Evaluation of Operational Albedo Algorithms For AVHRR, MODIS and VIIRS: Case Studies in Southern Africa

Science.gov (United States)

Privette, J. L.; Schaaf, C. B.; Saleous, N.; Liang, S.

2004-12-01

Shortwave broadband albedo is the fundamental surface variable that partitions solar irradiance into energy available to the land biophysical system and energy reflected back into the atmosphere. Albedo varies with land cover, vegetation phenological stage, surface wetness, solar angle, and atmospheric condition, among other variables. For these reasons, a consistent and normalized albedo time series is needed to accurately model weather, climate and ecological trends. Although an empirically-derived coarse-scale albedo from the 20-year NOAA AVHRR record (Sellers et al., 1996) is available, an operational moderate resolution global product first became available from NASA's MODIS sensor. The validated MODIS product now provides the benchmark upon which to compare albedo generated through 1) reprocessing of the historic AVHRR record and 2) operational processing of data from the future National Polar-Orbiting Environmental Satellite System's (NPOESS) Visible/Infrared Imager Radiometer Suite (VIIRS). Unfortunately, different instrument characteristics (e.g., spectral bands, spatial resolution), processing approaches (e.g., latency requirements, ancillary data availability) and even product definitions (black sky albedo, white sky albedo, actual or blue sky albedo) complicate the development of the desired multi-mission (AVHRR to MODIS to VIIRS) albedo time series -- a so-called Climate Data Record. This presentation will describe the different albedo algorithms used with AVHRR, MODIS and VIIRS, and compare their results against field measurements collected over two semi-arid sites in southern Africa. We also describe the MODIS-derived VIIRS proxy data we developed to predict NPOESS albedo characteristics. We conclude with a strategy to develop a seamless Climate Data Record from 1982- to 2020.

Estimating solar radiation using NOAA/AVHRR and ground measurement data

Science.gov (United States)

Fallahi, Somayeh; Amanollahi, Jamil; Tzanis, Chris G.; Ramli, Mohammad Firuz

2018-01-01

Solar radiation (SR) data are commonly used in different areas of renewable energy research. Researchers are often compelled to predict SR at ground stations for areas with no proper equipment. The objective of this study was to test the accuracy of the artificial neural network (ANN) and multiple linear regression (MLR) models for estimating monthly average SR over Kurdistan Province, Iran. Input data of the models were two data series with similar longitude, latitude, altitude, and month (number of months) data, but there were differences between the monthly mean temperatures in the first data series obtained from AVHRR sensor of NOAA satellite (DS1) and in the second data series measured at ground stations (DS2). In order to retrieve land surface temperature (LST) from AVHRR sensor, emissivity of the area was considered and for that purpose normalized vegetation difference index (NDVI) calculated from channels 1 and 2 of AVHRR sensor was utilized. The acquired results showed that the ANN model with DS1 data input with R2 = 0.96, RMSE = 1.04, MAE = 1.1 in the training phase and R2 = 0.96, RMSE = 1.06, MAE = 1.15 in the testing phase achieved more satisfactory performance compared with MLR model. It can be concluded that ANN model with remote sensing data has the potential to predict SR in locations with no ground measurement stations.

Estimation of the soil temperature from the AVHRR-NOAA satellite data applying split window algorithms

International Nuclear Information System (INIS)

Parra, J.C.; Acevedo, P.S.; Sobrino, J.A.; Morales, L.J.

2006-01-01

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)

Recent history of large-scale ecosystem disturbances in North America derived from the AVHRR satellite record.

Science.gov (United States)

Christopher Potter; Tan Pang-Ning; Vipin Kumar; Chris Kucharik; Steven Klooster; Vanessa Genovese; Warren Cohen; Sean. Healey

2005-01-01

Ecosystem structure and function are strongly affected 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...

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

-2013 vegetation seasons. To provide the retrieval of Ts.eff, E, Ta, NDVI, B, and LAI the previously developed technologies of AVHRR data processing have been refined and adapted to the region of interest. The updated linear regression estimators for Ts.eff and Tà have been built using representative training samples compiled for above vegetation seasons. The updated software package has been applied for AVHRR data processing to generate estimates of named values. To verify the accuracy of these estimates the error statistics of Ts.eff and Ta derivation has been investigated for various days of named seasons using comparison with in-situ ground-based measurements. On the base of special technology and Internet resources the remote sensing products Tls, E, NDVI, LAI derived from MODIS data and covering the study area have been extracted from LP DAAC web-site for the same vegetation seasons. The reliability of the MODIS-derived Tls estimates has been confirmed via comparison with analogous and collocated ground-, AVHRR-, and SEVIRI-based ones. The prepared remote sensing dataset has also included the SEVIRI-derived estimates of Tls, E, NDVI, Ta at daylight and night-time and daily estimates of LAI. The Tls estimates has been built utilizing the method and technology developed for the retrieval of Tls and E from 15 minutes time interval SEVIRI data in IR channels 10.8 and 12.0 µm (classified as 100% cloud-free and covering the area of interest) at three successive times without accurate a priori knowledge of E. Comparison of the SEVIRI-based Tls retrievals with independent collocated Tls estimates generated at the Land Surface Analysis Satellite Applications Facility (LSA SAF, Lisbon, Portugal) has given daily- or monthly-averaged values of RMS deviation in the range of 2°C for various dates and months during the mentioned vegetation seasons which is quite acceptable result. The reliability of the SEVIRI-based Tls estimates for the study area has been also confirmed by comparing

A Non-Stationary 1981–2012 AVHRR NDVI3g Time Series

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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.

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.

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

Midwest agriculture and ENSO: A comparison of AVHRR NDVI3g data and crop yields in the United States Corn Belt from 1982 to 2014

Science.gov (United States)

Glennie, Erin; Anyamba, Assaf

2018-06-01

A time series of Advanced Very High Resolution Radiometer (AVHRR) derived normalized difference vegetation index (NDVI) data were compared to National Agricultural Statistics Service (NASS) corn yield data in the United States Corn Belt from 1982 to 2014. The main objectives of the comparison were to assess 1) the consistency of regional Corn Belt responses to El Niño/Southern Oscillation (ENSO) teleconnection signals, and 2) the reliability of using NDVI as an indicator of crop yield. Regional NDVI values were used to model a seasonal curve and to define the growing season - May to October. Seasonal conditions in each county were represented by NDVI and land surface temperature (LST) composites, and corn yield was represented by average annual bushels produced per acre. Correlation analysis between the NDVI, LST, corn yield, and equatorial Pacific sea surface temperature anomalies revealed patterns in land surface dynamics and corn yield, as well as typical impacts of ENSO episodes. It was observed from the study that growing seasons coincident with La Niña events were consistently warmer, but El Niño events did not consistently impact NDVI, temperature, or corn yield data. Moreover, the El Niño and La Niña composite images suggest that impacts vary spatially across the Corn Belt. While corn is the dominant crop in the region, some inconsistencies between corn yield and NDVI may be attributed to soy crops and other background interference. The overall correlation between the total growing season NDVI anomaly and detrended corn yield was 0.61(p = 0.00013), though the strength of the relationship varies across the Corn Belt.

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

Impacts of Land Cover and Seasonal Variation on Maximum Air Temperature Estimation Using MODIS Imagery

Directory of Open Access Journals (Sweden)

Yulin Cai

2017-03-01

Full Text Available Daily maximum surface air temperature (Tamax is a crucial factor for understanding complex land surface processes under rapid climate change. Remote detection of Tamax has widely relied on the empirical relationship between air temperature and land surface temperature (LST, a product derived from remote sensing. However, little is known about how such a relationship is affected by the high heterogeneity in landscapes and dynamics in seasonality. This study aims to advance our understanding of the roles of land cover and seasonal variation in the estimation of Tamax using the MODIS (Moderate Resolution Imaging Spectroradiometer LST product. We developed statistical models to link Tamax and LST in the middle and lower reaches of the Yangtze River in China for five major land-cover types (i.e., forest, shrub, water, impervious surface, cropland, and grassland and two seasons (i.e., growing season and non-growing season. Results show that the performance of modeling the Tamax-LST relationship was highly dependent on land cover and seasonal variation. Estimating Tamax over grasslands and water bodies achieved superior performance; while uncertainties were high over forested lands that contained extensive heterogeneity in species types, plant structure, and topography. We further found that all the land-cover specific models developed for the plant non-growing season outperformed the corresponding models developed for the growing season. Discrepancies in model performance mainly occurred in the vegetated areas (forest, cropland, and shrub, suggesting an important role of plant phenology in defining the statistical relationship between Tamax and LST. For impervious surfaces, the challenge of capturing the high spatial heterogeneity in urban settings using the low-resolution MODIS data made Tamax estimation a difficult task, which was especially true in the growing season.

AVHRR-based drought-observing system for monitoring the environment and socioeconomic activities

Science.gov (United States)

Kogan, F.

From all natural disaster, drought is the least understandable and the most damaging environmental phenomenon. Although in pre-satellite era, climate data were used for drought monitoring, drought specifics created problems in early drought detection start/end, monitoring its expansion/contraction, intensity and area coverage and the most important, timely estimation of the impacts on the environment and socioeconomic activities. The latest prevented to take prompt measures in mitigating negative consequences of drought for the society. Advances in remote sensing of the past ten years, contributed to the development of comprehensive drought monitoring system and numerous applications, which helped to make decisions for monitoring the environment and predicting sustainable socioeconomic activities. This paper discusses satellite-based land-surface observing system, which provides wells of information used for monitoring such unusual natural disaster as drought. This system was developed from the observations of the Advanced Very High Resolution Radiometer (AVHRR) flown on NOAA operational polar-orbiting satellites. The AVHRR data were packed into the Global Vegetation Index (GVI) product, which have served the global community since 1981. The GVI provided reflectances and indices (4 km spacial resolution) every seven days for each 16 km map cell between 75EN and 55ES covering all land ecosystems. The data includes raw and calibrated radiances in the visible, near infrared and infrared spectral bands, processed (with eliminated high frequency noise) radiances, normalized difference vegetation index (NDVI), 20-year climatology, vegetation condition indices and also products, such as vegetation health, drought, vegetation fraction, fire risk etc. In the past ten years, users around the world used this information addressing different issues of drought impacts on socioeconomic activities and responded positively to real time drought information place regularly on the

Effect of land use on the seasonal variation of streamwater quality in the Wei River basin, China

Science.gov (United States)

Yu, S.; Xu, Z.; Wu, W.; Zuo, D.

2015-05-01

The temporal effect of land use on streamwater quality needs to be addressed for a better understanding of the complex relationship between land use and streamwater quality. In this study, GIS and Pearson correlation analysis were used to determine whether there were correlations of land-use types with streamwater quality at the sub-basin scale in the Wei River basin, China, during dry and rainy seasons in 2012. Temporal variation of these relations was observed, indicating that relationships between water quality variables and proportions of different land uses were weaker in the rainy season than that in the dry season. Comparing with other land uses, agriculture and urban lands had a stronger relationship with water quality variables in both the rainy and dry seasons. These results suggest that the aspect of temporal effects should be taken into account for better land-use management.

Utilization of satellite remote sensing data on land surface characteristics in water and heat balance component modeling for vegetation covered territories

Science.gov (United States)

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

2010-05-01

The model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) for vegetation covered territory has been developed, allowing assimilating satellite remote sensing data on land surface condition as well as accounting for heterogeneities of vegetation and meteorological characteristics. The model provides the calculation of water and heat balance components (such as evapotranspiration Ev, soil water content W, sensible and latent heat fluxes and others ) as well as vertical soil moisture and temperature distributions, temperatures of soil surface and foliage, land surface brightness temperature for any time interval within vegetation season. To describe the landscape diversity soil constants and leaf area index LAI, vegetation cover fraction B, and other vegetation characteristics are used. All these values are considered to be the model parameters. Territory of Kursk region with square about 15 thousands km2 situated in the Black Earth zone of Central Russia was chosen for investigation. Satellite-derived estimates of land surface characteristics have been constructed under cloud-free condition basing AVHRR/NOAA, MODIS/EOS Terra and EOS Aqua, SEVIRI/Meteosat-8, -9 data. The developed technologies of AVHRR data thematic processing have been refined providing the retrieval of surface skin brightness temperature Tsg, air foliage temperature Ta, efficient surface temperature Ts.eff and emissivity E, as well as derivation of vegetation index NDVI, B, and LAI. The linear regression estimators for Tsg, Ta and LAI have been built using representative training samples for 2003-2009 vegetation seasons. The updated software package has been applied for AVHRR data thematic processing to generate named remote sensing products for various dates of the above vegetation seasons. The error statistics of Ta, Ts.eff and Тsg derivation has been investigated for various samples using comparison with in-situ measurements that has given RMS errors in the

Land use and land use change effects on nitrous oxide emissions in the seasonally dry ecosystems of Zimbabwe

DEFF Research Database (Denmark)

Nyamadzawo, G; Chirinda, Ngoni; Mapanda, F

2012-01-01

. The savanna woodlands cover over 95% of Zimbabwe’s forest area, and are divided into five woodland types: Acacia, miombo, mopane, teak (Baikiaea Plurijuga) and Terminalia-Combretaceae. This review is aimed at exploring the effects of land-use changes and land management practices on N2O emissions in Zimbabwe...... emissions were mainly concentrated in the wet season as N2O production is strongly enhanced by high soil moisture. During the dry season pyrogenic emissions were also important sources of N2O, contributing, an estimated 6.7 Gg N2O annually. Land use change in the form of biomass burning and conversion...... of emissions of N2O. Land-use change from savanna to agricultural production results in an immediate increase in N2O emissions. However, the emissions will decrease with time. The current estimates are associated with large uncertainties, thus, there is need for more detailed studies on the effects of land-use...

Climate variability and land cover change over the North American monsoon region (Invited)

Science.gov (United States)

Zeng, X.; Scheftic, W. D.; Broxton, P. D.

2013-12-01

The North American Monsoon System over Mexico and southwestern United States represents a weather/climate and ecosystem coupled "macrosystem". The weather and climate affect the seasonal and interannual variability of ecosystem, while the ecosystem change affects surface energy, water, and carbon fluxes that, in turn, affect weather and climate. Furthermore, long-term weather/climate data have a much coarser horizontal resolution than the satellite land cover data. Here the North American Regional Reanalysis (NARR) data at 32 km grid spacing will be combined with various satellite remote sensing products at 1 km and/or 8 km resolution from AVHRR, MODIS, and SPOT for the period of 1982 to present. Our analysis includes: a) precipitation, wind, and precipitable water data from NARR to characterize the North American monsoon; b) land cover type, normalized difference vegetation index (NDVI), green vegetation fraction, and leaf-area index (LAI) data to characterize the seasonal and interannual variability of ecosystem; c) assessing the consistency of various satellite products; and d) testing the coherence in the weather/climate and ecosystem variability.

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

International Nuclear Information System (INIS)

Kasischke, E.S.; French, N.H.F.; Harrell, P.; Christensen, N.L. Jr.; Ustin, S.L.; Barry, D.

1993-01-01

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

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...

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...

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

[An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

Science.gov (United States)

Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

2009-10-01

Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

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.)

Effects of Seasonal Land Surface Conditions on Hydrometeorological Dynamics in South-western North America

Science.gov (United States)

2015-09-21

rain gauges to measure precipitation , and 1 internal mini-flume to measure runoff . 9 Fig. 8. Processed fluxes measured at the two eddy...SECURITY CLASSIFICATION OF: Arid and semiarid landscapes in regions with seasonal precipitation experience dramatic changes that alter land surface...semiarid landscapes in regions with seasonal precipitation experience dramatic changes that alter land surface conditions, including soil moisture

Arctic sea ice albedo from AVHRR

Science.gov (United States)

Lindsay, R. W.; Rothrock, D. A.

1994-01-01

The seasonal cycle of surface albedo of sea ice in the Arctic is estimated from measurements made with the Advanced Very High Resolution Radiometer (AVHRR) on the polar-orbiting satellites NOAA-10 and NOAA-11. The albedos of 145 200-km-square cells are analyzed. The cells are from March through September 1989 and include only those for which the sun is more than 10 deg above the horizon. Cloud masking is performed manually. Corrections are applied for instrument calibration, nonisotropic reflection, atmospheric interference, narrowband to broadband conversion, and normalization to a common solar zenith angle. The estimated albedos are relative, with the instrument gain set to give an albedo of 0.80 for ice floes in March and April. The mean values for the cloud-free portions of individual cells range from 0.18 to 0.91. Monthly averages of cells in the central Arctic range from 0.76 in April to 0.47 in August. The monthly averages of the within-cell standard deviations in the central Arctic are 0.04 in April and 0.06 in September. The surface albedo and surface temperature are correlated most strongly in March (R = -0.77) with little correlation in the summer. The monthly average lead fraction is determined from the mean potential open water, a scaled representation of the temperature or albedo between 0.0 (for ice) and 1.0 (for water); in the central Arctic it rises from an average 0.025 in the spring to 0.06 in September. Sparse data on aerosols, ozone, and water vapor in the atmospheric column contribute uncertainties to instantaneous, area-average albedos of 0.13, 0.04, and 0.08. Uncertainties in monthly average albedos are not this large. Contemporaneous estimation of these variables could reduce the uncertainty in the estimated albedo considerably. The poor calibration of AVHRR channels 1 and 2 is another large impediment to making accurate albedo estimates.

Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

Science.gov (United States)

Ceglar, Andrej; Toreti, Andrea; Prodhomme, Chloe; Zampieri, Matteo; Turco, Marco; Doblas-Reyes, Francisco J

2018-01-22

Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.

AVHRR for monitoring global tropical deforestation

Science.gov (United States)

Malingreau, J. P.; Laporte, N.; Tucker, C. J.

1989-01-01

Advanced Very High Resolution Radiometer (AVHRR) data have been used to assess the dynamics of forest trnsformations in three parts of the tropical belt. A large portion of the Amazon Basin has been systematically covered by Local Area Coverage (LAC) data in the 1985-1987 period. The analysis of the vegetation index and thermal data led to the identification and measurement of large areas of active deforestation. The Kalimantan/Borneo forest fires were monitored and their impact was evaluated using the Global Area Coverage (GAC) 4 km resolution data. Finally, High Resolution Picture Transmission (HRPT) data have provided preliminary information on current activities taking place at the boundary between the savanna and the forest in the Southern part of West Africa. The AVHRR approach is found to be a highly valuable means for carrying out deforestation assessments in regional and global perspectives.

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.

Remote sensing of biomass burning in West Africa with NOAA-AVHRR

International Nuclear Information System (INIS)

Brustet, J.M.; Vickos, J.B.; Fontan, J.; Manissadjan, K.; Podaire, A.; Lavenu, F.

1991-01-01

Remote sensing measurements provide a valuable means of determining the extent of burning areas and estimating the overall distribution of the sources in time and space. The Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite is well adapted to a wide coverage of the large African savanna regions. It is necessary to watch the whole area even at times other then during the dry season, since two consecutive weeks without precipitation may be sufficient to allow the bushes to catch fire. The images examined in this chapter include the whole of West Africa - namely, within latitudes 5 degree and 14 degree N and 1 degree and 11 degree W. The study has been focused on a region that contains part of the Guinea territory, Mali, the Ivory Coast, and Burkina Faso

AVHRR Leads-ARI Polar Gridded Brightness Temperatures

Data.gov (United States)

National Aeronautics and Space Administration — This data set consists of AVHRR imagery selected from hard copy 'quick look' images to provide the best coverage possible over the Arctic approximately every three...

Global validation of two-channel AVHRR aerosol optical thickness retrievals over the oceans

International Nuclear Information System (INIS)

Liu Li; Mishchenko, Michael I.; Geogdzhayev, Igor; Smirnov, Alexander; Sakerin, Sergey M.; Kabanov, Dmitry M.; Ershov, Oleg A.

2004-01-01

The paper presents validation results for the aerosol optical thickness derived by applying a two-channel retrieval algorithm to Advanced Very High Resolution Radiometer (AVHRR) radiance data. The satellite retrievals are compared with ship-borne sun-photometer results. The comparison of spatial and temporal statistics of the AVHRR results and the ship measurements shows a strong correlation. The satellite retrieval results obtained with the original algorithm for a wavelength of 0.55μm are systematically higher than the sun-photometer measurements in the cases of low aerosol loads. The ensemble averaged satellite-retrieved optical thickness overestimates the ensemble averaged sun-photometer data by about 11% with a random error of about 0.04. Increasing the diffuse component of the ocean surface reflectance from 0.002 to 0.004 in the AVHRR algorithm produces a better match, with the ensemble-averaged AVHRR-retrieved optical thickness differing by only about 3.6% from the sun-photometer truth and having a small offset of 0.03

The Van Sant AVHRR image projected onto a rhombicosidodecahedron

Science.gov (United States)

Baron, Michael; Morain, Stan

1996-03-01

IDEATION, a design and development corporation, Santa Fe, New Mexico, has modeled Tom Van Sant's ``The Earth From Space'' image to a rhombicosidodecahedron. ``The Earth from Space'' image, produced by the Geosphere® Project in Santa Monica, California, was developed from hundreds of AVHRR pictures and published as a Mercator projection. IDEATION, utilizing a digitized Robinson Projection, fitted the image to foldable, paper components which, when interconnected by means of a unique tabular system, results in a rhombicosidodecahedron representation of the Earth exposing 30 square, 20 triangular, and 12 pentagonal faces. Because the resulting model is not spherical, the borders of the represented features were rectified to match the intersecting planes of the model's faces. The resulting product will be licensed and commercially produced for use by elementary and secondary students. Market research indicates the model will be used in both the demonstration of geometric principles and the teaching of fundamental spatial relations of the Earth's lands and oceans.

Long time-series of turbid coastal water using AVHRR: an example from Florida Bay, USA

Science.gov (United States)

Stumpf, Richard P.; Frayer, M. L.

1997-02-01

The AVHRR can provide information on the reflectance of turbid case II water, permitting examination of large estuaries and plumes from major rivers. The AVHRR has been onboard several NOAA satellites, with afternoon overpasses since 1981, offering a long time-series to examine changes in coastal water. We are using AVHRR data starting in December 1989, to examine water clarity in Florida Bay, which has undergone a decline since the late 1980's. The processing involves obtaining a nominal reflectance for red light with standard corrections including those for Rayleigh and aerosol path radiances. Established relationships between reflectance and the water properties being measured in the Bay provide estimates of diffuse attenuation and light limitation for phytoplankton and seagrass productivity studies. Processing also includes monthly averages of reflectance and attenuation. The AVHRR data set describes spatial and temporal patterns, including resuspension of bottom sediments in the winter, and changes in water clarity. The AVHRR also indicates that Florida Bay has much higher reflectivity relative to attenuation than other southeastern US estuaries.

Alternative method to validate the seasonal land cover regions of the conterminous United States

Science.gov (United States)

Zhiliang Zhu; Donald O. Ohlen; Raymond L. Czaplewski; Robert E. Burgan

1996-01-01

An accuracy assessment method involving double sampling and the multivariate composite estimator has been used to validate the prototype seasonal land cover characteristics database of the conterminous United States. The database consists of 159 land cover classes, classified using time series of 1990 1-km satellite data and augmented with ancillary data including...

Seasonal variation in standardized litter decomposition and effects of elevation and land use at Mount Kilimanjaro

Science.gov (United States)

Becker, Joscha; Kuzyakov, Yakov

2017-04-01

Decomposition is one of most important ecological steps in organic matter and nutrient cycles, but studies and reliable data from tropical regions in Africa are still scarce. At the global scale, litter decomposition and recycling is controlled by climatic factors and land-use intensity. These factors can be linked to specific ecosystem characteristics along the unique elevation gradient of Mt. Kilimanjaro. Our objectives were to assess the effects of climatic conditions (i.e. elevation) and land-use intensity on C turnover and stabilization and investigated the seasonal variations. Tea-bag Index (see www.teatime4science.org) was used to measure decomposition of a standardized litter substrate by microorganisms and mesofauna coffee plantations or cloud forest (S=0.11) respectively and strongly increased again to a maximum of S=0.41 in the alpine helichrysum ecosystem. During all seasons, we found the highest decomposition rates at mid elevation. However, during both warm seasons the peak is shifted upslope. Savanna experienced the strongest seasonal variation, with 23 times higher S-values in dry- compared to rainy season. Mean annual k-values increased for about 30% with increasing land-use intensity. C stabilization in Mt. Kilimanjaro ecosystems is strongly dependent on seasonal moisture limitation (lower slope) and perennial temperature limitation (alpine zone). Ecosystems at mid elevation (around 1920 & 2120m) represent the interception zone of optimal moisture and temperature conditions. High input and fast turnover drive the C sequestration in these ecosystems, while restrains on decomposition control the C turnover in lower and higher elevation zones. Land-use intensification decreases stabilization from new C inputs in transition zones from savanna to maize monocultures and from traditional homegardens to large-scale coffee plantations.

Estimation of land surface temperature based on satellite image data. Paper no. IGEC-1-117

International Nuclear Information System (INIS)

Torii, S.; Yano, T.; Iino, N.

2005-01-01

The aim of the present study is to predict a ground surface temperature (GST) of Kagoshima Prefecture in Kyushu Island, Japan, by using LANDSAT-5/TM and NOAA-11/AVHRR digital data. Image processing procedure is employed to aid in evaluating GST, in which the thermal images of AVHRR bands 4 and 5 are analysed. Emphasis is placed on the prediction accuracy of the existing atmospheric correlation equations taking the atmospheric attenuation effect into account, which are proposed by Tamba et. al., Bates and Diaz, and Sakkaida and Kawamura. It is disclosed that (I) the factor of the zenith angle need to be taken into account when the accurate GST is evaluated by using the atmospheric correction equations, (ii) that of Sakaida and Kawamura has better accuracy, (iii) LANDSAT-5/TM data contains a very high resolution level of the land, the estimated land surface temperature is higher than the measured value, and (iv) improved accuracy of the surface temperature is achieved if LANDSAT-5/TM data are used together with NOAA-11/AVHRR. (author)

The precision of the NDVI derived from AVHRR observations

International Nuclear Information System (INIS)

Roderick, M.; Smith, R.; Cridland, S.

1996-01-01

Vegetation studies using NOAA-AVHRR data have tended to focus on the use of the normalized difference vegetation index (NDVI). This unitless index is computed using near-infrared and red reflectances, and thus has both an accuracy and precision. This article reports on a formal statistical framework for assessing the precision of the NDVI derived from NOAA-AVHRR observations. The framework is based on the “best possible” precision concept, which assumes that signal quantization is the only source of observational error. While the radiance resolution of a spectral observation is essentially fixed by the instrument characteristics, the reflectance resolution is the radiance resolution divided by the cosine of the solar zenith angle. Using typical solar zenith angles for AVHRR image acquisitions over Australia, ± 0.01 NDVI units is typically with “best possible” precision attainable in the NDVI, although this degrades significantly over dark targets, and at large solar zenith angles. Transforming the computed NDVI into a single byte for disk storage results in little or no loss of precision. The framework developed in this article can be adapted to estimate the “best possible” precision of other vegetation indices derived using data from other remote sensing satellites. (author)

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.

Seasonal and interannual variability of solar radiation at Spirit, Opportunity and Curiosity landing sites

International Nuclear Information System (INIS)

Vicente-Retortillo, A.; Lemmon, M.T.; Martinez, G.; Valero, F.; Vazquez, L.; Martin, M.L.

2016-01-01

In this article we characterize the radiative environment at the landing sites of NASA's Mars Exploration Rover (MER) and Mars Science Laboratory (MSL) missions. We use opacity values obtained at the surface from direct imaging of the Sun and our radiative transfer model COMIMART to analyze the seasonal and interannual variability of the daily irradiation at the MER and MSL landing sites. In addition, we analyze the behavior of the direct and diffuse components of the solar radiation at these landing sites. (Author)

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression.

Science.gov (United States)

Chen, Qiang; Mei, Kun; Dahlgren, Randy A; Wang, Ting; Gong, Jian; Zhang, Minghua

2016-12-01

As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2 ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to

EUR-L3P-NAR_AVHRR_NOAA_19:1

Data.gov (United States)

National Aeronautics and Space Administration — 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...

Seasonal and interannual variability of solar radiation at Spirit, Opportunity and Curiosity landing sites

Energy Technology Data Exchange (ETDEWEB)

Vicente-Retortillo, A.; Lemmon, M.T.; Martinez, G.; Valero, F.; Vazquez, L.; Martin, M.L.

2016-07-01

In this article we characterize the radiative environment at the landing sites of NASA's Mars Exploration Rover (MER) and Mars Science Laboratory (MSL) missions. We use opacity values obtained at the surface from direct imaging of the Sun and our radiative transfer model COMIMART to analyze the seasonal and interannual variability of the daily irradiation at the MER and MSL landing sites. In addition, we analyze the behavior of the direct and diffuse components of the solar radiation at these landing sites. (Author)

AVHRR Leads-ARI Polar Gridded Brightness Temperatures, Version 1

Data.gov (United States)

National Aeronautics and Space Administration — This data set consists of AVHRR imagery selected from hard copy 'quick look' images to provide the best coverage possible over the Arctic approximately every three...

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.

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

Spatio-Temporal Changes in Vegetation Activity and Its Driving Factors during the Growing Season in China from 1982 to 2011

Directory of Open Access Journals (Sweden)

Bo Qu

2015-10-01

Full Text Available Using National Oceanographic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR and Climatic Research Unit (CRU climate datasets, we analyzed interannual trends in the growing-season Normalized Difference Vegetation Index (NDVI in China from 1982 to 2011, as well as the effects of climatic variables and human activities on vegetation variation. Growing-season (period between the onset and end of plant growth NDVI significantly increased (p < 0.01 on a national scale and showed positive trends in 52.76% of the study area. A multiple regression model was used to investigate the response of vegetation to climatic factors during recent and previous time intervals. The interactions between growing-season NDVI and climatic variables were more complex than expected, and a lag existed between climatic factors and their effects on NDVI. The regression residuals were used to show that over 6% of the study area experienced significantly human-induced vegetation variations (p < 0.05. These regions were mostly located in densely populated, reclaimed agriculture, afforestation, and conservation areas. Similar conclusions were drawn based on land-use change over the study period.

Clasificador genérico de objetos en imágenes AVHRR

OpenAIRE

Pascual Ramírez, Fermín; Paz Pellat, Fernando; Martínez Menes, Mario; Palacios Vélez, Enrique; Mejía Sáenz, Enrique; Rubio Granados, Erasmo

2010-01-01

El presente artículo describe un algoritmo para llevar a cabo una clasificación genérica de objetos utilizando imágenes del sensor advanced very high resolution radiometer (AVHRR), basado en la firma espectral de los objetos genéricos (suelo, mezcla suelo-vegetación, cuerpos de agua, nubes, etc.). Debido a las particularidades de las bandas disponibles en el sensor AVHRR, se presenta un algoritmo específico utilizando la banda 3a (B3a) y otro utilizando la banda 3b (B3b) de este sensor. Los a...

SAFARI 2000 AVHRR-derived Land Surface Temperature Maps, Africa, 1995-2000

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: Land Surface Temperature (LST) is a key indicator of land surface states, and can provide information on surface-atmosphere heat and mass fluxes,...

SAFARI 2000 AVHRR-derived Land Surface Temperature Maps, Africa, 1995-2000

Data.gov (United States)

National Aeronautics and Space Administration — Land Surface Temperature (LST) is a key indicator of land surface states, and can provide information on surface-atmosphere heat and mass fluxes, vegetation water...

Non-growing season soil CO2 efflux patterns in five land-use types in northern China

Science.gov (United States)

Overgrazing and unsuitable farming practices have led to grassland degradation in northern China. This studhy examined soil CO2 efflux (Fc) from five land-use types during the non-growing season on the southeastern edge of the Mongolian Plateau in China. The land-use types included three native v...

Detection of coal mine fires in the Jharia coal field using NOAA/AVHRR data

Energy Technology Data Exchange (ETDEWEB)

Agarwal, R.; Singh, D.; Chauhan, D.S.; Singh, K.P. [Harcourt Butler Technological Institute, Kanpur (India)

2006-09-15

Coal fires represent a major problem in most coal producing countries. The Jharia coal field (JCF) has been affected by surface and sub-surface coal fires since the beginning of mining in the region in the mid 1800s. Currently research is focused on using freely available satellite data such as NOAA/AVHRR, MODIS (moderate resolution imaging spectrometer) etc for various applications. The potential of National Oceanographic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) images for detecting coal fires and monitoring their progress and associated environmental hazards and risks to the local communities in the JCF has been reviewed. Three models, namely the thresholding model, the contextual model and the fuel mask model have been used to determine the potential fire pixels. Due to the coarse resolution of the NOAA/AVHRR data it was essential to determine sub-pixel fires as well. Results of this study have been verified using the MODIS active fires product, MOD14 (Terra). We have used ten images of NOAA/AVHRR for the year 2004 in this study, and the results are in broad agreement with the ground truth data.

AVHRR Polar 1 Km Level 1B Data Set

Data.gov (United States)

National Aeronautics and Space Administration — Please note that the machine on which these AVHRR data are processed has reached its life expectancy and will no longer be available as of 02 June 2008 until further...

A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description, Validation, and Case Study

Science.gov (United States)

Claverie, Martin; Matthews, Jessica L.; Vermote, Eric F.; Justice, Christopher O.

2016-01-01

In- land surface models, which are used to evaluate the role of vegetation in the context ofglobal climate change and variability, LAI and FAPAR play a key role, specifically with respect to thecarbon and water cycles. The AVHRR-based LAIFAPAR dataset offers daily temporal resolution,an improvement over previous products. This climate data record is based on a carefully calibratedand corrected land surface reflectance dataset to provide a high-quality, consistent time-series suitablefor climate studies. It spans from mid-1981 to the present. Further, this operational dataset is availablein near real-time allowing use for monitoring purposes. The algorithm relies on artificial neuralnetworks calibrated using the MODIS LAI/FAPAR dataset. Evaluation based on cross-comparisonwith MODIS products and in situ data show the dataset is consistent and reliable with overalluncertainties of 1.03 and 0.15 for LAI and FAPAR, respectively. However, a clear saturation effect isobserved in the broadleaf forest biomes with high LAI (greater than 4.5) and FAPAR (greater than 0.8) values.

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...

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...

Derivation of Coefficients for the Bidirectional Reflection Distribution Function from AVHRR-data over Europe, under Consideration of the Helmholtz Reciprocity Law

Science.gov (United States)

Billing, H.; Koslowsky, D.

In the AVHRR data of the polar orbiting NOAA Satellites, directional reflectance under a certain view from satellite and a certain illumination by the sun is measured. Due to the nearly sunsynchroneous orbit of the NOAA satellite, each area is seen under different viewing angles in successive days. Only after approximately 9 days, the conditions are again similar. Areas, seen in specular direction, may appear only half as bright, as if seen in antispecular direction. This deviation from a Lambertian reflector is a function of the surface roughness and the degree of coverage with vegetation. The NOAA afternoon satellites drift by half an hour from year to year. Thus even data from the same season, but different years, are seen under different illumination conditions. To derive the bidirectional reflection distribution function in dependence on satellite viewing angle and solar illumination becomes a very complicated procedure. Using the Helmholtz reciprocity principle (HRP), i.e. the symetrie in viewing and illumination, reduces the problem by one dimension. For different bidimensional reflection laws it will be tested, whether they can be formulated to fullfill the HRP. Via regression, the parameters will be deduced for time series of AVHRR data of 10 years from NOAA 11,14,16 and 17. Brdfunctions, suggested by Rao as well as a law, suggested by Ba seem to become unstable for low sun resp. large viewing zenit angles. Only brdfs with 4 coefficients can fit the observed distributions. A nonlinear temporal angular model (NTAM), suggested by Latifovic,Cihlar and Chen, seems to be suitable to describe even the hot spot and the dependence on plant growth. The coefficients of these brdf-function will be derived via regression for monthly series of cloud free data for the European area, where AVHRR data in full resolution are received in Berlin. Using these coefficients, monthly maps of surface roughness are produced for the above area for the time since 1985. Ba, M

Determining the rate of forest conversion in Mato Grosso, Brazil, using Landsat MSS and AVHRR data

Science.gov (United States)

Nelson, Ross; Horning, Ned; Stone, Thomas A.

1987-01-01

AVHRR-LAC thermal data and Landsat MSS and TM spectral data were used to estimate the rate of forest clearing in Mato Grosso, Brazil, between 1981 and 1984. The Brazilian state was stratified into forest and nonforest. A list sampling procedure was used in the forest stratum to select Landsat MSS scenes for processing based on estimates of fire activity in the scenes. Fire activity in 1984 was estimated using AVHRR-LAC thermal data. State-wide estimates of forest conversion indicate that between 1981 and 1984, 353,966 ha + or - 77,000 ha (0.4 percent of the state area) were converted per year. No evidence of reforestation was found in this digital sample. The relationship between forest clearing rate (based on MSS-TM analysis) and fire activity (estimated using AVHRR data) was noisy (R-squared = 0.41). The results suggest that AVHRR data may be put to better use as a stratification tool than as a subsidiary variable in list sampling.

Integração de imagens NOAA/AVHRR: rede de cooperação para monitoramento nacional da safra de soja Integration of NOAA/AVHRR images: cooperation network towards national soybean crop monitoring

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.An early assessment of national crop development conditions while the plants are still in the fields is highly needed to calculate correctly projections for decision-making and policies related to government planning and food security. The aim of this study

Hurricane Satellite (HURSAT) from Advanced Very High Resolution Radiometer (AVHRR)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Huricane Satellite (HURSAT)-Advanced Very High Resolution Radiometer (AVHRR) is used to extend the HURSAT data set such that appling the Objective Dvorak technique...

GHRSST Level 2P NEODAAS AVHRR18 Local SST:1

Data.gov (United States)

National Aeronautics and Space Administration — The production of these AVHRR L2P data is a NEODAAS activity in collaboration with the UK National Centre for Ocean Forecasting (NCOF). NEODAAS-Dundee acquires...

GHRSST Level 2P NEODAAS AVHRR17 Local SST:1

Data.gov (United States)

National Aeronautics and Space Administration — The production of these AVHRR L2P data is a NEODAAS activity in collaboration with the UK National Centre for Ocean Forecasting (NCOF). NEODAAS-Dundee acquires...

LAI, FAPAR and FCOVER products derived from AVHRR long time series: principles and evaluation

Science.gov (United States)

Verger, A.; Baret, F.; Weiss, M.; Lacaze, R.; Makhmara, H.; Pacholczyk, P.; Smets, B.; Kandasamy, S.; Vermote, E.

2012-04-01

Continuous and long term global monitoring of the terrestrial biosphere has draught an intense interest in the recent years in the context of climate and global change. Developing methodologies for generating historical data records from data collected with different satellite sensors over the past three decades by taking benefits from the improvements identified in the processing of the new generation sensors is a new central issue in remote sensing community. In this context, the Bio-geophysical Parameters (BioPar) service within Geoland2 project (http://www.geoland2.eu) aims at developing pre-operational infrastructures for providing global land products both in near real time and off-line mode with long time series. In this contribution, we describe the principles of the GEOLAND algorithm for generating long term datasets of three key biophysical variables, leaf area index (LAI), Fraction of Absorbed Photosynthetic Active Radiation (FAPAR) and cover fraction (FCOVER), that play a key role in several processes, including photosynthesis, respiration and transpiration. LAI, FAPAR and FCOVER are produced globally from AVHRR Long Term Data Record (LTDR) for the 1981-2000 period at 0.05° spatial resolution and 10 days temporal sampling frequency. The proposed algorithm aims to ensure robustness of the derived long time series and consistency with the ones developed in the recent years, and particularly with GEOLAND products derived from VEGETATION sensor. The approach is based on the capacity of neural networks to learn a particular biophysical product (GEOLAND) from reflectances from another sensor (AVHRR normalized reflectances in the red and near infrared bands). Outliers due to possible cloud contamination or residual atmospheric correction are iteratively eliminated. Prior information based on the climatology is used to get more robust estimates. A specific gap filing and smoothing procedure was applied to generate continuous and smooth time series of decadal

Future Climate Impact on the Desertification in the Dry Land Asia Using AVHRR GIMMS NDVI3g Data

Directory of Open Access Journals (Sweden)

Lijuan Miao

2015-04-01

Full Text Available Dry Land Asia is the largest arid and semi-arid region in the northern hemisphere that suffers from land desertification. Over the period 1982–2011, there were both overall improvement and regional degeneration in the vegetation NDVI. We analyze future climate changes in these area using two ensemble-average methods from CMIP5 data. Bayesian Model Averaging shows a better capability to represent the future climate and less uncertainty represented by the 22-model ensemble than does the Simple Model Average. From 2006 to 2100, the average growing season temperature value will increase by 2.9 °C, from 14.4 °C to 17.3 °C under three climate scenarios (RCP 26, RCP 45 and RCP 85. We then conduct multiple regression analysis between climate changes compiled from the Climate Research Unit database and vegetation greenness from the GIMMS NDVI3g dataset. There is a general acceleration in the desertification trend under the RCP 85 scenario in middle and northern part of Middle Asia, northwestern China except Xinjiang and the Mongolian Plateau (except the middle part. The RCP 85 scenario shows a more severe desertification trend than does RCP 26. Desertification in dry land Asia, particularly in the regions highlighted in this study, calls for further investigation into climate change impacts and adaptations.

Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

Science.gov (United States)

Steffen, K.; Bindschadler, R.; Casassa, G.; Comiso, J.; Eppler, D.; Fetterer, F.; Hawkins, J.; Key, J.; Rothrock, D.; Thomas, R.;

Intercomparison of 30+ years of AVHRR and Landsat-5 TM Surface Reflectance using Multiple Pseudo-Invariant Calibration Sites

Science.gov (United States)

Santamaría-Artigas, A. E.; Franch, B.; Vermote, E.; Roger, J. C.; Justice, C. O.

2017-12-01

The 30+ years daily surface reflectance long term data record (LTDR) from the Advanced Very High Resolution Radiometer (AVHRR) is a valuable source of information for long-term studies of the Earth surface. This LTDR was generated by combining observations from multiple AVHRR sensors aboard different NOAA satellites starting from the early 1980s, and due to the lack of on-board calibration its quality should be evaluated. Previous studies have used observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) over pseudo-invariant calibration sites (PICS) as a calibrated reference to assess the performance of AVHRR products. However, this limits the evaluation to the period after MODIS launch. In this work, the AVHRR surface reflectance LTDR was evaluated against Landsat-5 Thematic Mapper (TM) data using observations from 4 well known pseudo-invariant calibration sites (i.e. Sonoran, Saharan, Sudan1, and Libya4) over an extended time period (1984-2011). For the intercomparison, AVHRR and TM observations of each site were extracted and averaged over a 20 km x 20 km area and aggregated to monthly mean values. In order to account for the spectral differences between sensors, Hyperion hyperspectral data from the Sonoran and Libya4 sites were convolved with sensor-specific relative spectral responses, and used to compute spectral band adjustment factors (SBAFs). Results of the intercomparison are reported in terms of the root mean square difference (RMSD) and determination coefficient (r2). In general, there is good agreement between the surface reflectance products from both sensors. The overall RMSD and r2 for all the sites and AVHRR/TM combinations were 0.03 and 0.85 for the red band, and 0.04 and 0.81 for the near-infrared band. These results show the strong performance of the AVHRR surface reflectance LTDR through all of the considered period. Thus, remarking its usefulness and value for long term Earth studies. Figure 1 shows the red (filled markers

Application of Satellite Data for Early Season Assessment of Fallowed Agricultural Lands for Drought Impact Reporting

Science.gov (United States)

Rosevelt, C.; Melton, F. S.; Johnson, L.; Verdin, J. P.; Thenkabail, P. S.; mueller, R.; Zakzeski, A.; Jones, J.

2013-12-01

Rapid assessment of drought impacts can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, or state emergency proclamations. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and land fallowing associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. Here we describe an approach for monthly mapping of land fallowing developed as part of a joint effort by USGS, USDA, and NASA to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of fallowed land from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of normalized difference vegetation index (NDVI) data from Landsat TM, ETM+, and MODIS. Our effort has been focused on development of leading indicators of drought impacts in the March - June timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. This capability complements ongoing work by USDA to produce and publicly release within-season estimates of fallowed acreage from the USDA Cropland Data Layer. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted along transects across the Central Valley at more than 200 fields per month from March - June, 2013. Here we present the algorithm for mapping fallowed acreage early in the season along with results from the accuracy assessment, and discuss potential applications to other regions.

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...

GHRSST Level 2P USA NAVOCEANO AVHRR17 Global SST:1

Data.gov (United States)

National Aeronautics and Space Administration — Multi-Channel SST retreivals generated in real-time from NOAA-17 AVHRR Global Area Coverage data. Used operationally in Navy oceanographic analyses and forecasts.

GHRSST Level 2P USA NAVOCEANO AVHRR18 Global SST:1

Data.gov (United States)

National Aeronautics and Space Administration — Multi-Channel SST retreivals generated in real-time from NOAA-18 AVHRR Global Area Coverage data. Used operationally in Navy oceanographic analyses and forecasts.

Seasonality and Management Affect Land Surface Temperature Differences Between Loblolly Pine and Switchgrass Ecosystems in Central Virginia

Science.gov (United States)

Ahlswede, B.; Thomas, R. Q.; O'Halloran, T. L.; Rady, J.; LeMoine, J.

2017-12-01

Changes in land-use and land management can have biogeochemical and biophysical effects on local and global climate. While managed ecosystems provide known food and fiber benefits, their influence on climate is less well quantified. In the southeastern United States, there are numerous types of intensely managed ecosystems but pine plantations and switchgrass fields represent two biogeochemical and biophysical extremes; a tall, low albedo forest with trees harvested after multiple decades vs. a short, higher albedo C4 grass field that is harvested annually. Despite the wide spread use of these ecosystems for timber and bioenergy, a quantitative, empirical evaluation of the net influence of these ecosystems on climate is lacking because it requires measuring both the greenhouse gas and energy balance of the ecosystems while controlling for the background weather and soil environment. To address this need, we established a pair of eddy flux towers in these ecosystems that are co-located (1.5 km apart) in Central Virginia and measured the radiative energy, non-radiative energy and carbon fluxes, along with associated biometeorology variables; the paired site has run since April 2016. During the first 1.5 years (two growing seasons), we found strong seasonality in the difference in surface temperature between the two ecosystems. In the growing seasons, both sites had similar surface temperature despite higher net radiation in pine. Following harvest of the switchgrass in September, the switchgrass temperatures increased relative to pine. In the winter, the pine ecosystem was warmer. We evaluate the drivers of these intra-annual dynamics and compare the climate influence of these biophysical differences to the differences in carbon fluxes between the sites using a suite of established climate regulation services metrics. Overall, our results show tradeoffs exist between the biogeochemical and biophysical climate services in managed ecosystems in the southeastern United

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

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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...

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.

Water quality of small seasonal wetlands in the Piedmont ecoregion, South Carolina, USA: Effects of land use and hydrological connectivity.

Science.gov (United States)

Yu, Xubiao; Hawley-Howard, Joanna; Pitt, Amber L; Wang, Jun-Jian; Baldwin, Robert F; Chow, Alex T

2015-04-15

Small, shallow, seasonal wetlands with short hydroperiod (2-4 months) play an important role in the entrapment of organic matter and nutrients and, due to their wide distribution, in determining the water quality of watersheds. In order to explain the temporal, spatial and compositional variation of water quality of seasonal wetlands, we collected water quality data from forty seasonal wetlands in the lower Blue Ridge and upper Piedmont ecoregions of South Carolina, USA during the wet season of February to April 2011. Results indicated that the surficial hydrological connectivity and surrounding land-use were two key factors controlling variation in dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) in these seasonal wetlands. In the sites without obvious land use changes (average developed area land use changes. The connected wetlands in more urbanized areas (average developed area = 12.3%) showed higher concentrations of dissolved organic matter (DOM) (DOC: 11.76 ± 6.09 mg L(-1), TDN: 0.74 ± 0.22 mg L(-1), mean ± standard error) compared to those in isolated wetlands (DOC: 7.20 ± 0.62 mg L(-1), TDN: 0.20 ± 0.08 mg L(-1)). The optical parameters derived from UV and fluorescence also confirmed significant portions of protein-like fractions likely originating from land use changes such as wastewater treatment and livestock pastures. The average of C/N molar ratios of all the wetlands decreased from 77.82 ± 6.72 (mean ± standard error) in February to 15.14 ± 1.58 in April, indicating that the decomposition of organic matter increased with the temperature. Results of this study demonstrate that the water quality of small, seasonal wetlands has a direct and close association with the surrounding environment. Copyright © 2015 Elsevier Ltd. All rights reserved.

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....

Automated cloud screening of AVHRR imagery using split-and-merge clustering

Science.gov (United States)

Gallaudet, Timothy C.; Simpson, James J.

1991-01-01

Previous methods to segment clouds from ocean in AVHRR imagery have shown varying degrees of success, with nighttime approaches being the most limited. An improved method of automatic image segmentation, the principal component transformation split-and-merge clustering (PCTSMC) algorithm, is presented and applied to cloud screening of both nighttime and daytime AVHRR data. The method combines spectral differencing, the principal component transformation, and split-and-merge clustering to sample objectively the natural classes in the data. This segmentation method is then augmented by supervised classification techniques to screen clouds from the imagery. Comparisons with other nighttime methods demonstrate its improved capability in this application. The sensitivity of the method to clustering parameters is presented; the results show that the method is insensitive to the split-and-merge thresholds.

Dry season distribution of land crabs, Gecarcinus quadratus (Crustacea: Gecarcinidae), in Corcovado National Park, Costa Rica.

Science.gov (United States)

Griffiths, Megan E; Mohammad, Basma A; Vega, Andres

2007-03-01

The land crab Gecarcinus quadratus is an engineering species that controls nutrient cycling in tropical forests. Factors regulating their coastal distribution are not fully understood. We quantified land crab distribution during the dry season at Sirena Field Station in Corcovado National Park, Costa Rica, and found that land crab burrow density decreases with increasing distance from the ocean. Leaf litter depth and tree seedling density are negatively correlated with land crab burrow density. Burrows are strongly associated with sand substrate and burrow density is comparatively low in clay substrate. Results suggest that G. quadratus is limited to a narrow coastal zone with sand substrate, and this distribution could have profound effects on plant community structure.

AVHRR Polar Pathfinder Twice-Daily 1.25 km EASE-Grid Composites

Data.gov (United States)

National Aeronautics and Space Administration — Please note that the machine on which these AVHRR data are processed has reached its life expectancy and will no longer be available as of 02 June 2008 until further...

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

Wet-dry seasonal and vertical geochemical variations in soil water and their driving forces under different land covers in southwest China karst

Science.gov (United States)

Wang, Peng; Hu, Bill X.; Wu, Chuanhao; Xu, Kai

2017-04-01

Karst aquifers supply drinking water for 25% of the world's population, and they are, however, vulnerable to climate change. Bimonthly hydrochemical data in karst soil water samples from July 2010 to July 2011 were obtained to reveal the seasonal and vertical geochemical variations in soil water under five vegetation types in Qingmuguan, a small karst catchment in southwest China. Soil water chemistry was dominated by Ca2+, HCO3-, and SO42- because of the dissolution of limestone, dolomite, and gypsum minerals in the strata. The predominant hydrochemical types in soil water were Ca2+-HCO3-, Ca2+-SO42-, and mixed Ca2+-HCO3-SO42-. Ca2+ and HCO3- concentrations ranked in the following order: shrub land > dry land > afforestation farmland > bamboo land > grassland. In warm and wet seasons, the main ion concentrations in soil water from grasslands were low. Na+, K+, Ca2+, Mg2+, HCO3-, SO42-, and Cl- concentrations in soil water from other lands were high. An opposite trend was observed in cold and dry seasons. Marked seasonal variations were observed in Ca2+, HCO3-, and NO3- in soil water from dry land. The main ion concentrations in soil water from bamboo lands decreased as soil depth increased. By contrast, the chemistry of soil water from other lands increased as soil depth increased. Their ions were accumulated in depth. A consistent high and low variation between the main ions in soil water and the contents of carbonate and CO2 was found in the soil. Hydrochemical changes in soil water were regulated by the effects of dilution and soil CO2.

Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis

Science.gov (United States)

Budde, M.E.; Tappan, G.; Rowland, James; Lewis, J.; Tieszen, L.L.

2004-01-01

The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.

Large-scale heterogeneity of Amazonian phenology revealed from 26-year long AVHRR/NDVI time-series

International Nuclear Information System (INIS)

Silva, Fabrício B; Shimabukuro, Yosio E; Aragão, Luiz E O C; Anderson, Liana O; Pereira, Gabriel; Cardozo, Franciele; Arai, Egídio

2013-01-01

Depiction of phenological cycles in tropical forests is critical for an understanding of seasonal patterns in carbon and water fluxes as well as the responses of vegetation to climate variations. However, the detection of clear spatially explicit phenological patterns across Amazonia has proven difficult using data from the Moderate Resolution Imaging Spectroradiometer (MODIS). In this work, we propose an alternative approach based on a 26-year time-series of the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) to identify regions with homogeneous phenological cycles in Amazonia. Specifically, we aim to use a pattern recognition technique, based on temporal signal processing concepts, to map Amazonian phenoregions and to compare the identified patterns with field-derived information. Our automated method recognized 26 phenoregions with unique intra-annual seasonality. This result highlights the fact that known vegetation types in Amazonia are not only structurally different but also phenologically distinct. Flushing of new leaves observed in the field is, in most cases, associated to a continuous increase in NDVI. The peak in leaf production is normally observed from the beginning to the middle of the wet season in 66% of the field sites analyzed. The phenoregion map presented in this work gives a new perspective on the dynamics of Amazonian canopies. It is clear that the phenology across Amazonia is more variable than previously detected using remote sensing data. An understanding of the implications of this spatial heterogeneity on the seasonality of Amazonian forest processes is a crucial step towards accurately quantifying the role of tropical forests within global biogeochemical cycles. (letter)

Land Surface Phenologies and Seasonalities of Croplands and Grasslands in the US Prairie Pothole Region Using Passive Microwave Data (2003-2015)

Science.gov (United States)

Alemu, W. G.; Henebry, G. M.

2017-12-01

Grasslands and wetlands in the Prairie Pothole Region (PPR) have been converted to croplands in recent years. Crops cultivated in the PPR are also changing: spring wheat and alfalfa/hay are being switched to corn and soybean due to biofuel demand. According to the USDA Cropland Data Layer (CDL) from 2003 to 2015, spring wheat significantly decreased (r2 = 0.74), while corn and soybeans significantly increased (r2 = 0.86). We characterized land surface phenologies and land surface seasonalities across the PPR using the finer temporal (twice daily) but much lower spatial (25 km) resolution Advanced Microwave Scanning Radiometer (AMSR: blended from AMSR-E and AMSR2) enhanced land surface parameters for 2003-2015 (DOY 91-330 annual cycles). We tracked the temporal development of these land surface parameters as a function of accumulated growing degree-days (AGDD) based on the AMSR retrieved air temperature data. Growing degree-days (GDD) revealed distinct seasonality typical to temperate grasslands and croplands. GDD peaks were 23°C and it peaks at 1700°C AGDD. Precipitable water vapor (V) displayed seasonality comparable to GDD. Vegetation optical depth (VOD) revealed distinct land surface phenologies for grasslands versus croplands. We explored the changing crop fractions within the 25 km AMSR pixels using the CDL. Crop-dominated sites VOD time series caught the early spring growth, ploughing, and crop growth dynamics. In contrast, the VOD time series at grass-dominated sites exhibited a lower but more extended amplitude throughout the non-frozen season. VODs peaked at 1.6 and 1.3 for croplands and grasslands, respectively. Croplands peaked about a month later than grasslands (2200 °C AGDD vs. 1600 °C AGDD). The other parameters available from the AMSR dataset—soil moisture (sm), and fractional open water (fw)—together with the AGDD time series constructed from the AMSR air temperature data revealed the passage of storm systems during the growing season. Soil

GHRSST Level 2P USA NAVOCEANO AVHRR METOP-A Global SST:1

Data.gov (United States)

National Aeronautics and Space Administration — Multi-Channel SST retreivals generated in real-time from METOP-A AVHRR Global Area Coverage data. Used operationally in Navy oceanographic analyses and forecasts.

