangeland degradation under the impacts of climatic and socio-economic changes over central Asia

    Science.gov (United States)

    Wang, K.; Zhang, L.; Dai, L.; Yan, D.

    2012-12-01

    Central Asia, encompassing the republics of Kazakhstan, Kyrgyz, Uzbekistan, Turkmenistan, Tajikistan and China's western Sinkiang, is a typical arid and semi-arid area. The climate in Central Asia is extreme arid, where summer is hot, cloudless and dry, and winter is moist and relatively warm in the south and cold and dry in the north. Rangeland, accounting for 46% of the entire area, is the main vegetation type in this area. Recent findings showed that climate change had caused unprecedented rangeland degradation in Central Asia over the past 30 years. Socio-economical change and environmental change due to the collapse of Soviet Union also accelerated rangeland degradation. Rangeland degradation adversely further deteriorated the environment. With the development of high resolution remote sensing images, an increasing attention has paid to study rangeland degradation in this area. However, previous investigations based on either Advanced Very High Resolution Radiometer (AVHRR) or Moderate Resolution Imaging Spectroradiometer (MODIS) data, has not integrate multi-resolution satellite data for investigating vegetation change and its response to climatic and socio-economic change . In this paper, we employed 30 years' remote sensing data, including both AVHRR ( 1982-2006) and MODIS (2000-2011) satellite data, and in-situ meteorological and social data (e.g. population, economic, and land use change data), to investigate rangeland degradation in the central Asia. We 1) analyzed the spatial-temporal variations of vegetation changes during the past 30 years, and 2) evaluated the roles of climatic and socio-economic factors as potential causes of observed vegetation changes. The results showed extensive area had statistically significant degradation trends (p<0.05). Precipitation was the main driver of rangeland degradation, while there were relatively weaker relationships between temperature and NDVI, indicating that water deficit largely limited vegetation activity

  2. JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

    Science.gov (United States)

    Folmer, M. J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J. M.; Nelson, J. A., Jr.; Goldberg, M.

    2016-12-01

    The National Oceanic and Atmospheric Administration (NOAA) Satellite Proving Ground (PG) for Marine, Precipitation, and Satellite Analysis (MPS) has been demonstrating and evaluating Suomi National Polar-orbiting Partnership (S-NPP) products along with other polar-orbiting satellite platforms in preparation for the Joint Polar Satellite System - 1 (JPSS-1) launch in March 2017. The first S-NPP imagery was made available to the MPS PG during the evolution of Hurricane Sandy in October 2012 and has since been popular in operations. Since this event the MPS PG Satellite Liaison has been working with forecasters on ways to integrate single-channel and multispectral imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Advanced Very High Resolution Radiometer (AVHRR)into operations to complement numerical weather prediction and geostationary satellite savvy National Weather Service (NWS) National Centers. Additional unique products have been introduced to operations to address specific forecast challenges, including the Cooperative Institute for Research in the Atmosphere (CIRA) Layered Precipitable Water, the National Environmental Satellite, Data, and Information Service (NESDIS) Snowfall Rate product, NOAA Unique Combined Atmospheric Processing System (NUCAPS) Soundings, ozone products from the Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS), and Infrared Atmospheric Sounding Interferometer (IASI). In addition, new satellite domains have been created to provide forecasters at the NWS Ocean Prediction Center and Weather Prediction Center with better quality imagery at high latitudes. This has led to research projects that are addressing forecast challenges such as tropical to extratropical transition and explosive cyclogenesis. This presentation will provide examples of how the MPS PG has been introducing and integrating

  3. Relationship between herbaceous biomass and 1km (2) advanced very high resolution radiometer (AVHRR) NDVI in Kruger National Park, South Africa

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2006-03-01

    Full Text Available The relationship between multi-year (1989-2003), herbaceous biomass and 1-km(2) Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data in Kruger National Park (KNP), South Africa is considered...

  4. Satellite RNAs and Satellite Viruses.

    Science.gov (United States)

    Palukaitis, Peter

    2016-03-01

    Satellite RNAs and satellite viruses are extraviral components that can affect either the pathogenicity, the accumulation, or both of their associated viruses while themselves being dependent on the associated viruses as helper viruses for their infection. Most of these satellite RNAs are noncoding RNAs, and in many cases, have been shown to alter the interaction of their helper viruses with their hosts. In only a few cases have the functions of these satellite RNAs in such interactions been studied in detail. In particular, work on the satellite RNAs of Cucumber mosaic virus and Turnip crinkle virus have provided novel insights into RNAs functioning as noncoding RNAs. These effects are described and potential roles for satellite RNAs in the processes involved in symptom intensification or attenuation are discussed. In most cases, models describing these roles involve some aspect of RNA silencing or its suppression, either directly or indirectly involving the particular satellite RNA.

  5. Robust satellite techniques for volcanicand seismic hazards monitoring

    Directory of Open Access Journals (Sweden)

    I. Scaffidi

    2004-06-01

    Full Text Available Several satellite techniques have been proposed to monitor events related to seismic and volcanic activity. A selfadaptive approach (RAT, Robust AVHRR Techniques has recently been proposed which seems able to recognise space-time anomalies, differently related to such events, also in the presence of highly variable contributions from atmospheric (transmittance, surface (emissivity and morphology and observational (time/season, but also solar and satellite zenithal angles conditions. On the basis of NOAA-AVHRR data, the RAT aprroach has already been applied to Mount Etna volcanic ash cloud monitoring in daytime, and to seismic area monitoring in Southern Italy. This paper presents the theoretical basis for the extension of RAT approach also to nighttime volcanic ash cloud detection, together with its possible implementation to lava flow monitoring. One example of successful forecasting (few days before of a new lava vent opening during the Mount Etna eruption of July 2001 will be discussed in some detail. Progress on the use of the same approach on seismically active area monitoring will be discussed by comparison with previous results achieved on the Irpinia-Basilicata earthquake (MS = 6.9, which occurred on November 23rd 1980 in Southern Italy.

  6. Satellite detection, tracing, and early warning of harmful algal blooms (HABs) for the Asian waters

    Science.gov (United States)

    Tang, D. L.

    Over the past two decades, Harmful Algal Blooms (HABs) appear to have increased in frequency, intensity and geographic distribution worldwide, and have caused large economic losses in aquacultured and wild fisheries in recent years. Understanding of the oceanic mechanisms is important for early warning of HAB events. The present study reported several extensive HABs in the Asian waters during 1998 to 2003 detected by satellite remote sensing data (SeaWiFS, NOAA AVHRR, and QuikScat) and in situ observations. An extensive HAB off southeastern Vietnamese waters during late June to July 2002 was detected and its related oceanographic features were analyzed. The HAB had high Chlorophyll-a (Chl-a) concentrations (up to 4.5 mg m-3), occurring about 200 km off the coast and about 200 km northeast of the Mekong River mouth, for a period of about 6 weeks. The bloom was dominated by the harmful algae haptophyte Phaeocystis cf. globosa, and caused a very significant mortality of aquacultured fishes and other marine life. In the same period, Sea Surface Temperature (SST) imagery showed a coldwater plume extending from the coast to the open sea, and QuikScat data showed strong southwesterly winds blowing parallel with the coastline. It indicated the HAB was induced and supported by offshore upwelling that bring nutrients from the deep ocean to the surface and from coastal water to the offshore, and the upwelling was driven by strong wind through Ekman transport when winds were parallel with the coastline. This study demonstrated the possibility of utilizing a combination of satellite data of Chl-a, SST and wind velocity together with coastal bathymetric information and in situ observation to give a better understanding of the biological oceanography of HABs; these results may help for the early warming of HAB.

  7. Comparison of Arctic Sea Ice Thickness from Satellites, Aircraft, and PIOMAS Data

    Directory of Open Access Journals (Sweden)

    Xuanji Wang

    2016-08-01

    Full Text Available In this study, six Arctic sea ice thickness products are compared: the AVHRR Polar Pathfinder-extended (APP-x, ICESat, CryoSat-2, SMOS, NASA IceBridge aircraft flights, and the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS. The satellite products are based on three different retrieval methods: an energy budget approach, measurements of ice freeboard, and the relationship between passive microwave brightness temperatures and thin ice thickness. Inter-comparisons are done for the periods of overlap from 2003 to 2013. Results show that ICESat sea ice is thicker than APP-x and PIOMAS overall, particularly along the north coast of Greenland and Canadian Archipelago. The relative differences of APP-x and PIOMAS with ICESat are −0.48 m and −0.31 m, respectively. APP-x underestimates thickness relative to CryoSat-2, with a mean difference of −0.19 m. The biases for APP-x, PIOMAS, and CryoSat-2 relative to IceBridge thicknesses are 0.18 m, 0.18 m, and 0.29 m. The mean difference between SMOS and CryoSat-2 for 0~1 m thick ice is 0.13 m in March and −0.24 m in October. All satellite-retrieved ice thickness products and PIOMAS overestimate the thickness of thin ice (1 m or less compared to IceBridge for which SMOS has the smallest bias (0.26 m. The spatial correlation between the datasets indicates that APP-x and PIOMAS are the most similar, followed by APP-x and CryoSat-2.

  8. On the optimal method for evaluating cloud products from passive satellite imagery using CALIPSO-CALIOP data: example investigating the CM SAF CLARA-A1 dataset

    Directory of Open Access Journals (Sweden)

    K.-G. Karlsson

    2013-02-01

    Full Text Available A method for detailed evaluation of a new satellite-derived global 28-yr cloud and radiation climatology (Climate Monitoring SAF Cloud, Albedo and Radiation dataset from AVHRR data, named CLARA-A1 from polar orbiting NOAA and Metop satellites is presented. The method combines 1 km and 5 km resolution cloud datasets from the CALIPSO-CALIOP cloud lidar for estimating cloud detection limitations and the accuracy of cloud top height estimations.

    Cloud detection is shown to work efficiently for clouds with optical thicknesses above 0.30 except for at twilight conditions when this value increases to 0.45. Some misclassifications generating erroneous clouds over land surfaces in semi-arid regions in the sub-tropical and tropical regions are revealed. In addition, a substantial fraction of all clouds remains undetected in the Polar regions during the polar winter season due to the lack of or an inverted temperature contrast between Earth surfaces and clouds.

    Subsequent cloud top height evaluation took into account the derived information about the cloud detection limits. It was shown that this has fundamental importance for the achieved results. An overall bias of −274 m was achieved compared to a bias of −2762 m if no measures were taken to compensate for cloud detection limitations. Despite this improvement it was concluded that high-level clouds still suffer from substantial height underestimations while the opposite is true for low-level (boundary layer clouds.

    The validation method and the specifically collected satellite dataset with optimal matching in time and space are suggested for a wider use in the future for evaluation of other cloud retrieval methods based on passive satellite imagery.

  9. Evidences of volcanic unrest on high-temperature fumaroles by satellite thermal monitoring: The case of Santa Ana volcano, El Salvador

    Science.gov (United States)

    Laiolo, M.; Coppola, D.; Barahona, F.; Benítez, J. E.; Cigolini, C.; Escobar, D.; Funes, R.; Gutierrez, E.; Henriquez, B.; Hernandez, A.; Montalvo, F.; Olmos, R.; Ripepe, M.; Finizola, A.