Estimating the beam attenuation coefficient in coastal waters from AVHRR imagery

Science.gov (United States)

Gould, Richard W.; Arnone, Robert A.

1997-09-01

This paper presents an algorithm to estimate particle beam attenuation at 660 nm ( cp660) in coastal areas using the red and near-infrared channels of the NOAA AVHRR satellite sensor. In situ reflectance spectra and cp660 measurements were collected at 23 stations in Case I and II waters during an April 1993 cruise in the northern Gulf of Mexico. The reflectance spectra were weighted by the spectral response of the AVHRR sensor and integrated over the channel 1 waveband to estimate the atmospherically corrected signal recorded by the satellite. An empirical relationship between integrated reflectance and cp660 values was derived with a linear correlation coefficient of 0.88. Because the AVHRR sensor requires a strong channel 1 signal, the algorithm is applicable in highly turbid areas ( cp660 > 1.5 m -1) where scattering from suspended sediment strongly controls the shape and magnitude of the red (550-650 nm) reflectance spectrum. The algorithm was tested on a data set collected 2 years later in different coastal waters in the northern Gulf of Mexico and satellite estimates of cp660 averaged within 37% of measured values. Application of the algorithm provides daily images of nearshore regions at 1 km resolution for evaluating processes affecting ocean color distribution patterns (tides, winds, currents, river discharge). Further validation and refinement of the algorithm are in progress to permit quantitative application in other coastal areas. Published by Elsevier Science Ltd

Seasonal Dynamics of Water Use Strategy of Two Salix Shrubs in Alpine Sandy Land, Tibetan Plateau.

Science.gov (United States)

Zhu, Yajuan; Wang, Guojie; Li, Renqiang

2016-01-01

Water is a limiting factor for plant growth and vegetation dynamics in alpine sandy land of the Tibetan Plateau, especially with the increasing frequency of extreme precipitation events and drought caused by climate change. Therefore, a relatively stable water source from either deeper soil profiles or ground water is necessary for plant growth. Understanding the water use strategy of dominant species in the alpine sandy land ecosystem is important for vegetative rehabilitation and ecological restoration. The stable isotope methodology of δD, δ18O, and δ13C was used to determine main water source and long-term water use efficiency of Salix psammophila and S. cheilophila, two dominant shrubs on interdune of alpine sandy land in northeastern Tibetan Plateau. The root systems of two Salix shrubs were investigated to determine their distribution pattern. The results showed that S. psammophila and S. cheilophila absorbed soil water at different soil depths or ground water in different seasons, depending on water availability and water use strategy. Salix psammophila used ground water during the growing season and relied on shallow soil water recharged by rain in summer. Salix cheilophila used ground water in spring and summer, but relied on shallow soil water recharged by rain in spring and deep soil water recharged by ground water in fall. The two shrubs had dimorphic root systems, which is coincident with their water use strategy. Higher biomass of fine roots in S. psammophila and longer fine roots in S. cheilophila facilitated to absorb water in deeper soil layers. The long-term water use efficiency of two Salix shrubs increased during the dry season in spring. The long-term water use efficiency was higher in S. psammophila than in S. cheilophila, as the former species is better adapted to semiarid climate of alpine sandy land.

Seasonal evaluation of the land surface sheme HTESSEL against remote sensing derived energy fluxes of the Transdanubian regions in Hungary

NARCIS (Netherlands)

Wipfler, E.L.; Metselaar, K.; Dam, van J.C.; Feddes, R.A.; Meijgaard, van E.; Ulft, van L.H.; Hurk, van den B.; Zwart, S.J.; Bastiaanssen, W.G.M.

2011-01-01

The skill of the land surface model HTESSEL is assessed to reproduce evaporation in response to land surface characteristics and atmospheric forcing, both being spatially variable. Evaporation estimates for the 2005 growing season are inferred from satellite observations of the Western part of

Monitoring and assessment of seasonal land cover changes using remote sensing: a 30-year (1987-2016) case study of Hamoun Wetland, Iran.

Science.gov (United States)

Kharazmi, Rasoul; Tavili, Ali; Rahdari, Mohammad Reza; Chaban, Lyudmila; Panidi, Evgeny; Rodrigo-Comino, Jesús

2018-05-23

The availability of Landsat data allows improving the monitoring and assessment of large-scale areas with land cover changes in rapid developing regions. Thus, we pretend to show a combined methodology to assess land cover changes (LCCs) in the Hamoun Wetland region (Iran) over a period of 30-year (1987-2016) and to quantify seasonal and decadal landscape and land use variabilities. Using the pixel-based change detection (PBCD) and the post-classification comparison (PCC), four land cover classes were compared among spring, summer, and fall seasons. Our findings showed for the water class a higher correlation between spring and summer (R 2  = 0.94) than fall and spring (R 2  = 0.58) seasons. Before 2000, ~ 50% of the total area was covered by bare soil and 40% by water. However, after 2000, more than 70% of wetland was transformed into bare soils. The results of the long-term monitoring period showed that fall season was the most representative time to show the inter-annual variability of LCCs monitoring and the least affected by seasonal-scale climatic variations. In the Hamoun Wetland region, land cover was highly controlled by changes in surface water, which in turn responded to both climatic and anthropogenic impacts. We were able to divide the water budget monitoring into three different ecological regimes: (1) a period of high water level, which sustained healthy extensive plant life, and approximately 40% of the total surface water was retained until the end of the hydrological year; (2) a period of drought during high evaporation rates was observed, and a mean wetland surface of about 85% was characterized by bare land; and (3) a recovery period in which water levels were overall rising, but they are not maintained from year to year. After a spring flood, in 2006 and 2013, grassland reached the highest extensions, covering till more than 20% of the region, and the dynamics of the ecosystem were affected by the differences in moisture. The Hamoun

The use of NOAA AVHRR satellite data for mapping sediment ...

African Journals Online (AJOL)

The use of NOAA AVHRR satellite data for mapping sediment variability in the marine and coastal environment. ... The area near Big Constance Lake, which has a persistently higher concentration of suspended sediment around the year, is a suspected non-depositional area. The southwest winds cause a circulation in the ...

Regional thermal patterns in Portugal using satellite images (NOAA AVHRR

Directory of Open Access Journals (Sweden)

António Lopes

1995-06-01

Full Text Available In this paper two NOAA AVHRR diurnal images (channel 4 are used to determine the required procedures aiming at a future operational analysis system in Portugal. Preprocessing and classification operations are described. Strong correlation between air and surface temperature is verified and rather detailed air temperature patterns can be inferred.

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.

Seasonal use of conservation reserve program lands by white-tailed deer in east-central South Dakota

Science.gov (United States)

Gould, Jeffrey H.; Jenkins, Kurt J.

1993-01-01

The Conservation Reserve Program (CRP_, a provision of the 1985 Food Security Act, subsidizes landowners to take highly erodible lands out of cultivation and seed them to perennial cover for 10years. In eastern South Dakota, 0.5 million ha were enrolled in the CRP from 1985 to 1990 (Agric. Stabilization and Conserv. Serv., Brookings, S.D., unpubl. Data), which represents the largest change in conservation land-use practices in the region since the 1956 Soil Bank Program (Goetz 1987).Although the CRP is anticipated to produce substantial benefits for some wildlife species, particularly ground-nesting birds, its significance to white-tailed deer (Odocoileus virginianus) in the northern Great Plains agricultural region is poorly understood. Higgins et al. (1987) speculated that proliferation of CRP grasslands may provide a missing habitat component in intensively managed farmland, thereby enhancing several species of wildlife, including white-tailed deer. Deer managers in the region have expressed concerns that improved cover associated with DRP plantings on private land could attract deer and reduce hunter success rates or lead to increased depredation of adjacent croplands or stored winter forages (L. Rice, S.D. Dep. Game, Fish, and Parks, Rapid City, pers. comm., 1989). Our objectives were to describe variation in deer use of CRP lands by season, diel period, and deer activity class as a means of assessing seasonal importance of CRP fields to white-tailed deer in agricultural Midwest.

Seasonal shifts in body temperature and use of microhabitats by Galapagos land iguanas (Conolophus pallidus)

Energy Technology Data Exchange (ETDEWEB)

Christian, K.; Tracy, C.R.; Porter, W.P.

1983-06-01

Seasonal differences in the body temperatures (T/sub b/) of free-ranging Galapagos land iguanas (Conolophus pallidus) were detected by temperature sensitive telemetry transmitters. Midday T/sub b/'s of iguanas average 4.4/sup 0/C lower in the Garua (cool) season than in the Hot season. Measured T/sub b/'s and those predicted from biophysical models permitted the following conclusions: (1) lower T/sub b/'s during the Garua season represent an active shift in thermoregulation by the iguanas rather than a passive result of a cooler season; (2) the average midday T/sub b/ selected by the iguanas in either season is the T/sub b/ that allows maintenance of a constant T/sub b/ for the longest possible portion of the day; (3) by exploiting the warmer microclimate created by a cliff face, the iguanas are able to maintain a constant T/sub b/ for a full hour longer than they could elsewhere in their home range. Census data demonstrated that the iguanas exploited the warmer microclimate created by the cliff extensively during the Garua season, and the cliff face was visited by the iguanas relatively infrequently during the Hot season. Thus, the exploitation of the microclimate created by the cliff results in seasonal differences in the pattern of space utilization within the home ranges of the iguanas. Within the Garua season the iguanas moved away from the cliff more often on sunny days than during cloudy days. It is concluded that the physical environment is an important determinant of patterns of space utilization both within and between seasons.

Assessing the effects of human-induced land degradation in the former homelands of northern South Africa with a 1 km AVHRR NDVI time-series

CSIR Research Space (South Africa)

Wessels, Konrad J

2004-05-15

Full Text Available been successfully estimated with the normalized dif- ference vegetation index (NDVI) derived from satellite data (Deering et al., 1975; Jury et al., 1997; Myneni et al., 1997; Prince, 1991b; Prince & Tucker, 1986; Tucker & Sellers, 1986). NDVI captures... productivity (NPP; Schloss et al., 1999). In arid and semiarid lands, seasonal sums of multitemporal NDVI are strongly corre- lated with vegetation production (Prince, 1991b; Prince & Tucker, 1986; Nicholson & Farrar, 1994; Nicholson et al., 1998). Human...

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...

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...

A New Approach for More Effective Fire Detection Method Using NOAA AVHRR Images

National Research Council Canada - National Science Library

Kalpoma, Kazi A; Haramoto, Yoshiaki; Kudoh, Jun-ich

2005-01-01

.... The Advanced Very High Resolution Radiometer (AVHRR) flown on the NOAA satellite series is one of the best systems for fire monitoring due to the combination of a very good temporal resolution of several images a day...

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...

A comprehensive emission inventory of biogenic volatile organic compounds in Europe: improved seasonality and land-cover

Directory of Open Access Journals (Sweden)

D. C. Oderbolz

2013-02-01

Full Text Available Biogenic volatile organic compounds (BVOC emitted from vegetation are important for the formation of secondary pollutants such as ozone and secondary organic aerosols (SOA in the atmosphere. Therefore, BVOC emission are an important input for air quality models. To model these emissions with high spatial resolution, the accuracy of the underlying vegetation inventory is crucial. We present a BVOC emission model that accommodates different vegetation inventories and uses satellite-based measurements of greenness instead of pre-defined vegetation periods. This approach to seasonality implicitly treats effects caused by water or nutrient availability, altitude and latitude on a plant stand. Additionally, we test the influence of proposed seasonal variability in enzyme activity on BVOC emissions. In its present setup, the emission model calculates hourly emissions of isoprene, monoterpenes, sesquiterpenes and the oxygenated volatile organic compounds (OVOC methanol, formaldehyde, formic acid, ethanol, acetaldehyde, acetone and acetic acid. In this study, emissions based on three different vegetation inventories are compared with each other and diurnal and seasonal variations in Europe are investigated for the year 2006. Two of these vegetation inventories require information on tree-cover as an input. We compare three different land-cover inventories (USGS GLCC, GLC2000 and Globcover 2.2 with respect to tree-cover. The often-used USGS GLCC land-cover inventory leads to a severe reduction of BVOC emissions due to a potential miss-attribution of broad-leaved trees and reduced tree-cover compared to the two other land-cover inventories. To account for uncertainties in the land-cover classification, we introduce land-cover correction factors for each relevant land-use category to adjust the tree-cover. The results are very sensitive to these factors within the plausible range. For June 2006, total monthly BVOC emissions decreased up to −27% with

Practical Application and Obstacles of AVHRR Thermal Data for Estimation of Effusion Rates at Tolbachik Volcano, Kamchatka Peninsula, Russian Federation

Science.gov (United States)

McAlpin, D. B.; Meyer, F. J.; Webley, P. W.

2017-12-01

Using thermal data from Advanced Very High Resolution Radiometer (AVHRR) sensors, we investigated algorithms to estimate the effusive volume of lava flows from the 2012-13 eruption of Tolbachik Volcano with high temporal resolution. AVHRR are polar orbiting, radiation detection instruments that provide reflectance and radiance data in six spectral bands with a ground resolution of 1.1 km². During the Tolbachik eruption of 2012-13, active AVHRR instruments were available aboard four polar orbiting platforms. Although the primary purpose of the instruments is climate and ocean studies, their multiple platforms provide global coverage at least twice daily, with data for all regions of the earth no older than six hours. This frequency makes the AVHRR instruments particularly suitable for the study of volcanic activity. While methods for deriving effusion rates from thermal observations have been previously published, a number of topics complicate their practical application. In particular, these include (1) unknown material parameters used in the estimation process; (2) relatively coarse resolution of thermal sensors; (3) optimizing a model to describe the number of thermal regimes within each pixel and (4) frequent saturation issues in thermal channels. We present ongoing investigations into effusion rate estimation from AVHRR data using the 2012-13 eruption of Tolbachik Volcano as a test event. For this eruption we studied approaches for coping with issues (1) - (4) to pave the way to a more operational implementation of published techniques. To address (1), we used Monte Carlo simulations to understand the sensitivity of effusion rate estimates to changes in material parameters. To study (2) and (3) we compared typical two-component (exposed lava on ambient background) and three-component models (exposed lava, cooled crust, ambient background) for their relative performance. To study issue (4), we compared AVHRR-derived effusion rates to reference data derived from

Application of principal component analysis and information fusion technique to detect hotspots in NOAA/AVHRR images of Jharia coalfield, India - article no. 013523

Energy Technology Data Exchange (ETDEWEB)

Gautam, R.S.; Singh, D.; Mittal, A. [Indian Institute of Technology Roorkee, Roorkee (India)

2007-07-01

Present paper proposes an algorithm for hotspot (sub-surface fire) detection in NOAA/AVHRR images in Jharia region of India by employing Principal Component Analysis (PCA) and fusion technique. Proposed technique is very simple to implement and is more adaptive in comparison to thresholding, multi-thresholding and contextual algorithms. The algorithm takes into account the information of AVHRR channels 1, 2, 3, 4 and vegetation indices NDVI and MSAVI for the required purpose. Proposed technique consists of three steps: (1) detection and removal of cloud and water pixels from preprocessed AVHRR image and screening out the noise of channel 3, (2) application of PCA on multi-channel information along with vegetation index information of NOAA/AVHRR image to obtain principal components, and (3) fusion of information obtained from principal component 1 and 2 to classify image pixels as hotspots. Image processing techniques are applied to fuse information in first two principal component images and no absolute threshold is incorporated to specify whether particular pixel belongs to hotspot class or not, hence, proposed method is adaptive in nature and works successfully for most of the AVHRR images with average 87.27% detection accuracy and 0.201% false alarm rate while comparing with ground truth points in Jharia region of India.

A CERES-like Cloud Property Climatology Using AVHRR Data

Science.gov (United States)

Minnis, P.; Bedka, K. M.; Yost, C. R.; Trepte, Q.; Bedka, S. T.; Sun-Mack, S.; Doelling, D.

2015-12-01

Clouds affect the climate system by modulating the radiation budget and distributing precipitation. Variations in cloud patterns and properties are expected to accompany changes in climate. The NASA Clouds and the Earth's Radiant Energy System (CERES) Project developed an end-to-end analysis system to measure broadband radiances from a radiometer and retrieve cloud properties from collocated high-resolution MODerate-resolution Imaging Spectroradiometer (MODIS) data to generate a long-term climate data record of clouds and clear-sky properties and top-of-atmosphere radiation budget. The first MODIS was not launched until 2000, so the current CERES record is only 15 years long at this point. The core of the algorithms used to retrieve the cloud properties from MODIS is based on the spectral complement of the Advanced Very High Resolution Radiometer (AVHRR), which has been aboard a string of satellites since 1978. The CERES cloud algorithms were adapted for application to AVHRR data and have been used to produce an ongoing CERES-like cloud property and surface temperature product that includes an initial narrowband-based radiation budget. This presentation will summarize this new product, which covers nearly 37 years, and its comparability with cloud parameters from CERES, CALIPSO, and other satellites. Examples of some applications of this dataset are given and the potential for generating a long-term radiation budget CDR is also discussed.

Operational digital image processing within the Bureau of Land Management

International Nuclear Information System (INIS)

Work, E.A.; Story, M.

1991-01-01

An overview of the use of operational digital image processing at the U.S. Bureau of Land Management (BLM) is presented. The BLM digital image analysis facility for the processing and analysis of aerial photography and satellite data is described, and its role within the Bureau's operational structure is explained. Attention is given to examples of BLM digital data analysis projects that have utilized Landsat (MSS and TM), NOAA-AVHRR, or SPOT data. These projects include: landcover mapping to assist land use planning or special projects; monitoring of wilderness units to detect unauthorized activities; stratification aid for detailed field inventories; identification/quantification of unauthorized use (agricultural and mineral trespass); and fire fuels mapping and updates. 3 refs

Seasonal monitoring of soil erosion at regional scale: An application of the G2 model in Crete focusing on agricultural land uses

Science.gov (United States)

Panagos, Panagos; Christos, Karydas; Cristiano, Ballabio; Ioannis, Gitas

2014-04-01

A new soil erosion model, namely G2, was applied in the island of Crete with a focus on agricultural land uses, including potential grazing lands. The G2 model was developed within the Geoland2 project as an agro-environmental service in the framework of the Global Monitoring for Environment and Security (GMES, now Copernicus) initiative. The G2 model takes advantage of the empirical background of the Universal Soil Loss Equation (USLE) and the Gavrilovic model, together with readily available time series of vegetation layers and 10-min rainfall intensity data to produce monthly time-step erosion risk maps at 300 m cell size. The innovations of the G2 model include the implementation of land-use influence parameters based on empirical data and the introduction of a corrective term in the estimation of the topographic influence factor. The mean annual erosion rate in Crete was found to be 8.123 t ha-1. The season from October to January (the rainy season in Crete) was found to be the most critical, accounting for 80% of the annual erosion in the island. Seasonal erosion figures proved to be crucial for the identification of erosion hotspots and of risky land uses. In Crete, high annual erosion figures were detected in natural grasslands and shrublands (14.023 t ha-1), mainly due to the intensification of livestock grazing during the past decades. The G2 model allows for the integrated spatio-temporal monitoring of soil erosion per land-use type based on moderate data input requirements and existing datasets.

User's guide to image processing applications of the NOAA satellite HRPT/AVHRR data. Part 1: Introduction to the satellite system and its applications. Part 2: Processing and analysis of AVHRR imagery

Science.gov (United States)

Huh, Oscar Karl; Leibowitz, Scott G.; Dirosa, Donald; Hill, John M.

1986-01-01

The use of NOAA Advanced Very High Resolution Radar/High Resolution Picture Transmission (AVHRR/HRPT) imagery for earth resource applications is provided for the applications scientist for use within the various Earth science, resource, and agricultural disciplines. A guide to processing NOAA AVHRR data using the hardware and software systems integrated for this NASA project is provided. The processing steps from raw data on computer compatible tapes (1B data format) through usable qualitative and quantitative products for applications are given. The manual is divided into two parts. The first section describes the NOAA satellite system, its sensors, and the theoretical basis for using these data for environmental applications. Part 2 is a hands-on description of how to use a specific image processing system, the International Imaging Systems, Inc. (I2S) Model 75 Array Processor and S575 software, to process these data.

Characterization of Land Transitions Patterns from Multivariate Time Series Using Seasonal Trend Analysis and Principal Component Analysis

Directory of Open Access Journals (Sweden)

Benoit Parmentier

2014-12-01

Full Text Available Characterizing biophysical changes in land change areas over large regions with short and noisy multivariate time series and multiple temporal parameters remains a challenging task. Most studies focus on detection rather than the characterization, i.e., the manner by which surface state variables are altered by the process of changes. In this study, a procedure is presented to extract and characterize simultaneous temporal changes in MODIS multivariate times series from three surface state variables the Normalized Difference Vegetation Index (NDVI, land surface temperature (LST and albedo (ALB. The analysis involves conducting a seasonal trend analysis (STA to extract three seasonal shape parameters (Amplitude 0, Amplitude 1 and Amplitude 2 and using principal component analysis (PCA to contrast trends in change and no-change areas. We illustrate the method by characterizing trends in burned and unburned pixels in Alaska over the 2001–2009 time period. Findings show consistent and meaningful extraction of temporal patterns related to fire disturbances. The first principal component (PC1 is characterized by a decrease in mean NDVI (Amplitude 0 with a concurrent increase in albedo (the mean and the annual amplitude and an increase in LST annual variability (Amplitude 1. These results provide systematic empirical evidence of surface changes associated with one type of land change, fire disturbances, and suggest that STA with PCA may be used to characterize many other types of land transitions over large landscape areas using multivariate Earth observation time series.

LBA Regional Land Cover from AVHRR, 1-Degree, 1987 (Defries and Townshend)

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: This data set consists of a subset of a 1-degree global land cover product (DeFries and Townshend 1994). The subset was created for the study area of the...

Quantification of Impact of Orbital Drift on Inter-Annual Trends in AVHRR NDVI Data

Directory of Open Access Journals (Sweden)

Jyoteshwar R. Nagol

2014-07-01

Full Text Available The Normalized Difference Vegetation Index (NDVI time-series data derived from Advanced Very High Resolution Radiometer (AVHRR have been extensively used for studying inter-annual dynamics of global and regional vegetation. However, there can be significant uncertainties in the data due to incomplete atmospheric correction and orbital drift of the satellites through their active life. Access to location specific quantification of uncertainty is crucial for appropriate evaluation of the trends and anomalies. This paper provides per pixel quantification of orbital drift related spurious trends in Long Term Data Record (LTDR AVHRR NDVI data product. The magnitude and direction of the spurious trends was estimated by direct comparison with data from MODerate resolution Imaging Spectrometer (MODIS Aqua instrument, which has stable inter-annual sun-sensor geometry. The maps show presence of both positive as well as negative spurious trends in the data. After application of the BRDF correction, an overall decrease in positive trends and an increase in number of pixels with negative spurious trends were observed. The mean global spurious inter-annual NDVI trend before and after BRDF correction was 0.0016 and −0.0017 respectively. The research presented in this paper gives valuable insight into the magnitude of orbital drift related trends in the AVHRR NDVI data as well as the degree to which it is being rectified by the MODIS BRDF correction algorithm used by the LTDR processing stream.

LBA Regional Land Cover from AVHRR, 1-Degree, 1987 (Defries and Townshend)

Data.gov (United States)

National Aeronautics and Space Administration — This data set consists of a subset of a 1-degree global land cover product (DeFries and Townshend 1994). The subset was created for the study area of the Large Scale...

Land cover/land use change in semi-arid Inner Mongolia: 1992-2004

Energy Technology Data Exchange (ETDEWEB)

John, Ranjeet; Chen Jiquan; Lu Nan; Wilske, Burkhard, E-mail: ranjeet.john@utoledo.ed [Department of Environmental Sciences, University of Toledo, Toledo, OH 43606 (United States)

2009-10-15

The semi-arid grasslands in Inner Mongolia (IM) are under increasing stress owing to climate change and rapid socio-economic development in the recent past. We investigated changes in land cover/land use and landscape structure between 1992 and 2004 through the analysis of AVHRR and MODIS derived land cover data. The scale of analysis included the regional level (i.e. the whole of IM) as well as the level of the dominant biomes (i.e. the grassland and desert). We quantified proportional change, rate of change and the changes in class-level landscape metrics using the landscape structure analysis program FRAGSTATS. The dominant land cover types, grassland and barren, 0.47 and 0.27 million km{sup 2}, respectively, have increased proportionally. Cropland and urban land use also increased to 0.15 million km{sup 2} and 2197 km{sup 2}, respectively. However, the results further indicated increases in both the homogeneity and fragmentation of the landscape. Increasing homogeneity was mainly related to the reduction in minority cover types such as savanna, forests and permanent wetlands and increasing cohesion, aggregation index and clumpy indices. Conversely, increased fragmentation of the landscape was based on the increase in patch density and the interspersion/juxtaposition index (IJI). It is important to note the socio-economic growth in this fragile ecosystem, manifested by an increasing proportion of agricultural and urban land use not just at the regional level but also at the biome level in the context of regional climate change and increasing water stress.

Land cover/land use change in semi-arid Inner Mongolia: 1992-2004

International Nuclear Information System (INIS)

John, Ranjeet; Chen Jiquan; Lu Nan; Wilske, Burkhard

2009-01-01

The semi-arid grasslands in Inner Mongolia (IM) are under increasing stress owing to climate change and rapid socio-economic development in the recent past. We investigated changes in land cover/land use and landscape structure between 1992 and 2004 through the analysis of AVHRR and MODIS derived land cover data. The scale of analysis included the regional level (i.e. the whole of IM) as well as the level of the dominant biomes (i.e. the grassland and desert). We quantified proportional change, rate of change and the changes in class-level landscape metrics using the landscape structure analysis program FRAGSTATS. The dominant land cover types, grassland and barren, 0.47 and 0.27 million km 2 , respectively, have increased proportionally. Cropland and urban land use also increased to 0.15 million km 2 and 2197 km 2 , respectively. However, the results further indicated increases in both the homogeneity and fragmentation of the landscape. Increasing homogeneity was mainly related to the reduction in minority cover types such as savanna, forests and permanent wetlands and increasing cohesion, aggregation index and clumpy indices. Conversely, increased fragmentation of the landscape was based on the increase in patch density and the interspersion/juxtaposition index (IJI). It is important to note the socio-economic growth in this fragile ecosystem, manifested by an increasing proportion of agricultural and urban land use not just at the regional level but also at the biome level in the context of regional climate change and increasing water stress.

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...

Comparison of Cloud Detection Using the CERES-MODIS Ed4 and LaRC AVHRR Cloud Masks and CALIPSO Vertical Feature Mask

Science.gov (United States)

Trepte, Q. Z.; Minnis, P.; Palikonda, R.; Bedka, K. M.; Sun-Mack, S.

2011-12-01

Accurate detection of cloud amount and distribution using satellite observations is crucial in determining cloud radiative forcing and earth energy budget. The CERES-MODIS (CM) Edition 4 cloud mask is a global cloud detection algorithm for application to Terra and Aqua MODIS data with the aid of other ancillary data sets. It is used operationally for the NASA's Cloud and Earth's Radiant Energy System (CERES) project. The LaRC AVHRR cloud mask, which uses only five spectral channels, is based on a subset of the CM cloud mask which employs twelve MODIS channels. The LaRC mask is applied to AVHRR data for the NOAA Climate Data Record Program. Comparisons among the CM Ed4, and LaRC AVHRR cloud masks and the CALIPSO Vertical Feature Mask (VFM) constitute a powerful means for validating and improving cloud detection globally. They also help us understand the strengths and limitations of the various cloud retrievals which use either active and passive satellite sensors. In this paper, individual comparisons will be presented for different types of clouds over various surfaces, including daytime and nighttime, and polar and non-polar regions. Additionally, the statistics of the global, regional, and zonal cloud occurrence and amount from the CERES Ed4, AVHRR cloud masks and CALIPSO VFM will be discussed.

Comparison of infiltration capacity of permanent grassland and arable land during the 2011 growing season

OpenAIRE

Tomáš Mašíček; F. Toman; M. Vičanová

2012-01-01

The aim of this paper was to compare the rate of infiltration and cumulative infiltration in permanent grassland (PG) and in arable land over the course of the 2011 growing season. The measurement of water infiltration into soil was conducted via ponded infiltration method based on the use of two concentric cylinders in field conditions. Kostiakov equations were applied to evaluate the ponded infiltration. Based on field measurements, the dependence of infiltration rate (v) on time (t) was de...

An algorithm for the detection of the white-tide ('mucilage') phenomenon in the Adriatic Sea using AVHRR data

International Nuclear Information System (INIS)

Tassan, S.

1993-01-01

An algorithm using AVHRR data has been set up for the detection of a white tide consisting of algae secretion ('mucilage'), an event occurring in the Adriatic Sea under particular meteorological conditions. The algorithm, which includes an ad hoc procedure for cloud masking, has been tested with reference to the mucilage map obtained from the analysis of contemporary Thematic Mapper data, as well as by comparing consecutive AVHRR scenes. The main features of the exceptional mucilage phenomenon that took place in the northern basin of the Adriatic Sea in summer 1989 are shown by a time series of maps

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;

Comparison of Ant Community Diversity and Functional Group Composition Associated to Land Use Change in a Seasonally Dry Oak Forest.

Science.gov (United States)

Cuautle, M; Vergara, C H; Badano, E I

2016-04-01

Ants have been used to assess land use conversion, because they reflect environmental change, and their response to these changes have been useful in the identification of bioindicators. We evaluated ant diversity and composition associated to different land use change in a temperate forest (above 2000 m asl) in Mexico. The study was carried out in "Flor del Bosque" Park a vegetation mosaic of native Oak Forests and introduced Eucalyptus and grasslands. Species richness, dominance and diversity rarefaction curves, based on ant morphospecies and functional groups, were constructed and compared among the three vegetation types, for the rainy and the dry seasons of 2008-2009. Jaccard and Sorensen incidence-based indices were calculated to obtain similarity values among all the habitats. The Oak Forest was a rich dominant community, both in species and functional groups; the Eucalyptus plantation was diverse with low dominance. The most seasonality habitat was the grassland, with low species and high functional group diversity during the dry seasons, but the reverse pattern during the wet season. The Oak Forest was more similar to the Eucalyptus plantation than to the grassland, particularly during the dry season. Oak Forests are dominated by Cold Climate Specialists, specifically Prenolepis imparis (Say). The Eucalyptus and the grassland are characterized by generalized Myrmicinae, as Pheidole spp. and Monomorium ebenium (Forel). The conservation of the native Oak Forest is primordial for the maintenance of Cold Climate Specialist ant communities. The microclimatic conditions in this forest, probably, prevented the invasion by opportunistic species.

Surface radiant flux densities inferred from LAC and GAC AVHRR data

Science.gov (United States)

Berger, F.; Klaes, D.

To infer surface radiant flux densities from current (NOAA-AVHRR, ERS-1/2 ATSR) and future meteorological (Envisat AATSR, MSG, METOP) satellite data, the complex, modular analysis scheme SESAT (Strahlungs- und Energieflüsse aus Satellitendaten) could be developed (Berger, 2001). This scheme allows the determination of cloud types, optical and microphysical cloud properties as well as surface and TOA radiant flux densities. After testing of SESAT in Central Europe and the Baltic Sea catchment (more than 400scenes U including a detailed validation with various surface measurements) it could be applied to a large number of NOAA-16 AVHRR overpasses covering the globe.For the analysis, two different spatial resolutions U local area coverage (LAC) andwere considered. Therefore, all inferred results, like global area coverage (GAC) U cloud cover, cloud properties and radiant properties, could be intercompared. Specific emphasis could be made to the surface radiant flux densities (all radiative balance compoments), where results for different regions, like Southern America, Southern Africa, Northern America, Europe, and Indonesia, will be presented. Applying SESAT, energy flux densities, like latent and sensible heat flux densities could also be determined additionally. A statistical analysis of all results including a detailed discussion for the two spatial resolutions will close this study.

Seasonal albedo of an urban/rural landscape from satellite observations

Science.gov (United States)

Brest, Christopher L.

1987-01-01

Using data from 27 calibrated Landsat observations of the Hartford, Connecticut area, the spatial distribution and seasonal variation of surface reflectance and albedo were examined. Mean values of visible reflectance, near-IR reflectance, and albedo are presented (for both snow-free and snow-cover observations) according to 14 land use/land cover categories. A diversity of albedo values was found to exist in this type of environment, associated with land cover. Many land-cover categories display a seasonal dependence, with intracategory seasonal differences being of comparable magnitude to intercategory differences. Key factors in determining albedo (and its seasonal dynamics) are the presence or absence of vegetation and the canopy structure. Snow-cover/snow-free differences range from a few percent (for urban land covers) to over 40 percent (for low-canopy vegetation).

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

SAFARI 2000 Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)

Data.gov (United States)

National Aeronautics and Space Administration — This data set consists of a southern African subset of the University of Maryland (UMD) 8-km Global Land Cover product in ASCII GRID and binary image files formats.

SAFARI 2000 Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: This data set consists of a southern African subset of the University of Maryland (UMD) 8-km Global Land Cover product in ASCII GRID and binary image files...

LBA Regional Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)

Data.gov (United States)

National Aeronautics and Space Administration — This data set is a subset of an 8-km global land cover product (DeFries et al. 1998). This subset was created for the study area of the Large Scale...

LBA Regional Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: This data set is a subset of an 8-km global land cover product (DeFries et al. 1998). This subset was created for the study area of the Large Scale...

NOAA Climate Data Record (CDR) of Visible and Near Infrared Reflectance from 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...

CLARA-A1: a cloud, albedo, and radiation dataset from 28 yr of global AVHRR data

Directory of Open Access Journals (Sweden)

K.-G. Karlsson

2013-05-01

Full Text Available A new satellite-derived climate dataset – denoted CLARA-A1 ("The CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data" – is described. The dataset covers the 28 yr period from 1982 until 2009 and consists of cloud, surface albedo, and radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer sensor carried by polar-orbiting operational meteorological satellites. Its content, anticipated accuracies, limitations, and potential applications are described. The dataset is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF project. The dataset has its strengths in the long duration, its foundation upon a homogenized AVHRR radiance data record, and in some unique features, e.g. the availability of 28 yr of summer surface albedo and cloudiness parameters over the polar regions. Quality characteristics are also well investigated and particularly useful results can be found over the tropics, mid to high latitudes and over nearly all oceanic areas. Being the first CM SAF dataset of its kind, an intensive evaluation of the quality of the datasets was performed and major findings with regard to merits and shortcomings of the datasets are reported. However, the CM SAF's long-term commitment to perform two additional reprocessing events within the time frame 2013–2018 will allow proper handling of limitations as well as upgrading the dataset with new features (e.g. uncertainty estimates and extension of the temporal coverage.

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...

Mesoscale structures viewed by SAR and AVHRR near the Canary islands

Directory of Open Access Journals (Sweden)

E. D. Barton

2001-07-01

Full Text Available Comparison of Synthetic Aperture Radar and Advanced Very High Resolution Radiometry images of sea surface backscatter and temperature during the peak of the summer Trade winds reveals many aspects of the regional oceanography of the Canary Islands. A strong correspondence occurs between the SAR and AVHRR signals. The generally uniform wind field is perturbed as it flows past the islands producing regions of calm immediately downstream. These are bounded by lines of strong horizontal wind shear that coincide with temperature fronts between warmer lee waters and the cooler surrounding ocean. Weaker winds prevail up to 50 km downstream while enhanced wind speed on the boundaries of the lee can extend more than 150 km. Lee waves are excited in the atmospheric inversion layer where the wind passes over abrupt island topography. Quantitative estimates of wind speed made with the CMOD4 algorithm are unreliable in the downstream region because wind direction is variable and unknown and because spatial gradients in air-sea temperature difference affect atmospheric boundary layer stability. A large anticyclone south of Tenerife strongly influenced the estimated wind speed probably because higher ocean temperatures in its centre caused atmospheric instability and increased radar backscatter. The temperature fronts marking boundaries of the upwelling filament and strong eddies observed in AVHRR appear as lines of current shear in the SAR images.

Use of remote sensing data in distributed hydrological models: applications in the Senegal River basin

DEFF Research Database (Denmark)

Sandholt, Inge; Andersen, Jens Asger; Gybkjær, Gorm

1999-01-01

Earth observation, remote sensing, hydrology, distributed hydrological modelling, West Africa, Senegal river basin, land cover, soil moisture, NOAA AVHRR, SPOT, Mike-she......Earth observation, remote sensing, hydrology, distributed hydrological modelling, West Africa, Senegal river basin, land cover, soil moisture, NOAA AVHRR, SPOT, Mike-she...

Relation between seasonally detrended shortwave infrared reflectance data and land surface moisture in semi-arid Sahel

DEFF Research Database (Denmark)

Olsen, Jørgen Lundegaard; Ceccato, Pietro; Proud, Simon Richard

2013-01-01

in vegetation moisture status, and is compared to detrended time series of the Normalized Difference Vegetation Index (NDVI). It was found that when plant available water is low, the SIWSI anomalies increase over time, while the NDVI anomalies decrease over time, but less systematically. Therefore SIWSI may......In the Sudano-Sahelian areas of Africa droughts can have serious impacts on natural resources, and therefore land surface moisture is an important factor. Insufficient conventional sites for monitoring land surface moisture make the use of Earth Observation data for this purpose a key issue...... Second Generation (MSG) satellite. We focused on responses in surface reflectance to soil- and surface moisture for bare soil and early to mid- growing season. A method for implementing detrended time series of the Shortwave Infrared Water Stress Index (SIWSI) is examined for detecting variations...

Decay Functions of Soil Moisture: Implications for Land Cover Controls on Actual Evapotranspiration During the Wet Season of a West-African Savanna

Science.gov (United States)

Bassiouni, M.; Ceperley, N. C.; Mande, T.; Parlange, M. B.

2012-04-01

The West-African savanna experiences extreme seasonal climate. The role of vegetation and the impact of agriculture on the regional hydrology of these areas are not well understood. A better understanding of such phenomena is crucial, as water resources are becoming unstable and populations dependent on rain-fed agriculture are more vulnerable. This study examines soil moisture dynamics during the 2010 rainy season in the Singou River Basin, Burkina Faso. Volumetric soil water content and meteorological data are collected from seven stations of a wireless sensor network. This network covers representative types of land cover in the watershed including riverbank, wetland, open savanna, agricultural parkland, and forested upland savanna. Vegetation was also surveyed throughout the season. Here, we present parameterizations and exploratory analysis of soil moisture decay functions at each station considered. Results are compared to the seasonal evolution of soil moisture storage, potential evapotranspiration and vegetation density. Preliminary results suggest these soil moisture measurements may be essential to understanding actual evapotranspiration and the hydrological influence of the types of land cover in the watershed over time. These findings contribute to improved modeling of the ecohydrological behavior of the Singou River Basin and up-scaling of the sensor network data for regional water management purposes as part of an integrated research and development project, Info4Dourou.

In-flight interband calibration on AVHRR data by a cloud-viewing technique

OpenAIRE

Wald , Lucien

1997-01-01

ISBN 90-5410-933-5; International audience; A significant degradation in the responsivity of the AVHRR radiometers aboard the NOAA satellite series, affects the index vegetation (NDVI), which is an important source of information for monitoring vegetation conditions on regional and global scales. Many studies have been carried out which use the viewing Earth calibration approach in order to provide accurate calibration correction coefficients for the computation of the vegetation index using ...

Land Cover Influence on Wet Season Storm Runoff Generation and Hydrologic Flowpaths in Central Panama

Science.gov (United States)

Birch, A. L.; Stallard, R. F.; Barnard, H. R.

2017-12-01

While relationships between land use/land cover and hydrology are well studied and understood in temperate parts of the world, little research exists in the humid tropics, where hydrologic research is often decades behind. Specifically, quantitative information on how physical and biological differences across varying land covers influence runoff generation and hydrologic flowpaths in the humid tropics is scarce; frequently leading to poorly informed hydrologic modelling and water policy decision making. This research effort seeks to quantify how tropical land cover change may alter physical hydrologic processes in the economically important Panama Canal Watershed (Republic of Panama) by separating streamflow into its different runoff components using end member mixing analysis. The samples collected for this project come from small headwater catchments of four varying land covers (mature tropical forest, young secondary forest, active pasture, recently clear-cut tropical forest) within the Smithsonian Tropical Research Institute's Agua Salud Project. During the past three years, samples have been collected at the four study catchments from streamflow and from a number of water sources within hillslope transects, and have been analyzed for stable water isotopes, major cations, and major anions. Major ion analysis of these samples has shown distinct geochemical differences for the potential runoff generating end members sampled (soil moisture/ preferential flow, groundwater, overland flow, throughfall, and precipitation). Based on this finding, an effort was made from May-August 2017 to intensively sample streamflow during wet season storm events, yielding a total of 5 events of varying intensity in each land cover/catchment, with sampling intensity ranging from sub-hourly to sub-daily. The focus of this poster presentation will be to present the result of hydrograph separation's done using end member mixing analysis from this May-August 2017 storm dataset. Expected

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)...

4 km NODC/RSMAS AVHRR Pathfinder Cloud Screened Version 5.0 Monthly Climatologies (1985-2006) (NODC Accession 0110657)

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 sea surface...

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...

Local and cross-seasonal associations of climate and land use with abundance of monarch butterflies Danaus plexippus

Science.gov (United States)

Saunders, Sarah P.; Ries, Leslie; Oberhasuer, Karen S.; Thogmartin, Wayne E.; Zipkin, Elise F.

2017-01-01

Quantifying how climate and land use factors drive population dynamics at regional scales is complex because it depends on the extent of spatial and temporal synchrony among local populations, and the integration of population processes throughout a species’ annual cycle. We modeled weekly, site-specific summer abundance (1994–2013) of monarch butterflies Danaus plexippus at sites across Illinois, USA to assess relative associations of monarch abundance with climate and land use variables during the winter, spring, and summer stages of their annual cycle. We developed negative binomial regression models to estimate monarch abundance during recruitment in Illinois as a function of local climate, site-specific crop cover, and county-level herbicide (glyphosate) application. We also incorporated cross-seasonal covariates, including annual abundance of wintering monarchs in Mexico and climate conditions during spring migration and breeding in Texas, USA. We provide the first empirical evidence of a negative association between county-level glyphosate application and local abundance of adult monarchs, particularly in areas of concentrated agriculture. However, this association was only evident during the initial years of the adoption of herbicide-resistant crops (1994–2003). We also found that wetter and, to a lesser degree, cooler springs in Texas were associated with higher summer abundances in Illinois, as were relatively cool local summer temperatures in Illinois. Site-specific abundance of monarchs averaged approximately one fewer per site from 2004–2013 than during the previous decade, suggesting a recent decline in local abundance of monarch butterflies on their summer breeding grounds in Illinois. Our results demonstrate that seasonal climate and land use are associated with trends in adult monarch abundance, and our approach highlights the value of considering fine-resolution temporal fluctuations in population-level responses to environmental

Examination of Regional Trends in Cloud Properties over Surface Sites Derived from MODIS and AVHRR using the CERES Cloud Algorithm

Science.gov (United States)

Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.; Sun-Mack, S.; Chen, Y.; Doelling, D. R.; Kato, S.; Rutan, D. A.

2017-12-01

Recent studies analyzing long-term measurements of surface insolation at ground sites suggest that decadal-scale trends of increasing (brightening) and decreasing (dimming) downward solar flux have occurred at various times over the last century. Regional variations have been reported that range from near 0 Wm-2/decade to as large as 9 Wm-2/decade depending on the location and time period analyzed. The more significant trends have been attributed to changes in overhead clouds and aerosols, although quantifying their relative impacts using independent observations has been difficult, owing in part to a lack of consistent long-term measurements of cloud properties. This paper examines new satellite based records of cloud properties derived from MODIS (2000-present) and AVHRR (1981- present) data to infer cloud property trends over a number of surface radiation sites across the globe. The MODIS cloud algorithm was developed for the NASA Clouds and the Earth's Radiant Energy System (CERES) project to provide a consistent record of cloud properties to help improve broadband radiation measurements and to better understand cloud radiative effects. The CERES-MODIS cloud algorithm has been modified to analyze other satellites including the AVHRR on the NOAA satellites. Compared to MODIS, obtaining consistent cloud properties over a long period from AVHRR is a much more significant challenge owing to the number of different satellites, instrument calibration uncertainties, orbital drift and other factors. Nevertheless, both the MODIS and AVHRR cloud properties will be analyzed to determine trends, and their level of consistency and correspondence with surface radiation trends derived from the ground-based radiometer data. It is anticipated that this initial study will contribute to an improved understanding of surface solar radiation trends and their relationship to clouds.

[Variability of vegetation growth season in different latitudinal zones of North China: a monitoring by NOAA NDVI and MSAVI].

Science.gov (United States)

Wang, Hong; Li, Xiaobing; Han, Ruibo; Ge, Yongqin

2006-12-01

In this study, North China was latitudinally divided into five zones, i.e., 32 degrees - 36 degrees N (Zone I), 36 degrees - 40 degrees N (Zone II), 40 degrees - 44 degrees N (Zone III), 44 degrees - 48 degrees N (Zone IV) and 48 degrees - 52 degrees N (Zone V), and the NOAA/ AVHRR NDVI and MSAVI time-series images from 1982 to 1999 were smoothed with Savitzky-Golay filter algorithm. Based on the EOF analysis, the principal components of NDVI and MSAVI for the vegetations in different latitudinal zones of North China were extracted, the annual beginning and ending dates and the length of growth season in 1982 - 1999 were estimated, and the related parameters were linearly fitted, aimed to analyze the variability of vegetation growth season. The results showed that the beginning date of the growth season in different zones tended to be advanced, while the ending date tended to be postponed with increasing latitude. The length of the growth season was also prolonged, with the prolonging time exceeded 10 days.

Validation of AVHRR- and MODIS-derived albedos of snow and ice surfaces by means of helicopter measurements

NARCIS (Netherlands)

Greuell, W.; Oerlemans, J.

2005-01-01

We describe the validation of surface albedos of snow and glacier ice as derived from Advanced Very High Resolution Radiometer (AVHRR) and MOderate Resolution Imaging Spectrometer (MODIS) satellite data. For this purpose we measured surface albedos from a helicopter over Vatnajökull, Iceland, and

Evaluation of Land Surface Models in Reproducing Satellite-Derived LAI over the High-Latitude Northern Hemisphere. Part I: Uncoupled DGVMs

Directory of Open Access Journals (Sweden)

Ning Zeng

2013-10-01

Full Text Available Leaf Area Index (LAI represents the total surface area of leaves above a unit area of ground and is a key variable in any vegetation model, as well as in climate models. New high resolution LAI satellite data is now available covering a period of several decades. This provides a unique opportunity to validate LAI estimates from multiple vegetation models. The objective of this paper is to compare new, satellite-derived LAI measurements with modeled output for the Northern Hemisphere. We compare monthly LAI output from eight land surface models from the TRENDY compendium with satellite data from an Artificial Neural Network (ANN from the latest version (third generation of GIMMS AVHRR NDVI data over the period 1986–2005. Our results show that all the models overestimate the mean LAI, particularly over the boreal forest. We also find that seven out of the eight models overestimate the length of the active vegetation-growing season, mostly due to a late dormancy as a result of a late summer phenology. Finally, we find that the models report a much larger positive trend in LAI over this period than the satellite observations suggest, which translates into a higher trend in the growing season length. These results highlight the need to incorporate a larger number of more accurate plant functional types in all models and, in particular, to improve the phenology of deciduous trees.

Application of drip irrigation technology for producing fruit of Salak ‘Gula Pasir’ (Salacca zalacca var. Gula Pasir off season on dry land

Directory of Open Access Journals (Sweden)

I N Rai

2014-10-01

Full Text Available Naturally, Salak Gula Pasir (Salacca zalacca var. Gula Pasir is flowering every three months or four times a year, but only one or two flowering seasons that the flowers can develop into fruit. The condition causes Salak Gula Pasir is available in the market in a short period (only 2-3 months i.e. at the time of harvest (on-season from December to February. This seasonal nature of Salak Gula Pasir occurs because Salak Gula Pasir is planted on dry land where irrigation depends only on rainfall, and drought occurs when water is shortage so that the plant internal water content is low that causes a high failure development rate of flower to become fruit (fruit-set failure. This study was aimed to overcome the fruit-set failure by providing drip irrigation. Two treatments (with drip irrigation and without drip irrigation/control with sixteen replicates were tested at Salak Gula Pasir production centre (at Sibetan village, Bebandem District, of Karangasem Regency, Bali at two harvest seasons, i.e. Gadu (July and Sela II (October. The results showed that the plant provided with drip irrigation significantly yielded fruit-set percentage higher that that without drip irrigation, both in Gadu and Sela II seasons. The percentages of fruit-set in Gadu and Sela II seasons provided with drip irrigation were 75.30% and 93.13%, respectively, while those without drip irrigation were only 59.94% and 61.67%, respectively. The increase of fruit-set observed for drip irrigation treatment associated with the increase of leaf chlorophyll content, relative water content (RWC of leaves, and leaf N, P, and K contents. The increase of fruit-set led to higher number of fruits and fruit weight per plant under drip irrigation than that without drip irrigation. Based on the results of this study, drip irrigation can be applied to produce Salak Gula Pasir planted out of season on dry land.

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

Science.gov (United States)

Potter, C. S.

1997-01-01

This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

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

Land cover mapping of Greater Mesoamerica using MODIS data

Science.gov (United States)

Giri, Chandra; Jenkins, Clinton N.

2005-01-01

A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.

The impact of land use and season on the riverine transport of mercury into the marine coastal zone.

Science.gov (United States)

Saniewska, Dominika; Bełdowska, Magdalena; Bełdowski, Jacek; Saniewski, Michał; Szubska, Marta; Romanowski, Andrzej; Falkowska, Lucyna

2014-11-01

In Mediterranean seas and coastal zones, rivers can be the main source of mercury (Hg). Catchment management therefore affects the load of Hg reaching the sea with surface runoff. The major freshwater inflows to the Baltic Sea consist of large rivers. However, their systems are complex and identification of factors affecting the outflow of Hg from its catchments is difficult. For this reason, a study into the impact of watershed land use and season on mercury biogeochemistry and transport in rivers was performed along two small rivers which may be considered typical of the southern Baltic region. Neither of these rivers are currently impacted by industrial effluents, thus allowing assessment of the influence of catchment terrain and season on Hg geochemistry. The study was performed between June 2008 and May 2009 at 13 sampling points situated at different terrain types within the catchments (forest, wetland, agriculture and urban). Hg analyses were conducted by CVAFS. Arable land erosion was found to be an important source of Hg to the aquatic system, similar to urban areas. Furthermore, inflows of untreated storm water discharge resulted in a fivefold increase of Hg concentration in the rivers. The highest Hg concentration in the urban runoff was observed with the greatest amount of precipitation during summer. Moderate rainfalls enhance the inflow of bioavailable dissolved mercury into water bodies. Despite the lack of industrial effluents entering the rivers directly, the sub-catchments with anthropogenic land use were important sources of Hg in the rivers. This was caused by elution of metal, deposited in soils over the past decades, into the rivers. The obtained results are especially important in the light of recent environmental conscience regulations, enforcing the decrease of pollution by Baltic countries.

Aspects of Seasonal and Long-term Trends in Fisheries and ...

African Journals Online (AJOL)

... Schilbe moebiusii and Hydrocynus tanzaniae. A distinct seasonal pattern in fish catches was found, where more fish were landed in the dry months (June, July, August and September) and less during peak of the rainy season (March to May). Reduction of fishing effort, crop farming and inaccessibility of fish landing sites ...

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.

Quantification of Surface Suspended Sediments along a River Dominated Coast with NOAA AVHRR and SeaWiFS Measurements: Louisiana, USA

Science.gov (United States)

Myint, S. W.; Walker, N. D.

2002-01-01

The ability to quantify suspended sediment concentrations accurately over both time and space using satellite data has been a goal of many environmental researchers over the past few decades This study utilizes data acquired by the NOAA Advanced Very High Resolution Radiometer (AVHRR) and the Orbview-2 Sea-viewing wide field-of-view (SeaWiFS) ocean colour sensor, coupled with field measurements to develop statistical models for the estimation of near-surface suspended sediment and suspended solids "Ground truth" water samples were obtained via helicopter, small boat and automatic water sampler within a few hours of satellite overpasses The NOAA AVHRR atmospheric correction was modified for the high levels of turbidity along the Louisiana coast. Models were developed based on the field measurements and reflectance/radiance measurements in the visible and near infrared Channels of NOAA-14 and Orbview-2 SeaWiFS. The best models for predicting surface suspended sediment concentrations were obtained with a NOAA AVHRR Channel 1 (580-680nm) cubic model, Channel 2 (725-1100 nm) linear mod$ and SeaWiFs Channel 6 (660-68Onm) power modeL The suspended sediment models developed using SeaWiFS Channel 5 (545-565 nm) were inferior, a result that we attribute mainly to the atmospheric correction technique, the shallow depth of the water samples and absorption effects from non-sediment water constituents.

Global two-channel AVHRR aerosol climatology: effects of stratospheric aerosols and preliminary comparisons with MODIS and MISR retrievals

International Nuclear Information System (INIS)

Geogdzhayev, Igor V.; Mishchenko, Michael I.; Liu Li; Remer, Lorraine

2004-01-01

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

Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools

Science.gov (United States)

O'Donnell, Michael S.; Aldridge, Cameron L.; Doherty, Kevin E.; Fedy, Bradley C.

2015-01-01

With rapidly changing landscape conditions within Wyoming and the potential effects of landscape changes on sage-grouse habitat, land managers and conservation planners, among others, need procedures to assess the location and juxtaposition of important habitats, land-cover, and land-use patterns to balance wildlife requirements with multiple human land uses. Biologists frequently develop habitat-selection studies to identify prioritization efforts for species of conservation concern to increase understanding and help guide habitat-conservation efforts. Recently, the authors undertook a large-scale collaborative effort that developed habitat-selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes in Wyoming, USA and for multiple life-stages (nesting, late brood-rearing, and winter). We developed these habitat models using resource selection functions, based upon sage-grouse telemetry data collected for localized studies and within each life-stage. The models allowed us to characterize and spatially predict seasonal sage-grouse habitat use in Wyoming. Due to the quantity of models, the diversity of model predictors (in the form of geographic information system data) produced by analyses, and the variety of potential applications for these data, we present here a resource that complements our published modeling effort, which will further support land managers.

Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

Science.gov (United States)

Osunmadewa, Babatunde Adeniyi; Gebrehiwot, Worku Zewdie; Csaplovics, Elmar; Adeofun, Olabinjo Clement

2018-03-01

Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

Directory of Open Access Journals (Sweden)

Osunmadewa Babatunde Adeniyi

2018-03-01

Full Text Available Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS and end of season (EOS was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0 and a significant decrease in other greenness trend maps (amplitude 1 and phase 1 was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0 was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1 was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

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...

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...

A method for an accurate in-flight calibration of AVHRR data for vegetation index calculation

OpenAIRE

Asmami , Mbarek; Wald , Lucien

1992-01-01

International audience; A significant degradation in the Advanced Very High Resolution Radiometer (AVHRR) responsitivity, on the NOAA satellite series, has occurred since the prelaunch calibration and with time since launch. This affects the index vegetation (NDVI), which is an important source of information for monitoring vegetation conditions on regional and global scales. Many studies have been carried out which use the Viewing Earth calibration approach in order to provide accurate calib...

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

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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...

Evaluating operational AVHRR sea surface temperature data at the coastline using surfers

Science.gov (United States)

Brewin, Robert J. W.; de Mora, Lee; Billson, Oliver; Jackson, Thomas; Russell, Paul; Brewin, Thomas G.; Shutler, Jamie D.; Miller, Peter I.; Taylor, Benjamin H.; Smyth, Tim J.; Fishwick, James R.

2017-09-01

Sea surface temperature (SST) is an essential climate variable that can be measured routinely from Earth Observation (EO) with high temporal and spatial coverage. To evaluate its suitability for an application, it is critical to know the accuracy and precision (performance) of the EO SST data. This requires comparisons with co-located and concomitant in situ data. Owing to a relatively large network of in situ platforms there is a good understanding of the performance of EO SST data in the open ocean. However, at the coastline this performance is not well known, impeded by a lack of in situ data. Here, we used in situ SST measurements collected by a group of surfers over a three year period in the coastal waters of the UK and Ireland, to improve our understanding of the performance of EO SST data at the coastline. At two beaches near the city of Plymouth, UK, the in situ SST measurements collected by the surfers were compared with in situ SST collected from two autonomous buoys located ∼7 km and ∼33 km from the coastline, and showed good agreement, with discrepancies consistent with the spatial separation of the sites. The in situ SST measurements collected by the surfers around the coastline, and those collected offshore by the two autonomous buoys, were used to evaluate the performance of operational Advanced Very High Resolution Radiometer (AVHRR) EO SST data. Results indicate: (i) a significant reduction in the performance of AVHRR at retrieving SST at the coastline, with root mean square errors in the range of 1.0 to 2.0 °C depending on the temporal difference between match-ups, significantly higher than those at the two offshore stations (0.4 to 0.6 °C); (ii) a systematic negative bias in the AVHRR retrievals of approximately 1 °C at the coastline, not observed at the two offshore stations; and (iii) an increase in the root mean square error at the coastline when the temporal difference between match-ups exceeded three hours. Harnessing new solutions

Agro-pastoral expansion and land use/land cover (LU/LC) change dynamics in Central-western Brazil

Science.gov (United States)

Sanga-Ngoie, K.; Yoshikawa, S.; Kanae, S.

2011-12-01

In Brazil, large-scale land cover changes following extensive deforestations are expected to generate big impacts onto the climate and the environment over this area, with eventually many negative feedbacks on the global scale. Mato Grosso State, located in the central western Brazil, is known to be the Brazilian state with the highest deforestation rate. Land use/land cover (LU/LC) changes have been reported to occur over large areas in this state due to the introduction of large-scale mechanized agriculture, extensive cattle ranching and uncontrolled slash-and-burn cultivation since the 1980s. In this study, we specifically aim at doing more detailed analysis for the causes of deforestation and savannization in this area, with special attention to agriculture and cattle ranching industry at the municipal district level in this state. Using GIS techniques and remotely-sensed NOAA/AVHRR data, we created 5-year Digital Vegetation Model Maps characterizing LU/LC features for every five years during the 1981-2001 periods using the PCA first components of the NOAA/AVHRR multi-spectral data. Our results make it clear that: (1) LU/LC changes among the phases are of the following 3 major types: degradation, recovery or transition; (2) The changes in LU/LC features are concomitant with the advance of cattle ranching and corn production activities toward the northern parts of the state, and with the expansion of soybean production in the central and western Mato Grosso; (3) Most of the agro-pastoral business are found in the southern Mato Grosso where about 46% of the state's deforestation during the 1981-2001 period occurred; (4) Rates of vegetation change are larger over non-inhabited areas (56%), especially in the north, than over the populated zones in the south (42%). Moreover, this work sheds some new light on the patterns of the changes in LU/LC features (deforestation and savannization) for each municipal district of Mato Grosso. In general, the following activities

Responses of Seasonal Precipitation Intensity to Global Warming

Science.gov (United States)

Lan, Chia-Wei; Lo, Min-Hui; Chou, Chia

2016-04-01

Under global warming, the water vapor increases with rising temperature at the rate of 7%/K. Most previous studies focus on the spatial differences of precipitation and suggest that wet regions become wetter and dry regions become drier. Our recent studies show a temporal disparity of global precipitation, which the wet season becomes wetter and dry season becomes drier; therefore, the annual range increases. However, such changes in the annual range are not homogeneous globally, and in fact, the drier trend over the ocean is much larger than that over the land, where the dry season does not become drier. Such precipitation change over land is likely because of decreased omega at 500hPa (more upward motion) in the reanalysis datasets from 1980 to 2013. The trends of vertical velocity and moist static energy profile over the increased precipitation regions become more unstable. The instability is most likely attributed to the change in specific humility below 400hPa. Further, we will use Coupled Model Intercomparison Project Phase 5 (CMIP5) archives to investigate whether the precipitation responses in dry season are different between the ocean and land under global warming.

Evaluating Impacts of climate and land use changes on streamflow using SWAT and land use models based CESM1-CAM5 Climate scenarios

Science.gov (United States)

Lin, Tzu Ping; Lin, Yu Pin; Lien, Wan Yu

2015-04-01

Climate change projects have various levels of impacts on hydrological cycles around the world. The impact of climate change and uncertainty of climate projections from general circulation models (GCMs) from the Coupled Model Intercomparison Project (CMIP5) which has been just be released in Taiwan, 2014. Since the streamflow run into ocean directly due to the steep terrain and the rainfall difference between wet and dry seasons is apparent; as a result, the allocation water resource reasonable is very challenge in Taiwan, particularly under climate change. The purpose of this study was to evaluate the impacts of climate and land use changes on a small watershed in Taiwan. The AR5 General Circulation Models(GCM) output data was adopted in this study and was downscaled from the monthly to the daily weather data as the input data of hydrological model such as Soil and Water Assessment Tool (SWAT) model in this study. The spatially explicit land uses change model, the Conservation of Land Use and its Effects at Small regional extent (CLUE-s), was applied to simulate land use scenarios in 2020-2039. Combined climate and land use change scenarios were adopted as input data of the hydrological model, the SWAT model, to estimate the future streamflows. With the increasing precipitation, increasing urban area and decreasing agricultural and grass land, the annual streamflow in the most of twenty-three subbasins were also increased. Besides, due to the increasing rainfall in wet season and decreasing rainfall in dry season, the difference of streamflow between wet season and dry season are also increased. This result indicates a more stringent challenge on the water resource management in future. Therefore, impacts on water resource caused by climate change and land use change should be considered in water resource planning for the Datuan river watershed. Keywords: SWAT, GCM, CLUE-s, streamflow, climate change, land use change

Soil Moisture and Sea Surface Temperatures equally important for Land Climate in the Warm Season

Science.gov (United States)

Orth, R.; Seneviratne, S. I.

2015-12-01

Both sea surface temperatures (SSTs) and soil moisture (SM) are important drivers of climate variability over land. In this study we present a comprehensive comparison of SM versus SST impacts on land climate in the warm season. We perform ensemble experiments with the Community Earth System Model (CESM) where we set SM or SSTs to median conditions, respectively, to remove their inter-annual variability, whereby the other component - SST or SM - is still interactively computed. In contrast to earlier experiments performed with prescribed SSTs, our experiments suggest that SM is overall as important as SSTs for land climate, not only in the midlatitudes but also in the tropics and subtropics. Mean temperature and precipitation are reduced by 0.1-0.5 K and 0-0.2 mm, respectively, whereas their variability at different time scales decreases by 10-40% (temperature) and 0-10% (precipitation) when either SM or SSTs are prescribed. Also drought occurrence is affected, with mean changes in the maximum number of cumulative dry days of 0-0.75 days. Both SM and SST-induced changes are strongest for hot temperatures (up to 0.7 K, and 50%), extreme precipitation (up to 0.4 mm, and 20%), and strong droughts (up to 2 days). Local climate changes in response to removed SM variability are controlled - to first order - by the land-atmosphere coupling and the natural SM variability. SST-related changes are partly controlled by the relation of local temperature or precipitation with the El Niño-Southern Oscillation. Moreover removed SM or SST variabilities both induce remote effects by impacting the atmospheric circulation. Our results are similar for the present day and the end of the century. We investigate the inter-dependency between SM and SST and find a sufficient degree of independence for the purpose of this study. The robustness of our findings is shown by comparing the response of CESM to removed SM variability with four other global climate models. In summary, SM and SSTs

Study on Remote Sensing Image Characteristics of Ecological Land: Case Study of Original Ecological Land in the Yellow River Delta

Science.gov (United States)

An, G. Q.

2018-04-01

Takes the Yellow River Delta as an example, this paper studies the characteristics of remote sensing imagery with dominant ecological functional land use types, compares the advantages and disadvantages of different image in interpreting ecological land use, and uses research results to analyse the changing trend of ecological land in the study area in the past 30 years. The main methods include multi-period, different sensor images and different seasonal spectral curves, vegetation index, GIS and data analysis methods. The results show that the main ecological land in the Yellow River Delta included coastal beaches, saline-alkaline lands, and water bodies. These lands have relatively distinct spectral and texture features. The spectral features along the beach show characteristics of absorption in the green band and reflection in the red band. This feature is less affected by the acquisition year, season, and sensor type. Saline-alkali land due to the influence of some saline-alkaline-tolerant plants such as alkali tent, Tamarix and other vegetation, the spectral characteristics have a certain seasonal changes, winter and spring NDVI index is less than the summer and autumn vegetation index. The spectral characteristics of a water body generally decrease rapidly with increasing wavelength, and the reflectance in the red band increases with increasing sediment concentration. In conclusion, according to the spectral characteristics and image texture features of the ecological land in the Yellow River Delta, the accuracy of image interpretation of such ecological land can be improved.

STUDY ON REMOTE SENSING IMAGE CHARACTERISTICS OF ECOLOGICAL LAND: CASE STUDY OF ORIGINAL ECOLOGICAL LAND IN THE YELLOW RIVER DELTA

Directory of Open Access Journals (Sweden)

G. Q. An

2018-04-01

Full Text Available Takes the Yellow River Delta as an example, this paper studies the characteristics of remote sensing imagery with dominant ecological functional land use types, compares the advantages and disadvantages of different image in interpreting ecological land use, and uses research results to analyse the changing trend of ecological land in the study area in the past 30 years. The main methods include multi-period, different sensor images and different seasonal spectral curves, vegetation index, GIS and data analysis methods. The results show that the main ecological land in the Yellow River Delta included coastal beaches, saline-alkaline lands, and water bodies. These lands have relatively distinct spectral and texture features. The spectral features along the beach show characteristics of absorption in the green band and reflection in the red band. This feature is less affected by the acquisition year, season, and sensor type. Saline-alkali land due to the influence of some saline-alkaline-tolerant plants such as alkali tent, Tamarix and other vegetation, the spectral characteristics have a certain seasonal changes, winter and spring NDVI index is less than the summer and autumn vegetation index. The spectral characteristics of a water body generally decrease rapidly with increasing wavelength, and the reflectance in the red band increases with increasing sediment concentration. In conclusion, according to the spectral characteristics and image texture features of the ecological land in the Yellow River Delta, the accuracy of image interpretation of such ecological land can be improved.

A Comparison Between SST and AOT Derived from AVHRR and MODIS Data in the Frame of the CREPAD Program

Science.gov (United States)

Robles-Gonzalez, Cristina; Fernandez-Renau, Alix; Lopez Gordillo, Noelia; Sevilla, Angel Garcia; Suarez, Juana Santana

2010-12-01

Since 1997, the INTA-CREPAD (Centre for REception, Processing, Archiving and Dissemination of Earth Observation Data) program distributes freely some of the most demanded low-resolution remote sensing products: SST, Ocean Chl-a, NDVI, AOD... The data input for such products are captured at the Canary Space Station (Centro Espacial de Canarias, CEC). The data sensors received at the station and used in the CREPAD program are AVHRR, SEAWIFS and MODIS. In this study SST and AOD retrieved by CREPAD algorithms from AVHRR and the SEADAS derived SST and AOD from MODIS have compared. SST values agree very well within 0.1±0.5oC and the coefficient of correlation of the images is 0.9. AOD validation gives good results taking into account the differences in the algorithms used. Mean AOD difference at 0.630 μm is 0.01±0.05 and the correlation coefficient is 0.6.

Faunal diversity during rainy season in reclaimed sodic land of Uttar Pradesh, India.

Science.gov (United States)

Singh, S K; Srivastava, S P; Tandon, Pankaj; Azad, B S

2009-07-01

Faunal diversity is an indicator of soil amelioration. Estimating the population size or density of an animal species in an area is fundamental to understand its status and demography and to plan for its management and conservation. Considering this, faunal diversity in reclamed sodic land was monitored during rainy season 2000-01 at different locations of district viz., Aligarh, Etah, Fatehpur, Mainpuri and Raebareli in Uttar Pradesh. The Shannon-Weiner species diversity index (H) of different fauna complex of each location was compared with zero years (1995-1996) indexes (before reclamation). Insects diversity index, in reclaimed sodic soil, varied from 3.8178 (Fatehpur: Bariyampur) to 4.623 (Fatehpur: Katoghan), which was 3.028 in zero year at Katoghan in Fatehpur 'H' index of other-arthropods ranged widely from 0.9743 (Etah: Bawali) to 2.0674 (Mainpuri: Pundari). The species diversity index of molluscs registered as high as 1.8637 at Ladhauwa site in Aligarh, which exhibited identical with Saripur site of Raebareli. 'H' index of mammal resulted with the highest (2.19) at Pundari in district Mainpuri. The avifauna and amphibian's indices were recovered maximal at Saripur site of Raebareli and Bariyampur site of Fatehpur respectively. Our result revealed that various fauna enriched with soil reclamation, which is good indicator of restoration of land, primarily due to soil-arthropods and earthworms and its eventual improvement along with succeeding rice-wheat cropping system widespread over there. It clearly shows that soil fauna strongly affects the composition of natural vegetation and we suggest that this knowledge might improve the restoration and conservation of biodiversity.

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...

Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 2 (JMA/MRI-CPS2): atmosphere-land-ocean-sea ice coupled prediction system for operational seasonal forecasting

Science.gov (United States)

Takaya, Yuhei; Hirahara, Shoji; Yasuda, Tamaki; Matsueda, Satoko; Toyoda, Takahiro; Fujii, Yosuke; Sugimoto, Hiroyuki; Matsukawa, Chihiro; Ishikawa, Ichiro; Mori, Hirotoshi; Nagasawa, Ryoji; Kubo, Yutaro; Adachi, Noriyuki; Yamanaka, Goro; Kuragano, Tsurane; Shimpo, Akihiko; Maeda, Shuhei; Ose, Tomoaki

2018-02-01

This paper describes the Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 2 (JMA/MRI-CPS2), which was put into operation in June 2015 for the purpose of performing seasonal predictions. JMA/MRI-CPS2 has various upgrades from its predecessor, JMA/MRI-CPS1, including improved resolution and physics in its atmospheric and oceanic components, introduction of an interactive sea-ice model and realistic initialization of its land component. Verification of extensive re-forecasts covering a 30-year period (1981-2010) demonstrates that JMA/MRI-CPS2 possesses improved seasonal predictive skills for both atmospheric and oceanic interannual variability as well as key coupled variability such as the El Niño-Southern Oscillation (ENSO). For ENSO prediction, the new system better represents the forecast uncertainty and transition/duration of ENSO phases. Our analysis suggests that the enhanced predictive skills are attributable to incremental improvements resulting from all of the changes, as is apparent in the beneficial effects of sea-ice coupling and land initialization on 2-m temperature predictions. JMA/MRI-CPS2 is capable of reasonably representing the seasonal cycle and secular trends of sea ice. The sea-ice coupling remarkably enhances the predictive capability for the Arctic 2-m temperature, indicating the importance of this factor, particularly for seasonal predictions in the Arctic region.

Seasonal scale water deficit forecasting in Africa and the Middle East using NASA's Land Information System (LIS)

Science.gov (United States)

Shukla, Shraddhanand; Arsenault, Kristi R.; Getirana, Augusto; Kumar, Sujay V.; Roningen, Jeanne; Zaitchik, Ben; McNally, Amy; Koster, Randal D.; Peters-Lidard, Christa

2017-04-01

Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. A seamless and effective monitoring and early warning system is needed by regional/national stakeholders. Such system should support a proactive drought management approach and mitigate the socio-economic losses up to the extent possible. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of the LIS models used for drought and water availability monitoring in the region. The second part will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the monitoring and forecasting products through NASA's web-services. The water deficit forecasting system thus far incorporates NOAA's Noah land surface model (LSM), version 3.3, the Variable Infiltration Capacity (VIC) model, version 4.12, NASA GMAO's Catchment LSM, and the Noah Multi-Physics (MP) LSM (the latter two incorporate prognostic water table schemes). In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. The LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. The LIS software framework integrates these forcing datasets and drives the four LSMs and HyMAP. The Land Verification Toolkit (LVT) is used for the evaluation of the

Local to Global Scale Time Series Analysis of US Dryland Degradation Using Landsat, AVHRR, and MODIS

Science.gov (United States)

Washington-Allen, R. A.; Ramsey, R. D.; West, N. E.; Kulawardhana, W.; Reeves, M. C.; Mitchell, J. E.; Van Niel, T. G.

2011-12-01

Drylands cover 41% of the terrestrial land surface and annually generate $1 trillion in ecosystem goods and services for 38% of the global population, yet estimates of the global extent of Dryland degradation is uncertain with a range of 10 - 80%. It is currently understood that Drylands exhibit topological complexity including self-organization of parameters of different levels-of-organization, e.g., ecosystem and landscape parameters such as soil and vegetation pattern and structure, that gradually or discontinuously shift to multiple basins of attraction in response to herbivory, fire, and climatic drivers at multiple spatial and temporal scales. Our research has shown that at large geographic scales, contemporaneous time series of 10 to 20 years for response and driving variables across two or more spatial scales is required to replicate and differentiate between the impact of climate and land use activities such as commercial grazing. For example, the Pacific Decadal Oscillation (PDO) is a major driver of Dryland net primary productivity (NPP), biodiversity, and ecological resilience with a 10-year return interval, thus 20 years of data are required to replicate its impact. Degradation is defined here as a change in physiognomic composition contrary to management goals, a persistent reduction in vegetation response, e.g., NPP, accelerated soil erosion, a decline in soil quality, and changes in landscape configuration and structure that lead to a loss of ecosystem function. Freely available Landsat, Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradimeter (MODIS) archives of satellite imagery exist that provide local to global spatial coverage and time series between 1972 to the present from which proxies of land degradation can be derived. This paper presents time series assessments between 1972 and 2011 of US Dryland degradation including early detection of dynamic regime shifts in the Mojave and landscape pattern and

Utilizing remote sensing data for modeling water and heat regimes of the Black Earth Region territory of the European Russia

Science.gov (United States)

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

2014-05-01

At present physical-mathematical modeling processes of water and heat exchange between vegetation covered land surfaces and atmosphere is the most appropriate method to describe peculiarities of water and heat regime formation for large territories. The developed model of such processes (Land Surface Model, LSM) is intended for calculation evaporation, transpiration by vegetation, soil water content and other water and heat regime characteristics, as well as distributions of the soil temperature and humidity in depth utilizing remote sensing data from satellites on land surface and meteorological conditions. The model parameters and input variables are the soil and vegetation characteristics and the meteorological characteristics, correspondingly. Their values have been determined from ground-based observations or satellite-based measurements by radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua, SEVIRI/Meteosat-9, -10. The case study has been carried out for the part of the agricultural Central Black Earth region with coordinates 49.5 deg. - 54 deg. N, 31 deg. - 43 deg. E and a total area of 227,300 km2 located in the steppe-forest zone of the European Russia for years 2009-2012 vegetation seasons. From AVHRR data there have been derived the estimates of three types of land surface temperature (LST): land surface skin temperature Tsg, air-foliage temperature Ta and efficient radiation temperature Ts.eff, emissivity E, normalized vegetation index NDVI, vegetation cover fraction B, leaf area index LAI, cloudiness and precipitation. From MODIS data the estimates of LST Tls, E, NDVI and LAI have been obtained. The SEVIRI data have been used to build the estimates of Tls, Ta, E, LAI and precipitation. Previously developed method and technology of above AVHRR-derived estimates have been improved and adapted to the study area. To check the reliability of the Ts.eff and Ta estimations for named seasons the error statistics of their definitions has been analyzed through

Seasonally asymmetric enhancement of northern vegetation productivity

Science.gov (United States)

Park, T.; Myneni, R.

2017-12-01

Multiple evidences of widespread greening and increasing terrestrial carbon uptake have been documented. In particular, enhanced gross productivity of northern vegetation has been a critical role leading to observed carbon uptake trend. However, seasonal photosynthetic activity and its contribution to observed annual carbon uptake trend and interannual variability are not well understood. Here, we introduce a multiple-source of datasets including ground, atmospheric and satellite observations, and multiple process-based global vegetation models to understand how seasonal variation of land surface vegetation controls a large-scale carbon exchange. Our analysis clearly shows a seasonally asymmetric enhancement of northern vegetation productivity in growing season during last decades. Particularly, increasing gross productivity in late spring and early summer is obvious and dominant driver explaining observed trend and variability. We observe more asymmetric productivity enhancement in warmer region and this spatially varying asymmetricity in northern vegetation are likely explained by canopy development rate, thermal and light availability. These results imply that continued warming may facilitate amplifying asymmetric vegetation activity and cause these trends to become more pervasive, in turn warming induced regime shift in northern land.

Impacts of Rainfall Variability, Land Use and Land Cover Change on Stream Flow of the Black Volta Basin, West Africa

Directory of Open Access Journals (Sweden)

Komlavi Akpoti

2016-07-01

Full Text Available Potential implications of rainfall variability along with Land Use and Land Cover Change (LULC on stream flow have been assessed in the Black Volta basin using the SWAT model. The spatio-temporal variability of rainfall over the Black Volta was assessed using the Mann-Kendall monotonic trend test and the Sen’s slope for the period 1976–2011. The statistics of the trend test showed that 61.4% of the rain gauges presented an increased precipitation trend whereas the rest of the stations showed a decreased trend. However, the test performed at the 95% confidence interval level showed that the detected trends in the rainfall data were not statistically significant. Land use trends between the year 2000 and 2013 show that within thirteen years, land use classes like bare land, urban areas, water bodies, agricultural lands, deciduous forests and evergreen forests have increased respectively by 67.06%, 33.22%, 7.62%, 29.66%, 60.18%, and 38.38%. Only grass land has decreased by 44.54% within this period. Changes in seasonal stream flow due to LULC were assessed by defining dry and wet seasons. The results showed that from year 2000 to year 2013, the dry season discharge has increased by 6% whereas the discharge of wet season has increased by 1%. The changes in stream flows components such us surface run-off (SURF_Q, lateral flow (LAT_Q and ground water contribution to stream flow (GW_Q and also on evapotranspiration (ET changes due to LULC was evaluated. The results showed that between the year 2000 and 2013, SURF_Q and LAT_Q have respectively increased by 27% and 19% while GW_Q has decreased by 6% while ET has increased by 4.59%. The resultant effects are that the water yield to stream flow has increased by 4%.

A comprehensive set of benchmark tests for a land surface model of simultaneous fluxes of water and carbon at both the global and seasonal scale

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E. Blyth

2011-04-01

Full Text Available Evaluating the models we use in prediction is important as it allows us to identify uncertainties in prediction as well as guiding the priorities for model development. This paper describes a set of benchmark tests that is designed to quantify the performance of the land surface model that is used in the UK Hadley Centre General Circulation Model (JULES: Joint UK Land Environment Simulator. The tests are designed to assess the ability of the model to reproduce the observed fluxes of water and carbon at the global and regional spatial scale, and on a seasonal basis. Five datasets are used to test the model: water and carbon dioxide fluxes from ten FLUXNET sites covering the major global biomes, atmospheric carbon dioxide concentrations at four representative stations from the global network, river flow from seven catchments, the seasonal mean NDVI over the seven catchments and the potential land cover of the globe (after the estimated anthropogenic changes have been removed. The model is run in various configurations and results are compared with the data.

A few examples are chosen to demonstrate the importance of using combined use of observations of carbon and water fluxes in essential in order to understand the causes of model errors. The benchmarking approach is suitable for application to other global models.

Microphysical and radiative effects of aerosols on warm clouds during the Amazon biomass burning season as observed by MODIS: impacts of water vapor and land cover

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J. E. Ten Hoeve

2011-04-01

Full Text Available Aerosol, cloud, water vapor, and temperature profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondônia, Brazil. It is found that increasing background column water vapor (CWV throughout this transition season between the Amazon dry and wet seasons likely exerts a strong effect on cloud properties. As a result, proper analysis of aerosol-cloud relationships requires that data be stratified by CWV to account better for the influence of background meteorological variation. Many previous studies of aerosol-cloud interactions over Amazonia have ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction (CF is shown to increase or remain constant with aerosol optical depth (AOD, depending on the value of CWV, whereas the relationship between cloud optical depth (COD and AOD is quite different. COD increases with AOD until AOD ~ 0.3, which is assumed to be due to the first indirect (microphysical effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1 the inhibition of cloud development by absorbing aerosols (radiative effect/semi-direct effect and/or (2 a possible retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols within or above clouds or subpixel dark surface contamination in the measured cloud reflectance. If (1 is a contributing mechanism, as we suspect, then an empirically-derived increasing function between cloud drop number and aerosol concentration, assumed in a majority of global climate models, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The relationship between

Thermal signatures of urban land cover types: High-resolution thermal infrared remote sensing of urban heat island in Huntsville, AL

Science.gov (United States)

Lo, Chor Pang

1996-01-01

The main objective of this research is to apply airborne high-resolution thermal infrared imagery for urban heat island studies, using Huntsville, AL, a medium-sized American city, as the study area. The occurrence of urban heat islands represents human-induced urban/rural contrast, which is caused by deforestation and the replacement of the land surface by non-evaporating and non-porous materials such as asphalt and concrete. The result is reduced evapotranspiration and more rapid runoff of rain water. The urban landscape forms a canopy acting as a transitional zone between the atmosphere and the land surface. The composition and structure of this canopy have a significant impact on the thermal behavior of the urban environment. Research on the trends of surface temperature at rapidly growing urban sites in the United States during the last 30 to 50 years suggests that significant urban heat island effects have caused the temperatures at these sites to rise by 1 to 2 C. Urban heat islands have caused changes in urban precipitation and temperature that are at least similar to, if not greater than, those predicted to develop over the next 100 years by global change models. Satellite remote sensing, particularly NOAA AVHRR thermal data, has been used in the study of urban heat islands. Because of the low spatial resolution (1.1 km at nadir) of the AVHRR data, these studies can only examine and map the phenomenon at the macro-level. The present research provides the rare opportunity to utilize 5-meter thermal infrared data acquired from an airplane to characterize more accurately the thermal responses of different land cover types in the urban landscape as input to urban heat island studies.

Warming, Sheep and Volcanoes: Land Cover Changes in Iceland Evident in Satellite NDVI Trends

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Martha Raynolds

2015-07-01

Full Text Available In a greening Arctic, Iceland stands out as an area with very high increases in the AVHRR Normalized Difference Vegetation Index (NDVI, 1982–2010. We investigated the possible sources of this anomalous greening in Iceland’s dynamic landscape, analyzing changes due to volcanism and warming temperatures, and the effects of agricultural and industrial land use changes. The analysis showed the increases were likely due to reductions in grazing in erosion-prone rangelands, extensive reclamation and afforestation efforts, as well as a response to warming climate, including glacial retreat. Like Scandinavia and much of the rest of the Arctic, Iceland has shown a recent reduction in NDVI since 2002, but still above pre-2000 levels. Theil-Sen robust regression analysis of MODIS NDVI trends from 2002 to 2013 showed Iceland had a slightly negative NDVI trend of 0.003 NDVI units/year (p < 0.05, with significant decreases in an area three times greater (29,809 km2 than that with increases (9419 km2. Specific areas with large decreases in NDVI during the last decade were due to the formation of a large reservoir as a part of a hydroelectric power project (Kárahnjúkar, 2002–2009, and due to ashfall from two volcanic eruptions (Eyjafjallajökull, 2010; Grímsvötn, 2011. Increases in NDVI in the last decade were found in erosion control areas, around retreating glaciers, and in other areas of plant colonization following natural disturbance. Our analysis demonstrates the effectiveness of MODIS NDVI for identifying the causes of changes in land cover, and confirms the reduction in NDVI in the last decade using both the AVHRR and MODIS satellite data.

Seasonality of soil erosion under mediterranean conditions at the Alqueva Dam watershed.

Science.gov (United States)

Ferreira, Vera; Panagopoulos, Thomas

2014-07-01

The Alqueva reservoir created the largest artificial lake of Western Europe in 2010. Since then, the region has faced challenges due to land-use changes that may increase the risk of erosion and shorten the lifetime of the reservoir, increasing the need to promote land management sustainability. This paper investigates the aspect of seasonality of soil erosion using a comprehensive methodology that integrates the Revised Universal Soil Loss Equation (RUSLE) approach, geographic information systems, geostatistics, and remote-sensing. An experimental agro-silvo pastoral area (typical land-use) was used for the RUSLE factors update. The study confirmed the effect of seasonality on soil erosion rates under Mediterranean conditions. The highest rainfall erosivity values occurred during the autumn season (433.6 MJ mm ha(-1) h(-1)), when vegetation cover is reduced after the long dry season. As a result, the autumn season showed the highest predicted erosion (9.9 t ha(-1)), contributing 65 % of the total annual erosion. The predicted soil erosion for winter was low (1.1 t ha(-1)) despite the high rainfall erosivity during that season (196.6 MJ mm ha(-1) h(-1)). The predicted annual soil loss was 15.1 t ha(-1), and the sediment amount delivery was 4,314 × 10(3) kg. Knowledge of seasonal variation would be essential to outline sustainable land management practices. This model will be integrated with World Overview of Conservation Approaches and Technologies methods to support decision-making in that watershed, and it will involve collaboration with both local people and governmental institutions.

Dry season distribution of land crabs, Gecarcinus quadratus (Crustacea: Gecarcinidae, in Corcovado National Park, Costa Rica

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Megan E Griffiths

2007-03-01

Full Text Available The land crab Gecarcinus quadratus is an engineering species that controls nutrient cycling in tropical forests. Factors regulating their coastal distribution are not fully understood. We quantified land crab distribution during the dry season at Sirena Field Station in Corcovado National Park, Costa Rica, and found that land crab burrow density decreases with increasing distance from the ocean. Leaf litter depth and tree seedling density are negatively correlated with land crab burrow density. Burrows are strongly associated with sand substrate and burrow density is comparatively low in clay substrate. Results suggest that G. quadratus is limited to a narrow coastal zone with sand substrate, and this distribution could have profound effects on plant community structure. Rev. Biol. Trop. 55 (1: 219-224. Epub 2007 March. 31.El cangrejo terrestre Gecarcinus quadratus es una especie "ingeniera" que controla el ciclo de nutrientes en los bosques tropicales. Los factores que regulan su distribución a lo largo de las costas no se conocen de forma definitiva. Se cuantificó la distribución del cangrejo terrestre durante la estación seca en la Estación de Campo Sirena en el Parque Nacional de Corcovado, Costa Rica, y se encontró que la densidad de galerías del cangrejo terrestre disminuye al aumentar la distancia al océano. La profundidad de la hojarasca y la densidad de plántulas de especies arbóreas están negativamente correlacionadas con la densidad de galerías del cangrejo terrestre. Las galerías aparecen fuertemente asociadas con el sustrato arenoso y la densidad de galerías es comparativamente más baja en sustratos arcillosos. Estos resultados sugieren que G. quadratus se encuentra en una zona costera estrecha con sustrato arenoso, y que esta distribución podría tener efectos importantes en la estructura de la comunidad vegetal.

Local people's knowledge with regard to land use activities in southwest Madagascar - Conceptual insights for sustainable land management.

Science.gov (United States)

Fritz-Vietta, Nadine V M; Tahirindraza, H Stone; Stoll-Kleemann, Susanne

2017-09-01

Environmental conditions in the Mahafaly Plateau region in southwest Madagascar are harsh, with a long dry season and a short rainy season. The local people's land use capabilities and skills are adapted to these conditions. Nevertheless, they are currently confronted by drastic climatic changes, including longer dry seasons, which have resulted in food and water scarcities. It is therefore essential to ensure sustainable land management in the region. At present, the main land use activities are agriculture, livestock farming, natural resource collection including timber and non-timber forest products, and the practice of local customs. Land use activities have always resulted in land conversion, yet over time this ecological transformation also leads to the accumulation of knowledge. The aim of the present article is therefore twofold. First, it aims to examine local people's knowledge with regard to land use activities and the transmission of this knowledge from one generation to the next; second, it considers the extent to which local people's knowledge may contribute to the development of sustainable land management. Our research is based on more than 80 qualitative interviews with local inhabitants of the Mahafaly Plateau region. Our analysis of local people's knowledge identifies four categories: ecological knowledge, knowledge related to natural resource usage, knowledge of names, and the interconnection between knowledge and belief. Furthermore, these knowledge categories provide conceptual insights for sustainable land management. Along with the long-term persistence of natural resources and their functions and the satisfaction of basic needs through resource usage, both the recognition of mental images as a regulating mechanism and the maintenance of the relation between the natural and the supernatural world have a role to play in sustainable land management in the study area. Local knowledge transmission processes serve to foster ongoing learning and

Runoff changes have a land cover specific effect on the seasonal fluxes of terminal electron acceptors in the boreal catchments.

Science.gov (United States)

Mattsson, Tuija; Lehtoranta, Jouni; Ekholm, Petri; Palviainen, Marjo; Kortelainen, Pirkko

2017-12-01

Climate change influences the volume and seasonal distribution of runoff in the northern regions. Here, we study how the seasonal variation in the runoff affects the concentrations and export of terminal electron acceptors (i.e. TEAs: NO 3 , Mn, Fe and SO 4 ) in different boreal land-cover classes. Also, we make a prediction how the anticipated climate change induced increase in runoff will alter the export of TEAs in boreal catchments. Our results show that there is a strong positive relationship between runoff and the concentration of NO 3 -N, Mn and Fe in agricultural catchments. In peaty catchments, the relationship is poorer and the concentrations of TEAs tend to decrease with increasing runoff. In forested catchments, the correlation between runoff and TEA concentrations was weak. In most catchments, the concentrations of SO 4 decrease with an increase in runoff regardless of the land cover or season. The wet years export much higher amounts of TEAs than the dry years. In southern agricultural catchments, the wet years increased the TEA export for both spring (January-May) and autumn (September-December) periods, while in the peaty and forested catchments in eastern and northern Finland the export only increased in the autumn. Our predictions for the year 2099 indicate that the export of TEAs will increase especially from agricultural but also from forested catchments. Additionally, the predictions show an increase in the export of Fe and SO 4 for all the catchments for the autumn. Thus, the climate induced change in the runoff regime is likely to alter the exported amount of TEAs and the timing of the export downstream. The changes in the amounts and timing in the export of TEAs have a potential to modify the mineralization pathways in the receiving water bodies, with feedbacks in the cycling of C, nutrients and metals in aquatic ecosystems. Copyright © 2017 Elsevier B.V. All rights reserved.

Long-term trends in vegetation phenology and productivity over Namaqualand using the GIMMS AVHRR NDVI3g data from 1982 to 2011

CSIR Research Space (South Africa)

Davis, CL

2017-07-01

Full Text Available Vegetation monitoring of arid and semi-arid environments using remotely sensed vegetation indices over long periods of time is essential to improve the understanding of the processes related to change. In this paper, 30 years of biweekly AVHRR NDVI3...

Integração de imagens NOAA/AVHRR: rede de cooperação para monitoramento nacional da safra de soja

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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.

Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010

Science.gov (United States)

Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

2014-05-01

Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

Seasonal energy storage using bioenergy production from abandoned croplands

International Nuclear Information System (INIS)

Elliott Campbell, J; Zumkehr, Andrew; Lobell, David B; Genova, Robert C; Field, Christopher B

2013-01-01

Bioenergy has the unique potential to provide a dispatchable and carbon-negative component to renewable energy portfolios. However, the sustainability, spatial distribution, and capacity for bioenergy are critically dependent on highly uncertain land-use impacts of biomass agriculture. Biomass cultivation on abandoned agriculture lands is thought to reduce land-use impacts relative to biomass production on currently used croplands. While coarse global estimates of abandoned agriculture lands have been used for large-scale bioenergy assessments, more practical technological and policy applications will require regional, high-resolution information on land availability. Here, we present US county-level estimates of the magnitude and distribution of abandoned cropland and potential bioenergy production on this land using remote sensing data, agriculture inventories, and land-use modeling. These abandoned land estimates are 61% larger than previous estimates for the US, mainly due to the coarse resolution of data applied in previous studies. We apply the land availability results to consider the capacity of biomass electricity to meet the seasonal energy storage requirement in a national energy system that is dominated by wind and solar electricity production. Bioenergy from abandoned croplands can supply most of the seasonal storage needs for a range of energy production scenarios, regions, and biomass yield estimates. These data provide the basis for further down-scaling using models of spatially gridded land-use areas as well as a range of applications for the exploration of bioenergy sustainability. (letter)

Development of a Bi-National Great Lakes Coastal Wetland and Land Use Map Using Three-Season PALSAR and Landsat Imagery

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Laura Bourgeau-Chavez

2015-07-01

Full Text Available Methods using extensive field data and three-season Landsat TM and PALSAR imagery were developed to map wetland type and identify potential wetland stressors (i.e., adjacent land use for the United States and Canadian Laurentian coastal Great Lakes. The mapped area included the coastline to 10 km inland to capture the region hydrologically connected to the Great Lakes. Maps were developed in cooperation with the overarching Great Lakes Consortium plan to provide a comprehensive regional baseline map suitable for coastal wetland assessment and management by agencies at the local, tribal, state, and federal levels. The goal was to provide not only land use and land cover (LULC baseline data at moderate spatial resolution (20–30 m, but a repeatable methodology to monitor change into the future. The prime focus was on mapping wetland ecosystem types, such as emergent wetland and forested wetland, as well as to delineate wetland monocultures (Typha, Phragmites, Schoenoplectus and differentiate peatlands (fens and bogs from other wetland types. The overall accuracy for the coastal Great Lakes map of all five lake basins was 94%, with a range of 86% to 96% by individual lake basin (Huron, Ontario, Michigan, Erie and Superior.

The land management tool: Developing a climate service in Southwest UK

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Pete Falloon

2018-01-01

Full Text Available Seasonal climate forecasts (SCFs have significant potential to support shorter-term agricultural decisions and longer-term climate adaptation plans, but uptake in Europe has to date been low. Under the European Union funded project, European Provision Of Regional Impacts Assessments on Seasonal and Decadal Timescales (EUPORIAS we have developed the Land Management Tool (LMTool, a prototype seasonal climate service for land managers, working closely in collaboration with two stakeholder organizations, Clinton Devon Estates (CDE and the National Farmers Union (NFU. LMTool was one of several prototype climate services selected for development within EUPORIAS, including those for the UK transport network, food security in Ethiopia, renewable energy production, hydroelectric energy production in Sweden, and river management in two French basins. The LMTool provides SCFs (1–3 months ahead to farmers in the Southwest UK, alongside 14-day site specific weather forecasts during the winter months when the skill of seasonal forecasts is greatest.We describe the processes through which the LMTool was co-designed and developed with the farmers, its technical development and key features; critically examine the lessons learned and their implications for providing future climate services for land managers; and finally assess the feasibility of delivering an operational winter seasonal climate service for UK land managers.A number of key learning points from developing the prototype may benefit future work in climate services for the land management and agriculture sector; many of these points are also valid for climate services in other sectors. Prototype development strongly benefitted from; working with intermediaries to identify representative, engaged land managers; an iterative and flexible process of co-design with the farmer group; and from an interdisciplinary project team. Further work is needed to develop a better understanding of the role of

Land ECVs from QA4ECV using an optimal estimation framework

Science.gov (United States)

Muller, Jan-Peter; Kharbouche, Said; Lewis, Philip; Danne, Olaf; Blessing, Simon; Giering, Ralf; Gobron, Nadine; Lanconelli, Christian; Govaerts, Yves; Schulz, Joerg; Doutriaux-Boucher, Marie; Lattanzio, Alessio; Aoun, Youva

2017-04-01

In the ESA-DUE GlobAlbedo project (http://www.GlobAlbedo.org), a 15 year record of land surface albedo was generated from the European VEGETATION & MERIS sensors using optimal estimation. This was based on 3 broadbands (0.4-0.7, 0.7-3, 0.4-3µm) and fused data at level-2 after converting from spectral narrowband to these 3 broadbands with surface BRFs. A 10 year long record of land surface albedo climatology was generated from Collection 5 of the MODIS BRDF product for these same broadbands. This was employed as an a priori estimate for an optimal estimation based retrieval of land surface albedo when there were insufficient samples from the European sensors. This so-called MODIS prior was derived at 1km from the 500m MOD43A1,2 BRDF inputs every 8 days using the QA bits and the method described in the GlobAlbedo ATBD which is available from the website (http://www.globalbedo.org/docs/GlobAlbedo_Albedo_ATBD_V4.12.pdf). In the ESA-STSE WACMOS-ET project, FastOpt generated fapar & LAI based on this GlobAlbedo BRDF with associated per pixel uncertainty using the TIP framework. In the successor EU-FP7-QA4ECV* project, we have developed a 33 year record (1981-2014) of Earth surface spectral and broadband albedo (i.e. including the ocean and sea-ice) using optimal estimation for the land and where available, relevant sensors for "instantaneous" retrievals over the poles (Kharbouche & Muller, this conference). This requires the longest possible land surface spectral and broadband BRDF record that can only be supplied by a 16 year of MODIS Collection 6 BRDFs at 500m but produced on a daily basis. The CEMS Big Data computer at RAL was used to generate 7 spectral bands and 3 broadband BRDF with and without snow and snow_only. We will discuss the progress made since the start of the QA4ECV project on the production of a new fused land surface BRDF/albedo spectral and broadband CDR product based on four European sensors: MERIS, (A)ATSR(2), VEGETATION, PROBA-V and two US sensors

Comparación de los productos de TSM L3 generados a partir de los sensores AVHRR y MODIS frente al Golfo San Jorge, Argentina

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L. Allega

2017-12-01

Full Text Available Desde principios de la década de los 80, el sensor AVHRR a bordo de los satélites NOAA ha provisto de estimaciones de la temperatura de la superficie del mar (TSM a la comunidad científica en general. Hacia finales de la década de los 90, surge una nueva generación de radiómetros que combinan una mayor gama de mediciones espectrales con mejoras en la tecnología, como lo es el sensor  MODIS a bordo de los satélites Terra y Aqua. El desarrollo de este último sensor se basó en los años de trayectoria de la serie NOAA/AVHRR. La comprensión de la relación entre los productos derivados de distintos sensores es fundamental para el seguimiento continuo a largo plazo de cualquier variable y de la construcción de serie de tiempos combinados. El objetivo del presente trabajo fue realizar una comparación de los valores mensuales de TSM para el período 2003-2006 calculadas a partir de datos de la serie NOAA/AVHRR vs Aqua/MODIS sobre un sector de la Plataforma Continental Argentina frente al Golfo San Jorge. El análisis de las isotermas muestra un patrón de distribución similar durante todos los meses para ambos sensores. El coeficiente de correlación de Pearson tanto en el análisis estacional como mensual fue alto (> 0,8. El análisis comparativo de la temperatura medida en ambos sensores muestra que los productos de TSM son similares, teniendo en cuenta que la diferencia media de temperatura entre ambos sensores es inferior a 0,5ºC. Por lo tanto, para el estudio de largas series de tiempo de TSM en la plataforma continental argentina se puede utilizar en forma continua las mediciones de Aqua/MODIS, cuando ya no se disponen las de NOAA/AVHRR.

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...

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...

The Response of African Land Surface Phenology to Large Scale Climate Oscillations

Science.gov (United States)

Brown, Molly E.; de Beurs, Kirsten; Vrieling, Anton

2010-01-01

Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the African continent. Analysis of changes in phenology can provide quantitative information on the effect of climate variability on growing seasons in agricultural regions. Using a robust statistical methodology, we describe the relationship between phenology metrics derived from the 26 year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD), the Pacific Decadal Oscillation (PDO), and the Multivariate ENSO Index (MEI). We map the most significant positive and negative correlation for the four climate indices in Eastern, Western and Southern Africa between two phenological metrics and the climate indices. Our objective is to provide evidence of whether climate variability captured in the four indices has had a significant impact on the vegetative productivity of Africa during the past quarter century. We found that the start of season and cumulative NDVI were significantly affected by large scale variations in climate. The particular climate index and the timing showing highest correlation depended heavily on the region examined. In Western Africa the cumulative NDVI correlates with PDO in September-November. In Eastern Africa the start of the June-October season strongly correlates with PDO in March-May, while the PDO in December-February correlates with the start of the February-June season. The cumulative NDVI over this last season relates to the MEI of March-May. For Southern Africa, high correlations exist between SOS and NAO of September-November, and cumulative NDVI and MEI of March-May. The research shows that climate indices can be used to anticipate late start and variable vigor in the growing season of sensitive agricultural regions in Africa.

Mercury fluxes from air/surface interfaces in paddy field and dry land

Energy Technology Data Exchange (ETDEWEB)

Zhu Jinshan [Key Laboratory of Eco-Environments in Three Gorges Reservoir Region (Ministry of Education), College of Resources and Environment, Southwest University, No. 216, Tiansheng Street, Beibei, Chongqing 400715 (China); Wang Dingyong, E-mail: dywang@swu.edu.cn [Key Laboratory of Eco-Environments in Three Gorges Reservoir Region (Ministry of Education), College of Resources and Environment, Southwest University, No. 216, Tiansheng Street, Beibei, Chongqing 400715 (China)] [Chongqing Key Laboratory of Agricultural Resources and Environment, Chongqing 400716 (China); Liu Xiao; Zhang Yutong [Key Laboratory of Eco-Environments in Three Gorges Reservoir Region (Ministry of Education), College of Resources and Environment, Southwest University, No. 216, Tiansheng Street, Beibei, Chongqing 400715 (China)

2011-02-15

Research highlights: {yields} It was found that agricultural fields are important local atmospheric Hg sources in the region. {yields} The Hg emissions from dry cornfield were higher than those from the flooded rice paddy, higher mercury emissions in the warm season than the cold season, and during daytime than at night. {yields} Mercury evasion is strongly related to solar radiation which is important in the emission of Hg at both sites. - Abstract: In order to provide insight into the characteristics of Hg exchange in soil/water-air surface from cropland (including paddy field and dry land), Hg fluxes were measured in Chengjiang. Mercury fluxes were measured using the dynamic flux chamber method, coupled with a Lumex (registered) multifunctional Hg analyzer RA-915{sup +} (Lumex Ltd., Russia). The Hg fluxes from paddy field and dry land were alternatively measured every 30 min. Data were collected for 24-48 h once per month for 5 months. Mercury fluxes in both fields were synchronously measured under the same conditions to compare Hg emissions between paddy field and dry land over diurnal and seasonal periods and find out what factors affect Hg emission on each surface. These results indicated that air Hg concentrations at the monitoring site was double the value observed at the global background sites in Europe and North America. The Hg release fluxes were 46.5 {+-} 22.8 ng m{sup -2} h{sup -1} in the warm season, 15.5 {+-} 18.8 ng m{sup -2} h{sup -1} in the cold season for dry land, and 23.8 {+-} 15.6 ng m{sup -2} h{sup -1} in the warm season, 6.3 {+-} 11.9 ng m{sup -2} h{sup -1} in the cold season for paddy field. Solar radiation is important in the emission of Hg over both sites. Hg exchange at the soil/air and water/air interfaces showed temporal variations. The amount of Hg emission from dry land was higher than that from the paddy field, and the emission in daytime was higher than that at night. Moreover, Hg emissions from land covered by crops, was lower

Land change monitoring, assessment, and projection (LCMAP) revolutionizes land cover and land change research

Science.gov (United States)

Young, Steven

2017-05-02

When nature and humanity change Earth’s landscapes - through flood or fire, public policy, natural resources management, or economic development - the results are often dramatic and lasting.Wildfires can reshape ecosystems. Hurricanes with names like Sandy or Katrina will howl for days while altering the landscape for years. One growing season in the evolution of drought-resistant genetics can transform semiarid landscapes into farm fields.In the past, valuable land cover maps created for understanding the effects of those events - whether changes in wildlife habitat, water-quality impacts, or the role land use and land cover play in affecting weather and climate - came out at best every 5 to 7 years. Those high quality, high resolution maps were good, but users always craved more: even higher quality data, additional land cover and land change variables, more detailed legends, and most importantly, more frequent land change information.Now a bold new initiative called Land Change Monitoring, Assessment, and Projection (LCMAP) promises to fulfill that demand.Developed at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, LCMAP provides definitive, timely information on how, why, and where the planet is changing. LCMAP’s continuous monitoring process can detect changes as they happen every day that Landsat satellites acquire clear observations. The result will be to place near real-time information in the hands of land and resource managers who need to understand the effects these changes have on landscapes.

Reforesting degraded lands may not restore hydrological conditions

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Balcerak, Ernie

2013-12-01

By the 1980s, forest lands in the Himalayas in central Nepal had become severely degraded as people cleared land for pastures. This led to lowered soil infiltration capacities, resulting in increased surface runoff, soil erosion, and flooding during the rainy season.

Soil bacterial community response to differences in agricultural management along with seasonal changes in a Mediterranean region.

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Bevivino, Annamaria; Paganin, Patrizia; Bacci, Giovanni; Florio, Alessandro; Pellicer, Maite Sampedro; Papaleo, Maria Cristiana; Mengoni, Alessio; Ledda, Luigi; Fani, Renato; Benedetti, Anna; Dalmastri, Claudia

2014-01-01

Land-use change is considered likely to be one of main drivers of biodiversity changes in grassland ecosystems. To gain insight into the impact of land use on the underlying soil bacterial communities, we aimed at determining the effects of agricultural management, along with seasonal variations, on soil bacterial community in a Mediterranean ecosystem where different land-use and plant cover types led to the creation of a soil and vegetation gradient. A set of soils subjected to different anthropogenic impact in a typical Mediterranean landscape, dominated by Quercus suber L., was examined in spring and autumn: a natural cork-oak forest, a pasture, a managed meadow, and two vineyards (ploughed and grass covered). Land uses affected the chemical and structural composition of the most stabilised fractions of soil organic matter and reduced soil C stocks and labile organic matter at both sampling season. A significant effect of land uses on bacterial community structure as well as an interaction effect between land uses and season was revealed by the EP index. Cluster analysis of culture-dependent DGGE patterns showed a different seasonal distribution of soil bacterial populations with subgroups associated to different land uses, in agreement with culture-independent T-RFLP results. Soils subjected to low human inputs (cork-oak forest and pasture) showed a more stable bacterial community than those with high human input (vineyards and managed meadow). Phylogenetic analysis revealed the predominance of Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes phyla with differences in class composition across the site, suggesting that the microbial composition changes in response to land uses. Taken altogether, our data suggest that soil bacterial communities were seasonally distinct and exhibited compositional shifts that tracked with changes in land use and soil management. These findings may contribute to future searches for bacterial bio-indicators of soil

Soil bacterial community response to differences in agricultural management along with seasonal changes in a Mediterranean region.

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Annamaria Bevivino

Full Text Available Land-use change is considered likely to be one of main drivers of biodiversity changes in grassland ecosystems. To gain insight into the impact of land use on the underlying soil bacterial communities, we aimed at determining the effects of agricultural management, along with seasonal variations, on soil bacterial community in a Mediterranean ecosystem where different land-use and plant cover types led to the creation of a soil and vegetation gradient. A set of soils subjected to different anthropogenic impact in a typical Mediterranean landscape, dominated by Quercus suber L., was examined in spring and autumn: a natural cork-oak forest, a pasture, a managed meadow, and two vineyards (ploughed and grass covered. Land uses affected the chemical and structural composition of the most stabilised fractions of soil organic matter and reduced soil C stocks and labile organic matter at both sampling season. A significant effect of land uses on bacterial community structure as well as an interaction effect between land uses and season was revealed by the EP index. Cluster analysis of culture-dependent DGGE patterns showed a different seasonal distribution of soil bacterial populations with subgroups associated to different land uses, in agreement with culture-independent T-RFLP results. Soils subjected to low human inputs (cork-oak forest and pasture showed a more stable bacterial community than those with high human input (vineyards and managed meadow. Phylogenetic analysis revealed the predominance of Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes phyla with differences in class composition across the site, suggesting that the microbial composition changes in response to land uses. Taken altogether, our data suggest that soil bacterial communities were seasonally distinct and exhibited compositional shifts that tracked with changes in land use and soil management. These findings may contribute to future searches for bacterial bio

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

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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

Daytime Low Stratiform Cloud Detection on AVHRR Imagery

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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.

Seasonality and dietary requirements: will eating seasonal food contribute to health and environmental sustainability?

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Macdiarmid, Jennie I

2014-08-01

Eating more seasonal food is one proposal for moving towards more sustainable consumption patterns, based on the assumption that it could reduce the environmental impact of the diet. The aim of the present paper is to consider the implications of eating seasonal food on the different elements of sustainability (i.e. health, economics, society), not just the environment. Seasonality can be defined as either globally seasonal (i.e. produced in the natural production season but consumed anywhere in the world) or locally seasonal (i.e. produced in the natural production season and consumed within the same climatic zone). The environmental, health, economic and societal impact varies by the definition used. Global seasonality has the nutritional benefit of providing a more varied and consistent supply of fresh produce year round, but this increases demand for foods that in turn can have a high environmental cost in the country of production (e.g. water stress, land use change with loss of biodiversity). Greenhouse gas emissions of globally seasonal food are not necessarily higher than food produced locally as it depends more on the production system used than transportation. Eating more seasonal food, however, is only one element of a sustainable diet and should not overshadow some of the potentially more difficult dietary behaviours to change that could have greater environmental and health benefits (e.g. reducing overconsumption or meat consumption). For future guidelines for sustainable diets to be realistic they will need to take into account modern lifestyles, cultural and social expectations in the current food environment.

THE SEASONAL VARIABILITY OF CPUE AND CATCH-AT-SIZE DISTRIBUTION OF TROLL AND HANDLINE TUNA FISHERIES LANDED IN LABUHAN LOMBOK

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Bram Setyadji

2016-12-01

Full Text Available Troll and hand line tuna fisheries is one of the major fishing gears landed in Labuhan Lombok coastal fishing port (PPP Labuhan Lombok west Nusa Tenggara Barat province.  Both fisheries are strongly associated with fish aggregating devices (FAD’s. The main fishing ground is Indian Ocean southern part of this province.  Several source of data has been collected regularly. Data analysis comprised of monthlycatch and effort data samples based onport monitoring program during 2012 to 2015. The result showed the diclining of CPUE of yellow fin and skipjack tuna presumably related to fishing intensity of fleets and its variability that landed in PPP Labuhan Lombok.  The increasing CPUE of skipjack tuna in 2014 was predicted due to increasing aggregation around the FADs. Constrasting seasonal fishing index pattern between yellowfin and skipjack tuna foundin 4-month cycles, started in January.A length-weight relationship suggested that yellowfin tuna caught bysmall-scale fisheries were performing allometric growth pattern (b=2.963, r2=0.9737.

Forecasting the Seasonal Timing of Maine's Lobster Fishery

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Katherine E. Mills

2017-11-01

Full Text Available The fishery for American lobster is currently the highest-valued commercial fishery in the United States, worth over US$620 million in dockside value in 2015. During a marine heat wave in 2012, the fishery was disrupted by the early warming of spring ocean temperatures and subsequent influx of lobster landings. This situation resulted in a price collapse, as the supply chain was not prepared for the early and abundant landings of lobsters. Motivated by this series of events, we have developed a forecast of when the Maine (USA lobster fishery will shift into its high volume summer landings period. The forecast uses a regression approach to relate spring ocean temperatures derived from four NERACOOS buoys along the coast of Maine to the start day of the high landings period of the fishery. Tested against conditions in past years, the forecast is able to predict the start day to within 1 week of the actual start, and the forecast can be issued 3–4 months prior to the onset of the high-landings period, providing valuable lead-time for the fishery and its associated supply chain to prepare for the upcoming season. Forecast results are conveyed in a probabilistic manner and are updated weekly over a 6-week forecasting period so that users can assess the certainty and consistency of the forecast and factor the uncertainty into their use of the information in a given year. By focusing on the timing of events, this type of seasonal forecast provides climate-relevant information to users at time scales that are meaningful for operational decisions. As climate change alters seasonal phenology and reduces the reliability of past experience as a guide for future expectations, this type of forecast can enable fishing industry participants to better adjust to and prepare for operating in the context of climate change.