    2017-06-01

    On October 1st, 2005, Santa Ana volcano (El Salvador) underwent a VEI 3 phreatomagmatic eruption after approximately one century of rest. Casualties and damages to some of the local infrastructures and surrounding plantations were followed by the evacuation of the nearby communities. The analysis of MODIS (Moderate Resolution Imaging Spectroradiometer) infrared data reveals that the main explosion was preceded by a one-year-long thermal unrest, associated to the development of a fumaroles field, located at the western rim of the summit crater lake. By combining space-based thermal flux and ground-based measurements (seismicity, sulfur emissions and lake temperatures), we suggest that the activity observed at Santa Ana between 2004 and 2005 was driven by the gradual intrusion of an undegassed magma body at a very shallow depth. Magma injection induced thermal anomalies associated with sustained degassing from the fumaroles field and promoted the interaction between the magmatic-hydrothermal system and the overlying water table. This process culminated into the VEI 3 phreatomagmatic eruption of October 2005 that strongly modified the shallow structure of the crater area. The subsequent three-years-long activity resulted from self-sealing of the fracture system and by the opening of a new fracture network directly connecting the deeper hydrothermal system with the crater lake. Our results show that satellite-based thermal data allow us to detect the expansion of the high-temperature fumarolic field. This may precede an explosive eruption and/or a lava dome extrusion. In particular, we show that thermal records can be analyzed with other geochemical (i.e. SO2 emissions) and geophysical (seismicity) data to track a shallow magmatic intrusion interacting with the surrounding hydrothermal system. This provides a remarkable support for volcano monitoring and eruption forecasting, particularly in remote areas where permanent ground data acquisition is hazardous, expensive

  10. Impact of satellite-based lake surface observations on the initial state of HIRLAM. Part I: evaluation of remotely-sensed lake surface water temperature observations

    Directory of Open Access Journals (Sweden)

    Homa Kheyrollah Pour

    2014-05-01

    Full Text Available Lake Surface Water Temperature (LSWT observations are used to improve the lake surface state in the High Resolution Limited Area Model (HIRLAM, a three-dimensional numerical weather prediction (NWP model. In this paper, satellite-derived LSWT observations from the Moderate Resolution Imaging Spectroradiometer (MODIS and the Along-Track Scanning Radiometer (AATSR are evaluated against in-situ measurements collected by the Finnish Environment Institute (SYKE for a selection of large- to medium-size lakes during the open-water season. Data assimilation of these LSWT observations into the HIRLAM is in the paper Part II. Results show a good agreement between MODIS and in-situ measurements from 22 Finnish lakes, with a mean bias of −1.13°C determined over five open-water seasons (2007–2011. Evaluation of MODIS during an overlapping period (2007–2009 with the AATSR-L2 product currently distributed by the European Space Agency (ESA shows a mean (cold bias error of −0.93°C for MODIS and a warm mean bias of 1.08°C for AATSR-L2. Two additional LSWT retrieval algorithms were applied to produce more accurate AATSR products. The algorithms use ESA's AATSR-L1B brightness temperature product to generate new L2 products: one based on Key et al. (1997 and the other on Prata (2002 with a finer resolution water mask than used in the creation of the AATSR-L2 product distributed by ESA. The accuracies of LSWT retrievals are improved with the Key and Prata algorithms with biases of 0.78°C and −0.11°C, respectively, compared to the original AATSR-L2 product (3.18°C.

  11. Global Monitoring RSEM System for Crop Production by Incorporating Satellite-based Photosynthesis Rates and Anomaly Data of Sea Surface Temperature

    Science.gov (United States)

    Kaneko, D.; Sakuma, H.

    2014-12-01

    The first author has been developing RSEM crop-monitoring system using satellite-based assessment of photosynthesis, incorporating meteorological conditions. Crop production comprises of several stages and plural mechanisms based on leaf photosynthesis, surface energy balance, and the maturing of grains after fixation of CO2, along with water exchange through soil vegetation-atmosphere transfer. Grain production in prime countries appears to be randomly perturbed regionally and globally. Weather for crop plants reflects turbulent phenomena of convective and advection flows in atmosphere and surface boundary layer. It has been difficult for scientists to simulate and forecast weather correctly for sufficiently long terms to crop harvesting. However, severely poor harvests related to continental events must originate from a consistent mechanism of abnormal energetic flow in the atmosphere through both land and oceans. It should be remembered that oceans have more than 100 times of energy storage compared to atmosphere and ocean currents represent gigantic energy flows, strongly affecting climate. Anomalies of Sea Surface Temperature (SST), globally known as El Niño, Indian Ocean dipole, and Atlantic Niño etc., affect the seasonal climate on a continental scale. The authors aim to combine monitoring and seasonal forecasting, considering such mechanisms through land-ocean biosphere transfer. The present system produces assessments for all continents, specifically monitoring agricultural fields of main crops. Historical regions of poor and good harvests are compared with distributions of SST anomalies, which are provided by NASA GSFC. Those comparisons fairly suggest that the Worst harvest in 1993 and the Best in 1994 relate to the offshore distribution of low temperature anomalies and high gaps in ocean surface temperatures. However, high-temperature anomalies supported good harvests because of sufficient solar radiation for photosynthesis, and poor harvests because

  12. Kalman filter physical retrieval of surface emissivity and temperature from SEVIRI infrared channels: a validation and inter-comparison study

    Directory of Open Access Journals (Sweden)

    G. Masiello

    2015-04-01

    Full Text Available A Kalman filter based approach for the physical retrieval of surface temperature and emissivity from SEVIRI (Spinning Enhanced Visible and Infrared Imager infrared observations has been developed and validated against in situ and satellite observations. Validation for land has been provided based on in situ observations from the two permanent stations Evora and Gobabeb operated by Karlsruhe Institute of Technology (KIT within the framework of EUMETSAT's Satellite Application Facility on Land Surface Analysis (LSA-SAF. Sea surface retrievals have been intercompared on a broad spatial scale with equivalent satellite products (MODIS or Moderate Resolution Imaging Spectroradiometer and AVHRR or Advanced Very High Resolution Radiometer and ECMWF (European Centre for Medium Range Weather Forecasts analyses. Results show that for surface temperature the algorithm yields an accuracy of ≈ ± 1.5 °C in case of land and ≈ ± 1.0 °C in case of sea surface. Comparisons with polar satellite instruments over the sea surface show nearly zero temperature bias. Over the land surface the retrieved emissivity follows the seasonal vegetation cycle and allows to identify desert sand regions because of strong reststrahlen bands of Quartz in the SEVIRI channel at 8.7 μm. Considering the two validation stations, we have that emissivity retrieved in SEVIRI channel 10.8 μm over the gravel plains of the Namib desert is in excellent agreement with in situ observations. Over Evora, the seasonal variation of emissivity with vegetation is successfully retrieved and yields emissivity values for green and dry vegetation that are in good agreement with spectral library data. The algorithm has been applied to the SEVIRI full disk and emissivity maps on that global scale have been physically retrieved for the first time.

  13. Centriolar satellites

    DEFF Research Database (Denmark)

    Tollenaere, Maxim A X; Mailand, Niels; Bekker-Jensen, Simon

    2015-01-01

    Centriolar satellites are small, microscopically visible granules that cluster around centrosomes. These structures, which contain numerous proteins directly involved in centrosome maintenance, ciliogenesis, and neurogenesis, have traditionally been viewed as vehicles for protein trafficking...... highlight newly discovered regulatory mechanisms targeting centriolar satellites and their functional status, and we discuss how defects in centriolar satellite components are intimately linked to a wide spectrum of human diseases....

  14. The influence of topographic structures on night-time surface temperatures: Evaluation of a satellite thermal image of the upper Rhine plain and the surrounding highlands. [Germany and Switzerland

    Science.gov (United States)

    Gossmann, H. (Principal Investigator)

    1980-01-01

    The author has identified the following significant results. Satellite data supplied the same information as aerial IR registrations with corresponding averaging for all studies requiring a survey of the thermal pattern within an area measuring 10 km x 10 km ore more, provided that sufficiently precise control points could be established for the purpose of geometric rectification in the surroundings of the area observed. Satellite thermal data are more comprehensive than aircraft data for studies on a regional, rather than a local scale, since airborne images often obscure the basic correlation in thermal patterns because of a variety of irrelevant topographical detail. The satellite data demonstrate the dependence of surface temperature on relief more clearly than comparable airborne imagery.

  15. Satellite theory

    Science.gov (United States)

    Kozai, Y.

    1981-04-01

    The dynamical characteristics of the natural satellite of Mars, Jupiter, Saturn, Uranus and Neptune are analyzed on the basis of the solar tidal perturbation factor and the oblateness factor of the primary planet for each satellite. For the inner satellites, for which the value of the solar tidal factor is much smaller than the planetary oblateness factor, it is shown that the eccentricity and inclination of satellite orbits are generally very small and almost constant; several pairs of inner satellites are also found to exhibit commensurable mean motions, or secular accelerations in mean longitude. In the case of the outer satellites, for which solar perturbations are dominant, secular perturbations and long-period perturbations may be derived by the solution of equations of motion reduced to one degree of freedom. The existence of a few satellites, termed intermediary satellites, for which the solar tidal perturbation is on the order of the planetary oblateness factor, is also observed, and the pole of the orbital plane of the satellite is noted to execute a complex motion around the pole of the planet or the orbital plane of the planet.

  16. Detección de incendios en México utilizando imágenes AVHRR (temporada 1998

    Directory of Open Access Journals (Sweden)

    José Luis Palacio Prieto

    1999-01-01

    Full Text Available La temporada de incendios de 1998 en México fue excepcional. En ello contribuyeron los fenómenos meteorológicos del año anterior (huracanes y bajas temperaturas, principalmente que ocasionaron la deposición de grandes cantidades de material combustible. Por medio de 120 imágenes AVHRR se hace una evaluación de áreas incendiadas entre enero y junio de 1998. Se registran 8 147 pixeles aue refieren la oresencia de puntos calientes. oresumiblemente fuegos, durante el periodo referdo Se utilizo una base de datos de referenciapara revisar la exactitud del mapa de áreas incendiadas que se presenta. de 3 312 sitios de refencia, cerca de 94% de los mismos fueron detectados por los niveles de saturacion del canal 3 del sensor AVHRR

  17. A Multi-Channel Method for Retrieving Surface Temperature for High-Emissivity Surfaces from Hyperspectral Thermal Infrared Images

    Directory of Open Access Journals (Sweden)

    Xinke Zhong

    2015-06-01

    Full Text Available The surface temperature (ST of high-emissivity surfaces is an important parameter in climate systems. The empirical methods for retrieving ST for high-emissivity surfaces from hyperspectral thermal infrared (HypTIR images require spectrally continuous channel data. This paper aims to develop a multi-channel method for retrieving ST for high-emissivity surfaces from space-borne HypTIR data. With an assumption of land surface emissivity (LSE of 1, ST is proposed as a function of 10 brightness temperatures measured at the top of atmosphere by a radiometer having a spectral interval of 800–1200 cm−1 and a spectral sampling frequency of 0.25 cm−1. We have analyzed the sensitivity of the proposed method to spectral sampling frequency and instrumental noise, and evaluated the proposed method using satellite data. The results indicated that the parameters in the developed function are dependent on the spectral sampling frequency and that ST of high-emissivity surfaces can be accurately retrieved by the proposed method if appropriate values are used for each spectral sampling frequency. The results also showed that the accuracy of the retrieved ST is of the order of magnitude of the instrumental noise and that the root mean square error (RMSE of the ST retrieved from satellite data is 0.43 K in comparison with the AVHRR SST product.