Seasonal scale water deficit forecasting in Africa and the Middle East using NASA's Land Information System (LIS)

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Peters-Lidard, C. D.; Arsenault, K. R.; Shukla, S.; Getirana, A.; McNally, A.; Koster, R. D.; Zaitchik, B. F.; Badr, H. S.; Roningen, J. M.; Kumar, S.; Funk, C. C.

2017-12-01

A seamless and effective water deficit monitoring and early warning system is critical for assessing food security in Africa and the Middle East. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of drought and water availability monitoring products in the region. Next, it will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the products through NASA's web-services. The water deficit forecasting system thus far incorporates NASA GMAO's Catchment and the Noah Multi-Physics (MP) LSMs. In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. To establish a climatology from 1981-2015, the two LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. Comparison of the models' energy and hydrological budgets with independent observations suggests that major droughts are well-reflected in the climatology. The system uses seasonal climate forecasts from NASA's GEOS-5 (the Goddard Earth Observing System Model-5) and NCEP's Climate Forecast System-2, and it produces forecasts of soil moisture, ET and streamflow out to 6 months in the future. Forecasts of those variables are formulated in terms of indicators to provide forecasts of drought and water availability in the region. Current work suggests

Characterization of AVHRR global cloud detection sensitivity based on CALIPSO-CALIOP cloud optical thickness information: demonstration of results based on the CM SAF CLARA-A2 climate data record

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Karlsson, Karl-Göran; Håkansson, Nina

2018-02-01

The sensitivity in detecting thin clouds of the cloud screening method being used in the CM SAF cloud, albedo and surface radiation data set from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. The sensitivity, including its global variation, has been studied based on collocations of Advanced Very High Resolution Radiometer (AVHRR) and CALIOP measurements over a 10-year period (2006-2015). The cloud detection sensitivity has been defined as the minimum cloud optical thickness for which 50 % of clouds could be detected, with the global average sensitivity estimated to be 0.225. After using this value to reduce the CALIOP cloud mask (i.e. clouds with optical thickness below this threshold were interpreted as cloud-free cases), cloudiness results were found to be basically unbiased over most of the globe except over the polar regions where a considerable underestimation of cloudiness could be seen during the polar winter. The overall probability of detecting clouds in the polar winter could be as low as 50 % over the highest and coldest parts of Greenland and Antarctica, showing that a large fraction of optically thick clouds also remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud's geographical position. Best results were achieved over oceanic surfaces at mid- to high latitudes where at least 50 % of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over the Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 for the parts

Eutrophication potential of lakes: an integrated analysis of trophic state, morphometry, land occupation, and land use

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RF Silvino

Full Text Available AbstractDespite being inside a protected area, Lake Sumidouro has been impacted by the anthropogenic occupation of the surrounding area since the 1970’s, compromising the ecological integrity of the lake and the sustainable use of natural resources. This study examined the current trophic classification of the lake and developed methods for improving it through an integrated analysis of morphometric and limnological parameters, land use and land occupation in the watershed, and eutrophication potential. Data for the limnological parameters, land use and land occupation, and morphometric characteristics of Lake Sumidouro were collected in the rainy and dry seasons of 2009 and 2010. Depending on the trophic classification system used, Lake Sumidouro is classified as oligotrophic to hypereutrophic. In our study, the highest concentration of nutrients occurred in the rainy season, indicating that high nutrient inputs played an important role during this period. Areas of anthropogenic occupation comprised approximately 62.9% of the total area of the watershed, with pasture and urban settlement as the main types of land use. The influent total phosphorus load was estimated to be 15,824.3 kg/year. To maintain mesotrophic conditions, this load must be reduced by 29.4%. By comparing the isolated use of trophic state indices, this study demonstrated that comparing the trophic state classification with morphometric analyses, land use and land occupation types in the watershed, and potential phosphorus load provided better information to guide management actions for restoration and conservation. Furthermore, this approach also allowed for evaluating the vulnerability of the environment to the eutrophication process.

Impact of Land Use Change and Land Management on Irrigation Water Supply in Northern Java Coast

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Suria DarmaTarigan

2013-05-01

Full Text Available In Indonesia, paddy irrigation covers an area of 7,230,183 ha. Ten percent (10% of those area or 797,971 ha were supplied by reservoirs. As many as 237,790 ha (30% of those area supplied by reservoirs are situated downstream of Citarum Watershed called Northern Java Coast Irrigation Area or Pantura. Therefore, Citarum watershed is one of the most important watershed in Indonesia. Citarum is also categorized as one of most degraded watershed in Java. The study aimed to evaluate influence of land use change on irrigation water supply in Citarum watershed and land management strategies to reduce the impact. Tremendous land use change occurred in the past ten years in Citarum watershed. Settlement areas increases more than a double during 2000 to 2009 (81,686 ha to 176,442 ha and forest area decreased from 71,750 ha to 9,899 ha in the same time period. Land use change influences irrigation water supply through 2 factors: a decreasing storage capacity of watershed (hydrologic functions for dry season, and b decreasing storage capacity of reservoirs due to the sedimentation. Change of Citarum watershed hydrologic function was analyzed using 24 years’ time series discharge data (1984-2008 in combination with rainfall data from 2000 to 2008. Due to the land use change in this time period, discharge tend to decrease despite of increasing trend of rainfall. As a result irrigation area decreased 9,355 ha during wet season and 10,170 ha during dry season in the last ten years. Another threat for sustainability of water irrigation supply is reservoir sedimentation. Sedimentation rate in the past 10 years has reduced upper Citarum reservoir (Saguling half-life period (½ capacity sedimented from 294 to 28 years. If proper land management strategies be carried out, the half-life period of Saguling reservoir can be extended up to 86,4 years

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

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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...

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)

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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...

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)

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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...

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...

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

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Shiffman, Smadar; Nemani, Ramakrishna

2005-01-01

Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

Seasonal evaluation of the land surface scheme HTESSEL against remote sensing derived energy fluxes of the Transdanubian region in Hungary

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E. L. Wipfler

2011-04-01

Full Text Available The skill of the land surface model HTESSEL is assessed to reproduce evaporation in response to land surface characteristics and atmospheric forcing, both being spatially variable. Evaporation estimates for the 2005 growing season are inferred from satellite observations of the Western part of Hungary and compared to model outcomes. Atmospheric forcings are obtained from a hindcast run with the Regional Climate Model RACMO2. Although HTESSEL slightly underpredicts the seasonal evaporative fraction as compared to satellite estimates, the mean, 10th and 90th percentile of this variable are of the same magnitude as the satellite observations. The initial water as stored in the soil and snow layer does not have a significant effect on the statistical properties of the evaporative fraction. However, the spatial distribution of the initial soil and snow water significantly affects the spatial distribution of the calculated evaporative fraction and the models ability to reproduce evaporation correctly in low precipitation areas in the considered region. HTESSEL performs weaker in dryer areas. In Western Hungary these areas are situated in the Danube valley, which is partly covered by irrigated cropland and which also may be affected by shallow groundwater. Incorporating (lateral groundwater flow and irrigation, processes that are not included now, may improve HTESSELs ability to predict evaporation correctly. Evaluation of the model skills using other test areas and larger evaluation periods is needed to confirm the results.

Based on earlier sensitivity analysis, the effect of a number of modifications to HTESSEL has been assessed. A more physically based reduction function for dry soils has been introduced, the soil depth is made variable and the effect of swallow groundwater included. However, the combined modification does not lead to a significantly improved performance of HTESSEL.

Multi year changes of Aerosol Optical Depth in the monsoon region of the Indian Ocean since 1986 as seen in the AVHRR and TOMS data

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J. P. George

2008-02-01

Full Text Available Aerosol Optical Depth (AOD data based on AVHRR and TOMS was analyzed to find out the changes in the Indian Ocean from 1981 to 2004. Four regions covering Indian Ocean north of 10° S were studied in detail. The results strongly suggest that the mean value of AOD in these regions decreased from 1986–1990 to 1995–1999. The Arabian Sea and Bay of Bengal show increase thereafter whereas in the equatorial part it decreased further, during 2000–2004. The drop in AOD from the first to second period is evident in AVHRR and TOMS in the case of the Arabian Sea (North West Indian Ocean. The decrease in this case is prominent in summer. These results in general agree with the recently reported global decrease in AOD, "global brightening" and also the reversal of trend in some of the anthropogenic emissions.

Land use determinants of small mammals abundance and ...

African Journals Online (AJOL)

The objective of this study was to determine the relationship between land use types and practices and small mammal abundance and distribution. A field survey was used to collect data in three landscapes differing in plague incidences. Data collection was done both in the wet season (April-June 2012) and dry season ...

Comparison and Evaluation of Annual NDVI Time Series in China Derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 Products.

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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

Reconciling top-down and bottom-up estimates of CO2 fluxes to understand increased seasonal exchange in Northern ecosystems

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Bastos, A.; Ciais, P.; Zhu, D.; Maignan, F.; Wang, X.; Chevallier, F.; Ballantyne, A.

2017-12-01

Continuous atmospheric CO2 monitoring data indicate enhanced seasonal exchange in the high-latitudes in the Northern Hemisphere (above 40oN), mainly attributed to terrestrial ecosystems. Whether this enhancement is mostly explained by increased vegetation growth due to CO2 fertilization and warming, or by changes in land-use and land-management practices is still an unsettled question (e.g. Forkel et al. (2016) and Zeng et al. (2013)). Previous studies have shown that models present variable performance in capturing trends in CO2 amplitude at CO2 monitoring sites, and that Earth System Models present large spread in their estimates of such trends. Here we integrate data of atmospheric CO2 exchange in terrestrial ecosystems by a set of atmospheric CO2 inversions and a range of land-surface models to evaluate the ability of models to reproduce changes in CO2 seasonal exchange within the observation uncertainty. We then analyze the factors that explain the model spread to understand if the trend in seasonal CO2 amplitude may indeed be a useful metric to constrain future changes in terrestrial photosynthesis (Wenzel et al., 2016). We then compare model simulations with satellite and other observation-based datasets of vegetation productivity, biomass stocks and land-cover change to test the contribution of natural (CO2 fertilization, climate) and human (land-use change) factors to the increasing trend in seasonal CO2 amplitude. Forkel, Matthias, et al. "Enhanced seasonal CO2 exchange caused by amplified plant productivity in northern ecosystems." Science 351.6274 (2016): 696-699. Wenzel, Sabrina, et al. "Projected land photosynthesis constrained by changes in the seasonal cycle of atmospheric CO2." Nature 538, no. 7626 (2016): 499-501.Zeng, Ning, et al. "Agricultural Green Revolution as a driver of increasing atmospheric CO2 seasonal amplitude." Nature 515.7527 (2014): 394.

Characterization of land surface energy fluxes in a tropical lowland rice paddy

Science.gov (United States)

Chatterjee, Dibyendu; Tripathi, Rahul; Chatterjee, Sumanta; Debnath, Manish; Shahid, Mohammad; Bhattacharyya, Pratap; Swain, Chinmaya Kumar; Tripathy, Rojalin; Bhattacharya, Bimal K.; Nayak, Amaresh Kumar

2018-04-01

A field experiment was conducted in 2015 to study the land surface energy fluxes from tropical lowland rice paddy in eastern India with an objective to determine the mass, momentum, and energy exchange rates between rice paddies and the atmosphere. All the land surface energy fluxes were measured by eddy covariance (EC) system (make Campbell Scientific) in dry season (DS, 1-125 Julian days), dry fallow (DF, 126-181 Julian days), wet season (WS, 182-324 Julian days), and wet fallow (WF, 325-365 Julian days). The rice was cultivated in dry season (January-May) and wet season (July-November) in low wet lands and the ground is kept fallow during the remainder of the year. Results showed that albedo varied from 0.09 to 0.24 and showed positive value from morning 6:00 h until evening 18:00 h. Mean soil temperature (T g) was highest in DF, while the skin temperature (T s) was highest in WS. Average Bowen ratio (B) ranged from 0.21 to 0.64 and large variation in B was observed during the fallow periods as compared to the cropping seasons. The magnitude of aerodynamic, canopy, and climatological resistances increased with the progress of cropping season and their magnitudes decreased during the end of both cropping seasons and found minimum during the fallow periods. At a constant vapor pressure deficit (VPD) at 0.16, 0.18, 0.15, and 0.43 kPa, latent heat flux (LE) initially increased, but later it tended to level off with an increase in VPD. The actual evapotranspiration (ETa) during both the cropping seasons was higher than the fallow period. This study can be used as a source of default values for many land surface energy fluxes which are required in various meteorological or air-quality models for rice paddies. A larger imbalance of energy was observed during the wet season as the energy is stored and perhaps advected in the fresh water.

The influence of land surface parameters on energy flux densities derived from remote sensing data

Energy Technology Data Exchange (ETDEWEB)

Tittebrand, A.; Schwiebus, A. [Inst. for Hydrology und Meteorology, TU Dresden (Germany); Berger, F.H. [Observatory Lindenberg, German Weather Service, Lindenberg (Germany)

2005-04-01

Knowledge of the vegetation properties surface reflectance, normalised difference vegetation index (NDVI) and leaf area index (LAI) are essential for the determination of the heat and water fluxes between terrestrial ecosystems and the atmosphere. Remote sensing data can be used to derive spatial estimates of the required surface properties. The determination of land surface parameters and their influence on radiant and energy flux densities is investigated with data of different remote sensing systems. Sensitivity studies show the importance of correctly derived land surface properties to estimate the key quantity of the hydrological cycle, the evapotranspiration (L.E), most exactly. In addition to variable parameters like LAI or NDVI there are also parameters which are can not be inferred from satellite data but needed for the Penman-Monteith approach. Fixed values are assumed for these variables because they have little influence on L.E. Data of Landsat-7 ETM+ and NOAA-16 AVHRR are used to show results in different spatial resolution. The satellite derived results are compared with ground truth data provided by the Observatory Lindenberg of the German Weather Service. (orig.)

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...

Modeling Rainfall-Runoff Response to Land Use and Land Cover Change in Rwanda (1990–2016

Directory of Open Access Journals (Sweden)

Fidele Karamage

2017-02-01

Full Text Available Stormwater runoff poses serious environmental problems and public health issues in Rwanda, a tropical country that is increasingly suffering from severe floods, landslides, soil erosion and water pollution. Using the WetSpa Extension model, this study assessed the changes in rainfall runoff depth in Rwanda from 1990 to 2016 in response to precipitation and land use changes. Our results show that Rwanda has experienced a significant conversion of natural forest and grassland to cropland and built-up areas. During the period 1990–2016, 7090.02 km2 (64.5% and 1715.26 km2 (32.1% of forest and grassland covers were lost, respectively, while the cropland and built-up areas increased by 135.3% (8503.75 km2 and 304.3% (355.02 km2, respectively. According to our estimates, the land use change effect resulted in a national mean runoff depth increase of 2.33 mm/year (0.38%. Although precipitation change affected the inter-annual fluctuation of runoff, the long-term trend of runoff was dominated by land use change. The top five districts that experienced the annual runoff depth increase (all >3.8 mm/year are Rubavu, Nyabihu, Ngororero, Gakenke, and Musanze. Their annual runoff depths increased at a rate of >3.8 mm/year during the past 27 years, due to severe deforestation (ranging from 62% to 85% and cropland expansion (ranging from 123% to 293%. These areas require high priority in runoff control using terracing in croplands and rainwater harvesting systems such as dam/reservoirs, percolation tanks, storage tanks, etc. The wet season runoff was three times higher than the dry season runoff in Rwanda; appropriate rainwater management and reservation could provide valuable irrigation water for the dry season or drought years (late rainfall onsets or early rainfall cessations. It was estimated that a reservation of 30.5% (3.99 km3 of the runoff in the wet season could meet the cropland irrigation water gap during the dry season in 2016.

Seasonal habitat use and selection by grizzly bears in Northern British Columbia

Science.gov (United States)

Milakovic, B.; Parker, K.L.; Gustine, D.D.; Lay, R.J.; Walker, A.B.D.; Gillingham, M.P.

2012-01-01

We defined patterns of habitat use and selection by female grizzly bears (Ursus arctos) in the Besa-Prophet watershed of northern British Columbia. We fitted 13 adult females with Geographic Positioning System (GPS) radio-collars and monitored them between 2001 and 2004. We examined patterns of habitat selection by grizzly bears relative to topographical attributes and 3 potential surrogates of food availability: land-cover class, vegetation biomass or quality (as measured by the Normalized Difference Vegetation Index), and selection value for prey species themselves (moose [Alces alces], elk [Cervus elaphus], woodland caribou [Rangifer tarandus], Stone's sheep [Ovis dalli stonei]). Although vegetation biomass and quality, and selection values for prey were important in seasonal selection by some individual bears, land-cover class, elevation, aspect, and vegetation diversity most influenced patterns of habitat selection across grizzly bears, which rely on availability of plant foods and encounters with ungulate prey. Grizzly bears as a group avoided conifer stands and areas of low vegetation diversity, and selected for burned land-cover classes and high vegetation diversity across seasons. They also selected mid elevations from what was available within seasonal ranges. Quantifying relative use of different attributes helped place selection patterns within the context of the landscape. Grizzly bears used higher elevations (1,595??31 m SE) in spring and lower elevations (1,436??27 m) in fall; the range of average elevations used among individuals was highest (500 m) during the summer. During all seasons, grizzly bears most frequented aspects with high solar gain. Use was distributed across 10 land-cover classes and depended on season. Management and conservation actions must maintain a diverse habitat matrix distributed across a large elevational gradient to ensure persistence of grizzly bears as levels of human access increase in the northern Rocky Mountains

Modelling seasonal meltwater forcing of the velocity of land-terminating margins of the Greenland Ice Sheet

Science.gov (United States)

Koziol, Conrad P.; Arnold, Neil

2018-03-01

Surface runoff at the margin of the Greenland Ice Sheet (GrIS) drains to the ice-sheet bed, leading to enhanced summer ice flow. Ice velocities show a pattern of early summer acceleration followed by mid-summer deceleration due to evolution of the subglacial hydrology system in response to meltwater forcing. Modelling the integrated hydrological-ice dynamics system to reproduce measured velocities at the ice margin remains a key challenge for validating the present understanding of the system and constraining the impact of increasing surface runoff rates on dynamic ice mass loss from the GrIS. Here we show that a multi-component model incorporating supraglacial, subglacial, and ice dynamic components applied to a land-terminating catchment in western Greenland produces modelled velocities which are in reasonable agreement with those observed in GPS records for three melt seasons of varying melt intensities. This provides numerical support for the hypothesis that the subglacial system develops analogously to alpine glaciers and supports recent model formulations capturing the transition between distributed and channelized states. The model shows the growth of efficient conduit-based drainage up-glacier from the ice sheet margin, which develops more extensively, and further inland, as melt intensity increases. This suggests current trends of decadal-timescale slowdown of ice velocities in the ablation zone may continue in the near future. The model results also show a strong scaling between average summer velocities and melt season intensity, particularly in the upper ablation area. Assuming winter velocities are not impacted by channelization, our model suggests an upper bound of a 25 % increase in annual surface velocities as surface melt increases to 4 × present levels.

Land Surface Phenologies of the Northern Great Plains: Possible Futures Arising From Land and Climate Change

Science.gov (United States)

Henebry, G. M.; Wimberly, M. C.; Senay, G.; Wang, A.; Chang, J.; Wright, C. R.; Hansen, M. C.

2008-12-01

Land cover change across the Northern Great Plains of North America over the past three decades has been driven by changes in agricultural management (conservation tillage; irrigation), government incentives (Conservation Reserve Program; subsidies to grain-based ethanol), crop varieties (cold-hardy soybean), and market dynamics (increasing world demand). Climate change across the Northern Great Plains over the past three decades has been evident in trends toward earlier warmth in the spring and a longer frost-free season. Together these land and climate changes induce shifts in local and regional land surface phenologies (LSPs). Any significant shift in LSP may correspond to a significant shift in evapotranspiration, with consequences for regional hydrometeorology. We explored possible future scenarios involving land use and climate change in six steps. First, we defined the nominal draw areas of current and future biorefineries in North Dakota, South Dakota, Nebraska, Minnesota, and Iowa and masked those land cover types within the draw areas that were unlikely to change to agricultural use (open water, settlements, forests, etc.). Second, we estimated the proportion of corn and soybean remaining within the masked draw areas using MODIS-derived crop maps. Third, in each draw area, we modified LSPs to simulate crop changes for a control and two treatment scenarios. In the control, we used LSP profiles identified from MODIS Collection 5 NBAR data. In one treatment, we increased the proportion of tallgrass LSPs in the draw areas to represent widespread cultivation of a perennial cellulosic crop, like switchgrass. In a second treatment, we increased the proportion of corn LSPs in the draw areas to represent increased corn cultivation. Fourth, we characterized the seasonal progression of the thermal regime associated with the LSP profiles using MODIS Land Surface Temperature (LST) products. Fifth, we modeled the LSP profile as a quadratic function of accumulated

Biodiversity and Seasonal Changes of the Microbiome in Chernozem Agroecosystem

Science.gov (United States)

Kutovaya, Olga; Chernov, Timofey; Tkhakakhova, Azida; Ivanova, Ekaterina

2016-04-01

Studies of the influence of different agricultural technologies on the soil microbiome are widespread; they are important for understanding the dependence of the microbiome on environmental and soil factors and solution of practical problems related to the control of biochemical processes in soils used in agriculture. The seasonal variability (spring-summer-autumn) of the taxonomic structure of prokaryotic microbiomes in chernozems was studied using sequencing of the 16S rRNA gene. The DNA preparation was used as the matrix for a polymerase chain reaction with the use of a pair of universal primers to the variable region V4 of the 16S rRNA gene - F515 (GTGCCAGCMGCCGCGGTAA) and R806 (GGACTACVSGGGTATCTAAT). The preparation of the samples and sequencing were made on a GS Junior. The samples were collected from the topsoil (0-20 cm) horizons of a long-term fallow and croplands differing in the rates of application of mineral fertilizers (NPK). The results of the weighted UniFrac analysis show that the microbiomes of the fallow and field were distinctly distinguished and that the type of land use significantly affected the structure of the microbial community. The most sensitive to the type of land use were the representatives of the Firmicutes, Gemmatiomonades, and Verrucomicrobia phyla. The type of vegetation and aeration of the root-dwelling soil layer seem to be key factors of this influence. The microbiomes analyzed also differed by seasons: in the autumn samples, they were closer to the spring ones than to the summer ones. This fact evidences that the seasonal differences in the microbiomes are not simple gradual temporal changes; they reflect the influence of some ecological factors transforming the phylogenetic structure of prokaryotic communities. As the seasonal shift was equally expressed in the microbiomes of the field and fallow, it is logical to assume that it was caused by the factors common for two systems of land use. Statistically sensitive to seasonal

The Role of Suomi NPP VIIRS Data in Land Science and Applications.

Science.gov (United States)

Justice, C. O.; Csiszar, I. A.; Roman, M. O.; Vermote, E.

2014-12-01

The current Suomi-NPP mission was designed as a bridging mission to the Joint Polar Satellite System (JPSS) next-generation, operational satellites. The VIIRS instrument on-board Suomi-NPP provides continuity with NASA's Earth Observing System Moderate-resolution Imaging Spectroradiometer (MODIS) observations and a much-needed replacement of the long-serving, operational NOAA Advanced Very High Resolution Radiometer (AVHRR) system, to meet the expanding needs of Earth Science and Applications of Societal Benefit. Post-launch evaluation has proven the instrument to be excellent for land observations and capable of providing measurement continuity with MODIS. This provides a critical contribution to the scientific study of global change. Several regions of the World are undergoing rapid land transformations, driven by economic development and population growth. In addition, changes in climate conditions are resulting in ecosystem responses and changes in land cover and land use. Long-term, systematic observations of the global land surface at coarse resolution enable detection, monitoring and characterization of such changes to the land surface. A suite of Land environmental data records (EDRs) from the VIIRS, are being developed by NOAA to meet operational data needs, primarily for the National Weather Service (e.g., Albedo, Land Surface Temperature, Fractional Vegetation Cover, Surface Type, Snow and Ice Monitoring). Scientists funded by NOAA and NASA, have been evaluating and validating these products. Based on these evaluations, NASA is embarking on a program to develop enhanced and additional products to provide continuity with MODIS to meet the needs of the global change science community. In addition, and as with MODIS, data from the VIIRS can be used as input to a number of practical applications of societal benefit and the associated decision support systems. For example, progress with VIIRS data is being made in the areas of fire and agricultural monitoring

Spatio-Temporal Dynamics of Land-Use and Land-Cover in the Mu Us Sandy Land, China, Using the Change Vector Analysis Technique

Directory of Open Access Journals (Sweden)

Arnon Karnieli

2014-09-01

Full Text Available The spatial extent of desertified vs. rehabilitated areas in the Mu Us Sandy Land, China, was explored. The area is characterized by complex landscape changes that were caused by different drivers, either natural or anthropogenic, interacting with each other, and resulting in multiple consequences. Two biophysical variables, NDVI, positively correlated with vegetation cover, and albedo, positively correlated with cover of exposed sands, were computed from a time series of merged NOAA-AVHRR and MODIS images (1981 to 2010. Generally, throughout the study period, NDVI increased and albedo decreased. Improved understanding of spatial and temporal dynamics of these environmental processes was achieved by using the Change Vector Analysis (CVA technique applied to NDVI and albedo data extracted from four sets of consecutive Landsat images, several years apart. Changes were detected for each time step, as well as over the entire period (1978 to 2007. Four categories of land cover were created—vegetation, exposed sands, water bodies and wetlands. The CVA’s direction and magnitude enable detecting and quantifying finer changes compared to separate NDVI or albedo difference/ratio images and result in pixel-based maps of the change. Each of the four categories has a biophysical meaning that was validated in selected hot-spots, employing very high spatial resolution images (e.g., Ikonos. Selection of images, taking into account inter and intra annual variability of rainfall, enables differentiating between short-term conservancies (e.g., drought and long-term alterations. NDVI and albedo, although comparable to tasseled cap’s brightness and greenness indices, have the advantage of being computed using reflectance values extracted from various Landsat platforms since the early 1970s. It is shown that, over the entire study period, the majority of the Mu Us Sandy Land area remained unchanged. Part of the area (6%, mainly in the east, was under human

Results of agriclimatological studies using multiple satellite sensors like NOAA AVHRR; GMS IR and LANDSAT MSS and TM

International Nuclear Information System (INIS)

Choudhury, A.M.

1990-08-01

Bangladesh Space Research and Remote Sensing Organization (SPARRSO) routinely receives NOAA and GMS imagery and uses them in agrometeorological monitoring, it also uses LANDSAT MSS and TM data for this purpose. Analysis of multiple satellite sensor data shows advantages for high resolution sensors. However, in the ease of crop monitoring, a good correlation has been obtained between results obtained with NOAA AVHRR and LANDSAT MSS for vegetation index. Crop estimation has been made using all kinds of sensors and it has been found that higher resolution data always give more accurate results. (author). 3 refs

GloFAS-Seasonal: Operational Seasonal Ensemble River Flow Forecasts at the Global Scale

Science.gov (United States)

Emerton, Rebecca; Zsoter, Ervin; Smith, Paul; Salamon, Peter

2017-04-01

Seasonal hydrological forecasting has potential benefits for many sectors, including agriculture, water resources management and humanitarian aid. At present, no global scale seasonal hydrological forecasting system exists operationally; although smaller scale systems have begun to emerge around the globe over the past decade, a system providing consistent global scale seasonal forecasts would be of great benefit in regions where no other forecasting system exists, and to organisations operating at the global scale, such as disaster relief. We present here a new operational global ensemble seasonal hydrological forecast, currently under development at ECMWF as part of the Global Flood Awareness System (GloFAS). The proposed system, which builds upon the current version of GloFAS, takes the long-range forecasts from the ECMWF System4 ensemble seasonal forecast system (which incorporates the HTESSEL land surface scheme) and uses this runoff as input to the Lisflood routing model, producing a seasonal river flow forecast out to 4 months lead time, for the global river network. The seasonal forecasts will be evaluated using the global river discharge reanalysis, and observations where available, to determine the potential value of the forecasts across the globe. The seasonal forecasts will be presented as a new layer in the GloFAS interface, which will provide a global map of river catchments, indicating whether the catchment-averaged discharge forecast is showing abnormally high or low flows during the 4-month lead time. Each catchment will display the corresponding forecast as an ensemble hydrograph of the weekly-averaged discharge forecast out to 4 months, with percentile thresholds shown for comparison with the discharge climatology. The forecast visualisation is based on a combination of the current medium-range GloFAS forecasts and the operational EFAS (European Flood Awareness System) seasonal outlook, and aims to effectively communicate the nature of a seasonal

Variation of microorganism concentrations in urban stormwater runoff with land use and seasons.

Science.gov (United States)

Selvakumar, Ariamalar; Borst, Michael

2006-03-01

Stormwater runoff samples were collected from outfalls draining small municipal separate storm sewer systems. The samples were collected from three different land use areas based on local designation (high-density residential, low-density residential and landscaped commercial). The concentrations of microorganisms in the stormwater runoff were found to be similar in magnitude to, but less variable than, those reported in the stormwater National Pollutant Discharge Elimination System (NPDES) database. Microorganism concentrations from high-density residential areas were higher than those associated with low-density residential and landscaped commercial areas. Since the outfalls were free of sanitary wastewater cross-connections, the major sources of microorganisms to the stormwater runoff were most likely from the feces of domestic animals and wildlife. Concentrations of microorganisms were significantly affected by the season during which the samples were collected. The lowest concentrations were observed during winter except for Staphylococcus aureus. The Pearson correlation coefficients among different indicators showed weak linear relationships and the relationships were statistically significant. However, the relationships between indicators and pathogens were poorly correlated and were not statistically significant, suggesting the use of indicators as evidence of the presence of pathogens is not appropriate. Further, the correlation between the concentration of the traditionally monitored indicators (total coliforms and fecal coliforms) and the suggested substitutes (enterococci and E. coli) is weak, but statistically significant, suggesting that historical time series will be only a qualitative indicator of impaired waters under the revised criteria for recreational water quality by the US EPA.

Seasonal prediction of Indian summer monsoon: Sensitivity to ...

Indian Academy of Sciences (India)

trations, land-snow cover and soil moisture, etc. The seasonal ... tested at T85L26 resolution, which is equivalent to .... units, soil columns, and plant functional types (PFT). The ... soil texture. ... monthly rain product TB42 is not used here for the.

Understanding the Seasonal Greenness Trends and Controls in South Asia Using Satellite Based Observations

Science.gov (United States)

Sarmah, S.; Jia, G.; Zhang, A.; Singha, M.

2017-12-01

South Asia (SA) is one of the most remarkable regions in changing vegetation greenness along with its major expansion of agricultural activity, especially irrigated farming. However, SA is predicted to be a vulnerable agricultural regions to future climate changes. The influence of monsoon climate on the seasonal trends and anomalies of vegetation greenness are not well understood in the region which can provide valuable information about climate-ecosystem interaction. This study analyzed the spatio-temporal patterns of seasonal vegetation trends and variability using satellite vegetation indices (VI) including AVHRR Normalized Difference Vegetation Index (NDVI) (1982-2013) and MODIS Enhanced Vegetation Index (EVI) (2000-2013) in summer monsoon (SM) (June-Sept) and winter monsoon (WM) (Dec-Apr) seasons among irrigated cropland (IC), rainfed cropland (RC) and natural vegetation (NV). Seasonal VI variations with climatic factors (precipitation and temperature) and LULC changes have been investigated to identify the forcings behind the vegetation trends and variability. We found that major greening occurred in the last three decades due to the increase in IC productivity noticeably in WM, however, recent (2000-2013) greening trends were lower than the previous decades (1982-1999) in both the IC and RC indicating the stresses on them. The browning trends, mainly concentrated in NV areas were prominent during WM and rigorous since 2000, confirmed from the moderate resolution EVI and LULC datasets. Winter time maximal temperature had been increasing tremendously whereas precipitation trend was not significant over SA. Both the climate variability and LULC changes had integrated effects on the vegetation changes in NV areas specifically in hilly regions. However, LULC impact was intensified since 2000, mostly in north east India. This study also revealed a distinct seasonal variation in spatial distribution of correlation between VI's and climate anomalies over SA

Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

Science.gov (United States)

Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

2010-01-01

Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of

Trends in land surface phenology and atmospheric CO2 seasonality in the Northern Hemisphere terrestrial ecosystems

Science.gov (United States)

Gonsamo, A.; Chen, J. M.

2017-12-01

Northern terrestrial ecosystems have shown global warming-induced advances in start, delays in end, and thus increased lengths of growing season and gross photosynthesis in recent decades. The tradeoffs between seasonal dynamics of two opposing fluxes, CO2 uptake through photosynthesis and release through respiration, determine the influence of the terrestrial ecosystems on the atmospheric CO2 concentration and 13C/12C isotope ratio seasonality. Atmospheric CO2 and 13C/12C seasonality is controlled by vegetation phenology, but is not identical because growth will typically commence some time before and terminate some time after the net carbon exchange changes sign in spring and autumn, respectively. Here, we use 34-year satellite normalized difference vegetation index (NDVI) observations to determine how changes in vegetation productivity and phenology affect both the atmospheric CO2 and 13C/12C seasonality. Differences and similarities in recent trends of CO2 and 13C/12C seasonality and vegetation phenology will be discussed. Furthermore, we use the NDVI observations, and atmospheric CO2 and 13C/12C data to show the trends and variability of the timing of peak season plant activity. Preliminary results show that the peak season plant activity of the Northern Hemisphere extra-tropical terrestrial ecosystems is shifting towards spring, largely in response to the warming-induced advance of the start of growing season. Besides, the spring-ward shift of the peak plant activity is contributing the most to the increasing peak season productivity. In other words, earlier start of growing season is highly linked to earlier arrival of peak of season and higher NDVI. Changes in the timing of peak season plant activity are expected to disrupt the synchrony of biotic interaction and exert strong biophysical feedbacks on climate by modifying the surface albedo and energy budget.

Explaining variations in the diversity of parasitoid assemblages in a biosphere reserve of Mexico: evidence from vegetation, land management and seasonality.

Science.gov (United States)

González-Moreno, A; Bordera, S; Leirana-Alcocer, J; Delfín-González, H; Ballina-Gómez, H S

2017-11-23

Insect fauna biodiversity in natural protected areas has not been thoroughly studied. Therefore, the aim of this work was to assess whether and how vegetation types, land management and seasonality influence the diversity of Ichneumonidae (Hymenoptera) in the Ría Lagartos Biosphere Reserve (Mexico). A sampling programme was conducted using Malaise traps from 2008 to 2009 in three vegetation types, each with two conservation zones (core and buffer zones). Three seasons were considered: rainy, dry and north-winds (isolated storms from November to February). A total of 336 species were identified. Rarefaction and Generalized Linear Model indicated higher species richness and abundance, respectively, in the buffer zone of the dry forest; possible explanations for this finding include the intermediate disturbance hypothesis, wherein diversity can be higher in sites where disturbance is not very frequent or very intense, and the 'enemies hypothesis', wherein structural complexity and high plant diversity favour increased predators or, in this case, parasitoids. Diversity was higher during the rainy season, which may have been due to the higher availability of resources. Vegetation and management had a positive impact on the Coc (attack cocoons and pupae) and Myc (attack concealed larvae living in the fruiting bodies of mushrooms) parasitoid guilds. Members of the Coc guild are generalist parasitoids, which may be favoured in complex vegetation with a high richness of potential hosts and non-hosts. The Myc guild requires certain environmental conditions that promote fungal growth, such as humidity, that is absent in the other vegetation types of savannah and coastal dune scrubland.

Response of Amazon Fires to the 2015/2016 El Niño and Evaluation of a Seasonal Fire Season Severity Forecast

Science.gov (United States)

Randerson, J. T.

2016-12-01

Recent work has established that year-to-year variability in drought and fire within the Amazon responds to a dual forcing from ocean-atmosphere interactions in the tropical Pacific and North Atlantic. Teleconnections between the Pacific and the Amazon are strongest between October and March, when El Niño contributes to below-average precipitation during the wet season. A reduced build-up of soil moisture during the wet season, in turn, may limit water availability and transpiration in tropical forests during the following dry season, lowering surface humidity, drying fuels, and allowing fires to spread more easily through the understory. The delayed influence of soil moisture through this land - atmosphere coupling provides a means to predict fire season severity 3-6 months before the onset of the dry season. With the aim of creating new opportunities for forest conservation, we have developed an experimental seasonal fire forecasting system for the Amazon. The 2016 fire season severity forecast, released in June by UCI and NASA, predicts unusually high risk across eastern Peru, northern Bolivia, and Brazil. Several surface and satellite data streams confirm that El Niño teleconnections had a significant impact on wet season hydrology within the Amazon. Rainfall observations from the Global Precipitation Climatology Centre provided evidence that cumulative precipitation deficits during August-April were 1 to 2 standard deviations below the long-term mean for most of the basin. These observations were corroborated by strong negative terrestrial water storage anomalies measured by the Gravity Recovery and Climate Experiment, and by fluorescence and vegetation index observations from other sensors that indicated elevated canopy stress. By August 3rd, satellite observations showed above average fire activity in most, but not all, forecast regions. Using additional satellite observations that become available later this year, we plan to describe the full spatial and

Satellite view of seasonal greenness trends and controls in South Asia

Science.gov (United States)

Sarmah, Sangeeta; Jia, Gensuo; Zhang, Anzhi

2018-03-01

South Asia (SA) has been considered one of the most remarkable regions for changing vegetation greenness, accompanying its major expansion of agricultural activities, especially irrigated farming. The influence of the monsoon climate on the seasonal trends and anomalies of vegetation greenness is poorly understood in this area. Herein, we used the satellite-based Normalized Difference Vegetation Index (NDVI) to investigate various spatiotemporal patterns in vegetation activity during summer and winter monsoon (SM and WM) seasons and among irrigated croplands (IC), rainfed croplands (RC), and natural vegetation (NV) areas during 1982–2013. Seasonal NDVI variations with climatic factors (precipitation and temperature) and land use and cover changes (LUCC) have also been investigated. This study demonstrates that the seasonal dynamics of vegetation could improve the detailed understanding of vegetation productivity over the region. We found distinct greenness trends between two monsoon seasons and among the major land use/cover classes. Winter monsoons contributed greater variability to the overall vegetation dynamics of SA. Major greening occurred due to the increased productivity over irrigated croplands during the winter monsoon season; meanwhile, browning trends were prominent over NV areas during the same season. Maximum temperatures had been increasing tremendously during the WM season; however, the precipitation trend was not significant over SA. Both the climate variability and LUCC revealed coupled effects on the long term NDVI trends in NV areas, especially in the hilly regions, whereas anthropogenic activities (agricultural advancements) played a pivotal role in the rest of the area. Until now, advanced cultivation techniques have proven to be beneficial for the region in terms of the productivity of croplands. However, the crop productivity is at risk under climate change.

Global Trends in Seasonality of Normalized Difference Vegetation Index (NDVI, 1982–2011

Directory of Open Access Journals (Sweden)

Assaf Anyamba

2013-09-01

Full Text Available A 30-year series of global monthly Normalized Difference Vegetation Index (NDVI imagery derived from the Global Inventory Modeling and Mapping Studies (GIMMS NDVI3g archive was analyzed for the presence of trends in changing seasonality. Using the Seasonal Trend Analysis (STA procedure, over half (56.30% of land surfaces were found to exhibit significant trends. Almost half (46.10% of the significant trends belonged to three classes of seasonal trends (or changes. Class 1 consisted of areas that experienced a uniform increase in NDVI throughout the year, and was primarily associated with forested areas, particularly broadleaf forests. Class 2 consisted of areas experiencing an increase in the amplitude of the annual seasonal signal whereby increases in NDVI in the green season were balanced by decreases in the brown season. These areas were found primarily in grassland and shrubland regions. Class 3 was found primarily in the Taiga and Tundra biomes and exhibited increases in the annual summer peak in NDVI. While no single attribution of cause could be determined for each of these classes, it was evident that they are primarily found in natural areas (as opposed to anthropogenic land cover conversions and that they are consistent with climate-related ameliorations of growing conditions during the study period.

Northern Alaskan land surface response to reduced Arctic sea ice extent

Energy Technology Data Exchange (ETDEWEB)

Higgins, Matthew E. [University of Colorado, Cooperative Institute for Research in Environmental Sciences, Boulder, CO (United States); Cassano, John J. [University of Colorado, Cooperative Institute for Research in Environmental Sciences, Department of Atmospheric and Oceanic Sciences, Boulder, CO (United States)

2012-05-15

With Arctic sea ice extent at near-record lows, an improved understanding of the relationship between sea ice and the land surface is warranted. We examine the land surface response to changing sea ice by first conducting a simulation using the Community Atmospheric Model version 3.1 with end of the twenty-first century sea ice extent. This future atmospheric response is then used to force the Weather and Research Forecasting Model version 3.1 to examine the terrestrial land surface response at high resolution over the North Slope of Alaska. Similar control simulations with twentieth century sea ice projections are also performed, and in both simulations only sea ice extent is altered. In the future sea ice extent experiment, atmospheric temperature increases significantly due to increases in latent and sensible heat flux, particularly in the winter season. Precipitation and snow pack increase significantly, and the increased snow pack contributes to warmer soil temperatures for most seasons by insulating the land surface. In the summer, however, soil temperatures are reduced due to increased albedo. Despite warmer near-surface atmospheric temperatures, it is found that spring melt is delayed throughout much of the North Slope due to the increased snow pack, and the growing season length is shortened. (orig.)

Technical Efficiency of Wet Season Melon Farming

Directory of Open Access Journals (Sweden)

Ananti Yekti

2017-03-01

Full Text Available Melon is one of high-value horticulture commodity which is cultivated widely in Kulon Progo regency. The nature of agricultural products is heavily dependent on the season, so it causes the prices of agricultural products always fluctuated every time. In wet season the price of agricultural products tends to be more expensive. Melon cultivation in wet season provide an opportunity to earn higher profits than in the dry season. The price of agricultural products tends to be more expensive in wet season, thus melon cultivation in wet season prospectively generate high profits. In order to achieve high profitability, melon farming has to be done efficiently. Objective of this study was to 1 determined the factors that influence melon production in wet season 2 measured technical efficiency of melon farming and 3 identified the factors that influanced technical efficiency. Data collected during April – June 2014. Location determined by multistage cluster sampling. 45 samples of farmers who cultivated melon during wet season obtained based on quota sampling technique. Technical efficiency was measured using Cobb-Douglas Stochastic Frontier. The result reveals that 1 land use, quantity of seed, K fertilizer contributed significantly increasing melon production, while N fertilizer decreased melon production significantly 2 technical efficiency indeces ranged from 0.40 to 0.99, with a mean of  0.77; 3 farmer’s experience gave significant influence to technical efficiency of melon farming in wet season.

Multi-Season Regional Analysis of Multi-Species Occupancy: Implications for Bird Conservation in Agricultural Lands in East-Central Argentina

Science.gov (United States)

Goijman, Andrea Paula; Conroy, Michael. J.; Bernardos, Jaime Nicolás; Zaccagnini, María Elena

2015-01-01

Rapid expansion and intensification of agriculture create challenges for the conservation of biodiversity and associated ecosystem services. In Argentina, the total row crop planted area has increased in recent decades with the expansion of soybean cultivation, homogenizing the landscape. In 2003 we started the first long-term, large-scale bird monitoring program in agroecosystems of central Argentina, in portions of the Pampas and Espinal ecoregions. Using data from this program, we evaluated the effect of land use and cover extent on birds between 2003-2012, accounting for imperfect detection probabilities using a Bayesian hierarchical, multi-species and multi-season occupancy model. We tested predictions that species diversity is positively related to habitat heterogeneity, which in intensified agroecosystems is thought to be mediated by food availability; thus the extent of land use and cover is predicted to affect foraging guilds differently. We also infer about ecosystem services provisioning and inform management recommendations for conservation of birds. Overall our results support the predictions. Although many species within each guild responded differently to land use and native forest cover, we identified generalities for most trophic guilds. For example, granivorous gleaners, ground insectivores and omnivores responded negatively to high proportions of soybean, while insectivore gleaners and aerial foragers seemed more tolerant. Habitat heterogeneity would likely benefit most species in an intensified agroecosystem, and can be achieved with a diversity of crops, pastures, and natural areas within the landscape. Although most studied species are insectivores, potentially beneficial for pest control, some guilds such as ground insectivores are poorly represented, suggesting that agricultural intensification reduces ecological functions, which may be recovered through management. Continuation of the bird monitoring program will allow us to continue to

Multi-Season Regional Analysis of Multi-Species Occupancy: Implications for Bird Conservation in Agricultural Lands in East-Central Argentina.

Directory of Open Access Journals (Sweden)

Andrea Paula Goijman

Full Text Available Rapid expansion and intensification of agriculture create challenges for the conservation of biodiversity and associated ecosystem services. In Argentina, the total row crop planted area has increased in recent decades with the expansion of soybean cultivation, homogenizing the landscape. In 2003 we started the first long-term, large-scale bird monitoring program in agroecosystems of central Argentina, in portions of the Pampas and Espinal ecoregions. Using data from this program, we evaluated the effect of land use and cover extent on birds between 2003-2012, accounting for imperfect detection probabilities using a Bayesian hierarchical, multi-species and multi-season occupancy model. We tested predictions that species diversity is positively related to habitat heterogeneity, which in intensified agroecosystems is thought to be mediated by food availability; thus the extent of land use and cover is predicted to affect foraging guilds differently. We also infer about ecosystem services provisioning and inform management recommendations for conservation of birds. Overall our results support the predictions. Although many species within each guild responded differently to land use and native forest cover, we identified generalities for most trophic guilds. For example, granivorous gleaners, ground insectivores and omnivores responded negatively to high proportions of soybean, while insectivore gleaners and aerial foragers seemed more tolerant. Habitat heterogeneity would likely benefit most species in an intensified agroecosystem, and can be achieved with a diversity of crops, pastures, and natural areas within the landscape. Although most studied species are insectivores, potentially beneficial for pest control, some guilds such as ground insectivores are poorly represented, suggesting that agricultural intensification reduces ecological functions, which may be recovered through management. Continuation of the bird monitoring program will allow

A warm-season comparison of WRF coupled to the CLM4.0, Noah-MP, and Bucket hydrology land surface schemes over the central USA

Science.gov (United States)

Van Den Broeke, Matthew S.; Kalin, Andrew; Alavez, Jose Abraham Torres; Oglesby, Robert; Hu, Qi

2017-11-01

In climate modeling studies, there is a need to choose a suitable land surface model (LSM) while adhering to available resources. In this study, the viability of three LSM options (Community Land Model version 4.0 [CLM4.0], Noah-MP, and the five-layer thermal diffusion [Bucket] scheme) in the Weather Research and Forecasting model version 3.6 (WRF3.6) was examined for the warm season in a domain centered on the central USA. Model output was compared to Parameter-elevation Relationships on Independent Slopes Model (PRISM) data, a gridded observational dataset including mean monthly temperature and total monthly precipitation. Model output temperature, precipitation, latent heat (LH) flux, sensible heat (SH) flux, and soil water content (SWC) were compared to observations from sites in the Central and Southern Great Plains region. An overall warm bias was found in CLM4.0 and Noah-MP, with a cool bias of larger magnitude in the Bucket model. These three LSMs produced similar patterns of wet and dry biases. Model output of SWC and LH/SH fluxes were compared to observations, and did not show a consistent bias. Both sophisticated LSMs appear to be viable options for simulating the effects of land use change in the central USA.

Spatial and temporal patterns of land surface fluxes from remotely sensed surface temperatures within an uncertainty modelling framework

Directory of Open Access Journals (Sweden)

M. F. McCabe

2005-01-01

Full Text Available Characterising the development of evapotranspiration through time is a difficult task, particularly when utilising remote sensing data, because retrieved information is often spatially dense, but temporally sparse. Techniques to expand these essentially instantaneous measures are not only limited, they are restricted by the general paucity of information describing the spatial distribution and temporal evolution of evaporative patterns. In a novel approach, temporal changes in land surface temperatures, derived from NOAA-AVHRR imagery and a generalised split-window algorithm, are used as a calibration variable in a simple land surface scheme (TOPUP and combined within the Generalised Likelihood Uncertainty Estimation (GLUE methodology to provide estimates of areal evapotranspiration at the pixel scale. Such an approach offers an innovative means of transcending the patch or landscape scale of SVAT type models, to spatially distributed estimates of model output. The resulting spatial and temporal patterns of land surface fluxes and surface resistance are used to more fully understand the hydro-ecological trends observed across a study catchment in eastern Australia. The modelling approach is assessed by comparing predicted cumulative evapotranspiration values with surface fluxes determined from Bowen ratio systems and using auxiliary information such as in-situ soil moisture measurements and depth to groundwater to corroborate observed responses.

Effects of land-use patterns on in-stream nitrogen in a highly-polluted river basin in Northeast China

International Nuclear Information System (INIS)

Bu, Hongmei; Zhang, Yuan; Meng, Wei; Song, Xianfang

2016-01-01

This study investigated the effects of land-use patterns on nitrogen pollution in the Haicheng River basin in Northeast China during 2010 by conducting statistical and spatial analyses and by analyzing the isotopic composition of nitrate. Correlation and stepwise regressions indicated that land-use types and landscape metrics were correlated well with most river nitrogen variables and significantly predicted them during different sampling seasons. Built-up land use and shape metrics dominated in predicting nitrogen variables over seasons. According to the isotopic compositions of river nitrate in different zones, the nitrogen sources of the river principally originated from synthetic fertilizer, domestic sewage/manure, soil organic matter, and atmospheric deposition. Isotope mixing models indicated that source contributions of river nitrogen significantly varied from forested headwaters to densely populated towns of the river basin. Domestic sewage/manure was a major contributor to river nitrogen with the proportions of 76.4 ± 6.0% and 62.8 ± 2.1% in residence and farmland-residence zones, respectively. This research suggested that regulating built-up land uses and reducing discharges of domestic sewage and industrial wastewater would be effective methods for river nitrogen control. - Highlights: • Land-use types were correlated well with most nitrogen variables over seasons. • Built-up land dominated in predicting nitrogen variables during different seasons. • Shape metrics predicted most nitrogen variables in different seasons. • Nitrogen sources and their contributions were estimated using nitrate isotopes. • Domestic sewage mainly contributed to river nitrogen pollution in residence zone.

Effects of land-use patterns on in-stream nitrogen in a highly-polluted river basin in Northeast China

Energy Technology Data Exchange (ETDEWEB)

Bu, Hongmei, E-mail: buhm2004@163.com [Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101 (China); Zhang, Yuan; Meng, Wei [State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012 (China); Song, Xianfang [Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101 (China)

2016-05-15

This study investigated the effects of land-use patterns on nitrogen pollution in the Haicheng River basin in Northeast China during 2010 by conducting statistical and spatial analyses and by analyzing the isotopic composition of nitrate. Correlation and stepwise regressions indicated that land-use types and landscape metrics were correlated well with most river nitrogen variables and significantly predicted them during different sampling seasons. Built-up land use and shape metrics dominated in predicting nitrogen variables over seasons. According to the isotopic compositions of river nitrate in different zones, the nitrogen sources of the river principally originated from synthetic fertilizer, domestic sewage/manure, soil organic matter, and atmospheric deposition. Isotope mixing models indicated that source contributions of river nitrogen significantly varied from forested headwaters to densely populated towns of the river basin. Domestic sewage/manure was a major contributor to river nitrogen with the proportions of 76.4 ± 6.0% and 62.8 ± 2.1% in residence and farmland-residence zones, respectively. This research suggested that regulating built-up land uses and reducing discharges of domestic sewage and industrial wastewater would be effective methods for river nitrogen control. - Highlights: • Land-use types were correlated well with most nitrogen variables over seasons. • Built-up land dominated in predicting nitrogen variables during different seasons. • Shape metrics predicted most nitrogen variables in different seasons. • Nitrogen sources and their contributions were estimated using nitrate isotopes. • Domestic sewage mainly contributed to river nitrogen pollution in residence zone.

Hydrology of Ranger land application area

International Nuclear Information System (INIS)

McQuade, C.V.

1992-01-01

In 1984 Ranger Uranium Mines (RUM) began assessing the technique of water treatment by land application as a means of reducing the volume of stored water within the Restricted Release Zone. Knowledge of the hydrological characteristics of the treatment site is necessary for optimal day to day and season to season operation of the system and as an input into the assessment of the long-term viability of the site. This paper provides background information on the hydrological requirements for a water treatment site, describes the RUM's water treatment by land application system and summarises the operational statistics and current hydrological knowledge of the site. The general groundwater hydrology of the area comprises a surface soil aquifer overlying a semi-confined aquifer. Drainage of the surface aquifer follows the surface topography along the sandy clays. Vertical permeability ranges between 3 and 12 times greater than horizontal permeability. 7 refs., 2 tabs., 4 figs

Seasonal/Interannual Variations of Carbon Sequestration and Carbon Emission in a Warm-Season Perennial Grassland

OpenAIRE

Deepa Dhital; Tomoharu Inoue; Hiroshi Koizumi

2014-01-01

Carbon sequestration and carbon emission are processes of ecosystem carbon cycling that can be affected while land area converted to grassland resulting in increased soil carbon storage and below-ground respiration. Discerning the importance of carbon cycle in grassland, we aimed to estimate carbon sequestration in photosynthesis and carbon emission in respiration from soil, root, and microbes, for four consecutive years (2007–2010) in a warm-season perennial grassland, Japan. Soil carbon emi...

Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

Science.gov (United States)

Dalecios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

2014-05-01

By considering drought as a hazard, drought types are classified into three categories, namely meteorological or climatological, agrometeorological or agricultural and hydrological drought and as a fourth class the socioeconomic impacts can be considered. This paper addresses agrometeorological drought affecting agriculture within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with the quantification and monitoring of agrometeorological drought, which constitute part of risk identification. For the quantitative assessment of agrometeorological or agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural region of Greece characterized by vulnerable and drought-prone agriculture. The results show that every year there is a seasonal agrometeorological drought with a gradual increase in the areal extent and severity with peaks appearing usually during the summer. Drought monitoring is conducted by monthly remotely sensed VHI images. Drought early warning is developed using empirical relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought, respectively. The two fitted curves offer a seasonal

Rainforest-initiated wet season onset over the southern Amazon.

Science.gov (United States)

Wright, Jonathon S; Fu, Rong; Worden, John R; Chakraborty, Sudip; Clinton, Nicholas E; Risi, Camille; Sun, Ying; Yin, Lei

2017-08-08

Although it is well established that transpiration contributes much of the water for rainfall over Amazonia, it remains unclear whether transpiration helps to drive or merely responds to the seasonal cycle of rainfall. Here, we use multiple independent satellite datasets to show that rainforest transpiration enables an increase of shallow convection that moistens and destabilizes the atmosphere during the initial stages of the dry-to-wet season transition. This shallow convection moisture pump (SCMP) preconditions the atmosphere at the regional scale for a rapid increase in rain-bearing deep convection, which in turn drives moisture convergence and wet season onset 2-3 mo before the arrival of the Intertropical Convergence Zone (ITCZ). Aerosols produced by late dry season biomass burning may alter the efficiency of the SCMP. Our results highlight the mechanisms by which interactions among land surface processes, atmospheric convection, and biomass burning may alter the timing of wet season onset and provide a mechanistic framework for understanding how deforestation extends the dry season and enhances regional vulnerability to drought.

The correlated k-distribution technique as applied to the AVHRR channels

Science.gov (United States)

Kratz, David P.

1995-01-01

Correlated k-distributions have been created to account for the molecular absorption found in the spectral ranges of the five Advanced Very High Resolution Radiometer (AVHRR) satellite channels. The production of the k-distributions was based upon an exponential-sum fitting of transmissions (ESFT) technique which was applied to reference line-by-line absorptance calculations. To account for the overlap of spectral features from different molecular species, the present routines made use of the multiplication transmissivity property which allows for considerable flexibility, especially when altering relative mixing ratios of the various molecular species. To determine the accuracy of the correlated k-distribution technique as compared to the line-by-line procedure, atmospheric flux and heating rate calculations were run for a wide variety of atmospheric conditions. For the atmospheric conditions taken into consideration, the correlated k-distribution technique has yielded results within about 0.5% for both the cases where the satellite spectral response functions were applied and where they were not. The correlated k-distribution's principal advantages is that it can be incorporated directly into multiple scattering routines that consider scattering as well as absorption by clouds and aerosol particles.