  18. Multi-Sensor Calibration Studies of AVHRR-Heritage Channel Radiances Using the Simultaneous Nadir Observation Approach

    OpenAIRE

    Karl-Göran Karlsson; Erik Johansson

    2014-01-01

    The European Space Agency project for studies of cloud properties in the Climate Change Initiative programme (ESA-CLOUD-CCI) aims at compiling the longest possible time series of cloud products from one single multispectral sensor—The five-channel Advanced Very High Resolution Radiometer (AVHRR) instrument. A particular aspect here is to include corresponding products based on other existing (Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Along-Track Scanning Radiometer (AATS...

  19. Vegetation classification of East China with multi-temporal NOAA-AVHRR data

    Institute of Scientific and Technical Information of China (English)

    LI Junxiang; DA Liangjun; WANG Yujie; SONG Yongchang

    2006-01-01

    East China lies in the subtropical monsoon climatic zone and is dominated by subtropical evergreen broad-leaved forests,a unique vegetation type mainly distributed in East Asia with the largest distnbution in China.It is important to be able to monitor and estimate forest biomass and production,regional carbon storage,and global climate change impacts on these important vegetation types.In this paper,we used coarse resolution remote sensing data to identify the vegetation types in East China and developed a map of the spatial distribution of vegetation types in this region.Nineteen maximum normalized difference vegetation index(NDVI)composite images(acquisition time span of 7 months from February to August),which were derived from 10 days National Oceanographic and Atmospheric Administration(NOAA)Advanced Very High Resolution Radiometer(AVHRR)channel 1 and channel 2 observations,an unsupervised classification method,and the ISODATA algorithm were employed to identify the vegetation types.To reduce the dimensions of the dataset resulted in a total of 28 spectral clusters of land-cover of which two clusters were urban/bare soil and water,the images were processed using principal component analysis(PCA).The 26 remaining spectral clusters were merged into six vegetation types using the Chinese vegetation taxonomy system:evergreen broad-leaved forest,coniferous forest,bamboo forest,shrub-grass,aquatic vegetation,and agricultural vegetation.The spatial distribution and areal extent for the coniferous forests,shrub-grass,evergreen broad-leaved forests,and agricultural vegetation were calculated and comscale.The spatial accuracy and the area accuracy for coniferous forests,shrub-grass,evergreen broad-leaved forests,and agricultural vegetation were 79.2%,91.3%,68.2% and 95.9% and 92.1%,95.9%,63.8% and 90.5%,respectively.The spatial accuracy and area accuracy of the bamboo forest were 28.7% and 96.5%,respectively;the spatial accuracy of aquatic vegetation was 69.6%,but there

  20. Global two-channel AVHRR aerosol climatology: effects of stratospheric aerosols and preliminary comparisons with MODIS and MISR retrievals

    Energy Technology Data Exchange (ETDEWEB)

    Geogdzhayev, Igor V. [Department of Applied Physics and Applied Mathematics, Columbia University, 2880 Broadway, New York, NY 10025 (United States); NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States); Mishchenko, Michael I. [NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States)]. E-mail: crmim@giss.nasa.gov; Liu Li [NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States); Department of Earth and Environmental Sciences, Columbia University, 2880 Broadway, New York, NY 10025 (United States); Remer, Lorraine [NASA Goddard Space Flight Center, Code 913, Greenbelt, MD 20771 (United States)

    2004-10-15

    We present an update on the status of the global climatology of the aerosol column optical thickness and Angstrom exponent derived from channel-1 and -2 radiances of the Advanced Very High Resolution Radiometer (AVHRR) in the framework of the Global Aerosol Climatology Project (GACP). The latest version of the climatology covers the period from July 1983 to September 2001 and is based on an adjusted value of the diffuse component of the ocean reflectance as derived from extensive comparisons with ship sun-photometer data. We use the updated GACP climatology and Stratospheric Aerosol and Gas Experiment (SAGE) data to analyze how stratospheric aerosols from major volcanic eruptions can affect the GACP aerosol product. One possible retrieval strategy based on the AVHRR channel-1 and -2 data alone is to infer both the stratospheric and the tropospheric aerosol optical thickness while assuming fixed microphysical models for both aerosol components. The second approach is to use the SAGE stratospheric aerosol data in order to constrain the AVHRR retrieval algorithm. We demonstrate that the second approach yields a consistent long-term record of the tropospheric aerosol optical thickness and Angstrom exponent. Preliminary comparisons of the GACP aerosol product with MODerate resolution Imaging Spectrometer (MODIS) and Multiangle Imaging Spectro-Radiometer aerosol retrievals show reasonable agreement, the GACP global monthly optical thickness being lower than the MODIS one by approximately 0.03. Larger differences are observed on a regional scale. Comparisons of the GACP and MODIS Angstrom exponent records are less conclusive and require further analysis.

  1. Using field observations and satellite data for the study of energy and water cycle over heterogeneous landscape of the Tibetan Plateau

    Science.gov (United States)

    Ma, Yaoming

    2014-05-01

    The Tibetan Plateau, with the most prominent and complicated terrain on the globe and an elevation of more than 4000 m on average above sea leave (msl), is often called the "Third Pole" due to its significance parallel with Antarctica and the Arctic. The exchange of energy and water vapor between land surface and atmosphere over the Tibetan Plateau area play an important role in the Asian monsoon system, which in turn is a major component of both the energy and water cycles of the global climate system. Supported by the Chinese Academy of Sciences and some international organizations, a Third Pole Environment (TPE) Research Platform (TPEP) is now implementing over the Tibetan Plateau and surrounding area. The background of the establishment of the TPEP, the establishing and monitoring plan of long-term scale (5-10 years) of the TPEP will be shown firstly. Then the preliminary observational analysis results, such as the characteristics of land surface heat fluxes,CO2 flux and evapotranspiration (ET) partitioning (diurnal variation, inter-monthly variation and vertical variation etc), the characteristics of atmospheric and soil variables, the structure of the Atmospheric Boundary Layer (ABL) and the turbulent characteristics have also been shown in this study. The study on the regional distribution of land surface heat fluxes and ET are of paramount importance over heterogeneous landscape of the Tibetan Plateau. The parameterization methods based on satellite data (AVHRR and MODIS) and Atmospheric Boundary Layer (ABL) observations have been proposed and tested for deriving surface reflectance, surface temperature, net radiation flux, soil heat flux, sensible heat flux, latent heat flux and ET over heterogeneous landscape. As cases study, the methods were applied to the whole Tibetan Plateau area. Four scenes of AVHRR data and four scenes of MODIS data were used in this study. To validate the proposed methods, the ground-measured surface reflectance, surface

  2. Satellite Earth observation data to identify climate and anthropogenic pressures on Bucharest periurban forests

    Energy Technology Data Exchange (ETDEWEB)

    Zoran, Maria; Savastru, Roxana; Savastru, Dan [National Institute of R& D for Optoelectronics, MG5 Bucharest-Magurele, 077125 Romania (Romania); Dida, Adrian [University Transylvania of Brasov, Brasov (Romania)

    2016-03-25

    Satellite Earth observation data in the visible and near-infrared (VNIR) wavelengths represent a useful source of information for forest systems monitoring through derived biogeophysical parameters (vegetation index, leaf area index, canopy cover, fraction of absorbed photosynthetically active radiation, chlorophyll content, net primary production, canopy water stress, etc.). Use of satellite remote sensing data to assess forest spatio-temporal changes due to climatic or anthropogenic stressors is an excellent example of the value of multispectral and multitemporal observations. Fusion technique was applied to time-series multispectral and multitemporal satellite imagery (NOAA AVHRR, MODIS Terra/Aqua, Landsat ETM and IKONOS satellite data) for periurban forest areas Cernica-Branesti, placed in the neighboring of Bucharest town, Romania, over 2002-2014 period.

  3. Integração de imagens NOAA/AVHRR: rede de cooperação para monitoramento nacional da safra de soja

    Directory of Open Access Journals (Sweden)

    Anibal Gusso

    2013-04-01

    Full Text Available Uma avaliação inicial das condições do desenvolvimento da safra nacional, enquanto as plantas ainda estão nos campos, é altamente necessária para o cálculo correto das projeções na tomada de decisão e políticas relacionadas com o planejamento governamental e segurança alimentar. O objetivo deste trabalho foi avaliar a adequação dos dados NOAA/AVHRR (National Oceanic and Atmospheric Administration / Advanced Very High Resolution Radiometer em detectar mudanças nas condições da vegetação, devidas à ocorrência de estresse hídrico, na soja, por meio de uma combinação do índice NDVI (Normalized Difference Vegetation Index e da LST (Land Surface Temperature. Os dados LST e NDVI foram combinados e comparados pixel a pixel, sobre uma área de cultivo de soja, no Rio Grande do Sul. A relação teórica inversa prevista na combinação de LST e NDVI foi detectada. Foi observado que ocorre um aumento médio na LST em uma safra de ciclo normal (de 301,02 K para 308,36 K, quando comparada a uma safra sob condição de estresse hídrico, no desenvolvimento da cultura. Uma redução média do NDVI foi observada no ciclo normal (de 0,65 para 0,53, comparada com uma safra sob efeitos ocasionados pela estiagem no desenvolvimento da cultura. Foi observado maior correlação da produtividade municipal com LST (R2=0,78 do que com o NDVI (R2 = 0,59. Os resultados obtidos indicam que a integração de imagens do sensor AVHRR, proveniente de diferentes instituições, proporciona a adequada combinação espacial e temporal dos dados LST e NDVI, a fim de detectar a ocorrência de estresse hídrico, bem como sua intensidade, caracterizando as condições do ciclo de desenvolvimento da soja.

  4. Interaction between Meso-scale Eddies and Sub-polar Front in the East (Japan) Sea based on ARGO, AVHRR, and Numerical Model

    Science.gov (United States)

    Ro, Y.; Kim, E.

    2008-12-01

    The East (Japan) Sea is drawing keen international attentions from broad spectrum of groups such as scientists, diplomats, and defense officers for its geopolitical situation, peculiar scientific assets recognized as miniature ocean. From physical oceanographic aspect, it is very rich with many features such as basin-wide circulation pattern, boundary currents, sub-polar front, meso-scale eddy activities and deep water formation. The circulation pattern in the East (Japan) Sea has been of major interests for its peculiar gyre, a western boundary current and its separation that resembles the currents such as Kuroshio and Gulf Stream. In relation to the gyre system in the East Sea, the formation of the East Korea Warm Current (EKWC) has brought up with many numerical experiments. Numerical experiments suggested a new idea to explain the formation of the EKWC in that the potential energy supply into the Ulleung Basin (UB) from the meso-scale eddy is a key process. This is closely linked with the baroclinic instability and the meandering of offshore component of Tsushima Warm Current. The UB has drawn attentions for its role of the formation of two major boundary currents, EKWC, North Korea Warm Current (NKCC), their interaction with the mesoscale UWE, watermass exchange between the Northern Japan Basin and UB. Numerical experiments along with hydrographic and other satellite datasets such as AVHRR, altimeter and ARGO profiles have been analyzed to understand the formation of the UWE. We found that the influence of the bottom topography and frictional forcing against lateral boundary are all closely associated with the sub-polar front. Meandering of the axis of the sub-polar front is closely linked with the separation point of the EKWC, Ulleung Warm Eddy, and other small and meso-scale eddies on the sub-polar front. These will be demonstrated with results of the numerical modeling experiments and animation movie will be presented.

  5. Advances in satellite oceanography

    Science.gov (United States)

    Brown, O. B.; Cheney, R. E.