Variation and Trends of Landscape Dynamics, Land Surface Phenology and Net Primary Production of the Appalachian Mountains

Energy Technology Data Exchange (ETDEWEB)

Wang, Yeqiao; Zhao, Jianjun; Zhou, Yuyu; Zhang, Hongyan

2012-12-15

The gradients of the Appalachian Mountains in elevations and latitudes provide a unique regional perspective of landscape variations in the eastern United States and a section of the southeastern Canada. This study reveals patterns and trends of landscape dynamics, land surface phenology and ecosystem production along the Appalachian Mountains using time series data from Global Inventory Modeling and Mapping Studies (GIMMS) and AVHRR Global Production Efficiency Model (GloPEM) datasets. We analyzed the spatial and temporal patterns of Normalized Difference Vegetation Index (NDVI), length of growing season (LOS) and net primary production (NPP) of selected ecoregions along the Appalachian Mountains regions. We compared the results out of the Appalachian Mountains regions in different spatial contexts including the North America and the Appalachian Trail corridor area. To reveal latitudinal variations we analyzed data and compared the results between 30°N-40°N and 40°N-50°N latitudes. The result revealed significant decreases in annual peak NDVI in the Appalachian Mountains regions. The trend for the Appalachian Mountains regions was -0.0018 (R2=0.55, P<0.0001) NDVI unit decrease per year during 25 years between 1982 and 2006. The LOS had prolonged 0.3 day yr-1 during 25 years over the Appalachian Mountains regions. The NPP increased by 2.68 gC m-2yr-2 in Appalachian Mountains regions from 1981 to 2000. The comparison with the North America reveals the effects of topography and ecosystem compositions of the Appalachian Mountains. The comparison with the Appalachian Trail corridor area provides a regional mega-transect view of the measured variables.

Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

CSIR Research Space (South Africa)

Marshall, M

2013-03-01

Full Text Available , latent energy (LE: ET energy equivalent) during the rainy season is the primary regulator after solar forcing of energy balance seasonal variability, the strength of which changes signifi- cantly across land cover types (Ramier et al., 2009). At inter... Table 1. Acronyms and their definitions in order of appearance. Acronym Definition ET Evapotranspiration LE Latent Heat LSM Land Surface Model NDVI Normalized Difference Vegetation Index PET Potential Evapotranspiration AMMA African Monsoon...

Hydrologic parameters and land use reflection on water quality at Mun river, Thailand

International Nuclear Information System (INIS)

Akter, A.; Babel, M.S.

2005-01-01

The 'River Basin' is the land area surrounding one river from its headwaters to its mouth whereas the area drained by a river and its tributaries. So that the land use changes and excessive application of nutrients (Nitrogen and Phosphorus) in predominant agricultural river basins may have a great influence on water quality. Here the study area Mun River Basin is approximately of 69,701 km/sup 2/ and in 1994, out of the total basin area 'about 80 percent was covered by agricultural purposes. Also one of the driest parts of Thailand as well as one of the industrialized provinces in Thailand, Nakhon Ratchasima is situated at the upstream of the river. Accordingly the downstream part Ubon Ratchathani seems totally agricultural based area. To get the water quality changing trends due to land use, there are around forty water quality parameters has considered for the last ten years along with the basins hydrological parameters. For this study based on the fifteen years rainfall data, the whole year divided into two seasons namely wet season (May to October) and dry season (November to April). The result shows: (1) most of the physicochemical parameters are high in wet season; (2) heavy metals moreover appear higher at wet season and (3) although the presences of pesticides are very nominal, the higher values are detected at wet season. The conclusion draws for the water quality by having wet season water sampling and then the testing of water samples for selected seven parameters whereas the water samples are collected at a duration of one-week to three-week from April to October 2004. And this short duration analysis shows that the mean value of the nutrient shows not only higher at wet season (May to October) than April's data also exceed the existing Thailand's surface water quality standard. (author)

Estimating the Sensitivity of CLM-Crop to Plant Date and Growing Season Length

Science.gov (United States)

Drewniak, B. A.; Kotamarthi, V. R.

2012-12-01

The Community Land Model (CLM), the land component of the Community Earth System Model (CESM), is designed to estimate the land surface response to climate through simulated vegetation phenology and soil carbon and nitrogen dynamics. Since human influences play a significant role shaping the land surface, the vegetation has been expanded to include agriculture (CLM-Crop) for three crop types: corn, soybean, and spring wheat. CLM-Crop parameters, which define crop phenology, are optimized against AmeriFlux observations of gross primary productivity, net ecosystem exchange, and stored biomass and carbon, for two sites in the U.S. growing corn and soybean. However, there is uncertainty in the measurements and using a small subset of data to determine model parameters makes validation difficult. In order to account for the differences in plant behavior across climate zones, an input dataset is used to define the planting dates and the length of the growing season. In order to improve model performance, and to understand the impacts of uncertainty from the input data, we evaluate the sensitivity of crop productivity and production against planting date and the length of the growing season. First, CLM-Crop is modified to establish plant date based on temperature trends for the previous 10-day period, constrained against the range of observed planting dates. This new climate-based model is compared with the standard fixed plant dates to determine how sensitive the model is to when seeding occurs, and how comparable the climate calculated plant dates are to the fixed dates. Next, the length of the growing season will be revised to account for an alternative climate. Finally, both the climate-based planting and new growth season will be simulated together. Results of the different model runs will be compared to the standard model and to observations to determine the importance of planting date and growing season length on crop productivity and yield.

Land cover mapping of North and Central America—Global Land Cover 2000

Science.gov (United States)

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

Impacts of Land Use on Surface Water Quality in a Subtropical River Basin: A Case Study of the Dongjiang River Basin, Southeastern China

Directory of Open Access Journals (Sweden)

Jiao Ding

2015-08-01

Full Text Available Understanding the relationship between land use and surface water quality is necessary for effective water management. We estimated the impacts of catchment-wide land use on water quality during the dry and rainy seasons in the Dongjiang River basin, using remote sensing, geographic information systems and multivariate statistical techniques. The results showed that the 83 sites can be divided into three groups representing different land use types: forest, agriculture and urban. Water quality parameters exhibited significant variations between the urban-dominated and forest-dominated sites. The proportion of forested land was positively associated with dissolved oxygen concentration but negatively associated with water temperature, electrical conductivity, permanganate index, total phosphorus, total nitrogen, ammonia nitrogen, nitrate nitrogen and chlorophyll-a. The proportion of urban land was strongly positively associated with total nitrogen and ammonia nitrogen concentrations. Forested and urban land use had stronger impacts on water quality in the dry season than in the rainy season. However, agricultural land use did not have a significant impact on water quality. Our study indicates that urban land use was the key factor affecting water quality change, and limiting point-source waste discharge in urban areas during the dry season would be critical for improving water quality in the study area.

Seasonal precipitation patterns along pathways of South American low-level jets and aerial rivers

Science.gov (United States)

Poveda, Germán.; Jaramillo, Liliana; Vallejo, Luisa F.

2014-01-01

We study the seasonal dynamics of the eastern Pacific (CHOCO) and Caribbean low-level jets (LLJ), and aerial rivers (AR) acting on tropical and subtropical South America. Using the ERA-Interim reanalysis (1979-2012), we show that the convergence of both LLJs over the eastern Pacific-western Colombia contributes to the explanation of the region's world-record rainfall. Diverse variables involved in the transport and storage of moisture permit the identification of an AR over northern South America involving a midtropospheric easterly jet that connects the Atlantic and Pacific Oceans across the Andes, with stronger activity in April to August. Other major seasonal AR pathways constitute part of a large gyre originating over the tropical North Atlantic, veering to the southeast over the eastern Andes and reaching regions of northern Argentina and southeastern Brazil. We illustrate the distribution of average seasonal precipitation along the LLJs and AR pathways with data from the Tropical Rainfall Measuring Mission (1998-2011), combined with considerations of CAPE, topography, and land cover. In addition, the theory of the biotic pump of atmospheric moisture (BiPAM) is tested at seasonal time scales, and found to hold in 8 out of 12 ARs, and 22 out of 32 forest-covered tracks (64% in distance) along the ARs. Deviations from BiPAM's predictions of rainfall distribution are explained by the effects of topography, orography, and land cover types different from forests. Our results lend a strong observational support to the BiPAM theory at seasonal time scales over South American forested flat lands.

Retrieval of the Land Surface Reflectance for Landsat-8 and Sentinel-2 and its validation.

Science.gov (United States)

Roger, J. C.; Vermote, E.; Skakun, S.; Franch, B.; Holben, B. N.; Justice, C. O.

2017-12-01

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and a key parameter in the understanding of the land-surface-climate processes. For 25 years, Vermote and al. develop atmospheric corrections methods to define a land surface reflectance product for various satellites (AVHRR, MODIS, VIIRS…). This presentation highlights the algorithms developed both for Landsant-8 and Sentinel-2. We also emphasize the validation of the "Land surface reflectance" satellite products, which is a very important step to be done. For that purpose, we compared the surface reflectance products to a reference determined by using the accurate radiative transfer code 6S and very detailed measurements of the atmosphere obtained over the AERONET network (which allows to test for a large range of aerosol characteristics); formers being important inputs for atmospheric corrections. However, the application of this method necessitates the definition of a very detailed protocol for the use of AERONET data especially as far as size distribution and absorption are concerned, so that alternative validation methods or protocols could be compared. We describe here the protocol we have been working on based on our experience with the AERONET data and its application to Landsat-8 and Sentinel-2). We also derive a detailed error budget in relation to this approach. For a mean loaded atmosphere, t550 less than 0.25, the maximum uncertainty is 0.0025 corresponding to a relative uncertainty (in the RED channels): U 0.10, and 1% rsurf > 0.04.

CHANGE DETECTION IN LAND-USE AND LAND-COVER DYNAMICS AT A REGIONAL SCALE FROM MODIS TIME-SERIES IMAGERY

Directory of Open Access Journals (Sweden)

Y. Setiawan

2012-07-01

Full Text Available Remote sensing has long been used as a means of detecting and classifying changes on the land. Analysis of multi-year time series of land surface attributes and their seasonal change indicates a complexity of land use land cover change (LULCC. This paper explores the temporal complexity of land change considering temporal vegetation dynamics, in other words, distinguishing the changes regarding to their properties in long-term image analysis. This study is based on the hypothesis that land cover might be dynamics; however, consistent land use has a typical, distinct and repeated temporal pattern of vegetation index inter-annually. Therefore, pixels represent a change when the inter-annual temporal dynamics is changed. We analysed the dynamics pattern of long-term image data of wavelet-filtered MODIS EVI from 2001 to 2007. The change of temporal vegetation dynamics was detected by differentiating distance between two successive annual EVI patterns. Moreover, we defined the type of changes using the clustering method, which were then validated by ground check points and secondary data sets.

Climate-driven seasonal geocenter motion during the GRACE period

NARCIS (Netherlands)

Zhang, Hongyue; Sun, Y.

2018-01-01

Annual cycles in the geocenter motion time series are primarily driven by mass changes in the Earth’s hydrologic system, which includes land hydrology, atmosphere, and oceans. Seasonal variations of the geocenter motion have been reliably determined according to Sun et al. (J Geophys Res Solid

Land use determinants of small mammal abundance and distribution in a plague endemic area of Lushoto District, Tanzania.

Science.gov (United States)

Hieronimo, Proches; Kimaro, Didas N; Kihupi, Nganga I; Gulinck, Hubert; Mulungu, Loth S; Msanya, Balthazar M; Leirs, Herwig; Deckers, Jozef A

2014-07-01

Small mammals are considered to be involved in the transmission cycle of bubonic plague, still occurring in different parts of the world, including the Lushoto District in Tanzania. The objective of this study was to determine the relationship between land use types and practices and small mammal abundance and distribution. A field survey was used to collect data in three landscapes differing in plague incidences. Data collection was done both in the wet season (April-June 2012) and dry season (August-October 2012). Analysis of variance and Boosted Regression Trees (BRT) modelling technique were used to establish the relationship between land use and small mammal abundance and distribution. Significant variations (p ≤ 0.05) of small mammal abundance among land use types were identified. Plantation forest with farming, natural forest and fallow had higher populations of small mammals than the other aggregated land use types. The influence of individual land use types on small mammal abundance level showed that, in both dry and wet seasons, miraba and fallow tended to favour small mammals' habitation whereas land tillage practices had the opposite effect. In addition, during the wet season crop types such as potato and maize appeared to positively influence the distribution and abundance of small mammals which was attributed to both shelter and food availability. Based on the findings from this study it is recommended that future efforts to predict and map spatial and temporal human plague infection risk at fine scale should consider the role played by land use and associated human activities on small mammal abundance and distribution.

Parasites of edible land snails in Edo State, Nigeria

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Igbinosa I. B.

2016-12-01

Full Text Available Land snails are sources of protein to man and are hosts to a number of parasites. It is imperative that the roles of the snail hosts and parasites are clearly defined. Before then however, the parasites of the different land snails collected in any locality should be identified. Land snails were collected in the wild in both dry and wet seasons. The internal organs and the faeces were examined for the presence of parasite. In the rainy season of 2015, a total of 272 snails were collected across four major towns (Benin, Uromi, Ekpoma and Auchi in Edo State, Nigeria, while in the dry season, fewer snails (n=91 were handpicked. The snail species seen are: Achatina achatina (Linnaeus, 1758, Achatina fulica (Férussac, 1821, Acharchatina marginata (Swainson, 1982, Limicolaria aurora (Jay, 1839, L. flammea (Müller, 1774 and Limicolariopsis spp. The larvae of Strongyloides stercoralis were isolated from the various snail species with overall prevalence of 54.04 %. Snails positive with Alaria mesocercariae were L. aurora, L. flammea and Limicolariopsis spp. Additionally, few L. flammea were positive of the cercariae of Drocoelium dedriticum. Meanwhile, some samples of A. fulica harboured larvae of Angiostrongylus cantonesis, sporocysts of Fasciola gigantica and Schistosoma mansoni. Therefore, these edible snails could pose serious health hazard to man and animals by serving as a possible alternative parasite transmission route.

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 biomass and 1-km2 Advanced Very High Resolution Radiometer (AVHRR) NDVI in Kruger National Park, South Africa K. J. WESSELS*{, S. D. PRINCE{, N. ZAMBATIS{, S. MACFADYEN{, P. E. FROST§" and D. VAN ZYL§ {Department of Geography, University of Maryland... production (Prince and Justice 1991, Tucker et al. 1991a,b, Myneni et al. *Corresponding author. Email: wessels@geog.umd.edu International Journal of Remote Sensing Vol. 27, No. 5, 10 March 2006, 951–973 International Journal of Remote Sensing ISSN 0143...

The Effect of Agricultural Growing Season Change on Market Prices in Africa

Science.gov (United States)

deBeurs, K.M.; Brown, M. E.

2013-01-01

to plan effective adaptation strategies. Remote sensing data can also provide some understanding of the spatial extent of these changes and whether they are likely to continue. Given the agricultural nature of most economies on the African continent, agricultural production continues to be a critical determinant of both food security and economic growth (Funk and Brown, 2009). Crop phenological parameters, such as the start and end of the growing season, the total length of the growing season, and the rate of greening and senescence are important for planning crop management, crop diversification, and intensification. The World Food Summit of 1996 defined food security as: "when all people at all times have access to sufficient, safe, nutritious food to maintain a healthy and active life". Food security roughly depends on three factors: 1) availability of food; 2) access to food and 3) appropriate use of food, as well as adequate water and sanitation. The first factor is dependent on growing conditions and weather and climate. In a previous paper we have investigated this factor by evaluating the effect of large scale climate oscillation on land surface phenology (Brown et al., 2010). We found that all areas in Africa are significantly affected by at least one type of large scale climate oscillations and concluded that these somewhat predictable oscillations could perhaps be used to forecast agricultural production. In addition, we have evaluated changes in agricultural land surface phenology over time (Brown et al., 2012). We found that land surface phenology models, which link large-scale vegetation indices with accumulated humidity, could successfully predict agricultural productivity in several countries around the world. In this chapter we are interested in the effect of variability in peak timing of the growing season, or phenology, on the second factor of food security, food access. In this chapter we want to determine if there is a link between market prices

Effects of Climate and land use on diversity, prevalence, and seasonal transmission of avian hematozoa in American Samoa

Science.gov (United States)

Atkinson, Carter T.; Utuzurrum, Ruth B.; Seamon, Joshua O.; Schmaedick, Mark A.; Lapointe, Dennis; Apelgren, Chloe; Egan, Ariel N.; Watcher-Weatherwax, William

2016-01-01

The indigenous forest birds of American Samoa are increasingly threatened by changing patterns of rainfall and temperature that are associated with climate change as well as environmental stressors associated with agricultural and urban development, invasive species, and new introductions of avian diseases and disease vectors. Long term changes in their distribution, diversity, and population sizes could have significant impacts on the ecological integrity of the islands because of their critical role as pollinators and seed dispersers. We documented diversity of vector borne parasites on Tutuila and Ta‘u Islands over a 10-year period to expand earlier observations of Plasmodium, Trypanosoma, and filarial parasites, to provide better parasite identifications, and to create a better baseline for detecting new parasite introductions. We also identified potential mosquito vectors of avian Plasmodium and Trypanosoma, determined whether land clearing and habitat alterations associated with subsistence farming within the National Park of American Samoa can influence parasite prevalence, and determined whether parasite prevalence is correlated with seasonal changes in rainfall, temperature and wind speed.

Environmental, land cover and land use constraints on the distributional patterns of anurans: Leptodacylus species (Anura, Leptodactylidae from Dry Chaco

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Regina Gabriela Medina

2016-11-01

Full Text Available Subtropical dry forests are among the most vulnerable biomes to land transformation at a global scale. Among them, the Dry Chaco suffers an accelerated change due to agriculture expansion and intensification. The Dry Chaco ecoregion is characterized by high levels of endemisms and species diversity, which are the result of a variety of climates and reliefs, allowing a wide variety of environments. The amphibian group exhibits a high richness in the Dry Chaco, which has been barely studied in relation to land cover changes. We used ecological niche models (ENMs to assess the potential geographic distribution of 10 Leptodactylus species (Anura, Leptodactylidae, which are mainly distributed within the Dry Chaco. We characterized these distributions environmentally, analyzed their overlap with land cover classes, and assessed their diversity of ecoregions. Also, we evaluated how these species potential distribution is affected by the transformation of land, and quantified the proportional area of the potential distribution in protected areas. We found that temperature seasonality is the main constraint to the occurrence of the species studied, whose main habitats are savannas, grasslands and croplands. The main threats to these species are the effects of climate change over spatial patterns of seasonality, which could affect their breeding and reproduction mode; the loss of their natural habitat; the exposure to contaminants used by intensive agriculture and their underrepresentation in protected areas.

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

Science.gov (United States)

Riffler, M.; Wunderle, S.

2014-05-01

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 were

Quantifying outdoor water consumption of urban land use/land cover: sensitivity to drought.

Science.gov (United States)

Kaplan, Shai; Myint, Soe W; Fan, Chao; Brazel, Anthony J

2014-04-01

Outdoor water use is a key component in arid city water systems for achieving sustainable water use and ensuring water security. Using evapotranspiration (ET) calculations as a proxy for outdoor water consumption, the objectives of this research are to quantify outdoor water consumption of different land use and land cover types, and compare the spatio-temporal variation in water consumption between drought and wet years. An energy balance model was applied to Landsat 5 TM time series images to estimate daily and seasonal ET for the Central Arizona Phoenix Long-Term Ecological Research region (CAP-LTER). Modeled ET estimations were correlated with water use data in 49 parks within CAP-LTER and showed good agreement (r² = 0.77), indicating model effectiveness to capture the variations across park water consumption. Seasonally, active agriculture shows high ET (>500 mm) for both wet and dry conditions, while the desert and urban land cover types experienced lower ET during drought (<300 mm). Within urban locales of CAP-LTER, xeric neighborhoods show significant differences from year to year, while mesic neighborhoods retain their ET values (400-500 mm) during drought, implying considerable use of irrigation to sustain their greenness. Considering the potentially limiting water availability of this region in the future due to large population increases and the threat of a warming and drying climate, maintaining large water-consuming, irrigated landscapes challenges sustainable practices of water conservation and the need to provide amenities of this desert area for enhancing quality of life.

How reliable is the offline couple of WRF and VIC model? And how does high quality land cover data impact the VIC model simulation?

Science.gov (United States)

Tang, C.; Dennis, R. L.

2012-12-01

First, the ability of the offline coupling of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model to produce hydrological and climate variables was evaluated. The performance of the offline couple of WRF and VIC was assessed with respect to key simulated variables through a comparison with the calibrated VIC model simulation. A spatiotemporal comparison of the simulated evaporation (ET), soil moisture (SM), runoff, and baseflow produced by the VIC calibrated run (base data) and by the offline coupling run was conducted. The results showed that the offline couple of VIC with WRF was able to achieve good agreement in the simulation of monthly and daily soil moisture, and monthly evaporation. This suggests the VIC coupling should function without causing a large change in the moisture budget. However, the offline coupling showed most disagreement in daily and monthly runoff, and baseflow which is related to errors in WRF precipitation. Second, the sensitivity of the VIC model to the land cover was assessed by performing a sensitivity simulation using the National Land Cover Database (NLCD) instead of the older NLDAS/AVHRR data. Improved land cover is shown to achieve more accurate simulation of the streamflow.

Aerosol direct effect on solar radiation over the eastern Mediterranean Sea based on AVHRR satellite measurements

Science.gov (United States)

Georgakaki, Paraskevi; Papadimas, Christos D.; Hatzianastassiou, Nikos; Fotiadi, Aggeliki; Matsoukas, Christos; Stackhouse, Paul; Kanakidou, Maria; Vardavas, Ilias M.

2017-04-01

Despite the improved scientific understanding of the direct effect of aerosols on solar radiation (direct radiative effect, DRE) improvements are necessary, for example regarding the accuracy of the magnitude of estimated DREs and their spatial and temporal variability. This variability cannot be ensured by in-situ surface and airborne measurements, while it is also relatively difficult to capture through satellite observations. This becomes even more difficult when complete spatial coverage of extended areas is required, especially concerning areas that host various aerosol types with variable physico-chemical and optical aerosol properties. Better assessments of aerosol DREs are necessary, relying on aerosol optical properties with high spatial and temporal variation. The present study aims to provide a refined, along these lines, assessment of aerosol DREs over the eastern Mediterranean (EM) Sea, which is a key area for aerosol studies. Daily DREs are computed for 1˚ x1˚ latitude-longitude grids with the FORTH detailed spectral radiation transfer model (RTM) using input data for various atmospheric and surface parameters, such as clouds, water vapor, ozone and surface albedo, taken from the NASA-Langley Global Earth Observing System (GEOS) database. The model spectral aerosol optical depth (AOD), single scattering albedo and asymmetry parameter are taken from the Global Aerosol Data Set and the NOAA Climate Data Record (CDR) version 2 of Advanced Very High resolution Radiometer (AVHRR) AOD dataset which is available over oceans at 0.63 microns and at 0.1˚ x0.1˚ . The aerosol DREs are computed at the surface, the top-of-atmosphere and within the atmosphere, over the period 1985-1995. Preliminary model results for the period 1990-1993 reveal a significant spatial and temporal variability of DREs over the EM Sea, for example larger values over the Aegean and Black Seas, surrounded by land areas with significant anthropogenic aerosol sources, and over the

Remotely Sensed Northern Vegetation Response to Changing Climate: Growing Season and Productivity Perspective

Science.gov (United States)

Ganguly, S.; Park, Taejin; Choi, Sungho; Bi, Jian; Knyazikhin, Yuri; Myneni, Ranga

2016-01-01

Vegetation growing season and maximum photosynthetic state determine spatiotemporal variability of seasonal total gross primary productivity of vegetation. Recent warming induced impacts accelerate shifts on growing season and physiological status over Northern vegetated land. Thus, understanding and quantifying these changes are very important. Here, we first investigate how vegetation growing season and maximum photosynthesis state are evolved and how such components contribute on inter-annual variation of seasonal total gross primary productivity. Furthermore, seasonally different response of northern vegetation to changing temperature and water availability is also investigated. We utilized both long-term remotely sensed data to extract larger scale growing season metrics (growing season start, end and duration) and productivity (i.e., growing season summed vegetation index, GSSVI) for answering these questions. We find that regionally diverged growing season shift and maximum photosynthetic state contribute differently characterized productivity inter-annual variability and trend. Also seasonally different response of vegetation gives different view of spatially varying interaction between vegetation and climate. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation to changing climate.

Pairing FLUXNET sites to validate model representations of land-use/land-cover change

Science.gov (United States)

Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.

2018-01-01

Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

Diurnal and seasonal DOC and POC variability in the land-locked sea

Directory of Open Access Journals (Sweden)

Beata Szymczycha

2017-07-01

Full Text Available Organic matter is a minor yet important component of the marine environment. The aim of this study was to investigate the diurnal and seasonal changes in dissolved and particulate organic carbon (DOC and POC, respectively. Thus, DOC and POC as well as chlorophyll a (Chl a, δ13C, NO3−, NO2−, NH4+, PO43−, salinity, pH, and temperature were regularly measured in samples collected for 24 h (2-h resolution in the Gdańsk Deep (54°44.730′N, 19°08.531′E at three water depths (1, 10, and 40 m during sampling campaigns in 2011 (May, 2014 (May, and 2015 (January, March, May, July, September, November. Seasonal variations in DOC and POC followed the seasonality of Chl a (proportional trend and nutrients (reverse trend concentrations. Diurnal oscillations were detected in six out of the eight measurement series. The strongest diurnal variability in both POC and DOC occurred in May 2011 and March 2015, when phytoplankton activity was highest (high Chl a. The surprisingly low δ13C values (range: −28‰ to −24‰ measured over the course of the study revealed the gaps in our knowledge of the isotopic characteristics of terrestrial- vs. marine-derived particulate organic matter.

Analyzing the Relative Linkages of Land Use and Hydrologic Variables with Urban Surface Water Quality using Multivariate Techniques

Science.gov (United States)

Ahmed, S.; Abdul-Aziz, O. I.

2015-12-01

We used a systematic data-analytics approach to analyze and quantify relative linkages of four stream water quality indicators (total nitrogen, TN; total phosphorus, TP; chlorophyll-a, Chla; and dissolved oxygen, DO) with six land use and four hydrologic variables, along with the potential external (upstream in-land and downstream coastal) controls in highly complex coastal urban watersheds of southeast Florida, U.S.A. Multivariate pattern recognition techniques of principle component and factor analyses, in concert with Pearson correlation analysis, were applied to map interrelations and identify latent patterns of the participatory variables. Relative linkages of the in-stream water quality variables with their associated drivers were then quantified by developing dimensionless partial least squares (PLS) regression model based on standardized data. Model fitting efficiency (R2=0.71-0.87) and accuracy (ratio of root-mean-square error to the standard deviation of the observations, RSR=0.35-0.53) suggested good predictions of the water quality variables in both wet and dry seasons. Agricultural land and groundwater exhibited substantial controls on surface water quality. In-stream TN concentration appeared to be mostly contributed by the upstream water entering from Everglades in both wet and dry seasons. In contrast, watershed land uses had stronger linkages with TP and Chla than that of the watershed hydrologic and upstream (Everglades) components for both seasons. Both land use and hydrologic components showed strong linkages with DO in wet season; however, the land use linkage appeared to be less in dry season. The data-analytics method provided a comprehensive empirical framework to achieve crucial mechanistic insights into the urban stream water quality processes. Our study quantitatively identified dominant drivers of water quality, indicating key management targets to maintain healthy stream ecosystems in complex urban-natural environments near the coast.

Surface ozone seasonality under global change: Influence from dry deposition and isoprene emissions at northern mid-latitudes

Science.gov (United States)

Clifton, O.; Paulot, F.; Fiore, A. M.; Horowitz, L. W.; Malyshev, S.; Shevliakova, E.; Correa, G. J. P.; Lin, M.

2017-12-01

Identifying the contributions of nonlinear chemistry and transport to observed surface ozone seasonal cycles over land using global models relies on an accurate representation of ozone uptake by vegetation (dry deposition). It is well established that in the absence of ozone precursor emission changes, a warming climate will increase surface ozone in polluted regions, and that a rise in temperature-dependent isoprene emissions would exacerbate this "climate penalty". However, the influence of changes in ozone dry deposition, expected to evolve with climate and land use, is often overlooked in air quality projections. With a new scheme that represents dry deposition within the NOAA GFDL dynamic vegetation land model (LM3) coupled to the NOAA GFDL atmospheric chemistry-climate model (AM3), we simulate the impact of 21st century climate and land use on ozone dry deposition and isoprene emissions. This dry deposition parameterization is a version of the Wesely scheme, but uses parameters explicitly calculated by LM3 that respond to climate and land use (e.g., stomatal conductance, canopy interception of water, leaf area index). The parameterization includes a nonstomatal deposition dependence on humidity. We evaluate climatological present-day seasonal cycles of ozone deposition velocities and abundances with those observed at northern mid-latitude sites. With a set of 2010s and 2090s decadal simulations under a high climate warming scenario (RCP8.5) and a sensitivity simulation with well-mixed greenhouse gases following RCP8.5 but air pollutants held at 2010 levels (RCP8.5_WMGG), we examine changes in surface ozone seasonal cycles. We build on our previous findings, which indicate that strong reductions in anthropogenic NOx emissions under RCP8.5 cause the surface ozone seasonal cycle over the NE USA to reverse, shifting from a summer peak at present to a winter peak by 2100. Under RCP8.5_WMGG, we parse the separate effects of climate and land use on ozone dry

Land, Cryosphere, and Nighttime Environmental Products from Suomi NPP VIIRS: Overview and Status

Science.gov (United States)

Roman, Miguel O.; Justice, Chris; Csiszar, Ivan

2014-01-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-orbiting Partnership (S-NPP: http://npp.gsfc.nasa.gov/). VIIRS was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer (AVHRR) and provide observation continuity with NASA's Earth Observing System's (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA and NOAA funded scientists have been working to evaluate the instrument performance and derived products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the former National Polar-orbiting Environmental Satellite System (NPOESS). The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs and providing MODIS data product continuity. This paper will present to-date findings of the NASA Science Team's evaluation of the VIIRS Land and Cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization (http://viirsland.gsfc.nasa.gov/index.html). The paper will also discuss new capabilities being developed at NASA's Land Product Evaluation and Test Element (http://landweb.nascom.nasa.gov/NPP_QA/); including downstream data and products derived from the VIIRS Day/Night Band (DNB).

Characterization of the Cloud-Topped Boundary Layer at the Synoptic Scale Using AVHRR Observations during the SEMAPHORE Experiment.

Science.gov (United States)

Mathieu, A.; Sèze, G.; Lahellec, A.; Guerin, C.; Weill, A.

2003-12-01

Satellite platforms NOAA-11 and -12 Advanced Very High Resolution Radiometer (AVHRR) data are used during the daytime to study large sheets of stratocumulus over the North Atlantic Ocean. The application concerns an anticyclonic period of the Structure des Echanges Mer Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherché Expérimentale (SEMAPHORE) campaign (10 17 November 1993). In the region of interest, the satellite images are recorded under large solar zenith angles. Extending the SEMAPHORE area, a region of about 3000 × 3000 km2 is studied to characterize the atmospheric boundary layer. A statistical cloud classification method is applied to discriminate for low-level and optically thick clouds. For AVHRR pixels covered with thick clouds, brightness temperatures are used to evaluate the boundary layer cloud-top temperature (CTT). The objective is to obtain accurate CTT maps for evaluation of a global model. In this application, the full-resolution fields are reduced to match model grid size. An estimate of overall temperature uncertainty associated with each grid point is also derived, which incorporates subgrid variability of the fields and quality of the temperature retrieval. Results are compared with the SEMAPHORE campaign measurements. A comparison with “DX” products obtained with the same dataset, but at lower resolution, is also presented. The authors claim that such instantaneous CTT maps could be as intensively used as classical SST maps, and both could be efficiently complemented with gridpoint error-bar maps. They may be used for multiple applications: (i) to provide a means to improve numerical weather prediction and climatological reanalyses, (ii) to represent a boundary layer global characterization to analyze the synoptic situation of field experiments, and (iii) to allow validation and to test development of large-scale and mesoscale models.

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)...

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)...

Impact of Soil Moisture Assimilation on Land Surface Model Spin-Up and Coupled LandAtmosphere Prediction

Science.gov (United States)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Lawston, P.

2016-01-01

Advances in satellite monitoring of the terrestrial water cycle have led to a concerted effort to assimilate soil moisture observations from various platforms into offline land surface models (LSMs). One principal but still open question is that of the ability of land data assimilation (LDA) to improve LSM initial conditions for coupled short-term weather prediction. In this study, the impact of assimilating Advanced Microwave Scanning Radiometer for EOS (AMSR-E) soil moisture retrievals on coupled WRF Model forecasts is examined during the summers of dry (2006) and wet (2007) surface conditions in the southern Great Plains. LDA is carried out using NASAs Land Information System (LIS) and the Noah LSM through an ensemble Kalman filter (EnKF) approach. The impacts of LDA on the 1) soil moisture and soil temperature initial conditions for WRF, 2) land-atmosphere coupling characteristics, and 3) ambient weather of the coupled LIS-WRF simulations are then assessed. Results show that impacts of soil moisture LDA during the spin-up can significantly modify LSM states and fluxes, depending on regime and season. Results also indicate that the use of seasonal cumulative distribution functions (CDFs) is more advantageous compared to the traditional annual CDF bias correction strategies. LDA performs consistently regardless of atmospheric forcing applied, with greater improvements seen when using coarser, global forcing products. Downstream impacts on coupled simulations vary according to the strength of the LDA impact at the initialization, where significant modifications to the soil moisture flux- PBL-ambient weather process chain are observed. Overall, this study demonstrates potential for future, higher-resolution soil moisture assimilation applications in weather and climate research.

Hydrological changes impacts on annual runoff distribution in seasonally dry basins

Science.gov (United States)

Viola, F.; Caracciolo, D.; Feng, X.

2017-12-01

Runoff is expected to be modified in the next future by climate change as well as by land use change. Given its importance for water supply and ecosystem functioning, it is therefore imperative to develop adaptation strategies and new policies for regional water resources management and planning. To do so, the identification and attribution of natural flow regime shifts as a result of climate and land use changes are of crucial importance. In this context, the Budyko's curve has begun to be widely adopted to separate the contributions of climate and land use changes to the variation of runoff over long-term periods by using the multi-year averages of hydrological variables. In this study, a framework based on Fu's equation is proposed and applied to separate the impacts of climate and land use changes on the future annual runoff distribution in seasonally dry basins, such as those in Mediterranean climates. In particular, this framework improves a recently developed method to obtain annual runoff probability density function (pdf) in seasonally dry basins from annual rainfall and potential evapotranspiration statistics, and from knowledge of the Fu's equation parameter ω. The effect of climate change has been taken into account through the variation of the first order statistics of annual rainfall and potential evapotranspiration, consistent with general circulation models' outputs, while the Fu's equation parameter ω has been changed to represent land use change. The effects of the two factors of change (i.e., climate and land use) on the annual runoff pdf have been first independently and then jointly analyzed, by reconstructing the annual runoff pdfs for the current period and, based on likely scenarios, within the next 100 years. The results show that, for large basins, climate change is the dominant driver of the decline in annual runoff, while land use change is a secondary but important factor.

Simulation of Soil Frost and Thaw Fronts Dynamics with Community Land Model 4.5

Science.gov (United States)

Gao, J.; Xie, Z.

2016-12-01

Freeze-thaw processes in soils, including changes in frost and thaw fronts (FTFs) , are important physical processes. The movement of FTFs affects soil water and thermal characteristics, as well as energy and water exchanges between land surface and the atmosphere, and then the land surface hydrothermal process. In this study, a two-directional freeze and thaw algorithm for simulating FTFs is incorporated into the community land surface model CLM4.5, which is called CLM4.5-FTF. The simulated FTFs depth and soil temperature of CLM4.5-FTF compared well with the observed data both in D66 station (permafrost) and Hulugou station (seasonally frozen soil). Because the soil temperature profile within a soil layer can be estimated according to the position of FTFs, CLM4.5 performed better in soil temperature simulation. Permafrost and seasonally frozen ground conditions in China from 1980 to 2010 were simulated using the CLM4.5-FTF. Numerical experiments show that the spatial distribution of simulated maximum frost depth by CLM4.5-FTF has seasonal variation obviously. Significant positive active-layer depth trends for permafrost regions and negative maximum freezing depth trends for seasonal frozen soil regions are simulated in response to positive air temperature trends except west of Black Sea.

Consideration of land-use and land-cover changes in the projection of climate extremes over North America by the end of the twenty-first century

Science.gov (United States)

Alexandru, Adelina

2018-03-01

Changes in the essential climate extremes indices and surface variables for the end of the twenty-first century are assessed in this study based on two transient climate change simulations, with and without land-use and land-cover changes (LULCC), but identical atmospheric forcing. The two simulations are performed with the 5th generation of the Canadian Regional Climate Model (CRCM5) driven by the Canadian Earth System Model for the (2006-2100)-Representative Concentration Pathway 4.5 (RCP4.5) scenario. For the simulation with LULCC, land-cover data sets are taken from the global change assessment model (GCAM) representing the RCP4.5 scenario for the period 2006-2100. LULCC in RCP4.5 scenario suggest significant reduction in cultivated land (e.g. Canadian Prairies and Mississippi basin) due to afforestation. CRCM5 climate projections imply a general warming by the end of the twenty-first century, especially over the northern regions in winter. CRCM5 projects more warm spell-days per year over most areas of the continent, and implicitly more summer days and tropical nights at the expense of cold-spell, frost and ice days whose number is projected to decrease by up to 40% by the end of the twenty-first century with respect to the baseline period 1971-2000. Most land areas north of 45°N, in all seasons, as well as the southeastern United States in summer, exhibit increases in mean precipitation under the RCP4.5 scenario. In contrast, central parts of the continent in summer and much of Mexico in all seasons show reduced precipitation. In addition, large areas of North America exhibit changes of 10 to 40% (depending on the season and geographical location) in the number of heavy precipitation days. Results also suggest that the biogeophysical effects of LULCC on climate, assessed through differences between the two simulations, lead to warmer regional climates, especially in winter. The investigation of processes leading to this response shows high sensitivity of the

Seasonal and Interannual Variation in Energy Balance in the Semiarid Grassland Area of China

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Qun’ou Jiang

2015-01-01

Full Text Available Near surface energy budget changes have been proved to be induced by the land cover conversion through changing the surface physical properties, which can further impact the regional climate change. This study applies the DLS model to simulate the land cover under the business as usual (BAU scenario and then analyses the seasonal and interannual variation of energy balance in the semiarid grassland area of China based on the simulated land cover with the Weather Research and Forecasting (WRF model. The results indicate that the grassland will show a growing trend under the BAU scenario. Downward long wave radiation and downward short wave radiation will all have small-scale increase with time going by, while the surface net radiation will decrease from 2030 to 2050. However, there is obvious seasonal variation. Summer has the highest downward long wave radiation and downward short wave radiation, followed by spring and autumn. The lowest are in winter. As for the net surface radiation, there is obvious decrease in southeast of study area due to returning cropland to grassland. Those research conclusions can offer valuable information for the land use planning and relieving the effects of land cover change on climate change at the semiarid grassland area.

The potential of intercropping food crops and energy crop to improve productivity of a degraded agriculture land in arid tropics

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I.K.D. Jaya

2014-04-01

Full Text Available Degraded agricultural lands in the arid tropics have low soil organic carbon (SOC and hence low productivity. Poor farmers that their livelihoods depend highly on these types of lands are suffering. Cropping strategies that are able to improve the soil productivity are needed. In the present study, some intercropping models of food crops with bio-energy crop of castor (Ricinus communis L. were tested to assess their potential to improve the degraded land productivity. The intercropping models were: (1 castor - hybrid maize, (2 castor – short season maize, (3 castor – mungbean, and (4 castor –short season maize – mungbean. The results show that yields of the component crops in monoculture were relatively the same as in intercropping, resulted in a high Land Equivalent Ratio (LER. The highest LER (3.07 was calculated from intercropping castor plants with short season maize crops followed by mungbean with intercropping productivity of IDR 15,097,600.00 ha-1. Intercropping has a great potential to improve degraded agriculture land productivity and castor is a promising plant to improve biodiversity and area coverage on the land.

Deployment of Autonomous GPS Stations in Marie Byrd Land, Antartica

Science.gov (United States)

Donnellan, A.; Luyendyk, B.; Smith, M.; Dace, G.

1999-01-01

During the 1998-1999 Antarctic field season, we installed three autonomous GPS stations in Marie Byrd Land, West Antarctica to measure glacio-isostatic rebound and rates of spreading across the West Antartic Rift System.

Pathfinder Climate Data

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/NASA Pathfinder climate data CD-ROM contains seven data sets: Advanced Very High Resolution Radiometer (AVHRR)Land and Ocean, TIROS Operational Vertical...

Regional and climatic controls on seasonal dust deposition in the southwestern U.S.

Science.gov (United States)

Reheis, M.C.; Urban, F.E.

2011-01-01

Vertical dust deposition rates (dust flux) are a complex response to the interaction of seasonal precipitation, wind, changes in plant cover and land use, dust source type, and local vs. distant dust emission in the southwestern U.S. Seasonal dust flux in the Mojave-southern Great Basin (MSGB) deserts, measured from 1999 to 2008, is similar in summer-fall and winter-spring, and antecedent precipitation tends to suppress dust flux in winter-spring. In contrast, dust flux in the eastern Colorado Plateau (ECP) region is much larger in summer-fall than in winter-spring, and twice as large as in the MSGB. ECP dust is related to wind speed, and in the winter-spring to antecedent moisture. Higher summer dust flux in the ECP is likely due to gustier winds and runoff during monsoonal storms when temperature is also higher. Source types in the MSGB and land use in the ECP have important effects on seasonal dust flux. In the MSGB, wet playas produce salt-rich dust during wetter seasons, whereas antecedent and current moisture suppress dust emission from alluvial and dry-playa sources during winter-spring. In the ECP under drought conditions, dust flux at a grazed-and-plowed site increased greatly, and also increased at three annualized, previously grazed sites. Dust fluxes remained relatively consistent at ungrazed and currently grazed sites that have maintained perennial vegetation cover. Under predicted scenarios of future climate change, these results suggest that an increase in summer storms may increase dust flux in both areas, but resultant effects will depend on source type, land use, and vegetation cover. ?? 2011.

Forecasting Temporal and Spatial Climatological Influence for Land Suitability Evaluation in Bentota Sri Lanka

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Gayani Ranasinghe

2017-01-01

Full Text Available Climate change has raised much concern regarding its impacts on future land use planning, varying by region, time, and socio-economic development path. The principle purpose of land suitability evaluation is to predict the potential and limitation of the land for crop production and other land uses. This study was carried out to predict the temperature and rainfall trends as one of the major factor for evaluating land suitability. Climatic data such as monthly mean temperature, total monthly rainfall, maximum daily rainfall and total annual rainfall during last 30 years of all weather stations located in Bentota River basin was collected and analyzed applying time series analysis, correlation analysis and Manna Kendall trend test methods. Spatial distribution of forecast rainfall values was illustrated applying Arc GIS software. The findings revealed that monthly mean temperature and maximum daily rainfall had a general increasing trend whereas, total monthly rainfall and total annual rainfall showed a general decreasing trend in  Bentota area. It was indicated relatively high rainfall situations during May and October while low rainfall situations during January and February by occurring flood situation in once per five year. During Yala season the area will be received comparatively more rainfall (331mm than Maha season (300mm in future. Community and the farmers in this area can be aware about the anticipated spatial distribution of total monthly rainfall during two major seasons and flood occurrence periods. Decision makers should evaluate land suitability of Bentota area by considering above climatological influences and its spatial distribution pattern that identified as major outcome of this research. The approach and the methodology adopted in this study will be useful for other researchers, agriculturalist and planners to identify the future climatological influences and its spatial distribution pattern for land suitability evaluations

Modeled seasonality of glacial abrupt climate events

Energy Technology Data Exchange (ETDEWEB)

Flueckiger, Jacqueline [Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO (United States); Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, ETH Zuerich, Zurich (Switzerland); Knutti, Reto [Institute for Atmospheric and Climate Science, ETH Zuerich, Zurich (Switzerland); White, James W.C. [Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO (United States); Renssen, Hans [Vrije Universiteit Amsterdam, Faculty of Earth and Life Sciences, Amsterdam (Netherlands)

2008-11-15

Greenland ice cores, as well as many other paleo-archives from the northern hemisphere, recorded a series of 25 warm interstadial events, the so-called Dansgaard-Oeschger (D-O) events, during the last glacial period. We use the three-dimensional coupled global ocean-atmosphere-sea ice model ECBILT-CLIO and force it with freshwater input into the North Atlantic to simulate abrupt glacial climate events, which we use as analogues for D-O events. We focus our analysis on the Northern Hemisphere. The simulated events show large differences in the regional and seasonal distribution of the temperature and precipitation changes. While the temperature changes in high northern latitudes and in the North Atlantic region are dominated by winter changes, the largest temperature increases in most other land regions are seen in spring. Smallest changes over land are found during the summer months. Our model simulations also demonstrate that the temperature and precipitation change patterns for different intensifications of the Atlantic meridional overturning circulation are not linear. The extent of the transitions varies, and local non-linearities influence the amplitude of the annual mean response as well as the response in different seasons. Implications for the interpretation of paleo-records are discussed. (orig.)

Crop water stress maps for an entire growing season from visible and thermal UAV imagery

DEFF Research Database (Denmark)

Hoffmann, Helene; Jensen, Rasmus; Thomsen, Anton

2016-01-01

This study investigates whether a water deficit index (WDI) based on imagery from unmanned aerial vehicles (UAVs) can provide accurate crop water stress maps at different growth stages of barley and in differing weather situations. Data from both the early and late growing season are included...... to investigate whether the WDI has the unique potential to be applicable both when the land surface is partly composed of bare soil and when crops on the land surface are senescing. The WDI differs from the more commonly applied crop water stress index (CWSI) in that it uses both a spectral vegetation index (VI...... season because at this stage the remote sensing data represent crop water availability to a greater extent than they do in the early growing season, and because the WDI accounts for areas of ripe crops that no longer have the same need for irrigation. WDI maps can potentially serve as water stress maps...

Land-cover mapping using multitemporal, dual-frequency polarimetric SAR data

DEFF Research Database (Denmark)

Skriver, Henning; Schou, Jesper; Dierking, Wolfgang

2000-01-01

during the growing season acquired a lot of data over a Danish agricultural site. The data acquisitions were co-ordinated with ground surveys to obtain a detailed land cover map. The test area contains a large number of different land cover classes, such as more than 10 different crop types, deciduous......The Danish Center for Remote Sensing (DCRS) is, in collaboration with the Danish mapping agency, conducting a study on topographic mapping using SAR data, and land cover mapping results are presented. The Danish EMISAR system (an L- and C-band, fully polarimetric, airborne SAR) have in 1994 to 1999...

The importance of plot size and the number of sampling seasons on capturing macrofungal species richness.

Science.gov (United States)

Li, Huili; Ostermann, Anne; Karunarathna, Samantha C; Xu, Jianchu; Hyde, Kevin D; Mortimer, Peter E

2018-07-01

The species-area relationship is an important factor in the study of species diversity, conservation biology, and landscape ecology. A deeper understanding of this relationship is necessary, in order to provide recommendations on how to improve the quality of data collection on macrofungal diversity in different land use systems in future studies, a systematic assessment of methodological parameters, in particular optimal plot sizes. The species-area relationship of macrofungi in tropical and temperate climatic zones and four different land use systems were investigated by determining the macrofungal species richness in plot sizes ranging from 100 m 2 to 10 000 m 2 over two sampling seasons. We found that the effect of plot size on recorded species richness significantly differed between land use systems with the exception of monoculture systems. For both climate zones, land use system needs to be considered when determining optimal plot size. Using an optimal plot size was more important than temporal replication (over two sampling seasons) in accurately recording species richness. Copyright © 2018 British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Using Land Surface Phenology to Detect Land Use Change in the Northern Great Plains

Science.gov (United States)

Nguyen, L. H.; Henebry, G. M.

2017-12-01

The Northern Great Plains of the US have been undergoing many types of land cover / land use change over the past two decades, including expansion of irrigation, conversion of grassland to cropland, biofuels production, urbanization, and fossil fuel mining. Much of the literature on these changes has relied on post-classification change detection based on a limited number of observations per year. Here we demonstrate an approach to characterize land dynamics through land surface phenology (LSP) by synergistic use of image time series at two scales. Our study areas include regions of interest (ROIs) across the Northern Great Plains located within Landsat path overlap zones to boost the number of valid observations (free of clouds or snow) each year. We first compute accumulated growing degree-days (AGDD) from MODIS 8-day composites of land surface temperature (MOD11A2 and MYD11A2). Using Landsat Collection 1 surface reflectance-derived vegetation indices (NDVI, EVI), we then fit at each pixel a downward convex quadratic model linking the vegetation index to each year's progression of AGDD. This quadratic equation exhibits linearity in a mathematical sense; thus, the fitted models can be linearly mixed and unmixed using a set of LSP endmembers (defined by the fitted parameter coefficients of the quadratic model) that represent "pure" land cover types with distinct seasonal patterns found within the region, such as winter wheat, spring wheat, maize, soybean, sunflower, hay/pasture/grassland, developed/built-up, among others. Information about land cover corresponding to each endmember are provided by the NLCD (National Land Cover Dataset) and CDL (Cropland Data Layer). We use linear unmixing to estimate the likely proportion of each LSP endmember within particular areas stratified by latitude. By tracking the proportions over the 2001-2011 period, we can quantify various types of land transitions in the Northern Great Plains.

Effect of farming activities on seasonal variation of water quality of Bonsma Dam, KwaZulu-Natal

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Ayanda N. Shabalala

2013-07-01

Full Text Available Agriculture has both direct and indirect effects on the quality of surface water and groundwater and is among the leading causes of water quality degradation, mainly as a result of the excessive use of agrochemicals. Water samples were collected in a selected catchment area (Bonsma Dam in KwaZulu-Natal and analysed for physicochemical variables. The concentrations of most of the elements and total dissolved solids, as well as the pH and electrical conductivity values, met the water quality requirements for domestic, agricultural, livestock and aquatic ecosystem uses. However, the inlet streams feeding the dam were found to be eutrophic during the wet season. Analysis of nitrate in the water body of the study area indicated that agricultural applications of manure and fertilisers may be a potential source of nitrate contamination. Most elements were more concentrated in the dam during the wet season. The overall ionic conductivity values were also higher in the wet season, while the pH was lower. The outcome of this work links the concentrations of physicochemical variables to land use, agricultural practice and local geomorphology. Seasonal patterns in the concentration of physicochemical variables occur, as land use, rainfall and farming activities change seasonally, and these concentrations should therefore be determined periodically.

Climate change effect on Betula (birch) and Quercus (oak) pollen seasons in the United States

Science.gov (United States)

Zhang, Yong; Bielory, Leonard; Georgopoulos, Panos G.

2014-07-01

Climatic change is expected to affect the spatiotemporal patterns of airborne allergenic pollen, which has been found to act synergistically with common air pollutants, such as ozone, to cause allergic airway disease (AAD). Observed airborne pollen data from six stations from 1994 to 2011 at Fargo (North Dakota), College Station (Texas), Omaha (Nebraska), Pleasanton (California), Cherry Hill and Newark (New Jersey) in the US were studied to examine climate change effects on trends of annual mean and peak value of daily concentrations, annual production, season start, and season length of Betula (birch) and Quercus (oak) pollen. The growing degree hour (GDH) model was used to establish a relationship between start/end dates and differential temperature sums using observed hourly temperatures from surrounding meteorology stations. Optimum GDH models were then combined with meteorological information from the Weather Research and Forecasting (WRF) model, and land use land coverage data from the Biogenic Emissions Land use Database, version 3.1 (BELD3.1), to simulate start dates and season lengths of birch and oak pollen for both past and future years across the contiguous US (CONUS). For most of the studied stations, comparison of mean pollen indices between the periods of 1994-2000 and 2001-2011 showed that birch and oak trees were observed to flower 1-2 weeks earlier; annual mean and peak value of daily pollen concentrations tended to increase by 13.6 %-248 %. The observed pollen season lengths varied for birch and for oak across the different monitoring stations. Optimum initial date, base temperature, and threshold GDH for start date was found to be 1 March, 8 °C, and 1,879 h, respectively, for birch; 1 March, 5 °C, and 4,760 h, respectively, for oak. Simulation results indicated that responses of birch and oak pollen seasons to climate change are expected to vary for different regions.

Fallow land mapping for better crop monitoring in Huang-Huai-Hai Plain using HJ-1 CCD data

International Nuclear Information System (INIS)

Zhang, Miao; Wu, Bingfang; Meng, Jihua; Dong, Taifeng; You, Xingzhi

2014-01-01

The prediction of grain production is essential for socio-economic development planning, guidance and control of macro cropping structure adjustment. Fallow areas should be identified each growing season which is critical for grain production prediction. This paper focuses on fallow arable land monitoring during summer grain season in the Huang-Huai-Hai Plain using China Environment Satellite HJ-1 CCD data. With the two satellites HJ-1A and HJ-1B, high temporal Normalized Difference Vegetation Index (NDVI) can be obtained. HJ-1 CCD data were acquired from early March to early June in 2010 over the Huang-Huai-Hai Plain. Multi-temporal HJ-1 CCD data were pre-processed and time series of NDVI were derived. An algorithm for separating cropped and fallow areas was developed based on three key periods of NDVI in early-March, mid-April and mid-May, 2010. The influence of fallow arable lands to yield estimation and crop condition monitoring over the Huang-Huai-Hai Plain were also investigated and analyzed. Preliminary results in this paper showed that HJ-1 CCD data are capable for fallow land monitoring. Information of fallow arable lands is an essential part of crop monitoring and it should be incorporated into crop monitoring systems. In the future, the fallow lands over autumn grain season should also be identified and information of fallow arable lands should be generated yearly in order to get more reliable production prediction

Spatiotemporal Variation and the Role of Wildlife in Seasonal Water Quality Declines in the Chobe River, Botswana.

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J Tyler Fox

Full Text Available Sustainable management of dryland river systems is often complicated by extreme variability of precipitation in time and space, especially across large catchment areas. Understanding regional water quality changes in southern African dryland rivers and wetland systems is especially important because of their high subsistence value and provision of ecosystem services essential to both public and animal health. We quantified seasonal variation of Escherichia coli (E. coli and Total Suspended Solids (TSS in the Chobe River using spatiotemporal and geostatistical modeling of water quality time series data collected along a transect spanning a mosaic of protected, urban, and developing urban land use. We found significant relationships in the dry season between E. coli concentrations and protected land use (p = 0.0009, floodplain habitat (p = 0.016, and fecal counts from elephant (p = 0.017 and other wildlife (p = 0.001. Dry season fecal loading by both elephant (p = 0.029 and other wildlife (p = 0.006 was also an important predictor of early wet season E. coli concentrations. Locations of high E. coli concentrations likewise showed close spatial agreement with estimates of wildlife biomass derived from aerial survey data. In contrast to the dry season, wet season bacterial water quality patterns were associated only with TSS (p<0.0001, suggesting storm water and sediment runoff significantly influence E. coli loads. Our data suggest that wildlife populations, and elephants in particular, can significantly modify river water quality patterns. Loss of habitat and limitation of wildlife access to perennial rivers and floodplains in water-restricted regions may increase the impact of species on surface water resources. Our findings have important implications to land use planning in southern Africa's dryland river ecosystems.

How consistent are global long-term satellite LAI products in terms of interannual variability and trend?

Science.gov (United States)

Jiang, C.; Ryu, Y.; Fang, H.