    1983-01-01

    Technical advances and recent applications of active and passive satellite remote sensing techniques to the study of oceanic processes are summarized. The general themes include infrared and visible radiometry, active and passive microwave sensors, and buoy location systems. The surface parameters of sea surface temperature, windstream, sea state, altimetry, color, and ice are treated as applicable under each of the general methods.

  6. How consistent is cloudiness over Canada from satellite observations and modeling data?

    Science.gov (United States)

    Trishchenko, A. P.; Khlopenkov, K.; Latifovic, R.

    2004-05-01

    Being one of the major modulators of radiation budget and hydrological cycle, clouds are still significant challenge for modeling and satellite retrievals. For example, our analysis shows that for Western Canada the systematic difference in total cloud amounts between NCAR/NCEP Reanalysis-2 and ISCCP reaches 20-30 per cent. Especially difficult are satellite retrievals for Northern climate regions over snow-covered surface and during night-time. To understand better these differences and their influence on earth radiation budget in Northern latitudes, we are attempting to undertake the re-analysis of satellite AVHRR data over Canada using improved data processing and cloud detection algorithms. Details of cloud detection algorithm for day-time and night-time conditions over snow-free and snow-covered surfaces are discussed. Selected results of satellite retrievals for typical summer and winter conditions over Canada are compared to previous analyses, such as ISCCP and Pathfinder projects. Consistency between our cloud retrievals using AVHRR data and those available from MODIS will be also considered.

  7. Soil moisture and evapotranspiration of wetlands vegetation habitats retrieved from satellite images

    Science.gov (United States)

    Dabrowska-Zielinska, K.; Budzynska, M.; Kowalik, W.; Turlej, K.

    2010-08-01

    The research has been carried out in Biebrza Ramsar Convention test site situated in the N-E part of Poland. Data from optical and microwave satellite images have been analysed and compared to the detailed soil-vegetation ground truth measurements conducted during the satellite overpasses. Satellite data applied for the study include: ENVISAT.ASAR, ENVISAT.MERIS, ALOS.PALSAR, ALOS.AVNIR-2, ALOS.PRISM, TERRA.ASTER, and NOAA.AVHRR. Optical images have been used for classification of wetlands vegetation habitats and vegetation surface roughness expressed by LAI. Also, heat fluxes have been calculated using NOAA.AVHRR data and meteorological data. Microwave images have been used for the assessment of soil moisture. For each of the classified wetlands vegetation habitats the relationship between soil moisture and backscattering coefficient has been examined, and the best combination of microwave variables (wave length, incidence angle, polarization) has been used for mapping and monitoring of soil moisture. The results of this study give possibility to improve models of water cycle over wetlands ecosystems by adding information about soil moisture and surface heat fluxes derived from satellite images. Such information is very essential for better protection of the European sensitive wetland ecosystems. ENVISAT and ALOS images have been obtained from ESA for AO ID 122 and AOALO.3742 projects.

  8. A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description and Validation

    Directory of Open Access Journals (Sweden)

    Martin Claverie

    2016-03-01

    Full Text Available In- land surface models, which are used to evaluate the role of vegetation in the context of global climate change and variability, LAI and FAPAR play a key role, specifically with respect to the carbon and water cycles. The AVHRR-based LAI/FAPAR dataset offers daily temporal resolution, an improvement over previous products. This climate data record is based on a carefully calibrated and corrected land surface reflectance dataset to provide a high-quality, consistent time-series suitable for climate studies. It spans from mid-1981 to the present. Further, this operational dataset is available in near real-time allowing use for monitoring purposes. The algorithm relies on artificial neural networks calibrated using the MODIS LAI/FAPAR dataset. Evaluation based on cross-comparison with MODIS products and in situ data show the dataset is consistent and reliable with overall uncertainties of 1.03 and 0.15 for LAI and FAPAR, respectively. However, a clear saturation effect is observed in the broadleaf forest biomes with high LAI (>4.5 and FAPAR (>0.8 values.

  9. The Distribution and Abundance of Bird Species: Towards a Satellite, Data Driven Avian Energetics and Species Richness Model

    Science.gov (United States)

    Smith, James A.

    2003-01-01

    This paper addresses the fundamental question of why birds occur where and when they do, i.e., what are the causative factors that determine the spatio-temporal distributions, abundance, or richness of bird species? In this paper we outline the first steps toward building a satellite, data-driven model of avian energetics and species richness based on individual bird physiology, morphology, and interaction with the spatio-temporal habitat. To evaluate our model, we will use the North American Breeding Bird Survey and Christmas Bird Count data for species richness, wintering and breeding range. Long term and current satellite data series include AVHRR, Landsat, and MODIS.

  10. 27-day solar forcing of mesospheric temperature, water vapor and polar mesospheric clouds from the AIM SOFIE and CIPS satellite experiments

    Science.gov (United States)

    Thomas, Gary; Thurairajah, Brentha; von Savigny, Christian; Hervig, Mark; Snow, Martin

    2016-04-01

    Solar cycle variations of ultraviolet radiation have been implicated in the 11-year and 27-day variations of Polar Mesospheric Cloud (PMC) properties. Both of these variations have been attributed to variable solar ultraviolet heating and photolysis, but no definitive studies of the mechanisms are available. The solar forcing issue is critical toward answering the broader question of whether PMC's have undergone long-term changes, and if so, what is the nature of the responsible long-term climate forcings? One of the principal goals of the Aeronomy of Ice in the Mesosphere satellite mission was to answer the question: "How does changing solar irradiance affect PMCs and the environment in which they form?" We describe an eight-year data set from the AIM Solar Occultation for Ice Experiment (SOFIE) and the AIM Cloud Imaging and Particle Size (CIPS) experiment. Together, these instruments provide high-precision measurements of high-latitude summertime temperature (T), water vapor (H2O), and PMC ice properties for the period 2007-present. The complete temporal coverage of the summertime polar cap region for both the primary atmospheric forcings of PMC (T and H2O), together with a continually updated time series of Lyman-alpha solar irradiance, allows an in-depth study of the causes and effects of 27-day PMC variability. The small responses of these variables, relative to larger day-to-day changes from gravity waves, tides, inter-hemispheric coupling, etc. require a careful statistical analysis to isolate the solar influence. We present results for the 27-day responses of T, H2O and PMC for a total of 15 PMC seasons, (30 days before summer solstice to 60 days afterward, for both hemispheres). We find that the amplitudes and phase relationships are not consistent with the expected mechanisms of solar UV heating and photolysis - instead we postulate a primarily dynamical response, in which a periodic vertical wind heats/cools the upper mesosphere, and modulates PMC

  11. GHRSST Level 2P Global Subskin Sea Surface Temperature from the Advanced Microwave Scanning Radiometer 2 on the GCOM-W satellite (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Advanced Microwave Scanning Radiometer 2 (AMSR2) was launched on 18 May 2012, onboard the Global Change Observation Mission - Water (GCOM-W) satellite developed...

  12. GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Terra satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Moderate-resolution Imaging Spectroradiometer (MODIS) is a scientific instrument (radiometer) launched by NASA in 1999 on board the Terra satellite platform (a...

  13. GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Aqua satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Moderate-resolution Imaging Spectroradiometer (MODIS) is a scientific instrument (radiometer) launched by NASA in 2002 on board the Aqua satellite platform (a...

  14. Testing and Adapting a Daytime Four Band Satellite Ash Detection Algorithm for Eruptions in Alaska and the Kamchatka Peninsula, Russia

    Science.gov (United States)

    Andrup-Henriksen, G.; Skoog, R. A.

    2007-12-01

    Volcanic ash is detectable from satellite remote sensing due to the differences in spectral signatures compared to meteorological clouds. Recently a new global daytime ash detection algorithm was developed at University of Madison, Wisconsin. The algorithm is based on four spectral bands with the central wavelengths 0.65, 3.75, 11 and 12 micrometers that are common on weather satellite sensors including MODIS, AVHRR, GOES and MTSAT. The initial development of the algorithm was primarily based on MODIS data with global coverage. We have tested it using three years of AVHRR data in Alaska and the Kamchatka Peninsula, Russia. All the AVHRR data have been manually analyzed and recorded into an observational database during the daily monitoring performed by the remote sensing group at the Alaska Volcano Observatory (AVO). By taking the manual observations as accurate we were able to examine the accuracy of the four-channel algorithm for daytime data. The results were also compared to the current automated ash alarm used by AVO, based on the reverse absorption technique, also known as the split window method, with a threshold of -1.7K. This comparison indicates that the four- banded technique has a higher sensitivity to volcanic ash, but a greater number of false alarms. The algorithm was modified to achieve a false alarm rate comparable to current ash alarm while still maintaining increased sensitivity.

  15. Application of advanced very high resolution radiometer (AVHRR)-based vegetation health indices for estimation of malaria cases.

    Science.gov (United States)

    Rahman, Atiqur; Krakauer, Nir; Roytman, Leonid; Goldberg, Mitch; Kogan, Felix

    2010-06-01

    Satellite data may be used to map climatic conditions conducive to malaria outbreaks, assisting in the targeting of public health interventions to mitigate the worldwide increase in incidence of the mosquito-transmitted disease. This work analyzes correlation between malaria cases and vegetation health (VH) indices derived from satellite remote sensing for each week over a period of 14 years for Bandarban, Bangladesh. Correlation analysis showed that years with a high summer temperature condition index (TCI) tended to be those with high malaria incidence. Principal components regression was performed on patterns of weekly TCI during each of the two annual malaria seasons to construct a model as a function of the TCI. These models reduced the malaria estimation error variance by 57% if first-peak (June-July) TCI was used as the estimator and 74% if second-peak (August-September) was used, compared with an estimation of average number of malaria cases for each year.

  16. Inland Water Temperature: An Ideal Indicator for the National Climate Assessment

    Science.gov (United States)

    Hook, S. J.; Lenters, J. D.; O'Reilly, C.; Healey, N. C.

    2014-12-01

    NASA is a significant contributor to the U.S. National Climate Assessment (NCA), which is a central component of the 2012-2022 U.S. Global Change Research Program Strategic Plan. The NCA has identified the need for indicators that provide a clear, concise way of communicating to NCA audiences about not only the status and trends of physical drivers of the climate system, but also the ecological and socioeconomic impacts, vulnerabilities, and responses to those drivers. We are using thermal infrared satellite data in conjunction with in situ measurements to produce water temperatures for all the large inland water bodies in North America for potential use as an indicator for the NCA. Recent studies have revealed significant warming of inland waters throughout the world. The observed rate of warming is - in many cases - greater than that of the ambient air temperature. These rapid, unprecedented changes in inland water temperatures have profound implications for lake hydrodynamics, productivity, and biotic communities. Scientists are just beginning to understand the global extent, regional patterns, physical mechanisms, and ecological consequences of lake warming. As part of our earlier studies we have collected thermal infrared satellite data from those satellite sensors that provide long-term and frequent spaceborne thermal infrared measurements of inland waters including ATSR, AVHRR, and MODIS and used these to examine trends in water surface temperature for approximately 100 of the largest inland water bodies in the world. We are now extending this work to generate temperature time-series of all North American inland water bodies that are sufficiently large to be studied using 1km resolution satellite data for the last 3 decades. These data are then being related to changes in the surface air temperature and compared with regional trends in water surface temperature derived from CMIP5/IPCC model simulations/projections to better predict future temperature changes

  17. Satellite Communications

    CERN Document Server

    Pelton, Joseph N

    2012-01-01

    The field of satellite communications represents the world's largest space industry. Those who are interested in space need to understand the fundamentals of satellite communications, its technology, operation, business, economic, and regulatory aspects. This book explains all this along with key insights into the field's future growth trends and current strategic challenges. Fundamentals of Satellite Communications is a concise book that gives all of the key facts and figures as well as a strategic view of where this dynamic industry is going. Author Joseph N. Pelton, PhD, former Dean of the International Space University and former Director of Strategic Policy at Intelstat, presents a r

  18. A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

    Directory of Open Access Journals (Sweden)

    Robert M. Parinussa

    2016-10-01

    Full Text Available Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth’s surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1–2 GHz. Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E, as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM, and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm and descending (01:30 am paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for

  19. Satellite Geomagnetism

    DEFF Research Database (Denmark)

    Olsen, Nils; Stolle, Claudia

    2012-01-01

    Observations of Earth’s magnetic field from space began more than 50 years ago. A continuous monitoring of the field using low Earth orbit (LEO) satellites, however, started only in 1999, and three satellites have taken highprecision measurements of the geomagnetic field during the past decade...... ability to characterize and understand the many sources that contribute to Earth’s magnetic field. In this review, we summarize investigations of Earth’s interior and environment that have been possible through the analysis of high-precision magnetic field observations taken by LEO satellites........ The unprecedented time-space coverage of their data opened revolutionary new possibilities for monitoring, understanding, and exploring Earth’s magnetic field. In the near future, the three-satellite constellation Swarm will ensure continuity of such measurement and provide enhanced possibilities to improve our...