2016-12-01

Proper usage of global satellite LAI products requires comprehensive evaluation. To address this issue, the Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) subgroup proposed a four-stage validation hierarchy. During the past decade, great efforts have been made following this validation framework, mainly focused on absolute magnitude, seasonal trajectory, and spatial pattern of those global satellite LAI products. However, interannual variability and trends of global satellite LAI products have been investigated marginally. Targeting on this gap, we made an intercomparison between seven global satellite LAI datasets, including four short-term ones: MODIS C5, MODIS C6, GEOV1, MERIS, and three long-term products ones: LAI3g, GLASS, and GLOBMAP. We calculated global annual LAI time series for each dataset, among which we found substantial differences. During the overlapped period (2003 - 2011), MODIS C5, GLASS and GLOBMAP have positive correlation (r > 0.6) between each other, while MODIS C6, GEOV1, MERIS, and LAI3g are highly consistent (r > 0.7) in interannual variations. However, the previous three datasets show negative trends, all of which use MODIS C5 reflectance data, whereas the latter four show positive trends, using MODIS C6, SPOT/VGT, ENVISAT/MERIS, and NOAA/AVHRR, respectively. During the pre-MODIS era (1982 - 1999), the three AVHRR-based datasets (LAI3g, GLASS and GLOBMAP) agree well (r > 0.7), yet all of them show oscillation related with NOAA platform changes. In addition, both GLASS and GLOBMAP show clear cut-points around 2000 when they move from AVHRR to MODIS. Such inconsistency is also visible for GEOV1, which uses SPOT-4 and SPOT-5 before and after 2002. We further investigate the map-to-map deviations among these products. This study highlights that continuous sensor calibration and cross calibration are essential to obtain reliable global LAI time series.

Three Decades of Remote Sensing Based Tropical Forests Phenological Patterns and Trends

Science.gov (United States)

Didan, K.

2010-12-01

The faint climatic seasonality of tropical rain forests is believed to be the reason these biomes lack strong and detectable seasonality. Forest seasonality is a critical element of ecosystem functions. It moderates the echo-hydrology, carbon, and nutrient exchange of the area. While deciduous forests exhibit distinct and strong seasonality, tropical forests do not, yet they play a large role in the cycling of energy and mass. Tropical forests represent a large percentage of vegetated land and their importance to the Earth system stems from their biological diversity, their habitat role, their role in regulating global weather, and the role they play in carbon storage. While Tropical forests are well buffered by their sheer size, their vulnerability to climate change is exacerbated by the human pressure. All of this begs the questions of what are the patterns and characteristic of tropical forests phenology and are there any detectable trends over the last three decades of synoptic remote sensing. These three decades comprise different episodes of droughts and an ever increasing level of human encroachment. In so far understanding the function and dynamic of these biomes, field studies continue to play a major role, but synoptic remote sensing is emerging as a viable tool to addressing the spatial and temporal scale associated with this problem. Recent studies of Brazilian rainforest with synoptic remote sensing point to a sizable seasonal signal coincident with the dry season. However, these studies were not extensive in time or space and did not look at other rainforests. Using data from AVHRR and MODIS, we generated a 30 year record of the 2 bands Enhance Vegetation Index (EVI2), and analyzed the patterns and trends of land surface phenology across all tropical forests using the homogeneous phenology cluster approach. We chose EVI because of its superior performance over these dense forests, and we selected the homogeneous phenology cluster approach to abate the

Contrasting Convective Flux Gradients in the U.S. Corn Belt as a Result of Vegetation Land Cover Type

Science.gov (United States)

Hiestand, M.

2017-12-01

Phenological differences between extensive croplands and remnant forests in the U.S. Corn Belt have been suggested as enhancing spatial gradients of latent and sensible heat fluxes that contribute to the distribution and amounts of convective rainfall on mesoscales. However, the exact magnitude of the intra-seasonal variability in convective fluxes between these two land-cover types has yet to be quantified. Previous work suggesting that non-classical mesoscale circulations operate within the Corn Belt has not involved direct flux observations obtained using the eddy flux covariance technique. This study compares five day running means of daily heat fluxes between two Ameriflux towers (US-Bo1 in Illinois and US-MMS in Indiana) representing rain-fed cropland and remnant forest, respectively for the growing seasons of 1999-2008. Latent heat values normalized to the net radiation show higher rates of evapotranspiration at the forested site than over the cropland during the start of the growing season. However, toward the end of the growing season, latent heat fluxes from the forest decrease and the cropland becomes the dominate source of evapotranspiration. Conversely, croplands dominate sensible heat fluxes at the start of the growing season whereas the remnant forests are associated with strong sensible heat fluxes in late summer. These intra-seasonal spatial differences of latent and sensible heat fluxes across the Corn Belt imply differences in moisture pooling that are suggested as enhancing atmospheric convection during favorable synoptic conditions, especially near the boundaries of these two land cover types. Understanding the physical mechanisms by which the spatial distribution of vegetated land cover can generate contrasting latent and sensible heat fluxes will lay the groundwork for improving mesoscale precipitation forecasts in the Corn Belt, and determining the possible impacts of ongoing land-cover and climate changes there.

Land subsidence in Yunlin, Taiwan, due to Agricultural and Domestic Water Use

Science.gov (United States)

Hsu, K.; Lin, P.; Lin, Z.

2013-12-01

Subsidence in a layered aquifer is caused by groundwater excess extraction and results in complicated problems in Taiwan. Commonly, responsibility to subsidence for agricultural and domestic water users is difficulty to identify due to the lack of quantitative evidences. An integrated model was proposed to analyze subsidence problem. The flow field utilizes analytical solution for pumping in a layered system from Neuman and Witherspoon (1969) to calculate the head drawdown variation. The subsidence estimation applies Terzaghi (1943) one-dimensional consolidation theory to calculate the deformation in each layer. The proposed model was applied to estimate land subsidence and drawdown variation at the Yuanchang Township of Yunlin County in Taiwan. Groundwater data for dry-season periods were used for calibration and validation. Seasonal effect in groundwater variation was first filtered out. Dry-season pumping effect on land subsidence was analyzed. The results show that multi-layer pumping contributes more in subsidence than single-layer pumping on the response of drawdown and land subsidence in aquifer 2 with a contribution of 97% total change at Yuanchang station. Pumping in aquifer 2 contributes more significant than pumping in aquifer 3 to cause change in drawdown and land subsidence in aquifer 2 with a contribution of 70% total change at Yuanchang station. Larger area of subsidence in Yuanchang Township was attributed pumping at aquifer 2 while pumping at aquifer 3 results in significant subsidence near the well field. The single-layer user contributes most area of subsidence but the multi-layer user generates more serious subsidence.

Adaptation to seasonality and the winter freeze

Directory of Open Access Journals (Sweden)

Jill Christine Preston

2013-06-01

Full Text Available Flowering plants initially diversified during the Mesozoic era at least 140 million years ago in regions of the world where temperate seasonal environments were not encountered. Since then several cooling events resulted in the contraction of warm and wet environments and the establishment of novel temperate zones in both hemispheres. In response, less than half of modern angiosperm families have members that evolved specific adaptations to cold seasonal climates, including cold acclimation, freezing tolerance, endodormancy, and vernalization responsiveness. Despite compelling evidence for multiple independent origins, the level of genetic constraint on the evolution of adaptations to seasonal cold is not well understood. However, the recent increase in molecular genetic studies examining the response of model and crop species to seasonal cold offers new insight into the evolutionary lability of these traits. This insight has major implications for our understanding of complex trait evolution, and the potential role of local adaptation in response to past and future climate change. In this review, we discuss the biochemical, morphological, and developmental basis of adaptations to seasonal cold, and synthesize recent literature on the genetic basis of these traits in a phylogenomic context. We find evidence for multiple genetic links between distinct physiological responses to cold, possibly reinforcing the coordinated expression of these traits. Furthermore, repeated recruitment of the same or similar ancestral pathways suggests that land plants might be somewhat pre-adapted to dealing with temperature stress, perhaps making inducible cold traits relatively easy to evolve.

Estimación de la temperatura superficial del mar desde datos satelitales NOAA-AVHRR: validación de algoritmos aplicados a la costa norte de Chile Sea surface temperature estimation from NOAA-AVHRR satellite data: validation of algorithms applied to the northern coast of Chile

Directory of Open Access Journals (Sweden)

Juan C Parra

2011-01-01

Full Text Available Se aplicaron y compararon tres algoritmos del tipo Split-Window (SW, que permitieron estimar la temperatura superficial del mar desde datos aportados por el sensor Advanced Very High Resolution Radiometer (AVHRR, a bordo de la serie de satélites de la National Oceanic and Atmospheric Administration (NOAA. La validación de los algoritmos fue lograda por comparación con mediciones in situ de temperatura del mar provenientes de una boya hidrográfica, ubicada frente a la costa norte de Chile (21°21'S, 70°6'W; Región de Tarapacá, a 3 km de la costa aproximadamente. Los mejores resultados se obtuvieron por aplicación del algoritmo propuesto por Sobrino & Raissouni (2000. En efecto, diferencias entre la temperatura medida in situ y la estimada por SW, permitieron evidenciar una media y desviación estándar de 0,3° y 0,8°K, respectivamente.The present article applies and compares three split-window (SW algorithms, which allowed the estimation of sea surface temperature using data obtained from the Advanced Very High Resolution Radiometer (AVHRR on board the National Oceanic and Atmospheric Administration (NOAA series of satellites. The algorithms were validated by comparison with in situ measurements of sea temperature obtained from a hydrographical buoy located off the coast of northern Chile (21°21'S, 70°6'W; Tarapacá Región, approximately 3 km from the coast. The best results were obtained by the application of the algorithm proposed by Sobrino & Raissouni (2000. The mean and standard deviation of the differences between the temperatures measured in situ and those estimated by SW were 0.3° and 0.8°K, respectively.

Shifts in Arctic phenology in response to climate and anthropogenic factors as detected from multiple satellite time series

International Nuclear Information System (INIS)

Zeng, Heqing; Jia, Gensuo; Forbes, Bruce C

2013-01-01

There is an urgent need to reduce the uncertainties in remotely sensed detection of phenological shifts of high latitude ecosystems in response to climate changes in past decades. In this study, vegetation phenology in western Arctic Russia (the Yamal Peninsula) was investigated by analyzing and comparing Normalized Difference Vegetation Index (NDVI) time series derived from the Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and SPOT-Vegetation (VGT) during the decade 2000–2010. The spatial patterns of key phenological parameters were highly heterogeneous along the latitudinal gradients based on multi-satellite data. There was earlier SOS (start of the growing season), later EOS (end of the growing season), longer LOS (length of the growing season), and greater MaxNDVI from north to south in the region. The results based on MODIS and VGT data showed similar trends in phenological changes from 2000 to 2010, while quite a different trend was found based on AVHRR data from 2000 to 2008. A significantly delayed EOS (p < 0.01), thus increasing the LOS, was found from AVHRR data, while no similar trends were detected from MODIS and VGT data. There were no obvious shifts in MaxNDVI during the last decade. MODIS and VGT data were considered to be preferred data for monitoring vegetation phenology in northern high latitudes. Temperature is still a key factor controlling spatial phenological gradients and variability, while anthropogenic factors (reindeer husbandry and resource exploitation) might explain the delayed SOS in southern Yamal. Continuous environmental damage could trigger a positive feedback to the delayed SOS. (letter)

Seasonal changes of CO2, CH4 and N2O fluxes in relation to land-use change in tropical peatlands located in coastal area of South Kalimantan

International Nuclear Information System (INIS)

Inubushi, K.; Furukawa, Y.; Hadi, A.; Purnomo, E.; Tsuruta, H.

2003-01-01

Tropical peatland could be a source of greenhouse gases emission because it contains large amounts of soil carbon and nitrogen. However these emissions are strongly influenced by soil moisture conditions. Tropical climate is characterized typically by wet and dry seasons. Seasonal changes in the emission of carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O) were investigated over a year at three sites (secondary forest, paddy field and upland field) in the tropical peatland in South Kalimantan, Indonesia. The amount of these gases emitted from the fields varied widely according to the seasonal pattern of precipitation, especially methane emission rates were positively correlated with precipitation. Converting from secondary forest peatland to paddy field tended to increase annual emissions of CO 2 and CH 4 to the atmosphere (from 1.2 to 1.5 kg CO 2 -C m -2 y -1 and from 1.2 to 1.9 g CH 4 -C m -2 y -1 ), while changing land-use from secondary forest to upland tended to decrease these gases emissions (from 1.2 to 1.0 kg CO 2 -C m -2 y -1 and from 1.2 to 0.6 g CH 4 -C m -2 y -1 ), but no clear trend was observed for N 2 O which kept negative value as annual rates at three sites. (Author)

Seasonal abundance of the dolphinfish, Coryphaena hippurus, in Hawaii and the tropical Pacific Ocean

Directory of Open Access Journals (Sweden)

Syd Kraul

1999-12-01

Full Text Available This report looks at possible explanations for the seasonal abundance of the dolphinfish, Coryphaena hippurus, in Hawaii. In Hawaii and many parts of the Pacific Ocean, the abundance of C. hippurus (called mahimahi in Hawaii varies seasonally in a pattern that is fairly consistent from year to year. Size frequency analysis shows that this pattern of seasonal landings matches the pattern of cohort abundance in certain years. The strongest cohorts are spawned in July, often stay in our fishing zone for at least 5 months, and may comprise the predominant portion of the catch through October. Even though mahimahi spawn copiously all year in captivity, the data here suggest that wild mahimahi either spawn less frequently, or their larvae survive better at certain times of the year. Thus, seasonal abundance of mahimahi in Hawaii might be a function of cohort survival. The abundance pattern also fits the pattern of change in seasonal surface temperatures, and it is quite possible that mahimahi migrate north and south to stay in the sea surface thermocline associated with the 23°C isotherm. Natural growth rates were derived from our size frequency analyses, and the rates matched growth rates reported in a previous study of otolith ring deposition. A significant increase in longline fishing in 1989 increased total landings but did not reduce the catch quantity or sales price for charter boat mahimahi.

Land Use and Climate Alter Carbon Dynamics in Watersheds of Chesapeake Bay

Science.gov (United States)

Kaushal, S.; Duan, S.; Grese, M.; Pennino, M. J.; Belt, K. T.; Findlay, S.; Groffman, P. M.; Mayer, P. M.; Murthy, S.; Blomquist, J.

2011-12-01

There have been long-term changes in the quantity of organic carbon in streams and rivers globally. Shifts in the quality of organic carbon due to environmental changes may also impact downstream ecosystem metabolism and fate and transport of contaminants. We investigated long-term impacts of land use and hydrologic variability on organic carbon transport in watersheds of the Baltimore Long-Term Ecological Research (LTER) site and large rivers of the Chesapeake Bay. In small and medium-sized watersheds of the Baltimore LTER site, urban land use increased organic carbon concentrations in streams several-fold compared to forest and agricultural watersheds. Enzymatic activities of stream microbes were significantly altered across watershed land use during a record wet year. During the wet year, short-term bioassays showed that bioavailable dissolved organic carbon varied seasonally, but comprised a substantial proportion of the dissolved organic carbon pool. Similarly, measurements of biochemical oxygen demand across hydrologic variability suggest that reactive organic carbon export from small and medium-sized urban watersheds during storms can be substantial. At a larger regional scale, major tributaries such as the Potomac, Susquehanna, Patuxent, and Choptank rivers also showed similar variability as smaller watersheds in quantity and quality of organic carbon based on land use and climate. There were distinct isotopic values of d13C of particulate organic matter and fluorescence excitation emission matrices for rivers influenced by different land uses. Stable isotopic values of d13C of particulate organic matter and fluorescence excitation emission matrices showed marked seasonal changes in organic matter quality during spring floods in the Potomac River at Washington D.C. Across watershed size, there appeared to be differences in seasonal cycles of organic carbon quality and this may have been based on the degree of hydrologic connectivity between watersheds and

Effect of dry land transformation and quality of water use for crop irrigation on the soil bacterial community in the Mezquital Valley, Mexico

Science.gov (United States)

Lüneberg, Kathia; Schneider, Dominik; Daniel, Rolf; Siebe, Christina

2017-04-01

Soil bacteria are important determinants of soil fertility and ecosystem services as they participate in all biogeochemical cycles. Until now the comprehension of compositional and functional response that bacterial communities have to land use change and management, specifically in dry land its limited. Dry lands cover 40% of the world's land surface and its crop production supports one third of the global population. In this regions soil moisture is limited constraining farming to the rainy season or oblige to irrigate, as fresh water resources become scarce, to maintain productivity, treated or untreated wastewater for field irrigation is used. In this study the transformation of semiarid shrubland to agriculture under different land systems regarding quantity and quality of water use for crop irrigation on bacterial communities was investigated. The land systems included maize rain-fed plantations and irrigation systems with freshwater, untreated wastewater stored in a dam and untreated wastewater during dry and rainy season. Bacterial community structure and function was heavily affected by land use system and soil properties, whereas seasonality had a slighter effect. A soil moisture, nutrient and contaminant-content increasing gradient among the land use systems, going from rain fed plantation over fresh water, dam wastewater to untreated wastewater irrigated plantations was detected, this gradient diminished the abundance of Actinobacteria and Cyanobacteria, but enhanced the one from Bacteroidetes and Proteobacteria. Discernible clustering of the dry land soil communities coincides with the moisture, nutrient and contaminant gradient, being shrubland soil communities closer to the rain-fed's system and farer to the one from untreated wastewater irrigated soil. Soil moisture together with sodium content and pH were the strongest drivers of the community structure. Seasonality promoted shifts in the composition of soil bacteria under irrigation with

Land Cover Monitoring for Water Resources Management in Angola

Science.gov (United States)

Miguel, Irina; Navarro, Ana; Rolim, Joao; Catalao, Joao; Silva, Joel; Painho, Marco; Vekerdy, Zoltan

2016-08-01

The aim of this paper is to assess the impact of improved temporal resolution and multi-source satellite data (SAR and optical) on land cover mapping and monitoring for efficient water resources management. For that purpose, we developed an integrated approach based on image classification and on NDVI and SAR backscattering (VV and VH) time series for land cover mapping and crop's irrigation requirements computation. We analysed 28 SPOT-5 Take-5 images with high temporal revisiting time (5 days), 9 Sentinel-1 dual polarization GRD images and in-situ data acquired during the crop growing season. Results show that the combination of images from different sources provides the best information to map agricultural areas. The increase of the images temporal resolution allows the improvement of the estimation of the crop parameters, and then, to calculate of the crop's irrigation requirements. However, this aspect was not fully exploited due to the lack of EO data for the complete growing season.

Understanding Flood Seasonality and Its Temporal Shifts within the Contiguous United States

Energy Technology Data Exchange (ETDEWEB)

Ye, Sheng [Institute of Hydrology and Water Resources, School of Civil Engineering, Zhejiang University, Hangzhou, China; Li, Hong-Yi [Pacific Northwest National Laboratory, Richland, Washington; Leung, L. Ruby [Pacific Northwest National Laboratory, Richland, Washington; Guo, Jiali [College of Civil and Hydropower Engineering, China Three Gorges University, Yichang, China; State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China; Ran, Qihua [Institute of Hydrology and Water Resources, School of Civil Engineering, Zhejiang University, Hangzhou, China; Demissie, Yonas [Department of Civil and Environmental Engineering, Washington State University Tri-Cities, Richland, Washington; Sivapalan, Murugesu [Department of Geography and Geographic Information Science, University of Illinois at Urbana–Champaign, Champaign, Illinois; Department of Civil and Environmental Engineering, University of Illinois at Urbana–Champaign, Urbana, Illinois

2017-07-01

Understanding the causes of flood seasonality is critical for better flood management. This study examines the seasonality of annual maximum floods (AMF) and its changes before and after 1980 at over 250 natural catchments across the contiguous United States. Using circular statistics to define a seasonality index, our analysis focuses on the variability of the flood occurrence date. Generally, catchments with more synchronized seasonal water and energy cycles largely inherit their seasonality of AMF from that of annual maximum rainfall (AMR). In contrast, the seasonality of AMF in catchments with loosely synchronized water and energy cycles are more influenced by high antecedent storage, which is responsible for the amplification of the seasonality of AMF over that of AMR. This understanding then effectively explains a statistically significant shift of flood seasonality detected in some catchments in the recent decades. Catchments where the antecedent soil water storage has increased since 1980 exhibit increasing flood seasonality while catchments that have experienced increases in storm rainfall before the floods have shifted towards floods occurring more variably across the seasons. In the eastern catchments, a concurrent widespread increase in event rainfall magnitude and reduced soil water storage have led to a more variable timing of floods. Our findings of the role of antecedent storage and event rainfall on the flood seasonality provide useful insights for understanding future changes in flood seasonality as climate models projected changes in extreme precipitation and aridity over land.

Dynamic Mesoscale Land-Atmosphere Feedbacks in Fragmented Forests in Amazonia

Science.gov (United States)

Rastogi, D.; Baidya Roy, S.

2011-12-01

This paper investigates land-atmosphere feedbacks in disturbed rainforests of Amazonia. Deforestation along the rapidly expanding highways and road network has created the unique fishbone land cover pattern in Rondonia, a state in southwestern Amazonia. Numerical experiments and observations show that sharp gradients in land cover due to the fishbone heterogeneity triggers mesoscale circulations. These circulations significantly change the spatial pattern of local hydrometeorology, especially convection, clouds and precipitation. The primary research question now is can these changes in local hydrometeorology affect vegetation growth in the clearings. If so, that would be a clear indication that land-atmosphere feedbacks can affect vegetation recovery in fragmented forests. A computationally-efficient modeling tool consisting of a mesoscale atmospheric model dynamically coupled with a plant growth model has been specifically developed to identify the atmospheric feedback pathways. Preliminary experiments focus on the seasonal-scale feedbacks during the dry season. Results show that temperature, incoming shortwave and precipitation are the three primary drivers through which the feedbacks operate. Increasing temperature increases respiratory losses generating a positive feedback. Increased cloud cover reduces incoming PAR and photosynthesis, resulting in a positive feedback. Increased precipitation reduces water stress and promotes growth resulting in a negative feedback. The net effect is a combination of these 3 feedback loops. These findings can significantly improve our understanding of ecosystem resiliency in disturbed tropical forests.

Changes in Carbon Emissions in Colombian Savannas Derived From Recent Land use and Land Cover Change

Science.gov (United States)

Etter, A.; Sarmiento, A.

2007-12-01

The global contribution of carbon emissions from land use dynamics and change to the global carbon (C) cycle is still uncertain, a major concern in global change modeling. Carbon emission from fires in the tropics is significant and represents 9% of the net primary production, and 50% of worldwide C emissions from fires are attributable to savanna fires. Such emissions may vary significantly due to differences in ecosystem types. Most savanna areas are devoted to grazing land uses making methane emissions also important in savanna ecosystems. Land use change driven by intensification of grazing and cropping has become a major factor affecting C emission dynamics from savanna regions. Colombia has some 17 MHa of mesic savannas which have been historically burned. Due to changes in market demands and improved accessibility during the last 20 years, important areas of savannas changed land use from predominantly extensive grazing to crops and intensive grazing systems. This research models and evaluates the impacts of such land use changes on the spatial and temporal burning patterns and C emissions in the Orinoco savannas of Colombia. We address the effects of land use change patterns using remote sensing data from MODIS and Landsat, ecosystem mapping products, and spatial GIS analysis. First we map the expansion of the agricultural frontier from the 1980s-2000s. We then model the changes in land use from the 1980s using a statistical modeling approach to analyze and quantify the impact of accessibility, ecosystem type and land tenure. We calculate the effects on C emissions from fire regimes and other sources of C based on patterns and extent of burned areas in the 2000s for different savanna ecosystem types and land uses. In the Llanos the fire regime exhibits a marked seasonal variability with most fire events occurring during the dry season between December-March. Our analysis shows that fire frequencies vary consistently between 0.6 and 2.8 fires.yr-1 per 2

Relating groundwater to seasonal wetlands in southeastern Wisconsin, USA

Science.gov (United States)

Skalbeck, J.D.; Reed, D.M.; Hunt, R.J.; Lambert, J.D.

2009-01-01

Historically, drier types of wetlands have been difficult to characterize and are not well researched. Nonetheless, they are considered to reflect the precipitation history with little, if any, regard for possible relation to groundwater. Two seasonal coastal wetland types (wet prairie, sedge meadow) were investigated during three growing seasons at three sites in the Lake Michigan Basin, Wisconsin, USA. The six seasonal wetlands were characterized using standard soil and vegetation techniques and groundwater measurements from the shallow and deep systems. They all met wetland hydrology criteria (e.g., water within 30 cm of land surface for 5% of the growing season) during the early portion of the growing season despite the lack of appreciable regional groundwater discharge into the wetland root zones. Although root-zone duration analyses did not fit a lognormal distribution previously noted in groundwater-dominated wetlands, they were able to discriminate between the plant communities and showed that wet prairie communities had shorter durations of continuous soil saturation than sedge meadow communities. These results demonstrate that the relative rates of groundwater outflows can be important for wetland hydrology and resulting wetland type. Thus, regional stresses to the shallow groundwater system such as pumping or low Great Lake levels can be expected to affect even drier wetland types. ?? Springer-Verlag 2008.

Land surface anomalies preceding the 2010 Russian heat wave and a link to the North Atlantic oscillation

International Nuclear Information System (INIS)

Wright, Christopher K; Henebry, Geoffrey M; De Beurs, Kirsten M

2014-01-01

The Eurasian wheat belt (EWB) spans a region across Eastern Ukraine, Southern Russia, and Northern Kazakhstan; accounting for nearly 15% of global wheat production. We assessed land surface conditions across the EWB during the early growing season (April–May–June; AMJ) leading up to the 2010 Russian heat wave, and over a longer-term period from 2000 to 2010. A substantial reduction in early season values of the normalized difference vegetation index occurred prior to the Russian heat wave, continuing a decadal decline in early season primary production in the region. In 2010, an anomalously cold winter followed by an abrupt shift to a warmer-than-normal early growing season was consistent with a persistently negative phase of the North Atlantic oscillation (NAO). Regression analyses showed that early season vegetation productivity in the EWB is a function of both the winter (December–January–February; DJF) and AMJ phases of the NAO. Land surface anomalies preceding the heat wave were thus consistent with highly negative values of both the DJF NAO and AMJ NAO in 2010. (letter)

Experimental use of Land Surface Models in the La Plata Basin

Science.gov (United States)

Goncalves, L.; de Mattos, J. Z.; Sapucci, L. F.; Herdies, D. L.; Berbery, E. H.

2009-12-01

prescribed climatological monthly values of vegetation parameters whereas the experiment run used a combination of AVHRR and MODIS Leaf Area Index mapping to represent the changes in land surface characteristics at finer scales. The relationship between soil states and regional circulation patterns (e.g., the South American Monsoon and the South Atlantic Convergence Zone) was investigated and the results were also used to estimate the impacts of land surface changes in the frequency, duration, intensity and variability of occurrences of droughts and floods in the LPB.

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data

Science.gov (United States)

Hagensieker, Ron; Roscher, Ribana; Rosentreter, Johannes; Jakimow, Benjamin; Waske, Björn

2017-12-01

Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain. The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.

Land use changes and socio-economic development strongly deteriorate river ecosystem health in one of the largest basins in China.

Science.gov (United States)

Cheng, Xian; Chen, Liding; Sun, Ranhao; Kong, Peiru

2018-03-01

It is important to assess river ecosystem health in large-scale basins when considering the complex influence of anthropogenic activities on these ecosystems. This study investigated the river ecosystem health in the Haihe River Basin (HRB) by sampling 148 river sites during the pre- and post-rainy seasons in 2013. A model was established to assess the river ecosystem health based on water physicochemical, nutrient, and macroinvertebrate indices, and the health level was divided into "very poor," "poor," "fair," "good," and "excellent" according to the health score calculated from the assessment model. The assessment results demonstrated that the river ecosystem health of the HRB was "poor" overall, and no catchments were labeled "excellent." The percentages of catchments deemed to have "very poor," "poor," "fair," or "good" river ecosystem health were 12.88%, 40.91%, 40.15%, and 6.06%, respectively. From the pre- to the post-rainy season, the macroinvertebrate health levels improved from "poor" to "fair." The results of a redundancy analysis (RDA), path analysis of the structural equation model (SEM), and X-Y plots indicated that the land use types of forest land and grassland had positive relationships with river ecosystem health, whereas arable land, urban land, gross domestic product (GDP) per capita, and population density had negative relationships with river ecosystem health. The variance partitioning (VP) results showed that anthropogenic activities (including land use and socio-economy) together explained 30.9% of the variations in river ecosystem health in the pre-rainy season, and this value increased to 35.9% in the post-rainy season. Land use intensity was the first driver of river ecosystem health, and socio-economic activities was the second driver. Land use variables explained 20.5% and 25.7% of the variations in river ecosystem health in the pre- and post-rainy season samples, respectively, and socio-economic variables explained 12.3% and 17.2% of

Effects of plant cover on soil N mineralization during the growing season in a sandy soil

Science.gov (United States)

Yao, Y.; Shao, M.; Wei, X.; Fu, X.

2017-12-01

Soil nitrogen (N) mineralization and its availability plays a vital role in regulating ecosystem productivity and C cycling, particularly in semiarid and desertified ecosystems. To determine the effect of plant cover on N turnover in a sandy soil ecosystem, we measured soil N mineralization and inorganic N pools in soil solution during growing season in a sandy soil covered with various plant species (Artemisia desertorum, Salix psammophila, and Caragana korshinskii). A bare sandy soil without any plant was selected as control. Inorganic N pools and N mineralization rates decreased overtime during the growing season, and were not affected by soil depth in bare land soils, but were significantly higher at the 0-10 cm layer than those at the 10-20 cm soil layer under any plant species. Soil inorganic N pool was dominated by ammonium, and N mineralization was dominated by nitrification regardless of soil depth and plant cover. Soils under C. korshinskii have significant higher inorganic N pools and N mineralization rate than soils under bare land and A. desertorum and S. psammophila, and the effects of plant cover were greater at the 0-10 cm soil layer than at the 10-20 cm layer. The effects of C. korshinskii on soil inorganic N pools and mineralization rate varied with the stage of growing season, with greater effects on N pools in the middle growing season, and greater effects on mineralization rate at the last half of the growing season. The results from this study indicate that introduction of C. korshinskii has the potential to increase soil N turnover and availability in sandy soils, and thus to decrease N limitation. Caragana korshinskii is therefore recommend for the remediation of the desertified land.

Evaluation of the AMSR-E Data Calibration Over Land

Science.gov (United States)

Njoku, E.; Chan, T.; Crosson, W.; Limaye, A.

2004-01-01

Land observations by the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), particularly of soil and vegetation moisture changes, have numerous applications in hydrology, ecology and climate. Quantitative retrieval of soil and vegetation parameters relies on accurate calibration of the brightness temperature measurements. Analyses of the spectral and polarization characteristics of early versions of the AMSR-E data revealed significant calibration biases over land at 6.9 GHz. The biases were estimated and removed in the current archived version of the data Radiofrequency interference (RFI) observed at 6.9 GHz is more difficult to quanti@ however. A calibration analysis of AMSR-E data over land is presented in this paper for a complete annual cycle from June 2002 through September 2003. The analysis indicates the general high quality of the data for land applications (except for RFI), and illustrates seasonal trends of the data for different land surface types and regions.

Exploring the Factors Driving Seasonal Farmland Abandonment: A Case Study at the Regional Level in Hunan Province, Central China

OpenAIRE

Yu, Zhonglei; Liu, Lei; Zhang, Hua; Liang, Jinshe

2017-01-01

Farmland abandonment, including perennial and seasonal abandonment, is an important process of land use change that matters most to food security. Although there is a great deal of studies on farmland abandonment, seasonal abandonment, which is as serious as perennial abandonment, has attracted little academic attention. This paper takes Hunan Province in central China as its study area and uses a spatial regression model to examine the driving factors of seasonal farmland abandonment at the ...

Changes in the NDVI of Boreal Forests over the period 1984 to 2003 measured using time series of Landsat TM/ETM+ surface reflectance and the GIMMS AVHRR NDVI record.

Science.gov (United States)

McMillan, A. M.; Rocha, A. V.; Goulden, M. L.

2006-12-01

There is a prevailing opinion that the boreal landscape is undergoing change as a result of warming temperatures leading to earlier springs, greater forest fire frequency and possibly CO2 fertilization. One widely- used line of evidence is the GIMMS AVHRR NDVI record. Several studies suggest increasing rates of photosynthesis in boreal forests from 1982 to 1991 (based on NDVI increases) while others suggest declining photosynthesis from 1996 to 2003. We suspect that a portion of these changes are due to the successional stage of the forests. We compiled a time-series of atmospherically-corrected Landsat TM/ETM+ images spanning the period 1984 to 2003 over the BOREAS Northern Study Area and compared spatial and temporal patterns of NDVI between the two records. The Landsat time series is higher resolution and, together with the Canadian Fire Service Large Fire Database, provides stand-age information. We then (1) analyzed the agreement between the Landsat and GIMMS AVHRR time series; (2) determined how the stage of forest succession affected NDVI; (3) assessed how the calculation method of annual averages of NDVI affects decadal-scale trends. The agreement between the Landsat and the AVHRR was reasonable although the depression of NDVI associated with the aerosols from the Pinatubo volcano was greater in the GIMMS time series. Pixels containing high proportions of stands burned within a decade of the observation period showed very high gains in NDVI while the more mature stands were constant. While NDVI appears to exhibit a large sensitivity to the presence of snow, the choice of a May to September averaging period for NDVI over a June to August averaging period did not affect the interannual patterns in NDVI at this location because the snow pack was seldom present in either of these periods. Knowledge of the spatial and temporal patterns of wild fire will prove useful in interpreting trends of remotely-sensed proxies of photosynthesis.

Spatial Pattern of Soil Salinity in Area Around the Yellow River Delta and Its Seasonal Dynamics over a 3-year Period

Science.gov (United States)

Lai, J.; Ouyang, Z.

2017-12-01

Salt-affected land varies spatially and seasonally in terms of soil salinity. "Bohai Granary" is a newly proposed national-level program which was aimed to improve soil quality and mining grain production potential of the salt-affected land in east China. In this work, soil samples were monthly taken at 11 sites within Wudi county in the Yellow river delta. The spatial distribution pattern of soil salinity were investigated and its seasonal variation over 36 months were discussed. Our findings indicate that the vertical distribution type of soil salinity was bottom-accumulating in the near coastal area while its gradually turned into a type of surface-accumulating as the sampling site moving towards the inner land. The peak of the soil salinity along the soil profile alternately moved upwards and downwards during the growing seasons. However, there was no evidence for the increasing of the total salt amount within the upper 100cm of soil. Moreover, the salt was mostly accumulated in the upper soil (0-40cm) during the late spring and early summer season; and winter wheat was tend to be affected severely at this stage. Therefore, special field practices (e.g. regular irrigation to leach salt, good maintenance of drainage system) should be taken to minimize the threat of soil salinity.

The Copernicus Global Land Service: present and future

Science.gov (United States)

Lacaze, Roselyne; Smets, Bruno; Trigo, Isabel; Calvet, Jean-Christophe; Jann, Alexander; Camacho, Fernando; Baret, Frédéric; Kidd, Richard; Defourny, Pierre; Tansey, Kevin; Pacholczyk, Philippe; Balsamo, Gianpaolo; Szintai, Balazs

2013-04-01

From 1st January 2013, the Copernicus Global Land Service is operational, providing continuously to European, African and International users a set of biophysical variables describing the vegetation conditions, the energy budget at the continental surface and the water cycle over the whole globe at one kilometer resolution. These generic products can serve numerous applications such as agriculture and food security monitoring, weather forecast, climate change impact studies, water, forest and natural resources management. The Copernicus Global Land Service is built on the achievements of the BioPar component of the FP7 geoland2 project. Essential Climate Variables like the Leaf Area Index (LAI), the Fraction of PAR absorbed by the vegetation (FAPAR), the surface albedo, the Land Surface Temperature, the soil moisture, the burnt areas, the areas of water bodies, and additional vegetation indices, are generated every hour, every day or every 10 days on a reliable and automatic basis from Earth Observation satellite data. Beside this timely production, the available historical archives have been processed, using the same innovative algorithms, to get consistent time series as long as possible. As an example, more than 30 years of LAI and FAPAR relying on NOAA/AVHRR sensors (from 1981 to 2000) and SPOT/VGT sensors (from 1999 to the present) are now available. All products are accessible, free of charge and after registration, at the following address: http://www.geoland2.eu/core-mapping-services/biopar.html. Documentation describing the physical methodologies, the technical properties of products, and the results of validation exercises can also be downloaded. In view of service continuity, research and development are performed on two parallel ways. On one hand, the existing retrieval methodologies will be adapted to new input data sets (e.g. Proba-V and Sentinel-3 at 1km resolution) that will be used in replacement of current sensor (SPOT/VGT) which reached the end

Ecological and pest-management implications of sex differences in scarab landing patterns on grape vines.

Science.gov (United States)

González-Chang, Mauricio; Boyer, Stéphane; Lefort, Marie-Caroline; Nboyine, Jerry; Wratten, Steve D

2017-01-01

Melolonthinae beetles, comprising different white grub species, are a globally-distributed pest group. Their larvae feed on roots of several crop and forestry species, and adults can cause severe defoliation. In New Zealand, the endemic scarab pest Costelytra zealandica (White) causes severe defoliation on different horticultural crops, including grape vines ( Vitis vinifera ). Understanding flight and landing behaviours of this pest can help inform pest management decisions. Adult beetles were counted and then removed from 96 grape vine plants from 21:30 until 23:00 h, every day from October 26 until December 2, during 2014 and 2015. Also, adults were removed from the grape vine foliage at dusk 5, 10, 15, 20 and 25 min after flight started on 2015. Statistical analyses were performed using generalised linear models with a beta-binomial distribution to analyse proportions and with a negative binomial distribution for beetle abundance. By analysing C. zealandica sex ratios during its entire flight season, it is clear that the proportion of males is higher at the beginning of the season, gradually declining towards its end. When adults were successively removed from the grape vines at 5-min intervals after flight activity begun, the mean proportion of males ranged from 6-28%. The male proportion suggests males were attracted to females that had already landed on grape vines, probably through pheromone release. The seasonal and daily changes in adult C. zealandica sex ratio throughout its flight season are presented for the first time. Although seasonal changes in sex ratio have been reported for other melolonthines, changes during their daily flight activity have not been analysed so far. Sex-ratio changes can have important consequences for the management of this pest species, and possibly for other melolonthines, as it has been previously suggested that C. zealandica females land on plants that produce a silhouette against the sky. Therefore, long-term management

Effect of land cover on atmospheric processes and air quality over the continental United States – a NASA Unified WRF (NU-WRF model study

Directory of Open Access Journals (Sweden)

Z. Tao

2013-07-01

Full Text Available The land surface plays a crucial role in regulating water and energy fluxes at the land–atmosphere (L–A interface and controls many processes and feedbacks in the climate system. Land cover and vegetation type remains one key determinant of soil moisture content that impacts air temperature, planetary boundary layer (PBL evolution, and precipitation through soil-moisture–evapotranspiration coupling. In turn, it will affect atmospheric chemistry and air quality. This paper presents the results of a modeling study of the effect of land cover on some key L–A processes with a focus on air quality. The newly developed NASA Unified Weather Research and Forecast (NU-WRF modeling system couples NASA's Land Information System (LIS with the community WRF model and allows users to explore the L–A processes and feedbacks. Three commonly used satellite-derived land cover datasets – i.e., from the US Geological Survey (USGS and University of Maryland (UMD, which are based on the Advanced Very High Resolution Radiometer (AVHRR, and from the Moderate Resolution Imaging Spectroradiometer (MODIS – bear large differences in agriculture, forest, grassland, and urban spatial distributions in the continental United States, and thus provide an excellent case to investigate how land cover change would impact atmospheric processes and air quality. The weeklong simulations demonstrate the noticeable differences in soil moisture/temperature, latent/sensible heat flux, PBL height, wind, NO2/ozone, and PM2.5 air quality. These discrepancies can be traced to associate with the land cover properties, e.g., stomatal resistance, albedo and emissivity, and roughness characteristics. It also implies that the rapid urban growth may have complex air quality implications with reductions in peak ozone but more frequent high ozone events.

Irrigation-water quality during 1976 irrigation season in the Sulphur Creek basin, Yakima and Benton counties, Washington

Science.gov (United States)

Boucher, P.R.; Fretwell, M.O.

1982-01-01

A water-quality-sampling network was designed for the Sulphur Creek basin to observe the effects of farming practices on irrigation. Sediment and nutrient yield, discharge, and water temperature data were collected during the 1976 irrigation season and the following fall and winter. The suspended-sediment yield of the basin during this period was 2.0 tons per acre of irrigated cropland. Only about 3% of the net outflow of sediment occurred during the nonirrigation season. The yield computed by subbasin ranged from 0.7 to 7 tons per acre, depending mainly on land slope, but a high percentage of orchard land in the subbasins was probably also significant in reducing loads. Nutrient outflows during the study period were 1,180,000 pounds of nitrogen and 120,000 pounds of phosphorous. Nitrate-plus-nitrite represent 70% of the nitrogen outflow in the irrigation season and 84% in the nonirrigation season. The monitoring network was discontinued at the end of the study period, due largely to insufficient farmer participation. Network sensitivity in the control subbasins was inadequate to detect the effects of a planned demonstration program of best management practices. (USGS)

Land Use and Land Cover Change in Guangzhou, China, from 1998 to 2003, Based on Landsat TM /ETM+ Imagery

Directory of Open Access Journals (Sweden)

Yunpeng Wang

2007-07-01

Full Text Available Land use and land cover change is a major issue in global environment change,and is especially significant in rapidly developing regions in the world. With its economicdevelopment, population growth, and urbanization, Guangzhou, a major metropolitan inSouth China, have experienced a dramatic land use and land cover (LULC change over thepast 30 years. Fast LULC change have resulted in degradation of its ecosystems andaffected adversely the environment. It is urgently needed to monitor its LULC changes andto analyses the consequences of these changes in order to provide information for policy-makers to support sustainable development. This study employed two Landsat TM/ETM images in the dry season to detect LULC patterns in 1998 and 2003, and to examine LULCchanges during the period from 1998 to 2003. The type, rate, and pattern of the changesamong five counties of Guangzhou Municipality were analyzed in details by post-classification method. LULC conversion matrix was produced for each county in order toexplore and explain the urban expansion and cropland loss, the most significant types ofLULC change. Land use conversion matrixes of five counties were discussed respectivelyin order to explore and explain the inherence of land use change. The results showed thaturban expansion in these five counties kept an even rate of increase, while substantialamount of cropland vanished during the period. It is also noted that the conversion between cropland and orchard land was intensive. Forest land became the main source of new croplands.

Seasonal hydroclimatic impacts of Sun Corridor expansion

International Nuclear Information System (INIS)

Georgescu, M; Mahalov, A; Moustaoui, M

2012-01-01

Conversion of natural to urban land forms imparts influence on local and regional hydroclimate via modification of the surface energy and water balance, and consideration of such effects due to rapidly expanding megapolitan areas is necessary in light of the growing global share of urban inhabitants. Based on a suite of ensemble-based, multi-year simulations using the Weather Research and Forecasting (WRF) model, we quantify seasonally varying hydroclimatic impacts of the most rapidly expanding megapolitan area in the US: Arizona’s Sun Corridor, centered upon the Greater Phoenix metropolitan area. Using a scenario-based urban expansion approach that accounts for the full range of Sun Corridor growth uncertainty through 2050, we show that built environment induced warming for the maximum development scenario is greatest during the summer season (regionally averaged warming over AZ exceeds 1 °C). Warming remains significant during the spring and fall seasons (regionally averaged warming over AZ approaches 0.9 °C during both seasons), and is least during the winter season (regionally averaged warming over AZ of 0.5 °C). Impacts from a minimum expansion scenario are reduced, with regionally averaged warming ranging between 0.1 and 0.3 °C for all seasons except winter, when no warming impacts are diagnosed. Integration of highly reflective cool roofs within the built environment, increasingly recognized as a cost-effective option intended to offset the warming influence of urban complexes, reduces urban-induced warming considerably. However, impacts on the hydrologic cycle are aggravated via enhanced evapotranspiration reduction, leading to a 4% total accumulated precipitation decrease relative to the non-adaptive maximum expansion scenario. Our results highlight potentially unintended consequences of this adaptation approach within rapidly expanding megapolitan areas, and emphasize the need for undeniably sustainable development paths that account for

[Research on the influence of urban land use structure and pattern on nitrogen, phosphorus of wetland water environment in Xianlin New Town of Nanjing].

Science.gov (United States)

Cai, Chun-Xiao; Liu, Hong-Yu; Li, Yu-Feng; Wang, Cong; Hou, Ming-Hang

2014-08-01

The 10 typical wetlands in Xianlin New Townof Nanjing were classified into three categories, including rural wetland, suburban wetland, and urban wetland according to the influence of urbanization as well as the characteristics of wetland and LUCC of catchment regions. RDA was used to analyse the relationships between nitrogen and phosphorus in urban wetland and various types and patterns of land use. It was found that the water quality of the urban wetlands presented to be worse than that from rural wetlands, followed by sub urban wetlands. Secondly, according to all investigated wetlands, TP and TN turned out to be higher during the wet seasons than dry seasons. In addition, significant differences of TP were observed between wet and dry seasons for rural and suburban wetlands, and it was not so obvious for urban wetlands. However, the differences of TN was opposite to that of TP. Thirdly, factors affecting the water quality of wetlands were comprised of types and patterns of land use, and thus significant positive relationships were found between the concentrations of TN and TP and the impervious land, while negative correlations for meadows, woodlands and wetlands. What's more, higher remarkable differences were found in wetlands than those from meadows and woodlands. Regarding to patterns of land use, TP, TN concentrations were negatively correlated with the average patch shape in the dry and wet seasons, whereas positively relationships were observed for patch density and diversity index; furthermore, with refer to the impact of adjacent landscape, significant relationships were found between the content of TN and the patterns of land use and thus, a negative correlation in the wet season and a positive correlation in the dry season were observed, respectively.

An Estimation of Land Surface Temperatures from Landsat ETM+ ...

African Journals Online (AJOL)

Dr-Adeline

Keywords: Urban growth, urban heat Island, land surface temperatures, ... climate from the resulting increase in LST can impact on the development of ... were not available (due to high cloud cover) in a given season, 2011 images ..... Sailor, D.J. and H. Fan, 2002: Modeling the diurnal variability of effective albedo for cities.

A data assimilation framework for constraining upscaled cropland carbon flux seasonality and biometry with MODIS

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O. Sus

2013-04-01

Full Text Available Agroecosystem models are strongly dependent on information on land management patterns for regional applications. Land management practices play a major role in determining global yield variability, and add an anthropogenic signal to the observed seasonality of atmospheric CO2 concentrations. However, there is still little knowledge on spatial and temporal variability of important farmland activities such as crop sowing dates, and thus these remain rather crudely approximated within carbon cycle studies. In this study, we present a framework allowing for spatio-temporally resolved simulation of cropland carbon fluxes under observational constraints on land management and canopy greenness. We apply data assimilation methodology in order to explicitly account for information on sowing dates and model leaf area index. MODIS 250 m vegetation index data were assimilated both in batch-calibration for sowing date estimation and sequentially for improved model state estimation, using the ensemble Kalman filter (EnKF, into a crop carbon mass balance model (SPAc. In doing so, we are able to quantify the multiannual (2000–2006 regional carbon flux and biometry seasonality of maize–soybean crop rotations surrounding the Bondville Ameriflux eddy covariance site, averaged over 104 pixel locations within the wider area. (1 Validation at the Bondville site shows that growing season C cycling is simulated accurately with MODIS-derived sowing dates, and we expect that this framework allows for accurate simulations of C cycling at locations for which ground-truth data are not available. Thus, this framework enables modellers to simulate current (i.e. last 10 yr carbon cycling of major agricultural regions. Averaged over the 104 field patches analysed, relative spatial variability for biometry and net ecosystem exchange ranges from ∼7% to ∼18%. The annual sign of net biome productivity is not significantly different from carbon neutrality. (2 Moreover

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).

Diagnosing the Role of Transpiration in the Transition from Dry to Wet Season Over the Amazon Using Satellite Observations

Science.gov (United States)

Wright, J. S.; Fu, R.; Yin, L.; Chae, J.

2013-12-01

Reanalysis data indicates that land surface evapotranspiration plays a key role in determining the timing of wet season onset over the Amazon. Here, we use satellite observations of water vapor and its stable isotopes, carbon dioxide, leaf area index, and precipitation together with reanalysis data to explore the importance of transpiration in initiating the transition from dry season to wet season over the Amazon. The growth of vegetation in this region is primarily limited by the availability of sunlight rather than the availability of soil moisture, so that the increase of solar radiation during the dry season coincides with dramatic increases in leaf area index within forested ecosystems. This period of plant growth is accompanied by uptake of carbon dioxide and enrichment of heavy isotopes in water vapor, particularly near the land surface. Reanalysis data indicate that this pre-wet season enrichment of HDO is accompanied by sharp increases in the surface latent heat flux, which eventually triggers sporadic moist convection. The transport of transpiration-enriched near-surface air by this convection causes a dramatic increase in free-tropospheric HDO in late August and September. September also marks transition points in the annual cycles of leaf area index (maximum) and carbon dioxide (minimum). The increase in convective activity during this period creates convergence, enhancing moisture transport into the region and initiating the wet season.

Ecological mechanisms linking protected areas to surrounding lands.

Science.gov (United States)

Hansen, Andrew J; DeFries, Ruth

2007-06-01

Land use is expanding and intensifying in the unprotected lands surrounding many of the world's protected areas. The influence of this land use change on ecological processes is poorly understood. The goal of this paper is to draw on ecological theory to provide a synthetic framework for understanding how land use change around protected areas may alter ecological processes and biodiversity within protected areas and to provide a basis for identifying scientifically based management alternatives. We first present a conceptual model of protected areas embedded within larger ecosystems that often include surrounding human land use. Drawing on case studies in this Invited Feature, we then explore a comprehensive set of ecological mechanisms by which land use on surrounding lands may influence ecological processes and biodiversity within reserves. These mechanisms involve changes in ecosystem size, with implications for minimum dynamic area, species-area effect, and trophic structure; altered flows of materials and disturbances into and out of reserves; effects on crucial habitats for seasonal and migration movements and population source/sink dynamics; and exposure to humans through hunting, poaching, exotics species, and disease. These ecological mechanisms provide a basis for assessing the vulnerability of protected areas to land use. They also suggest criteria for designing regional management to sustain protected areas in the context of surrounding human land use. These design criteria include maximizing the area of functional habitats, identifying and maintaining ecological process zones, maintaining key migration and source habitats, and managing human proximity and edge effects.

Modelling seasonal farm labour demand: What can we learn from rural Kakamega district, western Kenya?

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Vincent Canwat

2012-09-01

Full Text Available Seasonality of agricultural activities causes fluctuation in the quantity of labour consumed by these activities, and yet many rural labour studies in developing countries still treat labour demand in agriculture as if it is the same across different farm operations. To unearth the amount of information hidden by this aggregated analysis, labour demand for specific farm operations was estimated based on data collected from Kakamega District. This analysis shows that increasing household size increases labour demand for planting, weeding and harvesting. Increasing the share of elderly household members has a negligible effect on labour demand for farm activities except for land preparation, with which it is positively related. Participation of primary school-going children in farm activities is the highest in planting and harvesting. Participation in off-farm employment seems to increase labour demand only during peak seasons. The area planted appears to have an insignificant effect on labour demand for land preparation. Planting sugar cane appears to reduce labour demand for weeding and primary processing, but planting tea increases labour demand for planting. Mechanising land preparation only reduces labour demand for land preparation, but it seems to be offset by other labour-intensive farm operations. The distance from water source is positively related to labour demand for land preparation, but the distance to the market is negatively related to labour demand for weeding and harvesting. These observations point to the need for supporting and investing in technological and organisational innovations in agriculture.

Effects of River Discharge and Land Use and Land Cover (LULC) on Water Quality Dynamics in Migina Catchment, Rwanda

Science.gov (United States)

Uwimana, Abias; van Dam, Anne; Gettel, Gretchen; Bigirimana, Bonfils; Irvine, Kenneth

2017-09-01

Agricultural intensification may accelerate the loss of wetlands, increasing the concentrations of nutrients and sediments in downstream water bodies. The objective of this study was to assess the effects of land use and land cover and river discharge on water quality in the Migina catchment, southern Rwanda. Rainfall, discharge and water quality (total nitrogen, total phosphorus, total suspended solids, dissolved oxygen, conductivity, pH, and temperature) were measured in different periods from May 2009 to June 2013. In 2011, measurements were done at the outlets of 3 sub-catchments (Munyazi, Mukura and Akagera). Between May 2012 and May 2013 the measurements were done in 16 reaches of Munyazi dominated by rice, vegetables, grass/forest or ponds/reservoirs. Water quality was also measured during two rainfall events. Results showed seasonal trends in water quality associated with high water flows and farming activities. Across all sites, the total suspended solids related positively to discharge, increasing 2-8 times during high flow periods. Conductivity, temperature, dissolved oxygen, and pH decreased with increasing discharge, while total nitrogen and total phosphorus did not show a clear pattern. The total suspended solids concentrations were consistently higher downstream of reaches dominated by rice and vegetable farming. For total nitrogen and total phosphorus results were mixed, but suggesting higher concentration of total nitrogen and total phosphorus during the dry and early rainy (and farming) season, and then wash out during the rainy season, with subsequent dilution at the end of the rains. Rice and vegetable farming generate the transport of sediment as opposed to ponds/reservoir and grass/forest.

Identification of land areas suitable for Fadama farming at Federal ...

African Journals Online (AJOL)

Fadama farming provides a platform for sustained crop cultivation during dry season. This research was directed towards identifying new land areas within the Federal University of Agriculture with the use of Geographical Information System (GIS). The few existing Fadama sites within the study area were searched and their ...

Biomass Burning, Land-Cover Change, and the Hydrological Cycle in Northern Sub-Saharan Africa

Science.gov (United States)

Ichoku, Charles; Ellison, Luke T.; Willmot, K. Elena; Matsui, Toshihisa; Dezfuli, Amin K.; Gatebe, Charles K.; Wang, Jun; Wilcox, Eric M.; Lee, Jejung; Adegoke, Jimmy;

Detecting and quantifying the extent of desertification and its impact in the semi-arid Sub-Saharan Africa: A case study of the Upper East Region, Ghana

Science.gov (United States)

Owusu, Alex B.