  20. Satellite (Natural)

    Science.gov (United States)

    Murdin, P.

    2000-11-01

    In its most general sense, any celestial object in orbit around a similar larger object. Thus, for example, the Magellanic Clouds are satellite galaxies of our own Milky Way galaxy. Without qualification, the term is used to mean a body in orbit around a planet; an alternative term is moon. The term natural satellite distinguishes these bodies from artificial satellites—spacecraft placed in orbi...

  1. Recent trends in agricultural production of Africa based on AVHRR NDVI time series

    Science.gov (United States)

    Vrieling, Anton; de Beurs, Kirsten M.; Brown, Molly E.

    2008-10-01

    African agriculture is expected to be hard-hit by ongoing climate change. Effects are heterogeneous within the continent, but in some regions resulting production declines have already impacted food security. Time series of remote sensing data allow us to examine where persistent changes occur. In this study, we propose to examine recent trends in agricultural production using 26 years of NDVI data. We use the 8-km resolution AVHRR NDVI 15-day composites of the GIMMS group (1981-2006). Temporal data-filtering is applied using an iterative Savitzky-Golay algorithm to remove noise in the time series. Except for some regions with persistent cloud cover, this filter produced smooth profiles. Subsequently two methods were used to extract phenology indicators from the profiles for each raster cell. These indicators include start of season, length of season, time of maximum NDVI, maximum NDVI, and cumulated NDVI over the season. Having extracted the indicators for every year, we aggregate them for agricultural areas at sub-national level using a crop mask. The aggregation was done to focus the analysis on agriculture, and allow future comparison with yield statistics. Trend analysis was performed for yearly aggregated indicators to assess where persistent change occurred during the 26-year period. Results show that the phenology extraction method chosen has an important influence on trend outcomes. Consistent trends suggest a rising yield trend for 500-1100 mm rainfall zones ranging from Senegal to Sudan. Negative yield trends are expected for the southern Atlantic coast of West Africa, and for western Tanzania.

  2. Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from Chinese Geostationary FengYun Meteorological Satellite (FY-2C Data

    Directory of Open Access Journals (Sweden)

    Jun Xia

    2008-02-01

    Full Text Available On the basis of the radiative transfer theory, this paper addressed the estimate ofLand Surface Temperature (LST from the Chinese first operational geostationarymeteorological satellite-FengYun-2C (FY-2C data in two thermal infrared channels (IR1,10.3-11.3 μ m and IR2, 11.5-12.5 μ m , using the Generalized Split-Window (GSWalgorithm proposed by Wan and Dozier (1996. The coefficients in the GSW algorithmcorresponding to a series of overlapping ranging of the mean emissivity, the atmosphericWater Vapor Content (WVC, and the LST were derived using a statistical regressionmethod from the numerical values simulated with an accurate atmospheric radiativetransfer model MODTRAN 4 over a wide range of atmospheric and surface conditions.The simulation analysis showed that the LST could be estimated by the GSW algorithmwith the Root Mean Square Error (RMSE less than 1 K for the sub-ranges with theViewing Zenith Angle (VZA less than 30° or for the sub-rangs with VZA less than 60°and the atmospheric WVC less than 3.5 g/cm2 provided that the Land Surface Emissivities(LSEs are known. In order to determine the range for the optimum coefficients of theGSW algorithm, the LSEs could be derived from the data in MODIS channels 31 and 32 provided by MODIS/Terra LST product MOD11B1, or be estimated either according tothe land surface classification or using the method proposed by Jiang et al. (2006; and theWVC could be obtained from MODIS total precipitable water product MOD05, or beretrieved using Li et al.’ method (2003. The sensitivity and error analyses in term of theuncertainty of the LSE and WVC as well as the instrumental noise were performed. Inaddition, in order to compare the different formulations of the split-window algorithms,several recently proposed split-window algorithms were used to estimate the LST with thesame simulated FY-2C data. The result of the intercomparsion showed that most of thealgorithms give

  3. Automated satellite cloud analysis: a multispectral approach to the problem of snow/cloud discrimination

    OpenAIRE

    Allen, Robert C. Jr.

    1987-01-01

    Approved for public release; distribution is unlimited An algorithm is developed and evaluated for discriminating among clouds, snow cover and clear land. The multispectral technique uses daytime images of AVHRR channels 1 (0.63^m). 3 (3.7jim) and 4 (11.0[im). Reflectance is derived for channel 3 by using the channel 4 emission temperature to estimate and remove the channel 3 thermal emission. Separation of clouds from snow and land is based primarily on this derived channel...

  4. Persistent and Widespread Winter Haze & Fog over the Indo-Gangetic Plains: A climatological perspective from satellite observations

    Science.gov (United States)

    Gautam, R.

    2014-12-01

    Each year during winter season (December-January), dense fog engulfs the Indo-Gangetic Plains (IGP) in southern Asia, for more than a month, disrupting daily life of millions of people inhabiting the IGP. The widespread nature of the fog is frequently visible in satellite imagery, extending over a stretch of ~1500 km; that covers parts of Pakistan, northern India, Nepal and Bangladesh. Both, haze and fog are a tightly-coupled system over the IGP, during winter months, and have been a major environmental/climatic issue since the past several decades. Trends in poor visibility suggest a significant increase in worsening air quality and foggy days over the IGP. The persistent and widespread nature of the winter haze and fog is strongly influenced by the regional meteorology during wintertime, i.e. a stable boundary layer, low temperatures, high relative humidity and light winds. The valley-type topography of the IGP, adjacent to the towering Himalaya, and high concentrations of pollution aerosols, further favors the persistence of hazy/foggy conditions. A satellite-based observational portrayal will be presented, using various cloud, aerosol and radiation datasets, to characterize the widespread nature of winter haze and fog, based on a multi-sensor assessment from MODIS, CERES, AVHRR and CALIPSO datasets. More specifically, based on these observations, we will present results on: long-term trends/variability of winter haze and fog, vertical characterization of aerosol/fog/low-clouds, as well as assessment of the direct radiative effect of the region-wide haze/fog system. Results from this work are anticipated to shed light on the overall interactions within the highly persistent and tightly-coupled haze-fog phenomena. Additionally, against the backdrop of a changing climate scenario, possible linkages between the winter-time fog cover, regional meteorology and aerosol loading will also be discussed over the IGP.

  5. Monitoring of wetlands Ecosystems using satellite images

    Science.gov (United States)

    Dabrowska-Zielinska, K.; Gruszczynska, M.; Yesou, H.; Hoscilo, A.

    Wetlands are very sensitive ecosystems, functioning as habitat for many organisms. Protection and regeneration of wetlands has been the crucial importance in ecological research and in nature conservation. Knowledge on biophysical properties of wetlands vegetation retrieved from satellite images will enable us to improve monitoring of these unique areas, very often impenetrable. The study covers Biebrza wetland situated in the Northeast part of Poland and is considered as Ramsar Convention test site. The research aims at establishing of changes in biophysical parameters as the scrub encroachment, lowering of the water table, and changes of the farming activity caused ecological changes at these areas. Data from the optical and microwave satellite images collected for the area of Biebrza marshland ecosystem have been analysed and compared with the detailed soil-vegetation ground measurements conducted in conjunction with the overflights. Satellite data include Landsat ETM, ERS-2 ATSR and SAR, SPOT VEGETATION, ENVISAT MERIS and ASAR, and NOAA AVHRR. From the optical data various vegetation indices have been calculated, which characterize the vegetation surface roughness, its moisture conditions and stage of development. Landsat ETM image has been used for classification of wetlands vegetation. For each class of vegetation various moisture indices have been developed. Ground data collected include wet and dry biomass, LAI, vegetation height, and TDR soil moisture. The water cloud model has been applied for retrieval of soil vegetation parameters taking into account microwave satellite images acquired at VV, HV and HH polarisations at different viewing angles. The vegetation parameters have been used for to distinguish changes, which occurred at the area. For each of the vegetation class the soil moisture was calculated from microwave data using developed algorithms. Results of this study will help mapping and monitoring wetlands with the high spatial and temporal

  6. Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements

    Directory of Open Access Journals (Sweden)

    Stefan Wunderle

    2008-04-01

    Full Text Available This study evaluates the ability to track grassland growth phenology in the Swiss Alps with NOAA-16 Advanced Very High Resolution Radiometer (AVHRR Normalized Difference Vegetation Index (NDVI time series. Three growth parameters from 15 alpine and subalpine grassland sites were investigated between 2001 and 2005: Melt-Out (MO, Start Of Growth (SOG, and End Of Growth (EOG.We tried to estimate these phenological dates from yearly NDVI time series by identifying dates, where certain fractions (thresholds of the maximum annual NDVI amplitude were crossed for the first time. For this purpose, the NDVI time series were smoothed using two commonly used approaches (Fourier adjustment or alternatively Savitzky-Golay filtering. Moreover, AVHRR NDVI time series were compared against data from the newer generation sensors SPOT VEGETATION and TERRA MODIS. All remote sensing NDVI time series were highly correlated with single point ground measurements and therefore accurately represented growth dynamics of alpine grassland. The newer generation sensors VGT and MODIS performed better than AVHRR, however, differences were minor. Thresholds for the determination of MO, SOG, and EOG were similar across sensors and smoothing methods, which demonstrated the robustness of the results. For our purpose, the Fourier adjustment algorithm created better NDVI time series than the Savitzky-Golay filter, since latter appeared to be more sensitive to noisy NDVI time series. Findings show that the application of various thresholds to NDVI time series allows the observation of the temporal progression of vegetation growth at the selected sites with high consistency. Hence, we believe that our study helps to better understand largescale vegetation growth dynamics above the tree line in the European Alps.

  7. Results of calibrations of the NOAA-11 AVHRR made by reference to calibrated SPOT imagery at White Sands, N.M

    Science.gov (United States)

    Nianzeng, Che; Grant, Barbara G.; Flittner, David E.; Slater, Philip N.; Biggar, Stuart F.; Jackson, Ray D.; Moran, M. S.