The semi-arid Sub-Saharan region of Africa is in a state of permanent instability at a variety of spatio-temporal momentum. Efforts at sustaining and managing this fragile but all-important ecosystem and its processes require collecting, storing and analyzing multispatial and temporal data that are accurate and continuously updated in terms of changes (degradation), types and magnitude of change. Remote sensing techniques based on multispectral satellite-acquired data (AVHRR, Landsat TM and ETM+) have demonstrated an immense potential as a means to detect, quantify, monitor and map these changes. However, much of what satellite sensors can detect and capture, especially in the form of vegetation index (NDVI), do not tell the entire story about land degradation. This research used multispectral remote sensing data from three sensors (AVHRR, Landsat TM, and ETM+ and IKONOS) to detect and quantify the spatio-temporal land degradation (desertification) to validate the local observation and perception of desertification. The study also analyzes data on crop production in search of evidence proving or disproving degradation in the semi-arid sahel-sudan savannah transitional vegetation zone of the UER, Ghana. Multispectral satellite-acquired NDVI, from AVHRR, Landsat TM & ETM+, show that vegetation greenness is on the ascendancy, although there are pockets (localized degradation) signs of severe land degradation; field evidence suggests that the increasing NDVI is caused by vegetation succession where locally adapted horsetail grasses have been displaced by environmentally efficient, short-lived, quick maturing and dense grasses due to excessive burning, rapid population growth and inappropriate development policies. Local people's perceptions, supported by crop production data, suggest extensive land degradation. Other evidence includes food insecurity, diseases, rainfall variability and land extensification to marginal lands. Convergence of evidence suggests that

Spatiotemporal Variability of Land Surface Phenology in China from 2001–2014

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Zhaohui Luo

2017-01-01

Full Text Available Land surface phenology is a highly sensitive and simple indicator of vegetation dynamics and climate change. However, few studies on spatiotemporal distribution patterns and trends in land surface phenology across different climate and vegetation types in China have been conducted since 2000, a period during which China has experienced remarkably strong El Niño events. In addition, even fewer studies have focused on changes of the end of season (EOS and length of season (LOS despite their importance. In this study, we used four methods to reconstruct Moderate Resolution Imaging Spectroradiometer (MODIS Enhanced Vegetation Index (EVI dataset and chose the best smoothing result to estimate land surface phenology. Then, the phenophase trends were analyzed via the Mann-Kendall method. We aimed to assess whether trends in land surface phenology have continued since 2000 in China at both national and regional levels. We also sought to determine whether trends in land surface phenology in subtropical or high altitude areas are the same as those observed in high latitude areas and whether those trends are uniform among different vegetation types. The result indicated that the start of season (SOS was progressively delayed with increasing latitude and altitude. In contrast, EOS exhibited an opposite trend in its spatial distribution, and LOS showed clear spatial patterns over this region that decreased from south to north and from east to west at a national scale. The trend of SOS was advanced at a national level, while the trend in Southern China and the Tibetan Plateau was opposite to that in Northern China. The transaction zone of the SOS within Northern China and Southern China occurred approximately between 31.4°N and 35.2°N. The trend in EOS and LOS were delayed and extended, respectively, at both national and regional levels except that of LOS in the Tibetan Plateau, which was shortened by delayed SOS onset more than by delayed EOS onset. The

Modeling Phosphorous Losses from Seasonal Manure Application Schemes

Science.gov (United States)

Menzies, E.; Walter, M. T.

2015-12-01

Excess nutrient loading, especially nitrogen and phosphorus, to surface waters is a common and significant problem throughout the United States. While pollution remediation efforts are continuously improving, the most effective treatment remains to limit the source. Appropriate timing of fertilizer application to reduce nutrient losses is currently a hotly debated topic in the Northeastern United States; winter spreading of manure is under special scrutiny. We plan to evaluate the loss of phosphorous to surface waters from agricultural systems under varying seasonal fertilization schemes in an effort to determine the impacts of fertilizers applied throughout the year. The Cayuga Lake basin, located in the Finger Lakes region of New York State, is a watershed dominated by agriculture where a wide array of land management strategies can be found. The evaluation will be conducted on the Fall Creek Watershed, a large sub basin in the Cayuga Lake Watershed. The Fall Creek Watershed covers approximately 33,000 ha in central New York State with approximately 50% of this land being used for agriculture. We plan to use the Soil and Water Assessment Tool (SWAT) to model a number of seasonal fertilization regimes such as summer only spreading and year round spreading (including winter applications), as well as others. We will use the model to quantify the phosphorous load to surface waters from these different fertilization schemes and determine the impacts of manure applied at different times throughout the year. More detailed knowledge about how seasonal fertilization schemes impact phosphorous losses will provide more information to stakeholders concerning the impacts of agriculture on surface water quality. Our results will help farmers and extensionists make more informed decisions about appropriate timing of manure application for reduced phosphorous losses and surface water degradation as well as aid law makers in improving policy surrounding manure application.

Investigation of Seasonal Landscape Freeze/Thaw Cycles in Relation to Cloud Structure in the High Northern Latitudes

Science.gov (United States)

Smith, Cosmo

2011-01-01

The seasonal freezing and thawing of Earth's cryosphere (the portion of Earth's surface permanently or seasonally frozen) has an immense impact on Earth's climate as well as on its water, carbon and energy cycles. During the spring, snowmelt and the transition between frozen and non-frozen states lowers Earth's surface albedo. This change in albedo causes more solar radiation to be absorbed by the land surface, raising surface soil and air temperatures as much as 5 C within a few days. The transition of ice into liquid water not only raises the surface humidity, but also greatly affects the energy exchange between the land surface and the atmosphere as the phase change creates a latent energy dominated system. There is strong evidence to suggest that the thawing of the cryosphere during spring and refreezing during autumn is correlated to local atmospheric conditions such as cloud structure and frequency. Understanding the influence of land surface freeze/thaw cycles on atmospheric structure can help improve our understanding of links between seasonal land surface state and weather and climate, providing insight into associated changes in Earth's water, carbon, and energy cycles that are driven by climate change.Information on both the freeze/thaw states of Earth's land surface and cloud characteristics is derived from data sets collected by NOAA's Special Sensor Microwave/Imager (SSM/I), the Advanced Microwave Scanning Radiometer on NASA's Earth Observing System(AMSR-E), NASA's CloudSat, and NASA's SeaWinds-on-QuickSCAT Earth remote sensing satellite instruments. These instruments take advantage of the microwave spectrum to collect an ensemble of atmospheric and land surface data. Our analysis uses data from radars (active instruments which transmit a microwave signal toward Earth and measure the resultant backscatter) and radiometers (passive devices which measure Earth's natural microwave emission) to accurately characterize salient details on Earth's surface

NEW SEASON NEW HOPES: OFF-SEASON OPTIMISM

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Oguz Ersan

2017-12-01

Full Text Available While literature on the relation between on-field sports performance and stock returns is ample, there is very limited evidence on off-season stage. Constituting around 3 months, off-seasons do not only occupy a significant part of the year but also represent totally different characteristics than on-seasons. They lack the periodic, unambiguous news events in on-seasons (match results, instead they are associated with highly uncertain transfer news and rumors. We show that this distinction has several impacts on the stock market performances of soccer clubs. Most notably, off-seasons generate substantially higher (excess returns. After controlling for other variables, the estimated effect of off-season periods is as high as 38.75%, annually. In line with several seminal studies, we link this fact to increased optimism and betting behavior through uncertain periods; and periods prior to the start of a new calendar (in our case, new season. For all of the examined 7 clubs (3 from Italy and 4 from Turkey, mean excess returns over the market are positive (negative in off-seasons (on-seasons. On-seasons are associated with increased trading activity due to more frequent news. Stocks of Italian clubs are evidently more volatile through off-seasons while volatility results for the stocks of Turkish clubs are not consistent.

Crop Condition Assessment with Adjusted NDVI Using the Uncropped Arable Land Ratio

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Miao Zhang

2014-06-01

Full Text Available Crop condition assessment in the early growing stage is essential for crop monitoring and crop yield prediction. A normalized difference vegetation index (NDVI-based method is employed to evaluate crop condition by inter-annual comparisons of both spatial variability (using NDVI images and seasonal dynamics (based on crop condition profiles. Since this type of method will generate false information if there are changes in crop rotation, cropping area or crop phenology, information on cropped/uncropped arable land is integrated to improve the accuracy of crop condition monitoring. The study proposes a new method to retrieve adjusted NDVI for cropped arable land during the growing season of winter crops by integrating 16-day composite Moderate Resolution Imaging Spectroradiometer (MODIS reflectance data at 250-m resolution with a cropped and uncropped arable land map derived from the multi-temporal China Environmental Satellite (Huan Jing Satellite charge-coupled device (HJ-1 CCD images at 30-m resolution. Using the land map’s data on cropped and uncropped arable land, a pixel-based uncropped arable land ratio (UALR at 250-m resolution was generated. Next, the UALR-adjusted NDVI was produced by assuming that the MODIS reflectance value for each pixel is a linear mixed signal composed of the proportional reflectance of cropped and uncropped arable land. When UALR-adjusted NDVI data are used for crop condition assessment, results are expected to be more accurate, because: (i pixels with only uncropped arable land are not included in the assessment; and (ii the adjusted NDVI corrects for interannual variation in cropping area. On the provincial level, crop growing profiles based on the two kinds of NDVI data illustrate the difference between the regular and the adjusted NDVI, with the difference depending on the total area of uncropped arable land in the region. The results suggested that the proposed method can be used to improve the assessment of

Influenza Seasonal Summary, 2014-2015 Season

Science.gov (United States)

2015-08-14

Influenza Seasonal Summarv 2014-2015 Season EpiData Center Department Communicable Disease Division NMCPHC-EDC-TR-394-2015 REPORT DOCUMENTATION... Influenza Seasonal Summary, 2014-2015 Season Sb. GRANT NUMBER $c. PROGRAM ELEMENT NUMBER 6. AUTHORjS) Sd. PROJECT NUMBER Ashleigh K McCabe, Kristen R...SUPPLEMENTARY NOTES 1<l. ABSTRACT This report summartzes influenza activity among Department of Navy (DON) and Depar1ment of Defense (DOD

Impact of climate change on mid-twenty-first century growing seasons in Africa

Energy Technology Data Exchange (ETDEWEB)

Cook, Kerry H.; Vizy, Edward K. [The University of Texas at Austin, Department of Geological Sciences, Jackson School of Geosciences, Austin, TX (United States)

2012-12-15

Changes in growing seasons for 2041-2060 across Africa are projected using a regional climate model at 90-km resolution, and confidence in the predictions is evaluated. The response is highly regional over West Africa, with decreases in growing season days up to 20% in the western Guinean coast and some regions to the east experiencing 5-10% increases. A longer growing season up to 30% in the central and eastern Sahel is predicted, with shorter seasons in parts of the western Sahel. In East Africa, the short rains (boreal fall) growing season is extended as the Indian Ocean warms, but anomalous mid-tropospheric moisture divergence and a northward shift of Sahel rainfall severely curtails the long rains (boreal spring) season. Enhanced rainfall in January and February increases the growing season in the Congo basin by 5-15% in association with enhanced southwesterly moisture transport from the tropical Atlantic. In Angola and the southern Congo basin, 40-80% reductions in austral spring growing season days are associated with reduced precipitation and increased evapotranspiration. Large simulated reductions in growing season over southeastern Africa are judged to be inaccurate because they occur due to a reduction in rainfall in winter which is over-produced in the model. Only small decreases in the actual growing season are simulated when evapotranspiration increases in the warmer climate. The continent-wide changes in growing season are primarily the result of increased evapotranspiration over the warmed land, changes in the intensity and seasonal cycle of the thermal low, and warming of the Indian Ocean. (orig.)

Developing a Land Suitability Index for Agricultural uses in Dry Lands from Geologic Point of View Using GIS - a Case Study from Jordan

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Mohammmad Al Farajat

2015-05-01

Full Text Available DOI:10.17014/ijog.2.2.63-76In the context of the study, a Multi-criteria evaluation (MCE in GIS was used in developing suitability index to optimize suitable lands for agricultural uses and seasonal farming in dry lands from geologic point of view. This study was performed in the areas between Mafraq and Zarqa Cities in Jordan which are classified as arid lands. The study aims at protecting groundwater from pollution, reducing soil salting, reducing irrigation water loss caused by evaporation, and increasing crop productivity. The geo-environmental parameters of the named area including geology, groundwater depths, soil depths and textures, climatic conditions, topographic settings, and groundwater vulnerability conditions were mapped and converted into layers with special rates, given weights, and then modeled using the multi criteria evaluation (MCE option, using Decision Making Modeling in IDRISI (GIS software to reach at the best choice of lands for agricultural activities, and also to determine which of these lands are suitable for summer farming and which are suitable for winter farming.

Reproductive characterization of three species of Giant African land ...

African Journals Online (AJOL)

Administrator

2011-09-05

Sep 5, 2011 ... wild lay eggs about two to three times per season. (Cobbinah et al., 2008). ... courtship and copulatory duration of three (3) species of. Giant African land ... digital stop watch and the snails were observed from 6.00 pm to. 7.00 am daily ..... trail following in apple snail, Pomacea canaliculata. J. Mollusc stud.

Simulation of water management for fodder beet to reduce yield losses under late season drought

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T. Noreldin

2016-12-01

Full Text Available The objectives of this study were to calibrate CropSyst model for fodder beet grown under full and late season drought and to use the simulation results to analyze the relationship between irrigation amount and yield, as well as in water management to reduce yield losses under full and late season drought. For this reason, two field experiments were implemented at El-Serw Agricultural Research Station in Demiatte governorate, during 2011/12 and 2012/13 growing seasons. Two irrigation treatments were studied: full irrigation and late season drought. The model was calibrated using the data obtained from the two seasons. Results indicated that the reduction in fodder beet yield under late season drought was 11 and 12% in 2011/12 and 2012/13 growing seasons, respectively. Calibration of CropSyst revealed that the percentage of difference between measured and predicted values were low in both growing seasons. The results also indicated that changing irrigation schedule after examining water stress index under full and late season drought led to increase in fodder beet yield, as well as water and land productivity. Thus, CropSyst model can give insight into when to apply irrigation water to minimize yield losses under late season drought.

Anthropogenic Land-use Change and the Dynamics of Amazon Forest Biomass

Science.gov (United States)

Laurance, William F.

2004-01-01

This project was focused on assessing the effects of prevailing land uses, such as habitat fragmentation, selective logging, and fire, on biomass and carbon storage in Amazonian forests, and on the dynamics of carbon sequestration in regenerating forests. Ancillary goals included developing GIs models to help predict the future condition of Amazonian forests, and assessing the effects of anthropogenic climate change and ENS0 droughts on intact and fragmented forests. Ground-based studies using networks of permanent plots were linked with remote-sensing data (including Landsat TM and AVHRR) at regional scales, and higher-resolution techniques (IKONOS imagery, videography, LIDAR, aerial photographs) at landscape and local scales. The project s specific goals were quite eclectic and included: Determining the effects of habitat fragmentation on forest dynamics, floristic composition, and the various components of above- and below-ground biomass. Assessing historical and physical factors that affect trajectories of forest regeneration and carbon sequestration on abandoned lands. Extrapolating results from local studies of biomass dynamics in fragmented and regenerating forests to landscape and regional scales in Amazonia, using remote sensing and GIS. Testing the hypothesis that intact Amazonian forests are functioning as a significant carbon sink. Examining destructive synergisms between forest fragmentation and fire. Assessing the short-term impacts of selective logging on aboveground biomass. Developing GIS models that integrate current spatial data on forest cover, deforestation, logging, mining, highway and roads, navigable rivers, vulnerability to wild fires, protected areas, and existing and planned infrastructure projects, in an effort to predict the future condition of Brazilian Amazonian forests over the next 20-25 years. Devising predictive spatial models to assess the influence of varied biophysical and anthropogenic predictors on Amazonian deforestation.

Comparative assessment of runoff characteristics under different land use patterns within a Himalayan watershed

Science.gov (United States)

Rai, S. C.; Sharma, E.

1998-10-01

Large quantities of sediments leave the Himalaya through its rivers. These rivers are charged with sediments depending on the types of land use in the watersheds. Land use/cover change and hydrology was studied in a watershed in the Sikkim Himalaya. The land use change from forest and agroforestry to open agriculture has increased by 11% from 1988 to 1992. During the same period substantial areas of dense mixed forests have been converted to open mixed and degraded forests as a result of high pressure on natural resources. Stream flow was highest in the rainy season and lowest in summer season in all the streams and all the three years (1994-1997) of the study. The water quality of streams from different microwatersheds varied significantly between seasons and streams. Sediment and nutrient loss was estimated in microwatersheds and soil loss from the total watershed ranged from 4·18 to 8·82 t ha-1 yr-1 during the three-year period of study. The annual total nitrogen loss estimated at the watershed outlet was at a rate of 33 kg ha-1, organic carbon 267 kg ha-1 and total phosphorus 5 kg ha-1. This study suggests that the upland microwatersheds can be hydroecologically sustainable only if good forest cover and dense forests with large cardamom-based agroforestry are maintained.

Land use and desertification in the Binh Thuan Province of Southeastern Vietnam: mitigation and adaptation options now and under climate change

Science.gov (United States)

Gobin, A.; Le Trinh, H.; Pham Ha, L.; Hens, L.

2012-04-01

Desertification and drought affects approximately 300,000 ha of land in the southeastern provinces of Vietnam, much of which is located on agricultural land and forest in the Binh Thuan Province. The methodology for analysing mitigation and adaptation options follows a chain of risk approach that includes a spatio-temporal characterisation of (1) the hazard, (2) the bio-physical and socio-economic impact, (3) the vulnerability to different activities as related to land uses, and (4) risk management options. The present forms of land degradation include sand dune formation and severe erosion (63%), degradation due to laterisation (14%), salinisation (13%), and rock outcrops (10%). The climate is characterized by a distinct dry season with high temperatures, a lot of sunshine and a warm land wind resulting in high evapotranspiration rates. Delays in the onset of the rainy season, e.g. with 20 days in 2010, cause a shift in the growing season. Damages due to drought are estimated at hundreds billion VND (US 1 = VND 20,8900) and contribute to poverty in the rural areas. The current risk-exposure is exacerbated further by climate change. Combined effects of desertification and climate change cause increased degradation of natural resources including land cover. At the same time land use changes are crucial in influencing responses to climate change and desertification. A further SWOT analysis combined with spatio-temporal analysis for each of the major sectors (agriculture, forestry and nature protection, urban and rural development, water resources and fisheries, industry) demonstrates a series of adaptation and mitigation options. Land is a valuable and limited resource. An integrated approach to land use and management is therefore essential to combat environmental hazards such as desertification and climate change.

Characterization of Land Surfaces with Satellite-borne Sensor

Science.gov (United States)

Qiao, Y.

Hot groundwater is a kind of valuable natural resources to be explored utilized. Shanxi Province, located in the eastern Loess Plateau of China, is rich in geothermal resources, most of which was found in irrigation well drilling or geological survey. Basic study is weak. Now new developed Remote Sensing technique provides geothermal study with an advanced way. Air-RS information of thermal infrared and dada from thermal channel of Meteorological Landset AVHRR has been used widely. A thermal infrared channel (TM6) was installed in the U.S. second Landset, Its resolving power of space is as high as 120m, 10 times more than one of AVHRR. A Landset earth recourses launched by China and Brazil (CBERS-1) in 1999, including a spectrum of thermal infrared. It is paid a great interested and attention to survey geothermal resources using thermal infrared. This article is a brief introduction of finding hot groundwater with on the bases of differences of thermal radiation of objects reflected by thermal infrared in the Landset, and treated with HIS colors changes. This study provides an advanced way widely used to exploit hot groundwater and to promote the development of tourism and geothermal medical in China.

Land-use regression panel models of NO2 concentrations in Seoul, Korea

Science.gov (United States)

Kim, Youngkook; Guldmann, Jean-Michel

2015-04-01

Transportation and land-use activities are major air pollution contributors. Since their shares of emissions vary across space and time, so do air pollution concentrations. Despite these variations, panel data have rarely been used in land-use regression (LUR) modeling of air pollution. In addition, the complex interactions between traffic flows, land uses, and meteorological variables, have not been satisfactorily investigated in LUR models. The purpose of this research is to develop and estimate nitrogen dioxide (NO2) panel models based on the LUR framework with data for Seoul, Korea, accounting for the impacts of these variables, and their interactions with spatial and temporal dummy variables. The panel data vary over several scales: daily (24 h), seasonally (4), and spatially (34 intra-urban measurement locations). To enhance model explanatory power, wind direction and distance decay effects are accounted for. The results show that vehicle-kilometers-traveled (VKT) and solar radiation have statistically strong positive and negative impacts on NO2 concentrations across the four seasonal models. In addition, there are significant interactions with the dummy variables, pointing to VKT and solar radiation effects on NO2 concentrations that vary with time and intra-urban location. The results also show that residential, commercial, and industrial land uses, and wind speed, temperature, and humidity, all impact NO2 concentrations. The R2 vary between 0.95 and 0.98.

Lidar observed seasonal variation of vertical canopy structure in the Amazon evergreen forests

Science.gov (United States)

Tang, H.; Dubayah, R.

2017-12-01

Both light and water are important environmental factors governing tree growth. Responses of tropical forests to their changes are complicated and can vary substantially across different spatial and temporal scales. Of particular interest is the dry-season greening-up of Amazon forests, a phenomenon undergoing considerable debates whether it is real or a "light illusion" caused by artifacts of passive optical remote sensing techniques. Here we analyze seasonal dynamic patterns of vertical canopy structure in the Amazon forests using lidar observations from NASA's Ice, Cloud, and and land Elevation Satellite (ICESat). We found that the net greening of canopy layer coincides with the wet-to-dry transition period, and its net browning occurs mostly at the late dry season. The understory also shows a seasonal cycle, but with an opposite variation to canopy and minimal correlation to seasonal variations in rainfall or radiation. Our results further suggest a potential interaction between canopy layers in the light regime that can optimize the growth of Amazon forests during the dry season. This light regime variability that exists in both spatial and temporal domains can better reveal the dry-season greening-up phenomenon, which appears less obvious when treating the Amazon forests as a whole.

Influence of agricultural land-use and pesticides on benthic macroinvertebrate assemblages in an agricultural river basin in southeast Brazil

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M Egler

Full Text Available Land-use alterations and pesticide run-offs are among the main causes for impairment in agricultural areas. We evaluated the influence of different land-uses (forest, pasture and intensive agriculture on the water quality and on benthic macroinvertebrate assemblages on three occasions: in the dry season, wet season and at the end of the wet season. Macroinvertebrates responded to this gradient of impairment: agricultural sites had significantly lower richness numbers than forested and pasture sites, and all major invertebrate groups were significantly affected. Most taxa found in forested sites were found in pasture sites, but often with lower densities. In this case, the loss of habitats due to sedimentation and the lower complexity of substrates seem to be the disruptive force for the macroinvertebrate fauna.

77 FR 75896 - Atlantic Highly Migratory Species; 2013 Atlantic Shark Commercial Fishing Season

Science.gov (United States)

2012-12-26

... the non-sandbar large coastal shark quotas and retention limits in 2013 and asked for the reasoning... geographical distribution of non-sandbar large coastal shark landings in the Atlantic throughout the season... the 2006 Consolidated HMS FMP on EFH, we reviewed the geographical range of all HMS and analyzed the...

Spatio-temporal variability of land use/land cover change (LULCC within the Huron River: Effects on stream flows

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Cheyenne Lei

Full Text Available We investigated possible influences of land use/land cover change (LULCC and precipitation on spatiotemporal changes in extreme stream flows within the watershed of the Huron River Basin during the summer seasons from 1992 to 2011. Within the basin, the urban landscape increased from 8% to 16% during the study period, while forest and agricultural lands declined by 7%. There was an increase in landscape heterogeneity within the watershed that varied from 1.21% in 1992 to 1.34% in 2011, with agricultural practices and forest regions competing due to the expansion of varying intensities of urban development. Normalized stream discharge from multiple subwatersheds increased over time, with an average increase from 0.21 m3 s−1 m to 1.64 m3 s−1 m over the study period. Land use and precipitation affected stream discharge, with increasing urban development exhibiting a 37% chance of affecting extreme stream flows within the watershed. More importantly, much of the precipitation observed within the watershed temporally affected stream discharge based on expansion of urban settlement within the basin. This caused a higher likelihood of flashiness, as runoff is more concentrated and stream flow became more variable. We concluded that, within the watersheds of the Huron River, LULCC is the major determinant of increased stream flow and potential flooding. Keywords: Urbanization, Land use, Land cover, Climate, Hydrology, ArcGIS, FRAGSTATS

VARIATIONS OF MICROORGANISM CONCENTRATIONS IN URBAN STORMWATER RUNOFF WITH LAND USE AND SEASONS

Science.gov (United States)

Stormwater runoff samples were collected from outfalls draining small municipal separate storm sewer systems. The samples were collected from three different land use areas based on local designation (high-density residential, low-density residential, and landscaped commercial)....

Aplicação de índices das condições de vegetação no monitoramento em tempo quase real da seca em Moçambique usando NOAA_AVHRR- NDVI

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Paulo Alberto Covele

2011-12-01

Full Text Available Este artigo tem por objetivo aplicar diferentes índices das condições de vegetação e avaliar suas diferenças e aptidão no monitoramento da distribuição espacial e temporal da seca em Moçambique com base em imagens NDVI da NOAA- AVHRR. Para tanto, avalia as differenças de aptidão dos índices das condições de vegetação especialmente o Índice das Condições de Vegetação (Vegetation Condition Index- VCI, Índice Padronizado de Vegetação (Standardized Vegetation Index- SVI e o Indicador de Productividade da Vegetação (Vegetation Productivity Indicator- VPI no monitoramento da seca em Moçambique. Estes índices são derivados a partir de imagens da Diferença Normalizada do Índice da Vegetação (Normalized Difference Vegetation Index- NDVI de 1981 a 2005, produzidas a partir dos canais 1 e 2 do sensor Advanced Very Higher Resolution Radiometer (AVHRR a bordo dos satélites da National Oceanic and Atmospheric Administration (NOAA.

Physiological and ecological consequences of sleeping-site selection by the Galapagos land iguana (Conolophus pallidus)

Energy Technology Data Exchange (ETDEWEB)

Christian, K.A.; Tracy, C.R.

1984-01-01

Field observations and biophysical models were combined to analyze sleeping-site selection by Galapagos land iguanas (Conolophus pallidus). Iguanas slept in different kinds of sleeping sites during different seasons. In the coolest season (garua), adult land iguanas were found in sleeping sites that were warmer than the coolest sites available. This may be because the garua season (cool, overcast, and foggy) is a time when environmental conditions mitigate against rapid warm-up in the mornings, so lizards may regulate nighttime body temperatures so that it is easier to warm up to preferred daytime body temperatures. In the warmest season, adult iguanas were found in the coolest sleeping sites available. This observation is consistent with hypotheses of voluntary hypothermia, which can be advantageous in energy conservation and in avoiding detrimental effects associated with maintenance of constant body temperatures throughout the day and night. Juvenile iguanas were found sleeping in rock crevices regardless of the ambient thermal environments. Such sites are likely to be important as refugia for this life stage, which, unlike the adult stage, is vulnerable to predation. It was concluded that selection of sleeping sites is a process that may help in avoidance of predation, optimization of body temperature at the end of the sleeping period, and reduction of metabolic costs during sleeping. The importance of some of these factors may change with the thermal milieu (e.g., season).

Influence of land-use patterns on benthic diatom communities and ...

African Journals Online (AJOL)

The objective of this study was to determine the effects of land-use patterns on both diatom community composition and water quality in tropical streams during the dry season. Benthic diatom collections and water quality sampling were done 4 times at 10 sites. A suite of environmental variables that varied with human ...

Hydrological responses of a watershed to historical land use evolution and future land use scenarios under climate change conditions

Directory of Open Access Journals (Sweden)

R. Quilbé

2008-01-01

Full Text Available Watershed runoff is closely related to land use but this influence is difficult to quantify. This study focused on the Chaudière River watershed (Québec, Canada and had two objectives: (i to quantify the influence of historical agricultural land use evolution on watershed runoff; and (ii to assess the effect of future land use evolution scenarios under climate change conditions (CC. To achieve this, we used the integrated modeling system GIBSI. Past land use evolution was constructed using satellite images that were integrated into GIBSI. The general trend was an increase of agricultural land in the 80's, a slight decrease in the beginning of the 90's and a steady state over the last ten years. Simulations showed strong correlations between land use evolution and water discharge at the watershed outlet. For the prospective approach, we first assessed the effect of CC and then defined two opposite land use evolution scenarios for the horizon 2025 based on two different trends: agriculture intensification and sustainable development. Simulations led to a wide range of results depending on the climatologic models and gas emission scenarios considered, varying from a decrease to an increase of annual and monthly water discharge. In this context, the two land use scenarios induced opposite effects on water discharge and low flow sequences, especially during the growing season. However, due to the large uncertainty linked to CC simulations, it is difficult to conclude that one land use scenario provides a better adaptation to CC than another. Nevertheless, this study shows that land use is a key factor that has to be taken into account when predicting potential future hydrological responses of a watershed.

Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods

Science.gov (United States)

Xian, George; Homer, Collin G.; Fry, Joyce

2009-01-01

The recent release of the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001, which represents the nation's land cover status based on a nominal date of 2001, is widely used as a baseline for national land cover conditions. To enable the updating of this land cover information in a consistent and continuous manner, a prototype method was developed to update land cover by an individual Landsat path and row. This method updates NLCD 2001 to a nominal date of 2006 by using both Landsat imagery and data from NLCD 2001 as the baseline. Pairs of Landsat scenes in the same season in 2001 and 2006 were acquired according to satellite paths and rows and normalized to allow calculation of change vectors between the two dates. Conservative thresholds based on Anderson Level I land cover classes were used to segregate the change vectors and determine areas of change and no-change. Once change areas had been identified, land cover classifications at the full NLCD resolution for 2006 areas of change were completed by sampling from NLCD 2001 in unchanged areas. Methods were developed and tested across five Landsat path/row study sites that contain several metropolitan areas including Seattle, Washington; San Diego, California; Sioux Falls, South Dakota; Jackson, Mississippi; and Manchester, New Hampshire. Results from the five study areas show that the vast majority of land cover change was captured and updated with overall land cover classification accuracies of 78.32%, 87.5%, 88.57%, 78.36%, and 83.33% for these areas. The method optimizes mapping efficiency and has the potential to provide users a flexible method to generate updated land cover at national and regional scales by using NLCD 2001 as the baseline.

Remote sensing data in Rangeland assessment and monitoring

International Nuclear Information System (INIS)

Hamid, Amna Ahmed; Ali, Mohamed M.

1999-01-01

The main objective of the paper is to illustrate the potential of remote sensing data in the study and monitoring of environmental changes in western Sudan where considerable part of the area is under rangeland use. Data from NOAA satellite AVHRR sensor as well as thematic mapper Tm was used to assess the environment of the area during 1982-1997. The AVHRR data was processed into vegetation index (NDVI) images. Image analysis and classification was done using image display and analysis (IDA) GIS method to study vegetation condition in time series. The obtained information from field observations. The result showed high correlation between the information the work concluded the followings: NDVI images and thematic mapper data proved to be efficient in environment change analysis. NOAA AVHRR satellite data can provide an early-warning indicator of an approaching disaster. Remote sensing integrated into a GIS can contribute effectively to improve land management through better understanding of environment variability.(Author)

Multisensor remote sensing data and GIS techniques for monitoring preservation areas - A case study

International Nuclear Information System (INIS)

Shimabukuro, Y.E.; Lee, D.C.L.; Dos Santos, J.R.

1992-01-01

The capability of remote sensing and Geographic Information System techniques for detecting and monitoring the anthropic alterations which sometimes occur in preservation areas is discussed. Attention is given to the Emas National Park in the southwest Goias State, Brazil. TM/Landsat data from July 29, 1988 (before a fire that occurred there) and August 14, 1988, (after the fire) and AVHRR/NOAA data obtained in this period covered by TM images were used to monitor the biomass burning. The TM images were registered to a topographic map in order to compile a data base including information such as drainage, roads, elevation, and vegetation type for this park. Pixels classified as burned areas using band 3 of AVHRR images were overlayed on the map derived from the data base. The integration of elevation, TM multitemporal data, and information derived from AVHRR images is found to be a valuable tool for managers in detecting and evaluating damage and in monitoring the regeneration process of land cover. 15 refs

Ecological and pest-management implications of sex differences in scarab landing patterns on grape vines

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Mauricio González-Chang

2017-04-01

Full Text Available Background Melolonthinae beetles, comprising different white grub species, are a globally-distributed pest group. Their larvae feed on roots of several crop and forestry species, and adults can cause severe defoliation. In New Zealand, the endemic scarab pest Costelytra zealandica (White causes severe defoliation on different horticultural crops, including grape vines (Vitis vinifera. Understanding flight and landing behaviours of this pest can help inform pest management decisions. Methods Adult beetles were counted and then removed from 96 grape vine plants from 21:30 until 23:00 h, every day from October 26 until December 2, during 2014 and 2015. Also, adults were removed from the grape vine foliage at dusk 5, 10, 15, 20 and 25 min after flight started on 2015. Statistical analyses were performed using generalised linear models with a beta-binomial distribution to analyse proportions and with a negative binomial distribution for beetle abundance. Results By analysing C. zealandica sex ratios during its entire flight season, it is clear that the proportion of males is higher at the beginning of the season, gradually declining towards its end. When adults were successively removed from the grape vines at 5-min intervals after flight activity begun, the mean proportion of males ranged from 6–28%. The male proportion suggests males were attracted to females that had already landed on grape vines, probably through pheromone release. Discussion The seasonal and daily changes in adult C. zealandica sex ratio throughout its flight season are presented for the first time. Although seasonal changes in sex ratio have been reported for other melolonthines, changes during their daily flight activity have not been analysed so far. Sex-ratio changes can have important consequences for the management of this pest species, and possibly for other melolonthines, as it has been previously suggested that C. zealandica females land on plants that produce a

TIME SERIES CHARACTERISTIC ANALYSIS OF RAINFALL, LAND USE AND FLOOD DISCHARGE BASED ON ARIMA BOX-JENKINS MODEL

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Abror Abror

2014-01-01

Full Text Available Indonesia located in tropic area consists of wet season and dry season. However, in last few years, in river discharge in dry season is very little, but in contrary, in wet season, frequency of flood increases with sharp peak and increasingly great water elevation. The increased flood discharge may occur due to change in land use or change in rainfall characteristic. Both matters should get clarity. Therefore, a research should be done to analyze rainfall characteristic, land use and flood discharge in some watershed area (DAS quantitatively from time series data. The research was conducted in DAS Gintung in Parakankidang, DAS Gung in Danawarih, DAS Rambut in Cipero, DAS Kemiri in Sidapurna and DAS Comal in Nambo, located in Tegal Regency and Pemalang Regency in Central Java Province. This research activity consisted of three main steps: input, DAS system and output. Input is DAS determination and selection and searching secondary data. DAS system is early secondary data processing consisting of rainfall analysis, HSS GAMA I parameter, land type analysis and DAS land use. Output is final processing step that consisting of calculation of Tadashi Tanimoto, USSCS effective rainfall, flood discharge, ARIMA analysis, result analysis and conclusion. Analytical calculation of ARIMA Box-Jenkins time series used software Number Cruncher Statistical Systems and Power Analysis Sample Size (NCSS-PASS version 2000, which result in time series characteristic in form of time series pattern, mean square errors (MSE, root mean square ( RMS, autocorrelation of residual and trend. Result of this research indicates that composite CN and flood discharge is proportional that means when composite CN trend increase then flood discharge trend also increase and vice versa. Meanwhile, decrease of rainfall trend is not always followed with decrease in flood discharge trend. The main cause of flood discharge characteristic is DAS management characteristic, not change in

Influence of season, temperature, and photoperiod on growth of the land snail Helix aperta

NARCIS (Netherlands)

Benbellil-Tafoughalt, S.; Koene, J.M.

2015-01-01

Growth strategies are often plastic and influenced by environmental conditions. Terrestrial gastropods are particularly affected by seasonal and climatic variables, and growth rate and size at maturity are key traits in their life history. Therefore, we investigated juvenile growth of Helix aperta

Natural radioactivity of the atmosphere over the Indian land mass, inside deep mines, and over adjoining oceans

International Nuclear Information System (INIS)

Mishra, U.C.; Rangarajan, C.; Eapen, C.D.

1980-01-01

Measurements of the activities of short-lived radon and thoron daughters, long-lived RaD ( 210 Pb), and cosmic-ray produced 7 Be in the surface atmosphere of different regions of India and the neighboring seas are presented. The seasonal and geographical variations of the activities and the meteorological significance of these variations are also discussed. Over land, the natural activities due to radon and thoron daughters undergo an annual and diurnal cycle, which is an index of the variation in the vertical mixing of the surface atmosphere. Over the oceans the diurnal variations are not so pronounced as over the land. Detailed measurements at stationary positions over the Arabian Sea showed significant changes in radon which were in phase at all the positions. The levels of radon daughters in the Kolar Gold Field mines, the second deepest in the world, have been measured. Maximum values are about 10 pCi/liter, and the daughter products are in a state of high disequilibrium. RaD( 210 Pb) over the land undergoes a seasonal cycle similar to radon with winter maximums and summer minimums, indicating that it is mainly supported from ambient radon. Beryllium-7 undergoes a seasonal cycle similar to stratospheric fallout with reduced amplitude. This can be interpreted as being due to the presence of a seasonally dependent stratospheric 7 Be mixing with a constant level of 7 Be produced within the troposphere itself

Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980-2004)

Science.gov (United States)

Wang, Bin; Lee, June-Yi; Kang, In-Sik; Shukla, J.; Park, C.-K.; Kumar, A.; Schemm, J.; Cocke, S.; Kug, J.-S.; Luo, J.-J.; Zhou, T.; Wang, B.; Fu, X.; Yun, W.-T.; Alves, O.; Jin, E. K.; Kinter, J.; Kirtman, B.; Krishnamurti, T.; Lau, N. C.; Lau, W.; Liu, P.; Pegion, P.; Rosati, T.; Schubert, S.; Stern, W.; Suarez, M.; Yamagata, T.

2009-07-01

Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial-temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80-90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.

Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980-2004)

Energy Technology Data Exchange (ETDEWEB)

Wang, Bin; Lee, June-Yi; Fu, X.; Liu, P. [University of Hawaii, Department of Meteorology and International Pacific Research Center, IPRC, School of Ocean and Earth Science and Technology, Honolulu, HI (United States); Kang, In-Sik; Kug, J.S. [Seoul National University, School of Earth and Environmental Sciences, Seoul (Korea); Shukla, J.; Jin, E.K.; Kinter, J.; Kirtman, B. [George Mason University and COLA, Climate Dynamics Program, Calverton, MD (United States); Park, C.K. [APEC Climate Center, Busan (Korea); Kumar, A.; Schemm, J. [Climate Prediction Center/NCEP, Camp Springs, MD (United States); Cocke, S.; Krishnamurti, T. [Florida State University, Tallahassee, FL (United States); Luo, J.J. [Frontier Research Center for Global Chnage, Yokohama (Japan); Zhou, T.; Wang, B. [Chinese Academy of Sciences, LASG/Institute of Atmospheric Physics, Beijing (China); Yun, W.T. [Korean Meteorological Administration, Seoul (Korea); Alves, O. [Bureau of Meteorology Research Center, Melburne (Australia); Lau, N.C.; Rosati, T.; Stern, W. [Princeton University, Geophysical Fluid Dynamics Laboratory/NOAA, Princeton, NJ (United States); Lau, W.; Pegion, P.; Schubert, S.; Suarez, M. [Godard Space Flight Center/NASA, Greenbelt, MD (United States)

2009-07-15

Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial-temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80-90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120 E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Nino 3.4 SST variation. The forecasts for 2 m air temperature are better in El Nino years than in La Nina years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model's slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework. (orig.)

Crop Yield Predictions - High Resolution Statistical Model for Intra-season Forecasts Applied to Corn in the US

Science.gov (United States)

Cai, Y.

2017-12-01

Accurately forecasting crop yields has broad implications for economic trading, food production monitoring, and global food security. However, the variation of environmental variables presents challenges to model yields accurately, especially when the lack of highly accurate measurements creates difficulties in creating models that can succeed across space and time. In 2016, we developed a sequence of machine-learning based models forecasting end-of-season corn yields for the US at both the county and national levels. We combined machine learning algorithms in a hierarchical way, and used an understanding of physiological processes in temporal feature selection, to achieve high precision in our intra-season forecasts, including in very anomalous seasons. During the live run, we predicted the national corn yield within 1.40% of the final USDA number as early as August. In the backtesting of the 2000-2015 period, our model predicts national yield within 2.69% of the actual yield on average already by mid-August. At the county level, our model predicts 77% of the variation in final yield using data through the beginning of August and improves to 80% by the beginning of October, with the percentage of counties predicted within 10% of the average yield increasing from 68% to 73%. Further, the lowest errors are in the most significant producing regions, resulting in very high precision national-level forecasts. In addition, we identify the changes of important variables throughout the season, specifically early-season land surface temperature, and mid-season land surface temperature and vegetation index. For the 2017 season, we feed 2016 data to the training set, together with additional geospatial data sources, aiming to make the current model even more precise. We will show how our 2017 US corn yield forecasts converges in time, which factors affect the yield the most, as well as present our plans for 2018 model adjustments.

Drought Dynamics and Vegetation Productivity in Different Land Management Systems of Eastern Cape, South Africa—A Remote Sensing Perspective

Directory of Open Access Journals (Sweden)

Valerie Graw

2017-09-01

Full Text Available Eastern Cape Province in South Africa has experienced extreme drought events during the last decade. In South Africa, different land management systems exist belonging to two different land tenure classes: commercial large scale farming and communal small-scale subsistence farming. Communal lands are often reported to be affected by land degradation and drought events among others considered as trigger for this process. Against this background, we analyzed vegetation response to drought in different land management and land tenure systems through assessing vegetation productivity trends and monitoring the intensity, frequency and distribution of the drought hazard in grasslands and communal and commercial croplands during drought and non-drought conditions. For the observation period 2000–2016, we used time series of 250 m Vegetation Condition Index (VCI based on the Moderate Resolution Imaging Spectroradiometer (MODIS Enhanced Vegetation Index (EVI and Climate Hazard Group InfraRed Precipitation with Station data (CHIRPS precipitation data with 5 km resolution. For the assessment of vegetation dynamics, we: (1 analyzed vegetation productivity in Eastern Cape over the last 16 years with EVI; (2 analyzed the impact of drought events on vegetation productivity in grasslands as well as commercial and communal croplands; and (3 compared precipitation-vegetation dynamics between the drought season 2015/2016 and the non-drought season 2011/2012. Change in total annual vegetation productivity could detect drought years while drought dynamics during the season could be rather monitored by the VCI. Correlation of vegetation condition and precipitation indicated areas experiencing significant vegetation productivity trends showing low and even negative correlation coefficients indicating other drivers for productivity change and drought impact besides rainfall.

Land application of mine water causes minimal uranium loss offsite in the wet-dry tropics: Ranger Uranium Mine, Northern Territory, Australia

International Nuclear Information System (INIS)

Mumtaz, Saqib; Streten, Claire; Parry, David L.; McGuinness, Keith A.; Lu, Ping; Gibb, Karen S.

2015-01-01

Ranger Uranium Mine (RUM) is situated in the wet-dry tropics of Northern Australia. Land application (irrigation) of stockpile (ore and waste) runoff water to natural woodland on the mine lease is a key part of water management at the mine. Consequently, the soil in these Land Application Areas (LAAs) presents a range of uranium (U) and other metals concentrations. Knowledge of seasonal and temporal changes in soil U and physicochemical parameters at RUM LAAs is important to develop suitable management and rehabilitation strategies. Therefore, soil samples were collected from low, medium, high and very high U sites at RUM LAAs for two consecutive years and the effect of time and season on soil physicochemical parameters particularly U and other major solutes applied in irrigation water was measured. Concentrations of some of the solutes applied in the irrigation water such as sulphur (S), iron (Fe) and calcium (Ca) showed significant seasonal and temporal changes. Soil S, Fe and Ca concentration decreased from year 1 to year 2 and from dry to wet seasons during both years. Soil U followed the same pattern except that we recorded an increase in soil U concentrations at most of the RUM LAAs after year 2 wet season compared to year 2 dry season. Thus, these sites did not show a considerable decrease in soil U concentration from year 1 to year 2. Sites which contained elevated U after wet season 2 also had higher moisture content which suggests that pooling of U containing rainwater at these sites may be responsible for elevated U. Thus, U may be redistributed within RUM LAAs due to surface water movement. The study also suggested that a decrease in U concentrations in LAA soils at very high U (>900 mg kg"−"1) sites is most likely due to transport of particulate matter bound U by surface runoff and U may not be lost from the surface soil due to vertical movement through the soil profile. Uranium attached to particulate matter may reduce its potential for

Urban Land: Study of Surface Run-off Composition and Its Dynamics

Science.gov (United States)

Palagin, E. D.; Gridneva, M. A.; Bykova, P. G.

2017-11-01

The qualitative composition of urban land surface run-off is liable to significant variations. To study surface run-off dynamics, to examine its behaviour and to discover reasons of these variations, it is relevant to use the mathematical apparatus technique of time series analysis. A seasonal decomposition procedure was applied to a temporary series of monthly dynamics with the annual frequency of seasonal variations in connection with a multiplicative model. The results of the quantitative chemical analysis of surface wastewater of the 22nd Partsjezd outlet in Samara for the period of 2004-2016 were used as basic data. As a result of the analysis, a seasonal pattern of variations in the composition of surface run-off in Samara was identified. Seasonal indices upon 15 waste-water quality indicators were defined. BOD (full), suspended materials, mineralization, chlorides, sulphates, ammonium-ion, nitrite-anion, nitrate-anion, phosphates (phosphorus), iron general, copper, zinc, aluminium, petroleum products, synthetic surfactants (anion-active). Based on the seasonal decomposition of the time series data, the contribution of trends, seasonal and accidental components of the variability of the surface run-off indicators was estimated.

Trend Analysis of Evapotranspiration over India- Observed from ...

Indian Academy of Sciences (India)

3

Future studies on the effects of ET changes on the hydrological cycle .... VI is useful for long-term monitoring of the land surface and climate related processes. .... were applied spatially using AVHRR Global Inventory Modelling and .... SRB uses cloud properties derived from International Satellite Cloud Climatology Project.

Land use/land cover and scale influences on in-stream nitrogen uptake kinetics

Science.gov (United States)

Covino, Tim; McGlynn, Brian; McNamara, Rebecca

2012-06-01

Land use/land cover change often leads to increased nutrient loading to streams; however, its influence on stream ecosystem nutrient transport remains poorly understood. Given the deleterious impacts elevated nutrient loading can have on aquatic ecosystems, it is imperative to improve understanding of nutrient retention capacities across stream scales and watershed development gradients. We performed 17 nutrient addition experiments on six streams across the West Fork Gallatin Watershed, Montana, USA, to quantify nitrogen uptake kinetics and retention dynamics across stream sizes (first to fourth order) and along a watershed development gradient. We observed that stream nitrogen (N) uptake kinetics and spiraling parameters varied across streams of different development intensity and scale. In more developed watersheds we observed a fertilization affect. This fertilization affect was evident as increased ash-free dry mass, chlorophylla, and ambient and maximum uptake rates in developed as compared to undeveloped streams. Ash-free dry mass, chlorophylla, and the number of structures in a subwatershed were significantly correlated to nutrient spiraling and kinetic parameters, while ambient and average annual N concentrations were not. Additionally, increased maximum uptake capacities in developed streams contributed to low in-stream nutrient concentrations during the growing season, and helped maintain watershed export at low levels during base flow. Our results indicate that land use/land cover change can enhance in-stream uptake of limiting nutrients and highlight the need for improved understanding of the watershed dynamics that control nutrient export across scales and development intensities for mitigation and protection of aquatic ecosystems.

Impacts of Land Cover Changes on Climate over China

Science.gov (United States)

Chen, L.; Frauenfeld, O. W.

2014-12-01

Land cover changes can influence regional climate through modifying the surface energy balance and water fluxes, and can also affect climate at large scales via changes in atmospheric general circulation. With rapid population growth and economic development, China has experienced significant land cover changes, such as deforestation, grassland degradation, and farmland expansion. In this study, the Community Earth System Model (CESM) is used to investigate the climate impacts of anthropogenic land cover changes over China. To isolate the climatic effects of land cover change, we focus on the CAM and CLM models, with prescribed climatological sea surface temperature and sea ice cover. Two experiments were performed, one with current vegetation and the other with potential vegetation. Current vegetation conditions were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations, and potential vegetation over China was obtained from Ramankutty and Foley's global potential vegetation dataset. Impacts of land cover changes on surface air temperature and precipitation are assessed based on the difference of the two experiments. Results suggest that land cover changes have a cold-season cooling effect in a large region of China, but a warming effect in summer. These temperature changes can be reconciled with albedo forcing and evapotranspiration. Moreover, impacts on atmospheric circulation and the Asian Monsoon is also discussed.

Factors of land abandonment in mountainous Mediterranean areas: the case of Montenegrin settlements.

Science.gov (United States)

Kerckhof, Annelies; Spalevic, Velibor; Van Eetvelde, Veerle; Nyssen, Jan

2016-01-01

Land use changes have been investigated in the surroundings of 14 rural Montenegrin settlements in order to get specific information about trends in land abandonment since around 1950. Permanently, seasonally and less inhabited settlements with different geographic conditions were studied. This was done by interviewing local inhabitants, which enabled a holistic approach to reveal the underlying processes of land abandonment. According to the observed patterns of land use change, the study sites can be categorized into intensified, urbanized, extensified, overgrown and forested cases. The category of extensified settlements is characterized by a highly reduced agricultural management intensity, resulting in an increase in grasslands and fruit trees at the expense of cropland. This land use change is mainly related to emigrating and aging inhabitants, having less livestock. Such extensive land use is found in both permanently inhabited and abandoned villages. Only some studied settlements became largely overgrown by bushes and forest. The steep average slope gradients and a large distance to the nearest city are explanatory factors of such land abandonment. Land use intensification takes place in low-lying areas located nearby towns.

Seasonal variation of carbon fluxes in a sparse savanna in semi arid Sudan.

Science.gov (United States)

Ardö, Jonas; Mölder, Meelis; El-Tahir, Bashir Awad; Elkhidir, Hatim Abdalla Mohammed

2008-12-01

Large spatial, seasonal and annual variability of major drivers of the carbon cycle (precipitation, temperature, fire regime and nutrient availability) are common in the Sahel region. This causes large variability in net ecosystem exchange and in vegetation productivity, the subsistence basis for a major part of the rural population in Sahel. This study compares the 2005 dry and wet season fluxes of CO2 for a grass land/sparse savanna site in semi arid Sudan and relates these fluxes to water availability and incoming photosynthetic photon flux density (PPFD). Data from this site could complement the current sparse observation network in Africa, a continent where climatic change could significantly impact the future and which constitute a weak link in our understanding of the global carbon cycle. The dry season (represented by Julian day 35-46, February 2005) was characterized by low soil moisture availability, low evapotranspiration and a high vapor pressure deficit. The mean daily NEE (net ecosystem exchange, Eq. 1) was -14.7 mmol d-1 for the 12 day period (negative numbers denote sinks, i.e. flux from the atmosphere to the biosphere). The water use efficiency (WUE) was 1.6 mmol CO2 mol H2O-1 and the light use efficiency (LUE) was 0.95 mmol CO2 mol PPFD-1. Photosynthesis is a weak, but linear function of PPFD. The wet season (represented by Julian day 266-273, September 2005) was, compared to the dry season, characterized by slightly higher soil moisture availability, higher evapotranspiration and a slightly lower vapor pressure deficit. The mean daily NEE was -152 mmol d-1 for the 8 day period. The WUE was lower, 0.97 mmol CO2 mol H2O-1 and the LUE was higher, 7.2 mumol CO2 mmol PPFD-1 during the wet season compared to the dry season. During the wet season photosynthesis increases with PPFD to about 1600 mumol m-2s-1 and then levels off. Based on data collected during two short periods, the studied ecosystem was a sink of carbon both during the dry and wet season

Seasonal variation of carbon fluxes in a sparse savanna in semi arid Sudan

Directory of Open Access Journals (Sweden)

El-Tahir Bashir

2008-12-01

Full Text Available Abstract Background Large spatial, seasonal and annual variability of major drivers of the carbon cycle (precipitation, temperature, fire regime and nutrient availability are common in the Sahel region. This causes large variability in net ecosystem exchange and in vegetation productivity, the subsistence basis for a major part of the rural population in Sahel. This study compares the 2005 dry and wet season fluxes of CO2 for a grass land/sparse savanna site in semi arid Sudan and relates these fluxes to water availability and incoming photosynthetic photon flux density (PPFD. Data from this site could complement the current sparse observation network in Africa, a continent where climatic change could significantly impact the future and which constitute a weak link in our understanding of the global carbon cycle. Results The dry season (represented by Julian day 35–46, February 2005 was characterized by low soil moisture availability, low evapotranspiration and a high vapor pressure deficit. The mean daily NEE (net ecosystem exchange, Eq. 1 was -14.7 mmol d-1 for the 12 day period (negative numbers denote sinks, i.e. flux from the atmosphere to the biosphere. The water use efficiency (WUE was 1.6 mmol CO2 mol H2O-1 and the light use efficiency (LUE was 0.95 mmol CO2 mol PPFD-1. Photosynthesis is a weak, but linear function of PPFD. The wet season (represented by Julian day 266–273, September 2005 was, compared to the dry season, characterized by slightly higher soil moisture availability, higher evapotranspiration and a slightly lower vapor pressure deficit. The mean daily NEE was -152 mmol d-1 for the 8 day period. The WUE was lower, 0.97 mmol CO2 mol H2O-1 and the LUE was higher, 7.2 μmol CO2 mmol PPFD-1 during the wet season compared to the dry season. During the wet season photosynthesis increases with PPFD to about 1600 μmol m-2s-1 and then levels off. Conclusion Based on data collected during two short periods, the studied ecosystem

Spatial patterns and temporal trends in the fisheries landings of the Messolonghi-Etoliko lagoons (Western Greek Coast

Directory of Open Access Journals (Sweden)

George Katselis

2003-12-01

Full Text Available The Messolonghi-Etoliko lagoon is one of the largest lagoon system in the northern Mediterranean coast. This area contains six clearly distinct lagoons with different topographic and hydrological features. The fishery landings of the lagoons are based on the ontogenic and seasonal migrations of the species. The total annual fishery landings of the barrier fish traps are estimated as 195 mt and are mainly composed of 16 species belonging to 8 families. Eel (Anguilla anguilla, the four species of Mugilidae (Liza saliens, L. aurata, L. ramada and Mugil cephalus, the two species of Sparidae (Sparus aurata and Diplodus annularis and one species of Mullidae (Mullus barbatus represent more than 92% of the total annual landings. The composition of the fishery landings varies between lagoons. The cluster analysis showed three groups of lagoons. The first group comprised lagoons in which the landings were dominated by eel, the second group was dominated by Mugilidae species and S. aurata, and the third by L. ramada and M. cephalus. The diversity index of the fishery landings is fairly constant in time, except for the Etoliko lagoon, where repeated anoxic crises decreased the diversity index value to almost zero in 1992. All the landing series showed a dominant annual cycle. Two seasonal patterns of the fishery landings were observed and linked to the fish spawning behaviour and/or their reaction to environmental forcings. The first one concerns species caught from summer to early autumn and the second pattern concerns species trapped during their autumn to winter offshore migration.

Seasonal contrasts in the response of coffee ants to agroforestry shade-tree management.

Science.gov (United States)

Teodoro, A V; Sousa-Souto, L; Klein, A-M; Tscharntke, T

2010-12-01

In many tropical landscapes, agroforestry systems are the last forested ecosystems, providing shade, having higher humidity, mitigating potential droughts, and possessing more species than any other crop system. Here, we tested the hypothesis that higher levels of shade and associated humidity in agroforestry enhance coffee ant richness more during the dry than rainy season, comparing ant richness in 22 plots of three coffee agroforestry types in coastal Ecuador: simple-shade agroforests (intensively managed with low tree species diversity), complex-shade agroforests (extensively managed with intermediate tree species diversity) and abandoned coffee agroforests (abandoned for 10-15 yr and resembling secondary forests). Seasonality affected responses of ant richness but not composition to agroforestry management, in that most species were observed in abandoned coffee agroforests in the dry season. In the rainy season, however, most species were found in simple-shade agroforests, and complex agroforestry being intermediate. Foraging coffee ants species composition did not change differently according to agroforestry type and season. Results show that shade appears to be most important in the dry seasons, while a mosaic of different land-use types may provide adequate environmental conditions to ant species, maximizing landscape-wide richness throughout the year. © 2010 Entomological Society of America

Soil emissions of nitric oxide in a seasonally dry tropical forest of Mexico

Science.gov (United States)

Davidson, Eric A.; Vitousek, Peter M.; Riley, Ralph; Matson, Pamela A.; Garcia-Mendez, Georgina; Maass, J. M.

1991-01-01

Soil emissions of NO were measured at the Chamela Biological Station, Mexico, using soil covers and a field apparatus of NO detection based on CrO3 conversion of NO to NO2 and detection of NO2 by chemiluminescence with Luminol. Mean NO fluxes from forest soils ranged from 0.14 to 0.52 ng NO-N/sq cm/hr during the dry season and from 0.73 to 1.27 ng NO-N/sq cm/hr during the wet season. A fertilized floodplain pasture exhibited higher fluxes, but an unfertilized upland pasture, which represents the fastest growing land use in the region, had flux rates similar to the forest sites. Wetting experiments at the end of the dry season caused large pulses of NO flux, equaling 10 percent to 20 percent of the estimated annual NO emissions of 0.5-1.0 kg N/ha from the forest sites. Absence of a forest canopy during the dry season and the first wet season rain probably results in substantial NO(x) export from the forest system that may be important to regional atmospheric chemical processes. Wetting experiments during the wet season and a natural rain event had little or no stimulatory effect on NO flux rates.

Beyond trend analysis: How a modified breakpoint analysis enhances knowledge of agricultural production after Zimbabwe's fast track land reform

Science.gov (United States)

Hentze, Konrad; Thonfeld, Frank; Menz, Gunter

2017-10-01

In the discourse on land reform assessments, a significant lack of spatial and time-series data has been identified, especially with respect to Zimbabwe's ;Fast-Track Land Reform Programme; (FTLRP). At the same time, interest persists among land use change scientists to evaluate causes of land use change and therefore to increase the explanatory power of remote sensing products. This study recognizes these demands and aims to provide input on both levels: Evaluating the potential of satellite remote sensing time-series to answer questions which evolved after intensive land redistribution efforts in Zimbabwe; and investigating how time-series analysis of Normalized Difference Vegetation Index (NDVI) can be enhanced to provide information on land reform induced land use change. To achieve this, two time-series methods are applied to MODIS NDVI data: Seasonal Trend Analysis (STA) and Breakpoint Analysis for Additive Season and Trend (BFAST). In our first analysis, a link of agricultural productivity trends to different land tenure regimes shows that regional clustering of trends is more dominant than a relationship between tenure and trend with a slightly negative slope for all regimes. We demonstrate that clusters of strong negative and positive productivity trends are results of changing irrigation patterns. To locate emerging and fallow irrigation schemes in semi-arid Zimbabwe, a new multi-method approach is developed which allows to map changes from bimodal seasonal phenological patterns to unimodal and vice versa. With an enhanced breakpoint analysis through the combination of STA and BFAST, we are able to provide a technique that can be applied on large scale to map status and development of highly productive cropping systems, which are key for food production, national export and local employment. We therefore conclude that the combination of existing and accessible time-series analysis methods: is able to achieve both: overcoming demonstrated limitations of

Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges

Directory of Open Access Journals (Sweden)

Annett Bartsch

2016-11-01

Full Text Available Most applications of land cover maps that have been derived from satellite data over the Arctic require higher thematic detail than available in current global maps. A range of application studies has been reviewed, including up-scaling of carbon fluxes and pools, permafrost feature mapping and transition monitoring. Early land cover mapping studies were driven by the demand to characterize wildlife habitats. Later, in the 1990s, up-scaling of in situ measurements became central to the discipline of land cover mapping on local to regional scales at several sites across the Arctic. This includes the Kuparuk basin in Alaska, the Usa basin and the Lena Delta in Russia. All of these multi-purpose land cover maps have been derived from Landsat data. High resolution maps (from optical satellite data serve frequently as input for the characterization of periglacial features and also flux tower footprints in recent studies. The most used map to address circumpolar issues is the CAVM (Circum Arctic Vegetation Map based on AVHRR (1 km and has been manually derived. It provides the required thematic detail for many applications, but is confined to areas north of the treeline, and it is limited in spatial detail. A higher spatial resolution circumpolar land cover map with sufficient thematic content would be beneficial for a range of applications. Such a land cover classification should be compatible with existing global maps and applicable for multiple purposes. The thematic content of existing global maps has been assessed by comparison to the CAVM and regional maps. None of the maps provides the required thematic detail. Spatial resolution has been compared to used classes for local to regional applications. The required thematic detail increases with spatial resolution since coarser datasets are usually applied over larger areas covering more relevant landscape units. This is especially of concern when the entire Arctic is addressed. A spatial

Effect of landcover/land-use changes on water availability in and ...

African Journals Online (AJOL)

2018-01-15

Jan 15, 2018 ... The images were downloaded for the June–September period which coincides with the cool dry season of Zimbabwe. Landsat MSS, TM and ETM (30 m resolution) images for the period 1984–2011 were downloaded and used for digital image classification in the Integrated Land and Water Information ...

Seasonality in the Austrian Economy: Common Seasonals and Forecasting

OpenAIRE

Kunst, Robert M.

1992-01-01

Abstract: Seasonal cointegration generalizes the idea of cointegration to processes with unit roots at frequencies different from 0. Here, also the dual notion of common trends, "common seasonals", is adopted for the seasonal case. Using a five-variable macroeconomic core system of the Austrian economy, it is demonstrated how common seasonals and seasonal cointegrating vectors look in practice. Statistical tests provide clear evidence on seasonal cointegration in the system. However, it is sh...

Impact of Climate Change on Soil and Groundwater Chemistry Subject to Process Waste Land Application

Science.gov (United States)

McNab, W. W.

2013-12-01

Nonhazardous aqueous process waste streams from food and beverage industry operations are often discharged via managed land application in a manner designed to minimize impacts to underlying groundwater. Process waste streams are typically characterized by elevated concentrations of solutes such as ammonium, organic nitrogen, potassium, sodium, and organic acids. Land application involves the mixing of process waste streams with irrigation water which is subsequently applied to crops. The combination of evapotranspiration and crop salt uptake reduces the downward mass fluxes of percolation water and salts. By carefully managing application schedules in the context of annual climatological cycles, growing seasons, and process requirements, potential adverse environmental impacts to groundwater can be mitigated. However, climate change poses challenges to future process waste land application efforts because the key factors that determine loading rates - temperature, evapotranspiration, seasonal changes in the quality and quantity of applied water, and various crop factors - are all likely to deviate from current averages. To assess the potential impact of future climate change on the practice of land application, coupled process modeling entailing transient unsaturated fluid flow, evapotranspiration, crop salt uptake, and multispecies reactive chemical transport was used to predict changes in salt loading if current practices are maintained in a warmer, drier setting. As a first step, a coupled process model (Hydrus-1D, combined with PHREEQC) was calibrated to existing data sets which summarize land application loading rates, soil water chemistry, and crop salt uptake for land disposal of process wastes from a food industry facility in the northern San Joaquin Valley of California. Model results quantify, for example, the impacts of evapotranspiration on both fluid flow and soil water chemistry at shallow depths, with secondary effects including carbonate mineral

Present scenario of landing and distribution of fish in Bangladesh.

Science.gov (United States)

Rahman, M; Khatun, S; Hossain, M B; Hassan, M N; Nowsad, A A K M

2013-11-15

The present study was designed to know the landing and distribution pathways of fish and types and nature of stakeholders involved in fish distribution chain in Bangladesh. A total of 237 fish landing centers and 5440 markets were detected. The number of landing center and market were highest in Chittagong and Dhaka division respectively. Stakeholders in fish distribution, viz., arotdars, paikers and retailers were found to be 6219, 39506 and 122922, respectively. A 84.71% of the landing centers were found to be operated year round while 15.29% were seasonal. The major fish production zones and major gateways of the country where inland capture and culture and marine capture fish landed were identified. In any locality 62.83% of the landed fish were transported within 100 km area and 5.73% of fish were transported beyond 500 km. The quantity of fish harvested from river, beel, Kaptai lake floodplain, pond, baor, coastal area/sea and shrimp/prawn farm were 5.25, 4.41, 0.13, 35.03, 38.22, 0.23, 10.93 and 5.80%, respectively. The common constraints identified were lack of adequate infrastructure facilities in the landing center and market, unhygienic environment, influence of middlemen, money lending at high rate etc. For the betterment of fish landing and distribution, appropriate authority should pay proper attention so that both quality and fair price are ensured.

Climate model biases in seasonality of continental water storage revealed by satellite gravimetry

Science.gov (United States)

Swenson, Sean; Milly, P.C.D.

2006-01-01

Satellite gravimetric observations of monthly changes in continental water storage are compared with outputs from five climate models. All models qualitatively reproduce the global pattern of annual storage amplitude, and the seasonal cycle of global average storage is reproduced well, consistent with earlier studies. However, global average agreements mask systematic model biases in low latitudes. Seasonal extrema of low‐latitude, hemispheric storage generally occur too early in the models, and model‐specific errors in amplitude of the low‐latitude annual variations are substantial. These errors are potentially explicable in terms of neglected or suboptimally parameterized water stores in the land models and precipitation biases in the climate models.

WATER CONSUMPTION BEHAVIOR DURING DRY SEASON AT PAMOR HAMLET, GROBOGAN DISTRICT

OpenAIRE

Ipung Purwanto

2017-01-01

Drought disaster in Grobogan District takes place almost every year. This research aims to study the household water consumption behavior during dry season. Precipitation data, soil map, and land cover map were collected. Historical information was also collected with snowball sampling and depth interview. Public perceptions were collected through Focus Group Discussion. Interview and direct observation were conducted to discover people behaviour in collecting water. Survey was also done to c...

Alluvial Mountain Meadow Source-Sink Dynamics: Land-Cover Effects on Water and Fluvial Carbon Export

Science.gov (United States)

Weiss, T.; Covino, T. P.; Wohl, E.; Rhoades, C.; Fegel, T.; Clow, D. W.

2017-12-01

Fluvial networks of historically glaciated mountain landscapes alternate between confined and unconfined valley segments. In low-gradient unconfined reaches, river-connected wet meadows commonly establish, and have been recognized as important locations of long-term water, carbon, and nutrient storage. Among connected meadow floodplains, sink-source behavior shifts as a function of flow state; storing water at high flows (snowmelt) and contributing toward higher late-season baseflows. Despite these benefits, historical and contemporary land-use practices often result in the simplification of wet meadow systems, leading to reduced river-floodplain connectivity, lower water-tables and reductions in hydrologic buffering capacity. In this study, we are exploring hydrologic-carbon relationships across a gradient of valley confinement and river-floodplain connectivity (connected, n=3; disconnected, n=4) within the Colorado Rockies. Our approach includes hydrologic analysis, fluorometric assays, water chemistry, instream metabolic measures, and land-cover assessment to examine patterns between land-form, carbon quantity and quality, and stream ecosystem productivity. Between different meadow types, preliminary results suggest differences between instream productivity, carbon qualities, and hydrologic-carbon sink-source dynamics across the season. These data and analyses will provide insight into water, carbon and nutrient flux dynamics as a function of land-cover in mountain headwaters.

Seasonal trend analysis and ARIMA modeling of relative humidity and wind speed time series around Yamula Dam

Science.gov (United States)

Eymen, Abdurrahman; Köylü, Ümran

2018-02-01

Local climate change is determined by analysis of long-term recorded meteorological data. In the statistical analysis of the meteorological data, the Mann-Kendall rank test, which is one of the non-parametrical tests, has been used; on the other hand, for determining the power of the trend, Theil-Sen method has been used on the data obtained from 16 meteorological stations. The stations cover the provinces of Kayseri, Sivas, Yozgat, and Nevşehir in the Central Anatolia region of Turkey. Changes in land-use affect local climate. Dams are structures that cause major changes on the land. Yamula Dam is located 25 km northwest of Kayseri. The dam has huge water body which is approximately 85 km2. The mentioned tests have been used for detecting the presence of any positive or negative trend in meteorological data. The meteorological data in relation to the seasonal average, maximum, and minimum values of the relative humidity and seasonal average wind speed have been organized as time series and the tests have been conducted accordingly. As a result of these tests, the following have been identified: increase was observed in minimum relative humidity values in the spring, summer, and autumn seasons. As for the seasonal average wind speed, decrease was detected for nine stations in all seasons, whereas increase was observed in four stations. After the trend analysis, pre-dam mean relative humidity time series were modeled with Autoregressive Integrated Moving Averages (ARIMA) model which is statistical modeling tool. Post-dam relative humidity values were predicted by ARIMA models.

FORWINE - Statistical Downscaling of Seasonal forecasts for wine

Science.gov (United States)

Cardoso, Rita M.; Soares, Pedro M. M.; Miranda, Pedro M. A.

2016-04-01

The most renowned viticulture regions in the Iberian Peninsula have a long standing tradition in winemaking and are considered world-class grapevine (Vitis Vinifera L.) producing regions. Portugal is the 11th wine producer in the world, with internationally acclaimed wines, such as Port wine, and vineyards across the whole territory. Climate is widely acknowledged of one of the most important factors for grapevine development and growth (Fraga et al. 2014a and b; Jackson et al. 1993; Keller 2010). During the growing season (April-October in the Northern Hemisphere) of this perennial and deciduous crop, the climatic conditions are responsible for numerous morphologically and physiological changes. Anomalously low February-March mean temperature, anomalously high May mean temperature and anomalously high March precipitation tend to be favourable to wine production in the Douro Valley. Seasonal forecast of precipitation and temperature tailored to fit critical thresholds, for crucial seasons, can be used to inform management practices (viz. phytosanitary measures, land operations, marketing campaigns) and develop a wine production forecast. Statistical downscaling of precipitation, maximum, minimum temperatures is used to model wine production following Santos et al. (2013) and to calculate bioclimatic indices. The skill of the ensemble forecast is evaluated through anomaly correlation, ROC area, spread-error ratio and CRPS

[Influence of land use change on dissolved organic carbon export in Naoli River watershed. Northeast China].

Science.gov (United States)

Yin, Xiao-min; Lyu, Xian-guo; Liu, Xing-tu; Xue, Zhen-shan

2015-12-01

The present study was conducted to evaluate the influence of land use change on dissolved organic carbon (DOC) export in Naoli River watershed, Northeast China. Seasonal variation of DOC concentrations of the river water and its relationship with land use in the whole watershed and 100 m riparian zone at the annual average scale were analyzed using the method of field sampling, laboratory analysis, GIS and statistics analysis. The results showed that the concentrations of DOC under base flow conditions in spring and summer were significantly higher than that in fall in the study watershed. The seasonal trend of DOC concentrations in wetland-watersheds was similar to that in all the sub-watersheds, while significantly different from that in non-wetland watersheds. On the annual average scale, percentage of wetland in the whole watershed and paddy field in the 100 m riparian zone had positive relationship with the DOC concentration in the river water, while percentage of forest in the whole watershed had negative relationship with it (P watershed played a significant role in the seasonal variation of DOC in river water of Naoli River watershed. Wetland in the watershed and paddy field in the 100 m riparian zone significantly promoted DOC export, while forest alleviated it. Land use change in the watershed in the past few decades dramatically changed the DOC balance of river water.

Exploring the Factors Driving Seasonal Farmland Abandonment: A Case Study at the Regional Level in Hunan Province, Central China

Directory of Open Access Journals (Sweden)

Zhonglei Yu

2017-01-01

Full Text Available Farmland abandonment, including perennial and seasonal abandonment, is an important process of land use change that matters most to food security. Although there is a great deal of studies on farmland abandonment, seasonal abandonment, which is as serious as perennial abandonment, has attracted little academic attention. This paper takes Hunan Province in central China as its study area and uses a spatial regression model to examine the driving factors of seasonal farmland abandonment at the county level. Our results show that farmland abandonment has striking spatial relativity, and there are two clustering zones with a high index of farmland abandonment (IFA in the Dongting plain and the basin in south-central Hunan, while a clustering zone of low IFA can be found in the mountains of southwest Hunan. Farmland abandonment at the regional level is negatively affected by the land productive potentialities, proportion of mechanized planting, ratio of effective irrigation, and distance to provincial capital, while it is positively associated with the variables mountainous terrain, per capita farmland area, and labor shortage. Additionally, farmland abandonment is also affected by adjacent areas through its spatial dependence. In short, seasonal farmland abandonment is also driven integratedly by the socioeconomic and environmental dimensions and spatial interaction of farm abandonment.

Seasonal comparison of two spatially distributed evapotranspiration mapping methods

Science.gov (United States)

Kisfaludi, Balázs; Csáki, Péter; Péterfalvi, József; Primusz, Péter

2017-04-01

More rainfall is disposed of through evapotranspiration (ET) on a global scale than through runoff and storage combined. In Hungary, about 90% of the precipitation evapotranspirates from the land and only 10% goes to surface runoff and groundwater recharge. Therefore, evapotranspiration is a very important element of the water balance, so it is a suitable parameter for the calibration of hydrological models. Monthly ET values of two MODIS-data based ET products were compared for the area of Hungary and for the vegetation period of the year 2008. The differences were assessed by land cover types and by elevation zones. One ET map was the MOD16, aiming at global coverage and provided by the MODIS Global Evaporation Project. The other method is called CREMAP, it was developed at the Budapest University of Technology and Economics for regional scale ET mapping. CREMAP was validated for the area of Hungary with good results, but ET maps were produced only for the period of 2000-2008. The aim of this research was to evaluate the performance of the MOD16 product compared to the CREMAP method. The average difference between the two products was the highest during summer, CREMAP estimating higher ET values by about 25 mm/month. In the spring and autumn, MOD16 ET values were higher by an average of 6 mm/month. The differences by land cover types showed a similar seasonal pattern to the average differences, and they correlated strongly with each other. Practically the same difference values could be calculated for arable lands and forests that together cover nearly 75% of the area of the country. Therefore, it can be said that the seasonal changes had the same effect on the two method's ET estimations in each land cover type areas. The analysis by elevation zones showed that on elevations lower than 200 m AMSL the trends of the difference values were similar to the average differences. The correlation between the values of these elevation zones was also strong. However weaker

Global Precipitation Responses to Land Hydrological Processes

Science.gov (United States)

Lo, M.; Famiglietti, J. S.

2012-12-01

Several studies have established that soil moisture increases after adding a groundwater component in land surface models due to the additional supply of subsurface water. However, impacts of groundwater on the spatial-temporal variability of precipitation have received little attention. Through the coupled groundwater-land-atmosphere model (NCAR Community Atmosphere Model + Community Land Model) simulations, this study explores how groundwater representation in the model alters the precipitation spatiotemporal distributions. Results indicate that the effect of groundwater on the amount of precipitation is not globally homogeneous. Lower tropospheric water vapor increases due to the presence of groundwater in the model. The increased water vapor destabilizes the atmosphere and enhances the vertical upward velocity and precipitation in tropical convective regions. Precipitation, therefore, is inhibited in the descending branch of convection. As a result, an asymmetric dipole is produced over tropical land regions along the equator during the summer. This is analogous to the "rich-get-richer" mechanism proposed by previous studies. Moreover, groundwater also increased short-term (seasonal) and long-term (interannual) memory of precipitation for some regions with suitable groundwater table depth and found to be a function of water table depth. Based on the spatial distributions of the one-month-lag autocorrelation coefficients as well as Hurst coefficients, air-land interaction can occur from short (several months) to long (several years) time scales. This study indicates the importance of land hydrological processes in the climate system and the necessity of including the subsurface processes in the global climate models.

The hierarchy of controls on snowmelt-runoff generation over seasonally-frozen hillslopes

OpenAIRE

Coles, Anna E.; Appels, Willemijn M.; McConkey, Brian G.; McDonnell, Jeffrey J.

2016-01-01

Understanding and modeling snowmelt-runoff generation in seasonally-frozen regions is a major challenge in hydrology. Partly, this is because the controls on hillslope-scale snowmelt-runoff generation are potentially extensive and their hierarchy is poorly understood. Understanding the relative importance of controls (e.g. topography, vegetation, land use, soil characteristics, and precipitation dynamics) on runoff response is necessary for model development, spatial extrapolation, and runoff...

Jump Landing Characteristics Predict Lower Extremity Injuries in Indoor Team Sports.

Science.gov (United States)

van der Does, H T D; Brink, M S; Benjaminse, A; Visscher, C; Lemmink, K A P M

2016-03-01

The aim of this study is to investigate the predictive value of landing stability and technique to gain insight into risk factors for ankle and knee injuries in indoor team sport players. Seventy-five male and female basketball, volleyball or korfball players were screened by measuring landing stability after a single-leg jump landing and landing technique during a repeated counter movement jump by detailed 3-dimensional kinematics and kinetics. During the season 11 acute ankle injuries were reported along with 6 acute and 7 overuse knee injuries by the teams' physical therapist. Logistic regression analysis showed less landing stability in the forward and diagonal jump direction (OR 1.01-1.10, p≤0.05) in players who sustained an acute ankle injury. Furthermore landing technique with a greater ankle dorsiflexion moment increased the risk for acute ankle injury (OR 2.16, p≤0.05). A smaller knee flexion moment and greater vertical ground reaction force increased the risk of an overuse knee injury (OR 0.29 and 1.13 respectively, p≤0.05). Less one-legged landing stability and suboptimal landing technique were shown in players sustaining an acute ankle and overuse knee injury compared to healthy players. Determining both landing stability and technique may further guide injury prevention programs. © Georg Thieme Verlag KG Stuttgart · New York.

[Soil moisture dynamics and water balance of Salix psammophila shrubs in south edge of Mu Us Sandy Land].

Science.gov (United States)

An, Hui; An, Yu

2011-09-01

Taking the artificial sand-fixing Salix psammophila shrubs with different plant density (0.2, 0.6, and 0.8 plants x m(-2)) in Mu Us Sandy Land as test objects, this paper studied the soil moisture dynamics and evapotranspiration during growth season. There existed obvious differences in the soil moisture dynamics and evapotranspiration among the shrubs. The soil moisture content changed in single-hump-shape with the increase of plant density, and in "S" shape during growth season, being closely correlated with precipitation. The evapotranspiration was the highest (114.5 mm) in the shrubs with a density 0.8 plants x m(-1), accounting for 90.8% of the total precipitation during growth season, and the lowest (109.7 mm) in the shrubs with a density 0.6 plants x m(-2) Based on the soil moisture dynamics and water balance characteristics, the appropriate planting density of S. psammophila shrubs in Mu Us Sandy Land could be 0.6 plants x m(-2).

[Characteristics of soil moisture variation in different land use types in the hilly region of the Loess Plateau, China].

Science.gov (United States)

Tang, Min; Zhao, Xi Ning; Gao, Xiao Dong; Zhang, Chao; Wu, Pu Te

2018-03-01

Soil water availability is a key factor restricting the ecological construction and sustainable land use in the loess hilly region. It is of great theoretical and practical significance to understand the soil moisture status of different land use types for the vegetation restoration and the effective utilization of land resources in this area. In this study, EC-5 soil moisture sensors were used to continuously monitor the soil moisture content in the 0-160 cm soil profile in the slope cropland, terraced fields, jujube orchard, and grassland during the growing season (from May to October) in the Yuanzegou catchment on the Loess Plateau, to investigate soil moisture dynamics in these four typical land use types. The results showed that there were differences in seasonal variation, water storage characteristics, and vertical distribution of soil moisture under different land use types in both the normal precipitation (2014) and dry (2015) years. The terraced fields showed good water retention capacity in the dry year, with the average soil moisture content of 0-60 cm soil layer in the growing season being 2.6%, 4.2%, and 1.8% higher than that of the slope cropland, jujube orchard, and grassland (all Pmoisture content of 0-60 cm soil layer in jujube orchard in the growing season was 2.9%, 3.8%, and 4.5% lower than that of slope cropland, terraced fields, and grassland, respectively (all Pmoisture in the surface layer (0-20 cm) and soil moisture in the middle layer (20-100 cm) under different land use types was large, and the trend for the similarity degree of soil moisture variation followed terraced fields > grassland > slope cropland > jujube orchard. The slope cropland in this area could be transformed into terraced fields to improve the utilization of precipitation and promote the construction of ecological agriculture. Aiming at resolving the severe water shortage in the rain-fed jujube orchard for the sustainable development of jujube orchard in the loess hilly

Abundance, Fishing Season and Management Strategy for Blue Swimming Crab (Portunus pelagicus) in Pangkajene Kepulauan, South Sulawesi, Indonesia.

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Wiyono, Eko Sri; Ihsan

2018-03-01

In order to manage blue swimming crabs in Pangkajene Kepulauan, management measures are required. Since the environment which affects the abundance of the blue swimming crab varies seasonally, it is necessary to take into account the seasonal nature with the aim of developing a management strategy. The objectives of this study are to define the abundance of and fishing season of blue swimming crabs in the Pangkajene Kepulauan waters, South Sulawesi, Indonesia. The fishing season was analysed using seasonal index analysis, while fish abundance was analysed by means of Equilibrium-Schaefer. The result of this study demonstrated that fishermen allocate their fishing gear all year, although the fish catch is seasonal. Based on analysis of the result, the fishing season for the blue swimming crabs is short. The peak fishing season starts in May and finishes in June. However, in order to enable their families to earn a living, fishermen operated their fishing gear throughout the year. As a result, both catch landing and effort were close to maximum sustainable yield (MSY). In order to reduce fishing pressure, it is necessary to reduce fishing gear and have a seasonal arrangement regarding fishing gear allocation.

Reconstruction of droughts in India using multiple land-surface models (1951-2015)

Science.gov (United States)

Mishra, Vimal; Shah, Reepal; Azhar, Syed; Shah, Harsh; Modi, Parth; Kumar, Rohini

2018-04-01

India has witnessed some of the most severe historical droughts in the current decade, and severity, frequency, and areal extent of droughts have been increasing. As a large part of the population of India is dependent on agriculture, soil moisture drought affecting agricultural activities (crop yields) has significant impacts on socio-economic conditions. Due to limited observations, soil moisture is generally simulated using land-surface hydrological models (LSMs); however, these LSM outputs have uncertainty due to many factors, including errors in forcing data and model parameterization. Here we reconstruct agricultural drought events over India during the period of 1951-2015 based on simulated soil moisture from three LSMs, the Variable Infiltration Capacity (VIC), the Noah, and the Community Land Model (CLM). Based on simulations from the three LSMs, we find that major drought events occurred in 1987, 2002, and 2015 during the monsoon season (June through September). During the Rabi season (November through February), major soil moisture droughts occurred in 1966, 1973, 2001, and 2003. Soil moisture droughts estimated from the three LSMs are comparable in terms of their spatial coverage; however, differences are found in drought severity. Moreover, we find a higher uncertainty in simulated drought characteristics over a large part of India during the major crop-growing season (Rabi season, November to February: NDJF) compared to those of the monsoon season (June to September: JJAS). Furthermore, uncertainty in drought estimates is higher for severe and localized droughts. Higher uncertainty in the soil moisture droughts is largely due to the difference in model parameterizations (especially soil depth), resulting in different persistence of soil moisture simulated by the three LSMs. Our study highlights the importance of accounting for the LSMs' uncertainty and consideration of the multi-model ensemble system for the real-time monitoring and prediction of

Determination of the influence of high clouds on the radiation field and on climate by analyzing NOAA AVHRR data. Die Bestimmung des Einflusses von hohen Wolken auf das Strahlungsfeld und auf das Klima durch Analyse von NOAA AVHRR-Daten

Energy Technology Data Exchange (ETDEWEB)

Berger, F H

1991-11-01

The influence of clouds on the radiation field and on climate is investigated over the North Sea by analyzing NOAA AVHRR data. The derived information was applied to calculate the cloud-climate efficiency at the top of atmosphere and at the surface. The cloud-climate efficiencies in the shortwave spectrum show a cooling effect of the earth/atmosphere system for all clouds and a strong dependence on the solar insolation. For the cloud-climate efficiency in the longwave region always heating of the earth/atmosphere system was observed. Because of the solar zenith angle effect thick high clouds with the same optical properties may lead to different effects in the earth/atmosphere system. A first approach of a comparison of the increasing cloud forcing (heating of the earth-atmosphere system) and an analysis of the relative topography 300/850 hPa shows that the increase of the cloud forcing is well correlated with an increase of the temperature in this layer. The deviation from the long-term mean of the pressure or temperature shows the same behaviour. (orig.).

Sources and transport of contaminants of emerging concern: A two-year study of occurrence and spatiotemporal variation in a mixed land use watershed.

Science.gov (United States)

Fairbairn, David J; Karpuzcu, M Ekrem; Arnold, William A; Barber, Brian L; Kaufenberg, Elizabeth F; Koskinen, William C; Novak, Paige J; Rice, Pamela J; Swackhamer, Deborah L

2016-05-01

The occurrence and spatiotemporal variation of 26 contaminants of emerging concern (CECs) were evaluated in 68 water samples in 2011-2012 in the Zumbro River watershed, Minnesota, U.S.A. Samples were collected across a range of seasonal/hydrological conditions from four stream sites that varied in associated land use and presence of an upstream wastewater treatment plant (WWTP). Selected CECs included human/veterinary pharmaceuticals, personal care products, pesticides, phytoestrogens, and commercial/industrial compounds. Detection frequencies and concentrations varied, with atrazine, metolachlor, acetaminophen, caffeine, DEET, and trimethoprim detected in more than 70% of samples, acetochlor, mecoprop, carbamazepine, and daidzein detected in 30%-50% of samples, and 4-nonylphenol, cotinine, sulfamethoxazole, erythromycin, tylosin, and carbaryl detected in 10%-30% of samples. The remaining target CECs were not detected in water samples. Three land use-associated trends were observed for the detected CECs. Carbamazepine, 4-nonylphenol, erythromycin, sulfamethoxazole, tylosin, and carbaryl profiles were WWTP-dominated, as demonstrated by more consistent loading and significantly greater concentrations downstream of the WWTP and during low-flow seasons. In contrast, acetaminophen, trimethoprim, DEET, caffeine, cotinine, and mecoprop patterns demonstrated both seasonally-variable non-WWTP-associated and continual WWTP-associated influences. Surface water studies of CECs often target areas near WWTPs. This study suggests that several CECs often characterized as effluent-associated have additional important sources such as septic systems or land-applied biosolids. Finally, agricultural herbicide (atrazine, acetochlor, and metolachlor) profiles were strongly influenced by agricultural land use and seasonal application-runoff, evident by significantly greater concentrations and loadings at upstream sites and in early summer when application and precipitation rates are

Study of Maowusu Sandy Land Vegetation Coverage Change Based on Modis Ndvi

Science.gov (United States)

Ye, Q.; Liu, H.; Lin, Y.; Han, R.

2018-04-01

This paper selected 2006-2016 MODIS NDVI data with a spatial resolution of 500m and time resolution of 16d, got the 11 years' time series NDVI data of Maowusu sandy land through mosaicking, projection transformation, cutting process in batch. Analysed the spatial and temporal distribution and variation characteristics of vegetation cover in year, season and month time scales by maximum value composite, and unary linear regression analysis. Then, we combined the meteorological data of 33 sites around the sandy area, analysed the response characteristics of vegetation cover change to temperature and precipitation through Pearson correlation coefficient. Studies have shown that: (1) The NDVI value has a stable increase trend, which rate is 0.0075 / a. (2) The vegetation growth have significantly difference in four seasons, the NDVI value of summer > autumn > spring > winter. (3) The NDVI value change trend is conformed to the gauss normal distribution in a year, and it comes to be largest in August, its green season is in April, and yellow season is in the middle of November, the growth period is about 220 d. (4) The vegetation has a decreasing trend from the southeast to the northwest, most part is slightly improved, and Etuokeqianqi improved significantly. (5) The correlation indexes of annual NDVI with temperature and precipitation are -0.2178 and 0.6309, the vegetation growth is mainly affected by precipitation. In this study, a complete vegetation cover analysis and evaluation model for sandy land is established. It has important guiding significance for the sand ecological environment protection.

Climate Impacts of Fire-Induced Land-Surface Changes

Science.gov (United States)

Liu, Y.; Hao, X.; Qu, J. J.

2017-12-01

One of the consequences of wildfires is the changes in land-surface properties such as removal of vegetation. This will change local and regional climate through modifying the land-air heat and water fluxes. This study investigates mechanism by developing and a parameterization of fire-induced land-surface property changes and applying it to modeling of the climate impacts of large wildfires in the United States. Satellite remote sensing was used to quantitatively evaluate the land-surface changes from large fires provided from the Monitoring Trends in Burning Severity (MTBS) dataset. It was found that the changes in land-surface properties induced by fires are very complex, depending on vegetation type and coverage, climate type, season and time after fires. The changes in LAI are remarkable only if the actual values meet a threshold. Large albedo changes occur in winter for fires in cool climate regions. The signs are opposite between the first post-fire year and the following years. Summer day-time temperature increases after fires, while nigh-time temperature changes in various patterns. The changes are larger in forested lands than shrub / grassland lands. In the parameterization scheme, the detected post-fire changes are decomposed into trends using natural exponential functions and fluctuations of periodic variations with the amplitudes also determined by natural exponential functions. The final algorithm is a combination of the trends, periods, and amplitude functions. This scheme is used with Earth system models to simulate the local and regional climate effects of wildfires.

Watershed Analysis of Nitrate Transport as a Result of Agricultural Inputs for Varying Land Use/Land Cover and Soil Type

Science.gov (United States)

Scott, M. E.; Sykes, J. F.

2006-12-01

The Grand River Watershed is one of the largest watersheds in southwestern Ontario with an area of approximately 7000 square kilometers. Ninety percent of the watershed is classified as rural, and 80 percent of the watershed population relies on groundwater as their source of drinking water. Management of the watershed requires the determination of the effect of agricultural practices on long-term groundwater quality and to identify locations within the watershed that are at a higher risk of contamination. The study focuses on the transport of nitrate through the root zone as a result of agricultural inputs with attenuation due to biodegradation. The driving force for transport is spatially and temporally varying groundwater recharge that is a function of land use/land cover, soil and meteorological inputs that yields 47,229 unique soil columns within the watershed. Fertilizer sources are determined from Statistics Canada's Agricultural Census and include livestock manure and a popular commercial fertilizer, urea. Accounting for different application rates yields 60,066 unique land parcels of which 22,809 are classified as croplands where manure and inorganic fertilizes are directly applied. The transport for the croplands is simulated over a 14-year period to investigate the impact of seasonal applications of nitrate fertilizers on the concentration leaching from the root zone to the water table. Based on land use/land cover maps, ArcView GIS is used to define the location of fertilizer applications within the watershed and to spatially visualize data and analyze results. The large quantity of input data is stored and managed using MS-Access and a relational database management system. Nitrogen transformations and ammonium and nitrate uptake by plants and transport through the soil column are simulated on a daily basis using Visual Basic for Applications (VBA) within MS-Access modules. Nitrogen transformations within the soil column were simplified using

Monitoring of livestock grazing effects on Bureau of Land Management land

Science.gov (United States)

Veblen, Kari E.; Pyke, David A.; Aldridge, Cameron L.; Casazza, Michael L.; Assal, Timothy J.; Farinha, Melissa A.

2013-01-01

Public land management agencies, such as the Bureau of Land Management (BLM), are charged with managing rangelands throughout the western United States for multiple uses, such as livestock grazing and conservation of sensitive species and their habitats. Monitoring of condition and trends of these rangelands, particularly with respect to effects of livestock grazing, provides critical information for effective management of these multiuse landscapes. We therefore investigated the availability of livestock grazing-related quantitative monitoring data and qualitative region-specific Land Health Standards (LHS) data across BLM grazing allotments in the western United States. We then queried university and federal rangeland science experts about how best to prioritize rangeland monitoring activities. We found that the most commonly available monitoring data were permittee-reported livestock numbers and season-of-use data (71% of allotments) followed by repeat photo points (58%), estimates of forage utilization (52%), and, finally, quantitative vegetation measurements (37%). Of the 57% of allotments in which LHS had been evaluated as of 2007, the BLM indicated 15% had failed to meet LHS due to livestock grazing. A full complement of all types of monitoring data, however, existed for only 27% of those 15%. Our data inspections, as well as conversations with rangeland experts, indicated a need for greater emphasis on collection of grazing-related monitoring data, particularly ground cover. Prioritization of where monitoring activities should be focused, along with creation of regional monitoring teams, may help improve monitoring. Overall, increased emphasis on monitoring of BLM rangelands will require commitment at multiple institutional levels.

Demography and behavior of polar bears summering on land in Alaska

Science.gov (United States)

Peacock, Lily

2014-01-01

satellite tags, 2003 – 2009) come to land during July – October. Based on these data, and an assumption that bears satellite-tagged on the spring time sea ice are representative of the entire SB population of independent bears, there would be an average of 230 bears on land each fall. In contrast to the SB population, in five of the world’s 19 polar bear populations (Obbard et al. 2010), polar bears spend significant periods of time on land (1 – 5 months) when ice completely melts. In these seasonal-ice populations (Amstrup et al. 2008), polar bears are largely in a hypophagic condition (e.g., Hobson et al. 2009), relying on fat stores from the spring hyperphagic season, when ringed seals (Phoca hispida) pup. In general, these seasonal-ice populations are demographically productive (Taylor et al. 2005), although recently an increase in the ice-free season has resulted in a population decline in western Hudson Bay (Stirling et al. 1999; Regehr et al. 2007). There have been measured declines in the body condition and productivity of polar bears in SB, and changes in these parameters have been linked to declining optimal ice habitat (e.g., Durner et al. 2009; Regehr et al. 2010). We do not understand the relationship between land-use and the overall status of the population. Individual polar bears that use land may have increased or decreased fitness, in comparison to polar bears that remain on ice in the autumn. This project, which focuses on the biology of animals that spend time on-shore, will help address this question. This project is funded by the Bureau of Ocean Energy Management (BOEM) under Agreement No. M09PG00025 and the USGS Outer Continental Shelf Program (OCS) for FY 2009-2014. Parts of this study are also funded by US Fish and Wildlife Service, Office of Marine Mammals Management; the Bureau of Land Management; and the North Slope Borough, Department of Wildlife Management. This report is comprehensive, describing results for achieving the overlap

Contribution of land use to rodent flea load distribution in the plague endemic area of Lushoto District, Tanzania.

Science.gov (United States)

Hieronimo, Proches; Kihupi, Nganga I; Kimaro, Didas N; Gulinck, Hubert; Mulungu, Loth S; Msanya, Balthazar M; Leirs, Herwig; Deckers, Jozef A

2014-07-01

Fleas associated with different rodent species are considered as the major vectors of bubonic plague, which is still rampant in different parts of the world. The objective of this study was to investigate the contribution of land use to rodent flea load distribution at fine scale in the plague endemic area of north-eastern Tanzania. Data was collected in three case areas namely, Shume, Lukozi and Mwangoi, differing in plague incidence levels. Data collection was carried out during both wet and dry seasons of 2012. Analysis of Variance and Boosted Regression Tree (BRT) statistical methods were used to clarify the relationships between fleas and specific land use characteristics. There was a significant variation (P ≤ 0.05) of flea indices in different land use types. Fallow and natural forest had higher flea indices whereas plantation forest mono-crop and mixed annual crops had the lowest flea indices among the aggregated land use types. The influence of individual land use types on flea indices was variable with fallow having a positive effect and land tillage showing a negative effect. The results also demonstrated a seasonal effect, part of which can be attributed to different land use practices such as application of pesticides, or the presence of grass strips around fields. These findings suggest that land use factors have a major influence on rodent flea abundance which can be taken as a proxy for plague infection risk. The results further point to the need for a comprehensive package that includes land tillage and crop type considerations on one hand and the associated human activities on the other, in planning and implementation of plague control interventions.

Conversion of tropical lowland forest reduces nutrient return through litterfall, and alters nutrient use efficiency and seasonality of net primary production.

Science.gov (United States)

Kotowska, Martyna M; Leuschner, Christoph; Triadiati, Triadiati; Hertel, Dietrich

2016-02-01

Tropical landscapes are not only rapidly transformed by ongoing land-use change, but are additionally confronted by increasing seasonal climate variation. There is an increasing demand for studies analyzing the effects and feedbacks on ecosystem functioning of large-scale conversions of tropical natural forest into intensively managed cash crop agriculture. We analyzed the seasonality of aboveground litterfall, fine root litter production, and aboveground woody biomass production (ANPP(woody)) in natural lowland forests, rubber agroforests under natural tree cover ("jungle rubber"), rubber and oil palm monocultures along a forest-to-agriculture transformation gradient in Sumatra. We hypothesized that the temporal fluctuation of litter production increases with increasing land-use intensity, while the associated nutrient fluxes and nutrient use efficiency (NUE) decrease. Indeed, the seasonal variation of aboveground litter production and ANPP(woody) increased from the natural forest to the plantations, while aboveground litterfall generally decreased. Nutrient return through aboveground litter was mostly highest in the natural forest; however, it was significantly lower only in rubber plantations. NUE of N, P and K was lowest in the oil palm plantations, with natural forest and the rubber systems showing comparably high values. Root litter production was generally lower than leaf litter production in all systems, while the root-to-leaf ratio of litter C flux increased along the land-use intensity gradient. Our results suggest that nutrient and C cycles are more directly affected by climate seasonality in species-poor agricultural systems than in species-rich forests, and therefore might be more susceptible to inter-annual climate fluctuation and climate change.

A new classification of large-scale climate regimes around the Tibetan Plateau based on seasonal circulation patterns

Directory of Open Access Journals (Sweden)

Xin-Gang Dai

2017-03-01

Full Text Available This study aims to develop a large-scale climate classification for investigating the characteristics of the climate regimes around the Tibetan Plateau based on seasonal precipitation, moisture transport and moisture divergence using in situ observations and ERA40 reanalysis data. The results indicate that the climate can be attributed to four regimes around the Plateau. They situate in East Asia, South Asia, Central Asia and the semi-arid zone in northern Central Asia throughout the dryland of northwestern China, in addition to the Köppen climate classification. There are different collocations of seasonal temperature and precipitation: 1 in phase for the East and South Asia monsoon regimes, 2 anti-phase for the Central Asia regime, 3 out-of-phase for the westerly regime. The seasonal precipitation concentrations are coupled with moisture divergence, i.e., moisture convergence coincides with the Asian monsoon zone and divergence appears over the Mediterranean-like arid climate region and westerly controlled area in the warm season, while it reverses course in the cold season. In addition, moisture divergence is associated with meridional moisture transport. The northward/southward moisture transport corresponds to moisture convergence/divergence, indicating that the wet and dry seasons are, to a great extent, dominated by meridional moisture transport in these regions. The climate mean southward transport results in the dry-cold season of the Asian monsoon zone and the dry-warm season, leading to desertification or land degradation in Central Asia and the westerly regime zone. The mean-wind moisture transport (MMT is the major contributor to total moisture transport, while persistent northward transient eddy moisture transport (TEMT plays a key role in dry season precipitation, especially in the Asian monsoon zone. The persistent TEMT divergence is an additional mechanism of the out-of-phase collocation in the westerly regime zone. In addition

The impact of organochlorines cycling in the cryosphere on global distributions and fate – 2. Land ice and temporary snow cover

International Nuclear Information System (INIS)

Hofmann, Lorenz; Stemmler, Irene; Lammel, Gerhard

2012-01-01

Global fate and transport of γ-HCH and DDT was studied using a global multicompartment chemistry-transport model, MPI-MCTM, with and without inclusion of land ice (in Antarctica and Greenland) or snow cover (dynamic). MPI-MCTM is based on coupled ocean and atmosphere general circulation models. After a decade of simulation 4.2% γ-HCH and 2.3% DDT are stored in land ice and snow. Neglection of land ice and snow in modelling would underestimate the total environmental residence time, τ ov , of γ-HCH and overestimate τ ov for DDT, both on the order of 1% and depending on actual compartmental distribution. Volatilisation of DDT from boreal, seasonally snow covered land is enhanced throughout the year, while volatilisation of γ-HCH is only enhanced during the snow-free season. Including land ice and snow cover in modelling matters in particular for the Arctic, where higher burdens are predicted to be stored. - Highlights: ► Land ice and snow hosts 2–4% of the global environmental burden of γ-HCH and DDT. ► Inclusion of land ice and snow cover matters for global environmental residence time. ► Including of land ice and snow cover matters in particular for the Arctic. - The inclusion of cycling in temporary snow cover and land ice in the model is found relevant for predicted POPs multicompartmental distribution and fate in the Arctic and on the global scale.

Modeling seasonal surface temperature variations in secondary tropical dry forests

Science.gov (United States)

Cao, Sen; Sanchez-Azofeifa, Arturo

2017-10-01

Secondary tropical dry forests (TDFs) provide important ecosystem services such as carbon sequestration, biodiversity conservation, and nutrient cycle regulation. However, their biogeophysical processes at the canopy-atmosphere interface remain unknown, limiting our understanding of how this endangered ecosystem influences, and responds to the ongoing global warming. To facilitate future development of conservation policies, this study characterized the seasonal land surface temperature (LST) behavior of three successional stages (early, intermediate, and late) of a TDF, at the Santa Rosa National Park (SRNP), Costa Rica. A total of 38 Landsat-8 Thermal Infrared Sensor (TIRS) data and the Surface Reflectance (SR) product were utilized to model LST time series from July 2013 to July 2016 using a radiative transfer equation (RTE) algorithm. We further related the LST time series to seven vegetation indices which reflect different properties of TDFs, and soil moisture data obtained from a Wireless Sensor Network (WSN). Results showed that the LST in the dry season was 15-20 K higher than in the wet season at SRNP. We found that the early successional stages were about 6-8 K warmer than the intermediate successional stages and were 9-10 K warmer than the late successional stages in the middle of the dry season; meanwhile, a minimum LST difference (0-1 K) was observed at the end of the wet season. Leaf phenology and canopy architecture explained most LST variations in both dry and wet seasons. However, our analysis revealed that it is precipitation that ultimately determines the LST variations through both biogeochemical (leaf phenology) and biogeophysical processes (evapotranspiration) of the plants. Results of this study could help physiological modeling studies in secondary TDFs.

An Evaluation of the Predictability of Austral Summer Season Precipitation over South America.

Science.gov (United States)

Misra, Vasubandhu

2004-03-01

In this study predictability of austral summer seasonal precipitation over South America is investigated using a 12-yr set of a 3.5-month range (seasonal) and a 17-yr range (continuous multiannual) five-member ensemble integrations of the Center for Ocean Land Atmosphere Studies (COLA) atmospheric general circulation model (AGCM). These integrations were performed with prescribed observed sea surface temperature (SST); therefore, skill attained represents an estimate of the upper bound of the skill achievable by COLA AGCM with predicted SST. The seasonal runs outperform the multiannual model integrations both in deterministic and probabilistic skill. The simulation of the January February March (JFM) seasonal climatology of precipitation is vastly superior in the seasonal runs except over the Nordeste region where the multiannual runs show a marginal improvement. The teleconnection of the ensemble mean JFM precipitation over tropical South America with global contemporaneous observed sea surface temperature in the seasonal runs conforms more closely to observations than in the multiannual runs. Both the sets of runs clearly beat persistence in predicting the interannual precipitation anomalies over the Amazon River basin, Nordeste, South Atlantic convergence zone, and subtropical South America. However, both types of runs display poorer simulations over subtropical regions than the tropical areas of South America. The examination of probabilistic skill of precipitation supports the conclusions from deterministic skill analysis that the seasonal runs yield superior simulations than the multiannual-type runs.

[Community traits of soil fauna in forestlands converted from cultivated lands in limestone red soil region of Ruichang, Jiangxi Province of China].

Science.gov (United States)

Li, Tao; Liu, Yuan-Qiug; Guo, Sheng-Mao; Ke, Guo-Qing; Zhang, Zhao; Xiao, Xu-Bao; Liu, Wu

2012-04-01

This paper studied the variations of the community composition and individuals' number of soil fauna in limestone red soil region of Ruichang, Jiangxi Province after six years of converting cultivated lands into forestlands. Three converted forestlands, including the lands of mixed multiple-species forest, bamboo-broadleaved forest, and tree-seedling integration, were selected as test objects, with cultivated lands as the comparison. A total of 34 orders, 17 classes, and 6 phyla of soil fauna were observed in the converted forestlands. The dominant group was Nematoda, accounting for 86.7% of the total, whereas Acarina, Enchytraeidae, and Collembola were the common groups. In the cultivated lands, soil fauna had 21 orders, 10 classes, and 5 phyla. The dominant group was also Nematoda, accounting 86.7% of the total, and Acarina and Enchytraeidae were the common groups. In the converted forestlands, the group number of rare species was greater than that in the cultivated lands (30 vs. 18), and, except in winter, the group number and average density were significantly higher than those in the cultivated lands (P soil fauna in the soil profiles showed an obvious surface accumulation, which was more apparent in converted forestlands than in cultivated lands, and the individuals' number had significant differences between the surface (0-5 cm) layer and the 5-10 cm and 10-15 cm layers (P soil fauna in the converted forestlands had a seasonal variation ranked in the order of summer > autumn > spring > winter, and there was a significant difference between summer-autumn and spring-winter. The average density of the soil fauna also had a seasonal variation but ranked as autumn > summer > spring > winter, and the differences among the seasons were significant (P soil fauna was significantly higher in converted forestlands than in cultivated lands, and was the highest in mixed multiple-species forestland and the least in tree-seedling integration land.

Change in land use in the Phoenix (1:250,000) Quadrangle, Arizona between 1970 and 1973: ERTS as an aid in a nationwide program for mapping general land use. [Phoenix Quadrangle, Arizona

Science.gov (United States)

Place, J. L.

1974-01-01

Changes in land use between 1970 and 1973 in the Phoenix (1:250,000 scale) Quadrangle in Arizona have been mapped using only the images from ERTS-1, tending to verify the utility of a standard land use classification system proposed for use with ERTS images. Types of changes detected have been: (1) new residential development of former cropland and rangeland; (2) new cropland from the desert; and (3) new reservoir fill-up. The seasonal changing of vegetation patterns in ERTS has complemented air photos in delimiting the boundaries of some land use types. ERTS images, in combination with other sources of information, can assist in mapping the generalized land use of the fifty states by the standard 1:250,000 quadrangles. Several states are already working cooperatively in this type of mapping.

Change in land use in the Phoenix (1:250,000) Quadrangle, Arizona between 1970 and 1972: Successful use of proposed land use classification system

Science.gov (United States)

Place, J. L.

1973-01-01

Changes in land use in the Phoenix (1:250,000 scale) Quadrangle in Arizona have been mapped using only the images from ERTS-1, tending to verify the utility of a land use classification system proposed for use with ERTS images. The period of change investigated was from November 1970 to late summer or early fall, 1972. Seasonal changes also were studied using successive ERTS images. Types of equipment used to aid interpretation included a color additive viewer, a twenty-power magnifier, a density slicer, and a diazo copy machine for making ERTS color composites in hard copy. Types of changes detected have been: (1) cropland or rangeland developed for new residential areas; (2) rangeland converted to new cropland; and (3) possibly new areas of industrial or commercial development. A map of land use previously compiled from air photos was updated in this manner.

Predictability of soil moisture and river flows over France for the spring season

Science.gov (United States)

Singla, S.; Céron, J.-P.; Martin, E.; Regimbeau, F.; Déqué, M.; Habets, F.; Vidal, J.-P.

2012-01-01

Sources of spring predictability of the hydrological system over France were studied on a seasonal time scale over the 1960-2005 period. Two random sampling experiments were set up in order to test the relative importance of the land surface initial state and the atmospheric forcing. The experiments were based on the SAFRAN-ISBA-MODCOU hydrometeorological suite which computed soil moisture and river flow forecasts over a 8-km grid and more than 880 river-gauging stations. Results showed that the predictability of hydrological variables primarily depended on the seasonal atmospheric forcing (mostly temperature and total precipitation) over most plains, whereas it mainly depended on snow cover over high mountains. However, the Seine catchment area was an exception as the skill mainly came from the initial state of its large and complex aquifers. Seasonal meteorological hindcasts with the Météo-France ARPEGE climate model were then used to force the ISBA-MODCOU hydrological model and obtain seasonal hydrological forecasts from 1960 to 2005 for the entire March-April-May period. Scores from this seasonal hydrological forecasting suite could thus be compared with the random atmospheric experiment. Soil moisture and river flow skill scores clearly showed the added value in seasonal meteorological forecasts in the north of France, contrary to the Mediterranean area where values worsened.

A daytime climatological distribution of high opaque ice cloud classes over the Indian summer monsoon region observed from 25-year AVHRR data

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A. Devasthale

2009-06-01

Full Text Available A daytime climatological spatio-temporal distribution of high opaque ice cloud (HOIC classes over the Indian subcontinent (0–40° N, 60° E–100° E is presented using 25-year data from the Advanced Very High Resolution Radiometers (AVHRRs for the summer monsoon months. The HOICs are important for regional radiative balance, precipitation and troposphere-stratosphere exchange. In this study, HOICs are sub-divided into three classes based on their cloud top brightness temperatures (BT. Class I represents very deep convection (BT<220 K. Class II represents deep convection (220 K<=BT<233 K and Class III background convection (233 K<=BT<253 K. Apart from presenting finest spatial resolution (0.1×0.1 degrees and long-term climatology of such cloud classes from AVHRRs to date, this study for the first time illustrates on (1 how these three cloud classes are climatologically distributed during monsoon months, and (2 how their distribution changes during active and break monsoon conditions. It is also investigated that how many deep convective clouds reach the tropopause layer during individual monsoon months. It is seen that Class I and Class II clouds dominate the Indian subcontinent during monsoon. The movement of monsoon over continent is very well reflected in these cloud classes. During monsoon breaks strong suppression of convective activity is observed over the Arabian Sea and the western coast of India. On the other hand, the presence of such convective activity is crucial for active monsoon conditions and all-India rainfall. It is found that a significant fraction of HOICs (3–5% reach the tropopause layer over the Bay of Bengal during June and over the north and northeast India during July and August. Many cases are observed when clouds penetrate the tropopause layer and reach the lower stratosphere. Such cases mostly occur during June compared to the other months.

The greening of the McGill Paleoclimate Model. Part I: Improved land surface scheme with vegetation dynamics

Energy Technology Data Exchange (ETDEWEB)

Wang, Yi; Mysak, Lawrence A.; Wang, Zhaomin [McGill University, Department of Atmospheric and Oceanic Sciences, Global Environmental and Climate Change Centre (GEC3), Montreal, QC (Canada); Brovkin, Victor [Potsdam Institute for Climate Impact Research (PIK), Potsdam (Germany)

2005-04-01

The formulation of a new land surface scheme (LSS) with vegetation dynamics for coupling to the McGill Paleoclimate Model (MPM) is presented. This LSS has the following notable improvements over the old version: (1) parameterization of deciduous and evergreen trees by using the model's climatology and the output of the dynamic global vegetation model, VECODE (Brovkin et al. in Ecological Modelling 101:251-261 (1997), Global Biogeochemical Cycles 16(4):1139, (2002)); (2) parameterization of tree leaf budburst and leaf drop by using the model's climatology; (3) parameterization of the seasonal cycle of the grass leaf area index; (4) parameterization of the seasonal cycle of tree leaf area index by using the time-dependent growth of the leaves; (5) calculation of land surface albedo by using vegetation-related parameters, snow depth and the model's climatology. The results show considerable improvement of the model's simulation of the present-day climate as compared with that simulated in the original physically-based MPM. In particular, the strong seasonality of terrestrial vegetation and the associated land surface albedo variations are in good agreement with several satellite observations of these quantities. The application of this new version of the MPM (the ''green'' MPM) to Holocene millennial-scale climate changes is described in a companion paper, Part II. (orig.)

Determination of bare soil and its seasonal variation using image analysis

International Nuclear Information System (INIS)

Pulido Fernandez, M.; Lavado Contador, J. F.; Schnabel, S.; Gomez Gutierrez, A.

2009-01-01

Bare soil is of outstanding interest as an indicator of land degradation because it is strongly related with water erosion, particularly in low-vegetated areas as those typical of the Mediterranean rangelands. In areas with high livestock densities, erosion can ultimately get to a partial or total soil loss, particularly at the beginning of the rainy season, when the surface cover is reduce after the dry summer period. Therefore, it is necessary to develop accurate methods allowing the quantification of soil exposed areas and their temporal dynamics. The main goal of this work is the determination of bare soil surface using aerial orthophotomaps and the analysis of the changes resulting from the analysis and classification of images corresponding to two contrasting seasons (summer and spring). (Author) 6 refs.

Effect of Plant Density and Land Race on the Growth and Yield of ...

African Journals Online (AJOL)

Field study was conducted at National Root Crops Research Institute out station Nyanya Research farm located at Zhewun Jidna Nasarawa State during 2007 and 2008 cropping seasons. The aim was to determine the effect of optimum plant population Density of sweet potato land races under improved management ...

Large-scale Validation of AMIP II Land-surface Simulations: Preliminary Results for Ten Models