    1991-01-01

    The calibration method reported here makes use of the reflectances of several large, uniform areas determined from calibrated and atmospherically corrected SPOT Haute Resolution Visible (HRV) scenes of White Sands, New Mexico. These reflectances were used to predict the radiances in the first two channels of the NOAA-11 Advanced Very High Resolution Radiometer (AVHRR). The digital counts in the AVHRR image corresponding to these known reflectance areas were determined by the use of two image registration techniques. The plots of digital counts versus pixel radiance provided the calibration gains and offsets for the AVHRR. A reduction in the gains of 4 and 13 percent in channels 1 and 2 respectively was found during the period 1988-11-19 to 1990-6-21. An error budget is presented for the method and is extended to the case of cross-calibrating sensors on the same orbital platform in the Earth Observing System (EOS) era.

  8. Scientific Satellites

    Science.gov (United States)

    1967-01-01

    followed Hale’s into orbit. In 1879, Jules Verne wrote about launching small satellites with a gun possessing a muzzle velocity of 10 000 m/sec (ref. 3...was activated in 1950.11 It was located only a few tens of miles from the spot where Jules Verne had his Baltimore Gun Club fire a manned projectile to...principle, satellites can be launched by a single impulse applied at the Earth’s surface-say, with a large cannon, & la Jules Verne (sec. 8-3). In

  9. An assessment of the accuracy of SST retrievals from AATSR onboard ESA's Envisat by validation with in situ radiometer and buoy data and other satellites

    Science.gov (United States)

    Corlett, G. K.; Aatsr Sst Validation Team

    The Advanced Along-Track Scanning Radiometer (AATSR) was launched on Envisat in March 2002. The AATSR instrument is a highly stable self-calibrating radiometer designed to make precise and accurate global Sea-Surface Temperature (SST) measurements. These data, when added to the large data set collected from its predecessors ATSR and ATSR-2, will provide a long-term record of SST measurements (>15 years) that can be used for independent monitoring and detecting of climate change. The formal specifications require that retrieved AATSR SST values achieve an absolute accuracy of better than ± 0.5 K, with ± 0.3 K (one sigma) adopted by the project as the target accuracy. An intensive SST validation programme has been in operation since launch that involves validating retrieved AATSR SST values against a) SST data retrieved from other satellite sensors such as AVHRR and MODIS b) a global network of buoy derived SST measurements and c) SST values determined from in-situ data collected from high-precision radiometers. This presentation will summarise the AATSR SST validation programme and will show that AATSR is currently meeting its objective to determine accurate global SST measurements to within 0.3 K (one sigma).

  10. Winter wheat production forecast in United States of America using AVHRR historical data and NCAR Growing Degree Day

    Science.gov (United States)

    Claverie, M.; Franch, B.; Vermote, E.; Becker-Reshef, I.; Justice, C. O.

    2015-12-01

    Wheat is one of the key cereals crop grown worldwide. Thus, accurate and timely forecasts of its production are critical for informing agricultural policies and investments, as well as increasing market efficiency and stability. Becker-Reshef et al. (2010) used an empirical generalized model for forecasting winter wheat production using combined BRDF-corrected daily surface reflectance from the Moderate resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG) with detailed official crop statistics and crop type masks. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season, percent wheat within the CMG pixel, and the final yields. This method predicts the yield approximately one month to six weeks prior to harvest. Recently, Franch et al. (2015) included Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data in order to improve the winter wheat production forecast by increasing the timeliness of the forecasts between a month to a month and a half prior to the peak NDVI (i.e. 1-2.5 months prior to harvest), while conserving the accuracy of the original model. In this study, we apply these methods to historical data from the Advanced Very High Resolution Radiometer (AVHRR). We apply both the original and the modified model to United States of America from 1990 to 2014 and inter-compare the AVHRR results to MODIS from 2000 to 2014.

  11. 面向皮卫星应用的MEMS陀螺温度控制系统设计%Design of Temperature Control System of Pico-Satellite MEMS Gyroscope

    Institute of Scientific and Technical Information of China (English)

    朱小丰; 王昊; 郑阳明; 韩柯; 金仲和

    2011-01-01

    A temperature control system of MEMS gyroscope which faces to Pico-Satellite application is designed, the principle is based on ADN8831 and TEC. The factors which influence the accuracy of the temperature control system is analyzed,and the R-T characteristics of thermistor which shows that the precision of the temperature control system is about ±0. 03 ℃ are fitted by Steinhart-Hart equation. The temperature control system is used for MEMS gyroscope which faces to Pico-Satellite application and the Allan variance theory is used to stochastic modeling of MEMS gyroscope, the results of temperature experiments show that Bias instability and Rate Random Walk of MEMS gyroscope are enhanced, which validates the effectiveness of the temperature control system, according to the characteristics of small volume & low power of Pico-Satellite.%设计了一种面向皮卫星应用的MEMS陀螺温度控制系统,其控制原理为基于ADN8831的TEC温度控制。分析了影响温控系统控制精度的各因素,并且通过Steinhart-Hart方程对热敏电阻的R-T特性进行拟合校准后表明,本温控系统的精度达到±0.03℃。将设计的温控系统应用于面向皮卫星的MEMS陀螺温度控制,通过Allan方差分析MEMS陀螺的误差项。通过不同温度下实验得出,当该温控系统存在时,零偏不稳定性和速率随机游走得到了不同程度的改善,验证了温控系统的有效性,满足了皮卫星体积小、功耗低的要求。

  12. Remotely sensed soil temperatures beneath snow-free skin-surface using thermal observations from tandem polar-orbiting satellites: An analytical three-time-scale model

    DEFF Research Database (Denmark)

    Zhan, Wenfeng; Zhou, Ji; Ju, Weimin

    2014-01-01

    ), which represents the instantaneous temperature; and the weather-change temperature cycle (WTC), which is divided into two parts to represent both the daily-averaged (WTCavg) and the instantaneous temperature (WTCinst). The DTC and WTCinst were further parameterized into four undetermined variables...

  13. DYNAMICAL ANALYSIS OF BANDA SEA CONCERNING WITH EL NINO, INDONESIAN THROUGH FLOW AND MONSOON BY USING SATELLITE DATA AND NUMERICAL MODEL

    Directory of Open Access Journals (Sweden)

    Bambang Sukresno

    2012-11-01

    Full Text Available Banda sea is subjected to external force such as El Nino South Oscillation (ENSO, Indonesian Through Flow (ITF andMonsoon. All of these component Combined with Current System, caused sea dynamic. This study aimed to get further knowledge aboutBanda sea dynamic. Based on this phenomenon , this study was conducted with an hypothesis that sea level anomaly (SLA and seasufrace temperature (SST will decrease during ENSO event. Also that SLA and SST will seasonally change concerning with Monsoon.The pattern of current in eastern of Banda sea will be seasonally different concerning with monsoon while in western of Banda sea isalmost constant according to ITFThis research carried out in Banda Sea within the rectangular region from 122.42 E to 131.47 E , Latitude 03.47 S to 07.65 S.in period of 1996 to 2006 consist of northwest monsoon, southeast monsoon, 1st transitional month in April and 2nd transitional monthin October. Spatial analysis used to analyze annual and seasonal distribution of SST and SLA from satellite dataset, also by comparisonbetween wind data, ITF pathway and numerical model. SST derived from NOAA / AVHRR satellite data by applying MCSST algorithm,SLA derived from Topex/ Poseidon and Jason-1 Satellite data by applying Inverse distance weighted interpolation, while numerical modelderived from barothropic model using Princeton ocean model.Sea level anomaly and sea surface temperature is decrease according to ENSO event, such as descrease of SLA and SST duringENSO event in 1997 , 2002 and 2004. Sea level anomaly and sea surface temperature is change according to Monsoon that reverse every6 (six month. SST and SLA get maximum level during northwest monsoon in November to March and get Minimum during Southeastmonsoon in May to September. There are strong correlation coefficient between annual Sea level anomaly and annual Sea SurfaceTemperature with index value up to 0.817104. on the other side correlation coefficient between seasonal Sea

  14. A Change Oriented Extension of EOF Analysis Applied to the 1996-1997 AVHRR Sea Surface Temperature Data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Conradsen, Knut; Andersen, Ole Baltazar

    2002-01-01

    autocorrelation between neighbouring observations. The results show that the large scale ocean events associated with the El Nino/Southern Oscillation (ENSO) related changes are concentrated in the first SST MAF/MAD mode and the two first SSH MAF/MAD modes. The MAD/MAF analysis also revealed a spatially...

  15. 4 km NODC/RSMAS AVHRR Pathfinder v.5.0 Sea Surface Temperature (SST) Climatologies (1985-2001)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 4 km Pathfinder effort at the National Oceanic and Atmospheric Administration (NOAA) National Oceanographic Data Center (NODC) and the University of Miami's...

  16. Analysis of H2-Ni Battery Temperature Oscillation Mechanism for GEO Satellites%GEO卫星氢镍蓄电池在轨温度波动机理分析

    Institute of Scientific and Technical Information of China (English)

    刘百麟; 周佐新

    2011-01-01

    在某地球静止轨道通信卫星平台布局的基础上,通过合理地简化和假设建立了南蓄电池舱作为热分析计算模型,对影响蓄电池在轨温度波动的机理进行分析.分析结果表明:在冬至,西板、对地+Y板和背地+Y板受照外热流的日变化会引起其内表面温度大幅度波动,通过舱内热辐射又会引起服务舱南板等结构板内表面温度波动,而服务舱南板通过导热将引起安装其上的蓄电池温度波动,这是导致蓄电池温度波动的根本原因.%Based on the layout of the GEO communications satellites bus, the thermal math model (TMM) of south satellite battery cabin was presented to analyze the mathematical mechanism that influences battery temperature on orbit. It is shown that daily change of orbit heat flux will obviously influences the temperatures of west board, +Y panel of Earth deck and +Y panel of anti-Earth deck, and further influences the temperature of service module (SM) structure board through radiation, which induces the battery temperate variation through SM board conduction. This is the key reason of battery temperature variation.

  17. Stereoscopic observations from meteorological satellites

    Science.gov (United States)

    Hasler, A. F.; Mack, R.; Negri, A.

    two satellites. A general solution for accurate height computation depends on precise navigation of the two satellites. Validation of the geosynchronous satellite stereo using high altitude mountain lakes and vertically pointing aircraft lidar leads to a height accuracy estimate of +/- 500 m for typical clouds which have been studied. Applications of the satellite stereo include: 1) cloud top and base height measurements, 2) cloud-wind height assignment, 3) vertical motion estimates for convective clouds (Mack et al. [13], [14]), 4) temperature vs. height measurements when stereo is used together with infrared observations and 5) cloud emissivity measurements when stereo, infrared and temperature sounding are used together (see Szejwach et al. [15]). When true satellite stereo image pairs are not available, synthetic stereo may be generated. The combination of multispectral satellite data using computer produced stereo image pairs is a dramatic example of synthetic stereoscopic display. The classic case uses the combination of infrared and visible data as first demonstrated by Pichel et al. [16]. Hasler et at. [17], Mosher and Young [18] and Lorenz [19], have expanded this concept to display many channels of data from various radiometers as well as real and simulated data fields. A future system of stereoscopic satellites would be comprised of both low orbiters (as suggested by Lorenz and Schmidt [20], [19]) and a global system of geosynchronous satellites. The low earth orbiters would provide stereo coverage day and night and include the poles. An optimum global system of stereoscopic geosynchronous satellites would require international standarization of scan rate and direction, and scan times (synchronization) and resolution of at least 1 km in all imaging channels. A stereoscopic satellite system as suggested here would make an extremely important contribution to the understanding and prediction of the atmosphere.

  18. Estimating root-zone moisture and evapotranspiration with AVHRR data[Advanced Very High Resolution Radiometer

    Energy Technology Data Exchange (ETDEWEB)

    Song, J.; Wesely, M. L.

    1999-10-08

    The parameterized subgrid-scale surface fluxes (PASS) model uses satellite data and limited surface observations to infer root-zone available moisture content and evapotranspiration rate with moderate spatial resolution over extended terrestrial areas. The ultimate goal of this work is to produce estimates of water loss by evapotranspiration, for application in hydrological models. The major advantage to the method is that it can be applied to areas having diverse surface characteristics where direct surface flux measurements either do not exist or are not feasible and where meteorological data are available from only a limited number of ground stations. The emphasis of this work with the PASS model is on improving (1) methods of using satellite remote sensing data to derive the essential parameters for individual types of surfaces over large areas, (2) algorithms for describing the interactions of near-surface atmospheric conditions with surface processes, and (3) algorithms for computing surface energy and water vapor flux at a scale close to the size of a satellite-derived image pixel. The PASS approach is being developed and tested further with observations from the 1997 Cooperative Atmosphere-Surface Exchange Study (CASES-97) at the Atmospheric Boundary Layer Experiments (ABLE) site in the Walnut River Watershed (WRW), an area of about 5,000 km{sup 2} in southern Kansas. Here the authors describe some of the progress made since the previous report.

  19. Sensor Calibration Inter-Comparison Methodologies and Applications TO AVHRR, MODIS, AND VIIRS Observations

    Science.gov (United States)

    Xiong, Xiaoxiong; Wu, Aisheng; Cao, Changyong; Doelling, David

    2012-01-01

    As more and more satellite observations become available to the science and user community, their on-orbit calibration accuracy and consistency over time continue to be an important and challenge issue, especially in the reflective solar spectral regions. In recent years, many sensor calibration inter-comparison methodologies have been developed by different groups and applied to a range of satellite observations, aiming to the improvement of satellite instrument calibration accuracy and data quality. This paper provides an overview of different methodologies developed for inter-comparisons of A VHRR and MODIS observations, and extends their applications to the Visible-Infrared Imaging Radiometer Suite (VIIRS) instrument. The first VIIRS was launched on-board the NPP spacecraft on October 28, 2011. The VIIRS, designed with MODIS heritage, collects data in 22 spectral bands from visible (VIS) to long-wave infrared (LWIR). Like both Terra and Aqua MODIS, the VIIRS on-orbit calibration is performed using a set of on-board calibrators (OBC), Methodologies discussed in this paper include the use of well-characterized ground reference targets, near simultaneous nadir overpasses (SNO), lunar observations, and deep convective clouds (DeC). Results from long-term A VHRR and MODIS observations and initial assessment of VIIRS on-orbit calibration are presented. Current uncertainties of different methodologies and potential improvements are also discussed in this paper.

  20. Remote sensing of pigment concentration and sea surface temperature on the continental shelf of China

    Science.gov (United States)

    Tang, Danling

    The combination of a population of more than 1.2 billion people and the recent rapid industrialization and large-scale infrastructure projects have placed a very heavy burden on the coastal environment in China. Algal blooms and red tides pose a serious threat to public health, fisheries and aquaculture industry. Consequently, a thorough assessment of their impacts on the coastal zone is urgently needed. This research is the first application of the historical satellite remote sensing archive to investigate temporal and spatial patterns of pigment concentrations (PC) and sea surface temperatures (SST) on the entire continental shelf of China. Firstly, I examined the temporal (annual/monthly) and spatial patterns of PC and SST on the continental shelf of China. The image availability for the study area was examined. A total of 2139 scenes were obtained from the study area during the years of the Nimbus-7 satellite mission (from 1978 to 1986), from which 76 monthly and 8 annual composite CZCS images were generated. AVHRR (Advanced Very High Resolution Radiometer) data from NOAA (National Oceanic & Atmospheric Administration) satellites were also examined. A distinctive high PC belt of about 50 km wide existed along the coastline of China, and a large plume of high PC was observed which extended nearly 500 km to the east from the Yangtze River. PC were high in the Yellow Sea (about 1--2 mg m-3 it decreased seawards and southeastwards with a minimum value in the Philippine Sea (about 0.2 mg m-3 ). Annual PC increased from 1979 and reached a peak in 1981; it dropped in 1982 with a strong El Nino. In the northern area (Yellow Sea), there were two peaks of PC in each year (spring and fall). In the southern area (northern South China Sea), PC was relatively low and constant over each year. A basin-wide gyre appeared in the center of the Yellow Sea in April 1986. Secondly, I focused on the Luzon Strait, a channel between the Philippine Sea and the South China Sea. High

  1. Honey Bees, Satellites and Climate Change

    Science.gov (United States)

    Esaias, W.

    2008-05-01

    Life isn't what it used to be for honey bees in Maryland. The latest changes in their world are discussed by NASA scientist Wayne Esaias, a biological oceanographer with NASA Goddard Space Flight Center. At Goddard, Esaias has examined the role of marine productivity in the global carbon cycle using visible satellite sensors. In his personal life, Esaias is a beekeeper. Lately, he has begun melding his interest in bees with his professional expertise in global climate change. Esaias has observed that the period when nectar is available in central Maryland has shifted by one month due to local climate change. He is interested in bringing the power of global satellite observations and models to bear on the important but difficult question of how climate change will impact bees and pollination. Pollination is a complex, ephemeral interaction of animals and plants with ramifications throughout terrestrial ecosystems well beyond the individual species directly involved. Pollinators have been shown to be in decline in many regions, and the nature and degree of further impacts on this key interaction due to climate change are very much open questions. Honey bee colonies are used to quantify the time of occurrence of the major interaction by monitoring their weight change. During the peak period, changes of 5-15 kg/day per colony represent an integrated response covering thousands of hectares. Volunteer observations provide a robust metric for looking at spatial and inter-annual variations due to short term climate events, complementing plant phenology networks and satellite-derived vegetation phenology data. In central Maryland, the nectar flows are advancing by about -0.6 d/y, based on a 15 yr time series and a small regional study. This is comparable to the regional advancement in the spring green-up observed with MODIS and AVHRR. The ability to link satellite vegetation phenology to honey bee forage using hive weight changes provides a basis for applying satellite

  2. GHRSST Level 2P Global 1 meter Sea Surface Temperature from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS)....

  3. GHRSST Level 2P Gridded Global Subskin Sea Surface Temperature from WindSat polarimetric radiometer on the Coriolis satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains sea surface temperature derived from observations made by the WindSat Polarimetric Radiometer developed by the Naval Research Laboratory (NRL)...

  4. A simple model of light transmission through the atmosphere over the Baltic Sea utilising satellite data

    Directory of Open Access Journals (Sweden)

    Marcin Paszkuta

    2008-06-01

    Full Text Available A simple spectral model of solar energy input to the sea surface was extended to incorporate space-borne data. The extension involved finding a method of determining aerosol optical thickness (on the basis of AVHRR data and the influence of cloudiness (on the basis of METEOSAT data on the solar energy flux. The algorithm for satellite data assimilation involves the analysis of satellite images from the point of view of cloud identification and their classification with respect to light transmission. Solar energy input values measured at the Earth's surface by traditional methods were used to calibrate and validate the model. Preliminary evaluation of the results indicates a substantial improvement in the accuracy of estimates of solar energy input to the sea surface in relation to models utilising only traditionally obtained data on the state of the atmosphere.

  5. On the role of sea surface temperature variability over the Tropical Indian Ocean in relation to summer monsoon using satellite data

    Digital Repository Service at National Institute of Oceanography (India)

    RameshKumar, M.R.; Muraleedharan, P.M.; Sathe, P.V.

    for to the skin SST, whereas the climatological values refer to either engine-intake water temperature or the bucketdifferent seasons, MCSST data with Reynolds and Smith (1994) data for all the five years except in case of July thermometer readings which were... taken at different depths. The difference in temperature between skin SST1991, namely, winter (represented by January), spring (represented by April), summer (represented by July), and the bulk SST varies from 11Kto21 K for differ- ent areas (Robinson...

  6. A Climate-Data Record (CDR) of the "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

    Science.gov (United States)

    Hall, Dorothy K.; Comiso, Josefino C.; DiGirolamo, Nocolo E.; Shuman, Christopher A.

    2011-01-01

    We have developed a climate-data record (CDR) of "clear-sky" ice-surface temperature (IST) of the Greenland Ice Sheet using Moderate-Resolution Imaging Spectroradiometer (MODIS) data. The CDR provides daily and monthly-mean IST from March 2000 through December 2010 on a polar stereographic projection at a resolution of 6.25 km. The CDR is amenable to extension into the future using Visible/Infrared Imager Radiometer Suite (VIIRS) data. Regional "clear-sky" surface temperature increases since the early 1980s in the Arctic, measured using Advanced Very High Resolution Radiometer (AVHRR) infrared data, range from 0.57 +/- 0.02 to 0.72 +/- 0.1 c per decade. Arctic warming has important implications for ice-sheet mass balance because much of the periphery of the Greenland Ice Sheet is already near O C during the melt season, and is thus vulnerable to rapid melting if temperatures continue to increase. An increase in melting of the ice sheet would accelerate sea-level rise, an issue affecting potentially billions of people worldwide. The IST CDR will provide a convenient data set for modelers and for climatologists to track changes of the surface temperature of the ice sheet as a whole and of the individual drainage basins on the ice sheet. The daily and monthly maps will provide information on surface melt as well as "clear-sky" temperature. The CDR will be further validated by comparing results with automatic-weather station data and with satellite-derived surface-temperature products.

  7. Simulation of the water regime for a vast agricultural region territory utilizing measurements from polar-orbital and geostationary meteorological satellites

    Science.gov (United States)

    Muzylev, Eugene; Uspensky, Alexander; Startseva, Zoya; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

    2013-04-01

    The model of land surface-atmosphere interaction has been developed to calculate the water and heat balance components for vast vegetation covered areas during the growing season. The model is adjusted to utilize estimates of the land surface and meteorological characteristics derived from satellite-based measurements of radiometers AVHRR/NOAA, MODIS/EOS Terra, Aqua, and SEVIRI/Meteosat-9. The studies have been conducted for the territory of the European Russia Central Black Earth Region (CCR) with area of 227,300 km2 comprising seven regions of the Russian Federation for years 2009-2012 vegetation seasons. The technologies of AVHRR and MODIS data thematic processing have been refined and adapted to the study region providing the retrieval of land surface temperature Tls and emissivity E, land-air temperature (temperature at vegetation cover level) Ta, normalized difference vegetation index NDVI, vegetation cover fraction B, as well as the leaf area index LAI. The updated linear regression estimators for Tls, Ta and LAI have been built using more representative training samples compiled for the above vegetation seasons. The updated software package has been applied for AVHRR data processing to generate named remote sensing products for various dates of the mentioned vegetation periods. On the base of special technology and Internet resources the remote sounding products (Tls, E, NDVI, LAI), derived from MODIS data and covering the CCR, have been downloaded from LP DAAC web-site for the same vegetation seasons. The new method and technology have been developed and adopted for the retrieval of Tls and E from SEVIRI data. The retrievals cover the region of interest and are produced at daylight and nighttime. Method provides the derivation of Tls and E from SEVIRI measurements carried out at three successive times (for example, at 11.00, 12.00, 13.00 UTC), classified as 100% cloud-free for the study region without accurate a priori knowledge of E. The validation of

  8. Coastal upwelling observed by multi-satellite sensors

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Coastal upwelling phenomenon along the China coast in the Yellow Sea during August 2007 is studied using ENVISAT Advanced Synthetic Aperture Radar (ASAR) data, NOAA Advanced AVHRR series Sea Surface Temperature (SST) data,and NASA QuikSCAT Scatterometer ocean surface wind data. A dark pattern in an ASAR image is interpreted as coastal upwelling. This is because the natural biogenic slicks associated with coastal upwelling damp the Bragg waves on the sea surface and thus make the surface smoother. Most of the incoming radar energy is reflected in the forward direction. As a result, the radar backscatter signal is very weak. Analyzing the concurrent AVHRR SST image, we find that the dark pattern in the ASAR image is indeed corresponding to the low SST area. The wind retrieval in the slicks dominant region is biased due to the low Normalised Radar Cross Section (NRCS) associated with the coastal upwelling. We applied a SST correction to the NRCS values to improve the accuracy of wind retrieval from ASAR data.

  9. Coastal upwelling observed by multi-satellite sensors

    Institute of Scientific and Technical Information of China (English)

    LI XiaoMing; LI XiaoFeng; HE MingXia

    2009-01-01

    Coastal upwelling phenomenon along the China coast in the Yellow Sea during August 2007 is studied using ENVISAT Advanced Synthetic Aperture Radar (ASAR) data, NOAA Advanced AVHRR series Sea Surface Temperature (SST) data, and NASA QuikSCAT Scatterometer ocean surface wind data. A dark pattern in an ASAR image is interpreted as coastal upwelling. This is because the natural biogenic slicks associated with coastal upwelling damp the Bragg waves on the sea surface and thus make the surface smoother. Most of the incoming radar energy is reflected in the forward direction. As a result, the radar backscatter signal is very weak. Analyzing the concurrent AVHRR SST Image, we find that the dark pattern in the ASAR image is indeed corresponding to the low SST area. The wind retrieval in the slicks dominant region is biased due to the low Normaliced Radar Cross Section (NRCS) associated with the coastal upwelling. We applied a SST correction to the NRCS values to improve the accuracy of wind retrieval from ASAR data.

  10. Coupling AVHRR imagery with biogeochemical models of methane emission from rice crops

    Science.gov (United States)

    Paliouras, Eleni Joyce

    2000-10-01

    Rice is a staple food source for much of the world and most of it is grown in paddies which remain flooded for a large part of the growing season. This anaerobic environment is ideal for the activities of methanogenic bacteria, that are responsible for the production of methane gas, some of which is released into the atmosphere. In order to better understand the role that rice cropping plays in the levels of atmospheric methane, several models have been developed to predict the methane flux from the paddies. These models generally utilize some type of nominal plant growth curve based on one or two pieces of ground truth data. Ideally, satellite data could be used instead to provide these models with an estimate of biomass change over the growing season, eliminating the need for related ground truth. A technique proposed to accomplish this is presented here, and results that demonstrate its success when applied to rice cropping areas of Texas are discussed. Also presented is a method for utilizing satellite data to map rice cropping areas that could eventually aid in a scheme for populating a GIS-type database with information on exact rice cropping areas. Such a database could then be directly tied to the methane emission models to obtain flux estimates for extensive regional areas.

  11. Coastal processes and hazards in the southern california bight: the use and requirements of multiple satellite sensors

    Science.gov (United States)

    Holt, B.; Digiacomo, P.; Washburn, L.; Jones, B. H.; Bosc, E.

    As part of an ongoing interdisciplinary study, we seek to provide a better understanding of the complex physical, ecological and biogeochemical processes in the coastal waters off southern California. At local and event-scales, this coastal area is characterized by phenomena such as eddies, internal waves and dust storms. At basin and climate scales, this region is impacted by the California Current (the eastern boundary current of the North Pacific) and remote forcing associated with ENSO events that strongly alter wind, current, water mass, and precipitation patterns. Furthermore, the Southern California Bight is adjacent to one of the largest industrialized urban populations in the world, which results in significant anthropogenic inputs to the coastal marine ecosystem, including such pollution hazard concerns as storm/waste-water runoff and oil spills. To address these diverse issues, we utilize a variety of satellite data including high-resolution ocean color observations (e.g., SeaWiFS, MODIS, and MERIS), sea surface temperature measurements (e.g., AVHRR, MODIS, and AATSR), and Synthetic Aperture Radar (SAR) imagery of surface features and derived wind fields (e.g., RADARSAT, ERS, and ASAR) that are complemented and validated by coincident field data (from moorings, drifters, ships, and shore-based HF radar). These synergistic data sets enable the detection, quantification and understanding of under-sampled and poorly described coastal ocean processes and pollution hazards of the type described above and an assessment of their ecological (e.g., harmful algal blooms), biogeochemical (carbon cycling), and human (pathogens) impact. We will present representative case studies on the observation of these processes and hazards that demonstrate the utility of multiple sensors, as well as assessments of where continuity in multi-sensor observations is required and identification of existing or foreseen observation gaps with recommendations on how these should be

  12. Geostationary Satellite (GOES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

  13. Neptune's small satellites

    Science.gov (United States)

    Thomas, P.

    1992-04-01

    The small satellites of Neptune and other planets discovered during the Voyager 2 mission are discussed in terms of their composition and relationship to the planetary systems. The satellite Proteus is described in terms of its orbit, five other satellites are described, and they are compared to ther small satellites and systems. Neptune's satellites are hypothesized to be related to the ring system, and the satellite Galatea is related to the confinement of the rings.

  14. Assimilation of Sea Surface Temperature in a doubly, two-way nested primitive equation model of the Ligurian Sea

    Science.gov (United States)

    Barth, A.; Alvera-Azcarate, A.; Rixen, M.; Beckers, J.-M.; Testut, C.-E.; Brankart, J.-M.; Brasseur, P.

    2003-04-01

    The GHER 3D primitive equation model is implemented with three different resolutions: a low resolution model (1/4^o) covering the whole Mediterranean Sea, an intermediate resolution model (1/20^o) of the Liguro-Provençal basin and a high resolution model (1/60^o) simulating the fine mesoscale structures in the Ligurian Sea. Boundary conditions and the averaged fields (feedback) are exchanged between two successive nesting levels. The model of the Ligurian Sea is also coupled with the assimilation package SESAM. It allows to assimilate satellite data and in situ observations using the local adaptative SEEK (Singular Evolutive Extended Kalman) filter. Instead of evolving the error space by the numerically expensive Lyapunov equation, a simplified algebraic equation depending on the misfit between observation and model forecast is used. Starting from the 1st January 1998 the low and intermediate resolution models are spun up for 18 months. The initial conditions for the Ligurian Sea are interpolated from the intermediate resolution model. The three models are then integrated until August 1999. During this period AVHRR Sea Surface Temperature of the Ligurian Sea is assimilated. The results are validated by using CTD and XBT profiles of the SIRENA cruise from the SACLANT Center. The overall objective of this study is pre-operational. It should help to identify limitations and weaknesses of forecasting methods and to suggest improvements of existing operational models.

  15. Analysis of China Vegetation Dynamics Using NOAA-AVHRR Data from 1982 to 2001%利用NOAA-AVHRR数据分析1982-2001年间中国植被的动态变化

    Institute of Scientific and Technical Information of China (English)

    HABIB Aziz Salim; 陈晓玲; 龚健雅; 王海燕; 张俐

    2009-01-01

    The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period,China's vegetation cover had tended to increase, compared to the early 1980s; mean annual NDVI increased 3.8%. The agricultural regions (Henan, Hebei, Anhui and Shandong) and the west of China are marked by an increase, while the eastern coastal regions are marked by a decrease. The correlation between monthly NDVI and monthly precipitation/temperature in the period 1982 to 2001 is significantly positive ( R2 =0.80, R2=0.84); indicating the close coupling between climate conditions (precipitation and temperature) and land surface response patterns over China. Examination of NDVI time series reveals two periods: (1) 1982-1989, marked by low values below average NDVI and persistence of drought with a signature large-scale drought during the 1982 and 1989; and (2) 1990-2001, marked by a wetter trend with region-wide high values above average NDVI and a maximum level occurring in 1994 and 1998.

  16. Study to assess the importance of errors introduced by applying NOAA 6 and NOAA 7 AVHRR data as an estimator of vegetative vigor: Feasibility study of data normalization

    Science.gov (United States)

    Duggin, M. J. (Principal Investigator); Piwinski, D.

    1982-01-01

    The use of NOAA AVHRR data to map and monitor vegetation types and conditions in near real-time can be enhanced by using a portion of each GAC image that is larger than the central 25% now considered. Enlargement of the cloud free image data set can permit development of a series of algorithms for correcting imagery for ground reflectance and for atmospheric scattering anisotropy within certain accuracy limits. Empirical correction algorithms used to normalize digital radiance or VIN data must contain factors for growth stage and for instrument spectral response. While it is not possible to correct for random fluctuations in target radiance, it is possible to estimate the necessary radiance difference between targets in order to provide target discrimination and quantification within predetermined limits of accuracy. A major difficulty lies in the lack of documentation of preprocessing algorithms used on AVHRR digital data.

  17. 热控涂层红外发射率对GEO卫星蓄电池温度波动的影响%Effect of Thermal Control Battery Temperature Coatings Infrared Emittance on Variation in GEO Satellite

    Institute of Scientific and Technical Information of China (English)

    刘百麟; 周佐新

    2012-01-01

    Based on DFH-3 satellite platform, the simplified south satellite battery cabin is presen- ted as the thermal analysis model. According to the mechanism of battery temperature variation, five combination schemes, in which the thermal control coatings of white paint,aluminized kapton and graphite-epoxy facesheet are used for inner panel of service module board, are proposed and used to analyze the effect of thermal control coatings infrared emittance on battery temperature. The analysis results show that the range of battery temperature variation can be reduced effectively by decreasing the thermal control coatings infrared emittance of inner panel in battery cabin, especially decreasing the thermal control coatings infrared emittance of fixing panel in battery cabin. The range of battery temperature variation in optimization scheme is decreased by 50% than that in original design scheme.%在东方红一3卫星平台的基础上,将合理简化后的南蓄电池舱作为热分析模型。根据影响蓄电池温度波动的机理,提出服务舱舱板内表面常用热控涂层(白漆、镀铝膜、碳蒙皮)的5种组合方案,并量化分析了热控涂层红外发射率对蓄电池温度波动的影响。分析结果表明:降低蓄电池舱舱板内表面热控涂层红外发射率,尤其是降低蓄电池安装舱板表面的热控涂层红外发射率,可有效减小蓄电池温度波动幅度。与基准方案相比,最优组合方案能使蓄电池温度波动幅度降低50%。

  18. GHRSST Level 2P Atlantic Regional Skin Sea Surface Temperature from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on the Meteosat Second Generation (MSG-1) satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Meteosat Second Generation (MSG) satellites are spin stabilized geostationary satellites operated by the European Organization for the Exploitation of...

  19. GHRSST Level 2P Atlantic Regional Skin Sea Surface Temperature from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on the Meteosat Second Generation (MSG-2) satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Meteosat Second Generation (MSG) satellites are spin stabilized geostationary satellites operated by the European Organization for the Exploitation of...

  20. GHRSST Level 2P Atlantic Regional Skin Sea Surface Temperature from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on the Meteosat Second Generation (MSG-3) satellite (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Meteosat Second Generation (MSG-3) satellites are spin stabilized geostationary satellites operated by the European Organization for the Exploitation of...